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Sustainable Development Goals (SDGs)
PDF Text
Report 2023-24
Copyright@NITI Aayog & MDoNER, 2025
NITI Aayog,
Government of India,
Sansad Marg, New Delhi - 110001, India
Ministry of Development of North Eastern Region
Vigyan Bhawan Annexe,
Maulana Azad Road, New Delhi - 110011
Source of Maps: Survey of India. Boundaries shown in the map
are as per the Political Map of India, Twelfth Edition (Newly
created districts maps provided by respective states and not
to scale).
Cover & Report Design by Rouge Communications
rougecommunications@gmail.com
Photo credits: Biju Boro, Pallav Bhuyan & Andrew Drewzy
Ministry of Development
of North Eastern Region
NORTH EASTERN REGION
DISTRICT SDG INDEX
REPORT 2023–24
II
The collective resolve to address development challenges across social, economic, and
environmental dimensions—while ensuring that no one is left behind—is more urgent today
than ever before. India has demonstrated remarkable resilience and unwavering commit-
ment in its pursuit of the Sustainable Development Goals. In this endeavour, our States
and Union Territories have played an instrumental role, championing SDG initiatives and
advancing a robust localisation model that reaffirms our belief in both cooperative and
competitive federalism.
The States of the North-Eastern Region are central to SDG localisation, given their unique
geography, rich cultural heritage, and intra-regional developmental disparities. Their
commendable efforts have led to the formulation of SDG-aligned vision documents, the
establishment of dedicated institutional frameworks, and the development of state-specific
monitoring systems—ensuring alignment with our broader localisation efforts.
To accelerate SDG progress and promote holistic regional development, NITI Aayog, in
partnership with the Ministry of Development of North Eastern Region and UNDP India,
launched the first-ever District-level SDG Index for the region in 2021. This initiative, shaped
through extensive consultation with all eight North-Eastern States, yielded invaluable insights
into the challenges hindering progress, while also illuminating opportunities to advance
sustainable development across the region. The positive reception of the 2021–2022 edition
has rightfully paved the way for this second iteration.
Shri Suman Bery
Vice Chairperson
National Institution for Transforming India (NITI Aayog)
Government of IndiaMessage
III
July, 2025
New Delhi, India
The North Eastern Region District SDG Index marks a significant step forward in localising
the global goals by translating them into region-specific targets and tracking progress at
the district level. Through data-driven governance, targeted interventions, and the facilita-
tion of peer learning among districts, this Index empowers States to respond more effec-
tively to local development priorities. These collaborative efforts stand as a testament to
India’s unwavering commitment to deepening SDG localisation and accelerating progress
throughout the region.
This initiative epitomises the spirit of cooperative federalism, bringing together the eight
North-Eastern States, NITI Aayog, and MDoNER in a unified pursuit of sustainable and
inclusive development. It also reflects the Honourable Prime Minister’s vision of Sabka
Saath, Sabka Vikas, Sabka Vishwas, Sabka Prayas.
We gratefully acknowledge the valuable contribution of the UNDP team in India, whose
technical expertise, dedication, and consistent support have been integral to the design
and implementation of this initiative. Their partnership has greatly enriched the process
and is deeply appreciated.
Suman Bery
IV
Sustainable Development Goals are at the top of India’s development agenda and their
importance has been repeatedly emphasised by Hon’ble Prime Minister, Shri Narendra Modi.
With this vision, India has accentuated its efforts to realise the SDGs, bouncing back from
the adverse effect the COVID-19 pandemic.
The SDG framework requires effective mechanisms and decentralisation to solve environ-
mental, social and economic challenges. Sub-national entities have utilised the SDG India
Index Report & Dashboard to strengthen their statistical systems and policy formulation.
In the true spirit of cooperative federalism, the Centre and States are working in unison
to realise the Agenda 2030. The first edition of the North East Region District SDG Index
and Dashboard has steered districts of the North East Region towards better monitoring
of achievement of SDGs and this edition would encourage them further.
The North Eastern Region is the country's most socially and ethnically diverse region,
with each State having distinct traditions and cultures. This diversity is its strength and
provides many opportunities for sustainable development. I am delighted that the Ministry
of Development of North Eastern Region has taken the initiative to bring out the NER
District SDG Index and Dashboard in collaboration with NITI Aayog. This monitoring tool
enables States, Ministries and various stakeholders to measure progress and examine the
impact at a granular level.
Shri B.V.R. Subrahmanyam
Chief Executive Officer
National Institution for Transforming India (NITI Aayog)
Government of India
Message
V
NITI Aayog has conducted state-level capacity-building workshops to better understand and
realise SDGs. I applaud the remarkable progress reported by States and districts on SDG
implementation with the development of the State Indicator Framework, District Indicator
Framework, SDG Coordination Cells and review systems at the local level. These steps to
localise SDGs are paramount for achieving the targets.
I compliment the Ministry of Development of North Eastern Region and UNDP India for their
unrelenting support in bringing out this second edition of the NER District SDG Index and
Dashboard. I congratulate the NITI Aayog team for their efforts in preparing this report. I
thank all the State governments of the region for their cooperation and active contribution
to the development of this Index.
B.V.R. Subrahmanyam
July, 2025
New Delhi, India
VI
Message
The North Eastern Region, with its vibrant mosaic of communities, culture, and ecology,
stands at a pivotal moment in its developmental journey. Despite longstanding challenges
such as inadequate connectivity, difficult terrain, and developmental disparities, the region
continues to move forward with resilience and purpose. It is in this context that the NER
District SDG Index & Dashboard 2023–24 becomes a vital instrument of change.
This second edition of the Index, jointly developed by NITI Aayog, Ministry of Development
of North Eastern Region and with technical support from UNDP India, reflects our sustained
commitment to localizing the Sustainable Development Goals at the most granular level.
It builds upon the momentum of the first edition and incorporates feedback, better data
systems, and enhanced district-level coverage, with 121 of the 131 districts of the region now
included. The Index now draws on 84 indicators sourced from both central and state data
systems—a testimony to improved reporting and institutional collaboration.
The findings of this edition are encouraging. A remarkable 85% of districts now fall within
the Front Runner category—a significant leap from 62% in the previous round. This progress
is a direct result of targeted interventions, saturation-based approaches under flagship
national schemes, and robust local efforts in SDG planning and implementation across the
eight NER states. Many districts have shown notable improvement in critical sectors such as
education, health, gender equity, and access to water and energy. The performance on Goal
5 (Gender Equality) and Goal 6 (Clean Water and Sanitation) is particularly commendable.
Shri Chanchal Kumar
Secretary
Ministry of Development of North Eastern Region
Government of India
New Delhi, India
VII
Chanchal Kumar
July, 2025
New Delhi, India
Yet, the journey is far from complete. Certain goals such as Goal 10 (Reduced Inequalities)
and Goal 12 (Responsible Consumption and Production) still show marked disparities across
districts. These require sustained focus and tailored strategies. The Index, by identifying
such gaps, offers actionable insights to guide interventions and resource deployment more
efficiently.
Importantly, the Index continues to foster a spirit of cooperative and competitive federalism
among the States and districts of the NER. Its expanded coverage and methodological rigor
make it not only a tool for benchmarking but also a roadmap for inclusive and sustainable
regional development.
I express my sincere appreciation to NITI Aayog and UNDP India for their unwavering
support in bringing out this updated edition. I also commend the efforts of the eight North
Eastern States for their valuable cooperation in data collection, consultations, and feedback.
VIII
The 17 Sustainable Development Goals lay out a bold agenda—to end poverty in all its
dimensions, drive inclusive economic growth, and protect the planet. These goals offer a
comprehensive framework to address some of the most persistent and emerging challenges
of our time, from climate change and inequality to public health and gender disparities.
For India, the SDGs are not just a global responsibility but a national priority. India’s lead-
ership in localizing the SDGs is a powerful example of translating global aspirations into
local action. Through this approach, states and union territories are tailoring the SDG
framework to their development needs—prioritizing goals, adopting relevant indicators,
and implementing innovative solutions.
A key enabler of this effort is the SDG India Index and Dashboard, developed by NITI Aayog.
It tracks and compares progress across all states and UTs, fostering evidence-based poli-
cymaking, transparency, and healthy competition.
India’s commitment to hyper-local monitoring is equally commendable. The launch of the
North East Region District SDG Index in 2021–22 brought district-level tracking to the eight
northeastern states. By measuring each district’s performance against specific targets,
the Index equips policymakers with the insights needed to focus efforts where they are
needed most.
This collaborative model between central and state governments has delivered meaningful
progress in the region—in areas such as renewable energy, poverty reduction, and digital
inclusion.
Dr. Angela Lusigi
Resident Representative
UNDP India
Message
IX
The latest NER District SDG Index 2023–24 builds on this foundation. It highlights achieve-
ments, uncovers emerging challenges, and provides a roadmap for action. It highlights
progress, identifies new challenges, and offers data-driven insights to accelerate action. By
spotlighting both high-performing districts and those needing more attention, it enables
focused interventions, efficient resource allocation, and inter-district learning. It also rein-
forces how local efforts in the Northeast contribute to the national vision of Viksit Bharat.
We commend the Government of India for its exemplary leadership in advancing
the SDG agenda. In particular, we thank the senior leadership of NITI Aayog and the
Ministry of Development of North Eastern Region for their vision and partnership. We
extend our appreciation to Shri Jyotiraditya M. Scindia, Union Minister for MDoNER;
Shri Suman Bery, Vice Chairperson of NITI Aayog; Shri B.V.R. Subrahmanyam, CEO of NITI
Aayog; and Shri Chanchal Kumar, Secretary of MDoNER.
I sincerely thank Shri Rajib Sen, Adviser to NITI Aayog, for steering this publication, and to the
state governments of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland,
Sikkim, and Tripura for their strong commitment to sustainable development in the region.
At UNDP, we remain a steadfast partner to the Government of India, committed to support-
ing this journey through technical expertise, innovative investment, integrated solutions
and institutionalcapabilities. Together, we can ensure that no district—and no one—is left
behind in India’s SDG journey.
July, 2025
New Delhi, India
Dr. Angela Lusigi
X
Acknowledgements
NITI Aayog has been consistently engaging with States and UTs for the adoption, implemen-
tation, and monitoring of the Sustainable Development Goals at the national and sub-na-
tional levels. The 'Indian Model of SDG Localisation', anchored in the core SDG principle
of ‘leaving no one behind', reflects India's relentless efforts towards the '2030 Agenda'.
NITI Aayog's SDG India Index has become the primary tool for SDG monitoring at the
national and sub-national levels. The North Eastern Region District SDG Index expands
the model to the district level to address the growing needs for reliable and comparable
data and supports evidence-based policymaking and targeted interventions. For a region
with such cultural and socio-economically diversity, as well as disparities, the NER District
SDG Index serves as a tool to fast-track the progress of SDGs at the districts in the region.
The second edition of the NER District SDG Index, developed collaboratively with the Ministry
of Development of North Eastern Region, State Governments of the north eastern region and
UNDP India, covers 15 SDGs and ranks 121 of 131 districts of the region. A notable achieve-
ment is the inclusion of 16 districts that were excluded last time due to data unavailability.
The Index is the first of its kind to measure regional progress through customised meth-
odology and metrics, highlighting significant progress in district-level data reporting. It
enables state-wise, district-wise, and SDG-wise comparisons and serves as a platform for
peer learning, mid-course correction, and better resource allocation.
We extend our deepest gratitude to MDoNER and the State Governments of Arunachal
Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura for their
continuous support, from consultations to data provision. The state-level workshops were
instrumental in refining this edition.
Shri Rajib Kumar Sen
Programme Director (SDGs)
National Institution for Transforming India (NITI Aayog)
Government of India
XI
Rajib Kumar Sen
Our sincere thanks to Shri Suman Bery, Hon’ble Vice Chairman, NITI Aayog, for his inspiring
leadership, and to Shri B.V.R. Subrahmanyam, CEO, NITI Aayog, for his constant encourage-
ment and support for localising efforts in the SDGs.
We are also thankful to Shri Chanchal Kumar, Ministry of Development of North Eastern
Region, for entrusting us with this critical initiative, and to Dr. Angela Lusigi, Resident
Representative, UNDP India, for her team’s strong partnership.
Special acknowledgements are due to the entire SDG team at NITI Aayog for their commit-
ment and dedication towards the development of the Report.
We sincerely hope that the NER District SDG Index will be a catalyst for inclusive and coor-
dinated ground-level implementation of the SDGs in the region.
July, 2025
New Delhi, India
XII
LIST OF ABBREVIATIONS
AIDS Acquired Immunodeficiency Syndrome
ANC Antenatal Care
ANM Auxiliary Nurse Midwifery
ATMs Automated Teller Machines
AYUSH Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homoeopathy
BCG Bacillus Calmette-Guerin
BCs Business Correspondents
BPL Below Poverty Line
CMSGUY Chief Minister's Samagra Gramya Unnayan Yojana
COVID-19 Coronavirus Disease
CSCs Common Service Centres
CSDGs Centre for Sustainable Development Goals
CSOs Civil Society Organisations
CSSEIP Centre for Study of Social Exclusion and Inclusive Policy
DPC District Planning Committee
DPT Diphtheria, Pertussis and Tetanus
FPS Fair Price Shops
FRUs First Referral Units
FSI Forest Survey of India
FY Financial Year
GIZ Deutsche Gesellschaft für Internationale Zusammenarbeit
GPI Gender Parity Indices
GPs Gram Panchayats
Hb Haemoglobin
HIV Human Immunodeficiency Virus
ICDS Integrated Child Development Services
IHHL Individual Household Latrines
IMR Infant Mortality Rate
JJM Jal Jeevan Mission
MDoNER Ministry of Development of North Eastern Region
MGNREGA Mahatma Gandhi National Rural Employment Guarantee Act
MIS Management Information System
MoEFCC Ministry of Environment, Forest and Climate Change
MoHFW Ministry of Health and Family Welfare
MoSPI Ministry of Statistics and Programme Implementation
MPI Multidimensional Poverty Index
MSMEs Micro, Small and Medium Enterprises
MSW Municipal Solid Waste
NAS National Achievement Survey
NBCC Newborn Care Corner
NBSU Newborn Stabilization Unit
NCRB National Crime Records Bureau
NER North Eastern Region
NFHS National Family Health Survey
XIII
NFSA National Food Security Act
NGOs Non-governmental Organisations
NIF National Indicator Framework
NITI National Institution for Transforming India
ODF Open Defecation Free
OPV Oral Polio Vaccine
PDS Public Distribution System
PMAY Pradhan Mantri Awas Yojana
PM-DevINE Prime Minister’s Development Initiative for North East Region
PMGSY Pradhan Mantri Gram Sadak Yojana
PMJAY Pradhan Mantri Jan Arogya Yojana
PMJDY Pradhan Mantri Jan Dhan Yojana
PMMVY Pradhan Mantri Matru Vandana Yojana
PRIs Panchayati Raj Institutions
PTR Pupil-Teacher Ratio
PwD Persons with Disabilities
PWS Piped Water Supply
SBA Skilled Birth Attendant
SBM Swachh Bharat Mission
SBM(G) Swachh Bharat Mission (Gramin)
SDGCAC Sustainable Development Goals Coordination and Acceleration Centre
SDGCC Sustainable Development Goals Coordination Centre
SDGs Sustainable Development Goals
SHGs Self-Help Groups
SIF State Indicator Framework
SNCU Special Newborn Care Unit
SRB Sex Ratio at Birth
SSSG SDG Strategy Support Group
TB Tuberculosis
THR Take Home Ration
TRIPS Trade-Related Aspects of Intellectual Property Rights
U-DISE+ Unified-District Information System for Education - Plus
ULBs Urban Local Bodies
UN United Nations
UNDP United Nations Development Programme
UNFCCC United Nations Framework Convention on Climate Change
UNFPA United Nations Population Fund
USD United States Dollar
U Ts Union Territories
VCs Village Councils
VEC Village Education Committee
WHO World Health Organization
XIV
Contents
Message from Vice Chairperson, NITI Aayog II
Message from CEO, NITI Aayog IV
Message from Secretary, MDoNER VI
Message from Resident Representative, UNDP-India VIII
Acknowledgements by Programme Director (SDGs),
NITI Aayog X
List of Abbreviations XVI
Executive Summary XX
Context & Overview
PAGE 1
1.
Introduction: SDGs and the
North Eastern Region (NER) 3
I
Photo courtesy of Alen John
XV
Metadata 172
Indicator Tables 201
Methodology & Results State Profiles
PAGE 153PAGE 11
PAGE 171
II III
IV
2.
Methodology and Framework of the North
Eastern Region District SDG Index 13
3.
Composite Results: NER District SDG Index
2023-24 21
Progress on Goals:
SDG 1No Poverty
29
SDG 2Zero Hunger 37
SDG 3Good Health and Well-being 45
SDG 4Quality Education 53
SDG 5Gender Equality 61
SDG 6Clean Water and Sanitation 69
SDG 7Affordable and Clean Energy 77
SDG 8Decent Work and Economic Growth 85
SDG 9Industry, Innovation and Infrastructure 93
SDG 10Reduced Inequalities 101
SDG 11Sustainable Cities and Communities 109
SDG 12Responsible Consumption and Production 117
SDG 13Climate Action 125
SDG 15Life on Land 133
SDG 16Peace, Justice and Strong Institutions 141
4.
Way Forward:
From Analysis to Action 150
i.Arunachal Pradesh [AR] 154
ii.Assam [AS] 156
iii.Manipur [MN] 158
iv.Meghalaya [ML] 160
v.Mizoram [MZ] 162
vi. Nagaland [NL] 164
vii.Sikkim [SK] 166
viii.Tripura [TR] 168
Metadata &
Indicator Tables
XVI
1. Overview
The North Eastern Region (NER) District SDG
Index, a collaborative effort by Ministry of
Development of North Eastern Region (MDoNER)
and NITI Aayog – with technical support from
UNDP, is the first of its kind progress tracking tool
for the NER, which is of critical significance to
the country’s development trajectory. The Index
measures the performance of the NER districts
on the Sustainable Development Goals (SDGs).
It is based on the methodology adopted by the
NITI Aayog’s SDG India Index, the principal and
official tool for monitoring progress on the SDGs
at the national and State/Union Territory levels.
The NER District SDG Index is aimed at enhancing
analytical understanding of sectoral issues as well
as data gaps while assisting in designing future
courses of action in the region. The first edition of
the NER District SDG Index Report 2021–22 was
released on 26 August 2021.
2. Introduction to the second edition
Enhanced coverage of districts: While the
first edition of the index covered 103 of 120
(86 percent) districts of the North Eastern Region,
this edition covers 121 out of 131 (92 percent)
districts.
Data: The second edition of the index has 84 indi-
cators. Out of 84 indicators, data for 41 indicators
is from various ministries/departments of Union
Government and data for 43 indicators is from
State sources. A significant improvement in the
district-level reporting to the Union Government
has been noted in the index.
3. Key findings and results obtained from the
second edition
Improvement in the overall performance of
districts: In this edition of the index, 85 percent
of the districts of the NER are in the Front Runner
category (overall score 65–99) compared to the
previous edition, where 62 percent of the districts
were in this category.
District-wise performance: The scores for the 121
districts ranges from 58.71 in Longding [AR] to
81.43 in Hnahthial [MZ].
EXECUTIVE SUMMARY
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
Composite
Score
14.88%
2.48%
0.83%
4.96%
9.09%
0.83%
5.79%
6.61%
91.74%
14.05%
27.27%
14.88%
40.50%
1.65%
4.13%21.49% 74.38%
4.96% 71.90% 21.49%
7.44% 48.76% 3.31%
42.98% 42.15%
35.54%37.19%
0.83%
0.83%
9.09% 76.03%
7.44%
33.88% 47.93% 11.57%
94.21%
6.61% 92.56%
24.79% 66.12%
55.37% 39.67%
30.58% 68.60%
67.77% 29.75%
85.12%
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Figure A. Goal-Wise Percentage of Districts in Each Category
XVII
SDG 8 Decent Work and Economic Growth
There has been a substantial improvement,
with Front Runner districts increasing from
69 (67 percent) to 111 (92 percent).
SDG 7 Affordable and Clean Energy
The number of Achiever districts (score
of 100) has doubled from 7 to 14.
This goal tracks village electrification
and the use of clean cooking fuel.
SDG 15 Life on Land
There has been a significant improvement,
with 26 districts (21.5 percent) achieving
Achiever status, up from 12 districts (12
percent). Similarly, 87 districts (72 percent)
are in the Front Runner category.
SDG 16 Peace, Justice and Strong Institutions
There is a positive trend with Front Runner districts
increasing from 64 (62 percent) to 90 (74 percent).
However, number of Aspirant districts have also
increased from 1 (<1 percent) to 5 (4 percent).
SDG 2 Zero Hunger
There is significant progress, with Front Runner
districts increasing from 49 (47.5 percent) to
83 (69 percent). Number of Aspirant districts
have dropped from 21 (20 percent) to just 1.
SDG 1 No Poverty
There has been an impressive improvement,
with 36 districts (30 percent) in the Front
Runner category (score of 65-99.99), up from
21 districts (20 percent). The Aspirant category
(score of 0–49) has dropped from 20 districts
(19.5 percent) to just 3 districts (2.5 percent).
SDG 5 Gender Equality
The region now has 112 districts (93 percent) in
the Front Runner category, up from 71 districts
(69 percent) in the last edition. The Aspirant
category has nearly disappeared, dropping from
5 districts (5 percent) to just 1 district (<1 percent).
SDG 6 Clean Water and Sanitation
Over 114 districts (94 percent) are now in Front
Runner category up from 81 districts (79 percent),
reflecting the impact of Jal Jeevan Mission -
Har Ghar Nal and Swachh Bharat Mission on access
to piped water and improved sanitation facilities.
SDG 4 Quality Education
There has been a significant growth in the
Front Runner districts rising from 36 (35 percent)
to 80 (66 percent). Only 11 districts (9 percent)
remain in the Aspirant category.
SDG 3 Good Health and Well-being
There is a strong improvement in Front Runner
districts increasing from 14 (14 percent) to 48
(40 percent). The Aspirant category has reduced
from 18 (17.5 percent) to just 6 (5 percent) only.
SDG 10 Reduced Inequalities
The number of Front Runner districts has gone
down from 59 (57 percent) to 43 (35.5 percent).
33 districts (27 percent) remain in the Aspirant
category (score of 0–49), up from 12 (12 percent),
requiring focused attention on relevant indicators.
SDG 9 Industry, Innovation
and Infrastructure
There has been significant progress in
Front Runner districts, increasing from
55 (53 percent) to 92 (76 percent).
SDG 13 Climate Action
4 districts (3.3 percent) have reached Achiever status
(score of 100), and the number of Front Runner
districts have gone up from 36 (35 percent) to 59
(49 percent), However, 49 districts (41 percent) still
remain in the Aspirant category, indicating a need
for targeted action across the North Eastern region.
SDG 12 Responsible Consumption
and Production
There is a decline in Front Runner districts
from 67 (65 percent) to 51 (43 percent).
18 districts (15 percent) remain in the
Aspirant category (score of 0–49).
FIGURE B. PROGRESS BETWEEN NER DISTRICT SDG INDEX 2023-24 AND 2021-22
XVIIIState-wiseoverallperformance
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ArunachalPradesh AssamM anipur MeghalayaM izoram Nagaland Sikkim Tripura
State-wisepercentageofdistrictsin eachperformancecategory
Achiever(100)FrontRunner(65-99)Performer(50-64)Aspirant(0-49) N/A
36%
(9 Districts)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ArunachalPradesh AssamM anipur MeghalayaM izoram Nagaland Sikkim Tripura
31.25%
(5 Districts)
12.5%
(2 Districts)
56.25%
(9 Districts)
100%
(8Districts)100%
(6 Districts)
100%
(11 Districts)
83.33%
(10 Districts)
75%
(12 Districts)
8.33%
(1 District)
8.33%
(1 District)
25%
(4 Districts)
5.71%
(2 Districts)
88.57%
(31 Districts)
59.26%
(16 Districts)
7.41%
(2 Districts)
33.33%
(9 Districts)
5.71%
(2 Districts)
Index
2023-24
Index
2021-22
48%
(12 Districts)
52%
(13Districts)
69.7%
(23 Districts)
12.12%
(4 Districts)
18.18%
(6 Districts)
50%
(8 Districts)
6.25%
(1 District)
43.75%
(7 Districts)
9.09%
(1 District)
90.91%
(10 Districts)
100%
(8 Districts)
100%
(4 Districts)
91.67%
(11 Districts)
8.33%
(1 District)
27.27%
(3 Districts)
63.64%
(7 Districts)
9.09%
(1 District)
Significant improvements have been observed
in the indicators linked to the National Family
Health Survey (NFHS) in sectors such as access to
clean cooking fuel, housing, electricity, sanitation,
drinking water, bank accounts, child and maternal
health services, schooling and attendance, birth
registration, unmet need for family planning,
health insurance, among others. This momentum
will be key to closing the gap with the national
average in the short and medium term and for
states to feature among the top states in the
long term. In this context, indicator level analysis
is crucial for identifying gaps and accelerating
progress in the short term and beyond. It would
also help in addressing intra-regional and inter-dis-
trict disparities to ensure that performance is in
line with or above the national average.
FIGURE C. STATE-WISE OVERALL PERFORMANCE COMPARED TO THE PREVIOUS EDITION
Overall, there has been an increase in the proportion of
districts in the Front Runner category from 62 percent in
the last edition to 85 percent in this edition. This signifies
the impact of the national flagship schemes coupled with
the localisation efforts of the states and saturation of
benefits through initiatives like the Aspirational Districts
Programme. The state wise performance based on the
composite scores of SDGs is provided below:
XIX
CONTEXT
& OVERVIEW
I
CHAPTER 1.1. Importance of SDGs in the NER
The SDG framework represents a comprehensive
global consensus on sustainable development
priorities, encompassing economic, environmen-
tal and social dimensions. It serves as a ready
reckoner for countries to formulate policies for
sustainable development with people and their
quality and ease of living at the centre as priorities.
For India's North Eastern Region, the SDGs hold
particular significance given the region's distinc-
tive ecological, cultural, and demographic char-
acteristics. The eight states comprising the NER
—Arunachal Pradesh, Assam, Manipur, Meghalaya,
Mizoram, Nagaland, Sikkim, and Tripura—feature
unique geographical landscapes and are home
to diverse tribal communities with rich cultural
heritage. The central challenge for this region
lies in fostering development that enhances living
standards while preserving traditional knowl-
edge systems, cultural practices, and indigenous
lifestyles.
The NER District SDG Index measures the
performance of the districts of the eight States on
SDGs and their corresponding targets. The Index
is based on NITI Aayog's SDG India Index – the
principal and official tool for monitoring progress
on the SDGs at the national and State/Union
Territory levels and shares the common ethos of
benchmarking performance and ranking on the
SDGs to foster competition among the districts.
The implementation of the SDGs in the North
Eastern Region faces significant challenges rooted
in the region's unique geographic, economic, and
social landscape. Economic vulnerability stands as
a primary concern, with the incidence of poverty
(National MPI NITI Aayog, 2023) in the region
ranging from 2.6 percent in Sikkim to 27.79 percent
in Meghalaya, while the national average is 24.85
percent. This economic fragility is compounded by
heavy dependence on agriculture, particularly in
states like Nagaland and Arunachal Pradesh, where
a significant proportion of the population depends
on subsistence farming that offers little resilience
against climate shocks. The limited access to
advanced agricultural technology, quality inputs,
and modern farming techniques further constrains
agricultural diversification and productivity.
The geographical characteristics of the region
–mountainous terrain, dense forests, and border
proximity, create natural barriers to industrial
development and infrastructure expansion,
particularly in the eastern regions of Arunachal
Pradesh. These constraints have led to a stagnation
in progress toward SDG 9 (Industry, Innovation and
Infrastructure) and limited employment oppor-
tunities in modern sectors. The interconnected
nature of the SDGs becomes evident as these
infrastructure and economic challenges directly
impact the region's ability to advance on SDGs
2 (Zero Hunger), 3 (Good Health and Wellbeing),
and 4 (Quality Education), areas where states
like Arunachal Pradesh, Assam, Meghalaya, and
Nagaland show substantial room for improvement.
The social dimension reveals how these develop-
ment gaps affect vulnerable populations dispro-
portionately. Women and adolescent girls bear
the heaviest burden of health inequities, with high
rates of malnutrition and anaemia where poor
socioeconomic conditions and difficult living
environments compound health challenges.
These health issues diminish cognitive capa-
bilities and productivity, creating a cycle that
hinders economic participation and advance-
ment. These challenges directly impact progress
on SDGs 3 (Good Health and Well-being) and
5 (Gender Equality). Addressing these gender-spe-
cific health inequities is essential not only for
individual well-being but also for enabling full
economic participation of women in the region's
development.
INTRODUCTION:
SDGs AND THE
NORTHEASTERN
REGION (NER)
CHAPTER 1
3
CONTEXT & OVERVIEW
The environmental aspects of sustainable develop-
ment present perhaps the most nuanced challenge
for the NER. The region represents an ecolog-
ical treasure, accounting for 25 percent of the
country's forest cover despite comprising just 7.98
percent of the geographical area and housing 43
percent of all plant species in India. However, this rich
biodiversity is under increasing threat from unsus-
tainable agricultural practices like Jhum cultivation,
unplanned urbanisation and unscientific extraction
of natural resources. The region is already witnessing
alarming patterns of climate change with intensified
rainfall, frequent floods, emerging resilient pest
variants and steadily rising temperatures. According
to the India State of Forest Report, 2023, the North
Eastern Region recorded a decline of 327.30 square
kilometres in forest cover. These environmental
challenges directly impact the region's progress on
SDG 13 (Climate Action), SDG 15 (Life on Land), and
SDG 12 (Sustainable Consumption and Production).
Preserving the region's unique ecosystems is not
merely an environmental concern but has profound
implications for sustainable livelihoods, water secu-
rity, and disaster resilience. In response, all North
Eastern states have established climate change
monitoring cells, and states like Assam have intro-
duced policy measures such as a "green tax" on old
vehicles to encourage more sustainable practices.
The complexity of these interconnected challenges
underscores why the SDG framework is particularly
valuable for the NER, offering a comprehensive
approach that addresses these multidimensional
issues while recognizing the importance of preserv-
ing the region's unique cultural identity and envi-
ronmental heritage.
1.2. State Initiatives to Accelerate and
Localize SDGs in the North Eastern Region
Arunachal Pradesh
Arunachal Pradesh prepared its draft SDG 2030
vision report in 2016, with targets for most SDGs to
be achieved by 2019, 2022 and 2030. The document
is a comprehensive plan of action to achieve the
targets by setting baseline data and strategies to
achieve the SDGs. Government of Arunachal Pradesh
held its first SDG workshop in December 2018 with
UNDP. The Planning and Investment Division of
Finance, Planning and Investment Department is the
nodal department for implementing and monitoring
SDGs in the State, and the Secretary (Planning and
Investment) is the state nodal officer.
The Arunachal Pradesh SDG Dashboard is an effort
by the Department of Planning and Investment,
Government of Arunachal Pradesh, to track and
monitor the implementation of the different poli-
cies to achieve the SDGs. A geographic map and
heatmap feature have been developed on the dash-
board to facilitate the overall monitoring of the
status of SDGs in each district of the State. The
State has also launched the CM Dashboard with
E-Jan Bhagidari – a web portal and mobile app for
citizens' feedback and real-time monitoring of SDGs
as part of the 2022 budgetary allocation.
The state’s planned budget allocation is linked to
the SDGs, and every year, an effort is made by the
Finance, Planning & Investment Department to
review the outcomes of the plan funds and necessary
corrective measures are being made based on the
outcomes visible in the reports.
42023-24NER DISTRICT SDG INDEX
Assam
Assam was one of India's first states to adopt the SDGs
into its policy processes. In 2016, the Government
of Assam established a Centre for Sustainable
Development Goals (CSDGs), a dedicated think tank
that provides research and technical support while
also promoting awareness of SDGs among the stake-
holders and across all levels of governance. It also
guides all the departments of the State on matters
related to SDGs. In 2016, the state launched "Vision
2030", outlining the state's aspirations for holistic
development, with a strong emphasis on preserving
biodiversity as a foundation for both sustainability
and economic progress. Since May 2016, strategic and
action plans were formulated for each department
under the Transformation & Development Department's
guidance, culminating in the publication of "Assam
Agenda 2030" in April 2018. The document provided
a framework to achieve Assam vision 2030 with the
support of different stakeholders in the State, empha-
sizing the importance of the involvement of public
servants, citizens, communities, different tiers of the
local Government, and members of the civil society.
The Transformation and Development Department
serves as the nodal department for monitoring the
progress of the SDGs. To support this mandate, 10
working groups were constituted. Eventually, 10 work-
ing groups were formed to plan and follow through
with achieving the SDGs within the specified time
period. In February 2020, the state published its
comprehensive State Indicator Framework and District
Indicator Framework.
In January 2023, the T&D Department established
a Project Management Unit (PMU) emphasizing the
state's commitment to effective implementation.
Throughout 2023, sensitization sessions, consultations,
and data cleaning processes were conducted, culmi-
nating in the Assam SDG State Indicator Framework
1.0, offering a comprehensive strategy for monitoring
progress and fostering holistic development aligned
with Target 2030. The report encompasses data for
the baseline year (2019-20) and the current year
(2022-23) for 267 indicators with targets for 2030. It
serves as a vital tool for the state to assess its progress
across 16 out of 17 SDGs (excluding Goal 14) over the
specified time period.
Assam has introduced many innovative schemes at
the local level to accelerate the SDGs. For example,
the Chief Minister's Atmanirbhar Asom Abhiyan aims
to generate employment opportunities in the state
through the setting up of new entrepreneurial ventures.
The Chief Minister's Samagara Gramya Unnayan
Yoajana Samagra Gramya Unnayan Yojana (CMSGUY,
also known as the Integrated Village Development
Programme), is an initiative aimed at the holistic devel-
opment of villages, and the programme is expected
to help the State achieve several of the Global Goals.
The Government of Assam has identified 270 state
indicators and 142 district indicators based on MoSPI's
guidelines. An SDG Strategy Support Group (SSSG)
was set up to support strategic thinking and integrated
implementation and oversee SDG-related activities
such as data collection and analysis. SSSG is chaired
by the Chief Secretary of the State, with key state
Government officials as members.
Manipur
Manipur developed its Vision 2030 document:
"Ensuring no one is left behind", in 2019, by consid-
ering the developmental needs and aspirations of the
State. Preparing the preliminary draft vision document
for Manipur was entrusted to the Centre for Study of
Social Exclusion and Inclusive Policy (CSSEIP) under
Manipur Central University. The Planning Department
is the nodal department for implementing SDGs in the
State. UNDP also collaborated with the Government
of Manipur on finalising the Vision Document.
Three committees have been constituted at the state
and district levels to monitor and implement the poli-
cies and programmes to achieve the SDG vision. The
Chief Secretary chairs the State Committee on SDGs,
and it monitors the targets, goals and achievements
of the SDGs biannually. The inter-departmental work-
ing group is chaired by the Administrative Secretary
(Planning), and its role is to carry out mapping and
re-aligning targets of the various centrally sponsored
schemes in line with the goals of the SDGs, as well
as to develop a suitable State Indicator Framework
in line with the National Indicator Framework. The
district-level working group is the third committee
and is chaired by the Deputy Commissioner of each
district. The function of this committee is to re-align
targets and monitor achievements of the targets and
goals at the field level.
The Planning department of the Government of
Manipur has also developed the State Indicator
Framework, which includes 15 SDGs with 108 indica-
tors. The Government of Manipur has encouraged the
participation of all relevant stakeholders in framing
policies for achieving the vision of the SDGs in the
State. Manipur University has organised state level
consultations involving nodal officers from about 35
departments. Public consultations were also organised
to bring on board members of civil society, academia
and citizens to understand the needs of the people at
the grassroots and to rank the SDGs in order of priority.
5
CONTEXT & OVERVIEW
Meghalaya
The Government of Meghalaya formed an SDG cell at the
State level in 2018 to coordinate the preparation of the
draft "Meghalaya Vision 2030" document and the imple-
mentation of SDGs in the State. The nodal department
for implementation and monitoring of the SDGs is the
Planning Department. Meghalaya has developed its SDG
monitoring framework along the lines of MoSPI's indicator
framework. The State Indicator Framework consists of
195 indicators, of which data for 130 indicators are also
included in the District Indicator Framework and 29 Block
Level Indicators.
In November 2024, an SDG Localisation kick-off work-
shop was conducted in Meghalaya organized by NITI
Aayog, the Government of Meghalaya and GIZ under the
Green and Sustainable Development Partnership (GSDP)
Support Project. The GSDP-NITI project aims to enhance
the implementation and monitoring of SDGs at the sub-
national level through setting up SDG Acceleration Centre
in States. In this event, the Government of Meghalaya has
launched its application and data dashboard to facilitate
sustainable way of data collection. The mobile application
allows stakeholders to easily access and input SDG related
data. Simultaneously, the collected data is available for
further use through a well-designed district-wise dash-
board. Integrated within the Chief Minister’s overarching
dashboard, it reflects progress and composite scores for
all 12 districts. The Hon’ble Chief Minister of Meghalaya
announced, “CM Catalytic Fund Phase 2” in November
2024 building on the success of Phase 1, which saw a
yearly disbursement of INR 10 crores in financial support
to districts for improvement of SDGs.” This fund, designed
to address financial constraints at the grassroots level,
signifies a departure from the traditional tied-fund model.
During phase II, districts that fall into the large and small
district categories would receive a yearly allocation of
₹ 12 crores. This fund comes in the form of ₹ 4 crores in
performance-based incentives and ₹ 8 crores in untied
funds. It empowers DCs to initiate projects and interven-
tions tailored to the needs of the districts. By doing so, the
initiative aims not only to alleviate financial constraints but
also to catalyze a bottom-up approach towards enhancing
SDG performance. In 2022, the Government of Meghalaya
set aside INR 9,182 crores for funding SDGs as part of its
annual budget for 2022–23. The DC Connect platform
has also been launched to track grassroots progress,
address grievances, and monitor key development metrics
through real-time dashboards. Districts are ranked quar-
terly, with top Performers receiving additional incentives
of up to ₹ 25 lakh (large districts) and ₹ 12.5 lakh (small
districts), ensuring accountability and fostering impactful
interventions.
Mizoram
Mizoram adopted State Vision 2030, a document which
outlines the targets, strategies and budgetary allocations
to achieve the SDGs in the State. The vision document
has set targets for 2019–20, 2024–25 and 2029–30. The
Planning & Programme Implementation Department is
the Nodal Department for implementing the SDGs. The
Government has set up different bodies and committees
to monitor the implementation of the policies at different
levels. The Chief Secretary chairs the high-level moni-
toring committee to review and monitor progress. The
technical committee on SDGs is chaired by the Director
of the Economics & Statistics Department to identify indi-
cators and update data on the progress made on SDGs.
All Nodal Officers of Line Departments are members of
this technical committee. An SDG Cell has been set up
in the Research & Development Branch of the Planning
& Programme Implementation Department headed by
the Principal Adviser.
The Government of Mizoram has developed the
Consolidated Indicator Framework (CIF) comprising of
93 indicators to monitor the progress of 11 districts on
SDGs. The District Planning Committee (DPC), chaired
by the Deputy Commissioner, monitors and reviews the
progress of implementation of the SDGs at regular inter-
vals. The Village Level Monitoring Committee, chaired by
the President/Chairperson of the Village Council or Local
council, is the local layer of the monitoring framework
in Mizoram and is responsible for monitoring the SDGs
implementation at the village level.
The SDG website for Mizoram, under the Planning &
Programme Implementation Department, is an online
platform that allows users to access the SDG vision for
the State, essential documents and state policies on SDGs,
the latest state and district indicator frameworks and
the initiatives undertaken by the Government to achieve
the SDGs in the State. The state has released a report
on ‘Localisation of Sustainable Development Goals in
Mizoram’ in August 2023. The state government has part-
nered with UNDP and has developed an SDG Dashboard
for monitoring of SDGs at state, village, ULB and village
levels which was launched in 2024. In November 2024,
the Government of Mizoram, in partnership with UNDP
organised a consultation on accelerating sustainable
development in Mizoram with CSOs and CSR entities in
Bangalore to network and create partnerships with poten-
tial partners for fast-tracking sustainable development
in the state. The Government in partnership with UNDP
is also in the process of creating a CSR Matchmaking
Platform to facilitate the same.
Nagaland
The Government of Nagaland launched the "Nagaland SDG
vision 2030" and "District SDG Localisation and Integration
Manual" in 2021. The document contains state-specific
short, medium and long-term targets with measurable
indicators and strategies that the State should adopt
to meet the developmental aspirations of the State and
62023-24NER DISTRICT SDG INDEX
the needs of the people while embracing sustainability.
It has also finalised the State Indicator Framework with
125 indicators and the District Indicator Framework with
130 indicators.
The Planning & Coordination Department is the nodal
department for SDGs. The State has also established
a High-Level Steering Committee headed by the Chief
Secretary for monitoring, policy review and course correc-
tion. The State has set up a Sustainable Development
Goals Coordination Centre (SDGCC) under the Planning
and Coordination Department, with the support of UNDP,
to streamline and coordinate the different departmental
activities and provide a more holistic environment for
the Government to carry out activities related to the
SDGs. SDG cells have also been created in all the related
departments, and a nodal officer has been nominated to
monitor the progress.
The SDG Coordination Centre (SDGCC), under the
Government of Nagaland has hosted ‘SDG One Stop
Destination’ – an immersive experience for increased
awareness on SDGs at the annual Hornbill Festival since
2021. The inclusion of 'Interaction with Differently Abled
Children' as part Hornbill Festival 2023 significantly
contributed to fostering inclusivity and deepening the
understanding of diverse abilities. The state also hosts SDG
Action Awards. This Award seeks individuals, organisations,
and institutions that inspire, empower and connect people
to drive action towards a more sustainable future through
their actions. The state organises several events like SDG
poster making, essay competitions and online quizzes to
sensitise the youth on SDGs. The SDGCC Nagaland annu-
ally organises SDG Innovation and Participatory Action
Research initiative to scale up grassroot innovations for
strengthening SDG localisation. The SDGCC has also
developed the Nagaland SDG Dashboard to track the
progress of the state and its districts on the indicators
under each SDG. In 2024, the SDGCC Nagaland released
a coffee table book titled “Weaving Dreams-a tribute
to the Inspiring Women of Nagaland”, celebrating the
contributions of 21 pioneering women of the state in
various fields of development, showcasing Nagaland’s
commitment towards Gender Equality.
Sikkim
Sikkim has developed and adopted its SDG Vision 2030,
which has identified the challenges, opportunities, and
strategies to meet the SDGs. The paper draws attention to
sustainable consumption, market expansion and livelihood
development, with a particular emphasis on sustainable
tourism, health and education.
The Planning and Development Department is the nodal
Department for the implementation of the SDGs, and the
Directorate of Economics, Statistics & Monitoring within
the Planning and Development Department is the nodal
Department for monitoring SDG implementation, report-
ing the progress on SDGs and identifying areas which
require mid-course corrections. The State has prepared
its State Indicator Framework based on 14 relevant SDGs.
The Government of Sikkim has involved various stake-
holders in discussions and consultations on SDG policies.
Subsequently, it outlined the concerns of the community
and industrialists and ways to mitigate and address them.
The Government also released "The Sikkim Action Plan
on Climate Change" report, which outlined the threats
to Sikkim's biodiversity and rural communities because
of climate change, and proposed actions to be taken to
address the challenges.
Tripura
In 2019, Tripura adopted its 2030 Vision Document. The
Planning (Economics & Statistics) Department is the
nodal agency in the State for SDG implementation in the
State. Tripura has four Working Groups for SDGs – social;
economic; environmental; peace, justice and partnership.
The State government has accorded highest priority for
development efforts in infrastructure, connectivity, agricul-
ture, safe drinking water, power, health and education. The
Planning Department is tasked to bring all departments
together in achieving the Goals and targets.
Tripura finalised its State Indicator Framework compris-
ing of 172 indicators and District Indicator Framework
comprising of 79 indicators in February 2020. The high-
level monitoring committee chaired by the Chief Secretary
streamlines the activities of all the State departments
of the Government to achieve the SDGs. This reflects a
"whole-of-government" approach for sustainable devel-
opment in the State. The State has spread awareness
about SDGs to the districts and panchayats. The Planning
Department has compiled the best practices covering
all major development sectors to achieve the SDGs.
The State is also taking steps to set aside resources for
SDG-based developmental projects. A vital feature of the
vision document of the State of Tripura is its emphasis on
"leaving no one behind", aligned with the foundational
vision of the SDGs and is creating specific strategies for
the scheduled tribe population in the State.
7
CONTEXT & OVERVIEW
METHODOLOGY
& RESULTS
II
2.1. Introducing the second NER SDG
Index – process, consultations with
the States
The successful uptake of the first edition of
the NER District SDG Index has resulted in the
preparation of the second edition. Following
the consultative process involving government
officials from eight states for the first NER SDG
Index, NITI Aayog took several steps to intensify
engagement from all eight North East States for
the second edition as well. These include:
•
Actively sought feedback and clarifications
on queries on the NER District Indicator
Framework from all eight NER States;
•
Organised eight in-person SDG consulta -
tions in collaboration with UNDP and the
respective State Governments across State
capitals of the NE States to address State
specific challenges and to encourage greater
engagement and discussion with various State
departments; and
•
Supported all the North-Eastern states in
developing capacity to collate information
and progress monitoring.
The consultations were highly participatory and
chaired by the Chief Secretary or Additional Chief
Secretary of the State with representatives from
State Government departments and the district
administration. During these consultations, officials
were briefed on the NER District SDG Index and
their State performance in the previous edition,
highlighting data gaps, resolving data discrep-
ancies and receiving feedback on the proposed
indicators. The state-wise consultations provided
a space for direct interaction and deliberation
between NITI Aayog, UNDP and the concerned
State and district-level officials for fast resolution
of any data-related issues to ensure quality and
reliable data. It provided a space for the resolu-
tion of data issues, addressing State-specific data
challenges, especially definitional challenges and
data periodicity. As a result, States could provide
reliable, timely and quality data.
Consequently, the States shared data, and the
resolution of any challenge that arose was
addressed by coordinating with the concerned
departments of the State Government. Following
this process, Goal-wise and composite district
scores and rankings were computed. Subsequently,
deliberations were held between NITI Aayog and
MDoNER and the report writing, preparation, and
review were undertaken.
The second edition of the NER District SDG
Index adopts a more participatory and inclusive
approach, fostering greater ownership of the SDGs
among State departments and governments. This
process has enabled better data reporting and
timely data collection.
The Index provides an overall view of the social,
economic and environmental aspects of the NER,
while reflecting the progress made by the states
and their districts. Despite a history of under-
development, political uncertainties, insurgency
and emerging ecological concerns, the NER is
striving to do well. The North-East focused SDG
Index will closely monitor the efforts and achieve-
ments and highlight critical gaps in the region and
METHODOLOGY AND FRAMEWORK
OF THE NORTH EASTERN REGION
DISTRICT SDG INDEX
CHAPTER 2
METHODOLOGY & RESULTS
13
serve as a helpful trigger for ramping up targeted
development initiatives by the Central and State
Governments.
2.2. Objectives
The objectives of the NER SDG Index 2.0 are to:
•
Rank the districts of the eight NER States
based on their relative performance across
the 15 SDGs (excluding Goal 14 which is not
applicable and Goal 17 for its limited applica-
bility at the district level).
•
Identify critical gaps and challenges in perfor-
mance and achievements to strategize neces-
sary corrective measures.
•
Highlight intra-state and inter-state disparities
across the eight states, facilitating the design
of suitable interventions.
•
Promote competitive federalism by enabling
state-wise, district-wise, and SDG-wise
comparisons. The ranking system also serves
as a valuable tool for peer learning and perfor-
mance improvement.
•
Create a platform for collaboration and enable
districts to share and adopt best practices
from their peers.
•
Identify data gaps in the statistical system
of the States and the sectors in which robust
and more frequent data collection needs to
be instituted.
2.3. Selection of indicators
As the first step, suitable indicators from the
National Indicator Framework, SDG India Index,
and the State Indicator Framework developed
by each North Eastern State were identified and
mapped with the targets. Guided by these indi-
cator frameworks and based on extensive consul-
tations with all eight NER States, NITI Aayog
prepared a list of 84 indicators, refining them
wherever needed to aid comparison. To determine
suitable metrics for inclusion in the Index, techni-
cally sound indicators based on valid quantitative
criteria were chosen that had:
i. Relevance to the SDG targets
ii. Alignment with the NIF, SDG India Index, and
the SIFs of the NER States
iii.
Data availability at the district level for most
of the 131 districts, from the official statistical
systems
iv.
The consent of the respective State
departments
v.
Data ownership, either administrative minis-
tries/departments at the Centre, survey-de-
rived, or by the line departments in the States
vi.
Due to prevailing data gaps, a threshold of
data availability of at least 80 percent of the
State-reported indicators for any given district
was taken as the benchmark for the computa-
tion of scores. Districts that reported data for
less than this number have been mentioned
but not included in the ranking scheme, to
avoid giving any undue advantage to them.
Therefore, 121 out of the total 131 districts have
been considered for computation and ranking.
All the States, especially with newly created
districts, are encouraged to report the data for
all possible indicators in the future for maxi-
mum utility of the Index.
vii.
Sufficient data coverage, such as data for at
least 70 percent of the districts is available for
any given indicator based on its applicability.
2.4. Target setting
A suitable target value for 2030 was set for each
indicator in one of the following ways:
i.
Identifying a quantifiable national target spec-
ified by the Government of India or
ii.
Selecting a quantifiable target specified under
the SDG framework for 2030 or
iii.
Determining a quantifiable target accepted
scientifically or set by technical standards or
iv.
Computing the average of the values from
the top five scores of the base year (year
2015 or NER SDG Index 2021-22, whichever
is available).
2.5. Normalisation of raw indicator values
Normalising indicator values to a standard scale of
0 to 100 was necessary to ensure comparability,
as different indicators had different ranges of
values. For instance, while Infant Mortality Rate
(IMR) is per 1,000 live births, the poverty rate
is measured as a percentage. In the normalised
range of 0 to 100, where 0 indicates the lowest
142023-24NER DISTRICT SDG INDEX
performance and 100 implies that the target has
been achieved.
For indicators where a higher value means better
performance, for example, the proportion of insti-
tutional deliveries, the following formula was used:
Where, x = raw data value
min(x) = minimum observed value of the indicator
in the dataset
T(x) = target value for the indicator
x’ = normalised value after rescaling
For indicators where the higher value implies
lower performance, for instance, IMR, the following
formula was used:
Where, x = raw data value
max(x) = maximum observed value of the indi-
cator in the dataset
T(x) = target value for the indicator
x’ = normalised value after rescaling
Where the districts had achieved beyond the
target set, the normalised score was capped at 100.
2.6. Computation of district scores
Post normalisation of values, the district-wise
score for each Goal was computed. According to
the following formula, this was estimated as the
arithmetic mean of the normalised values of all
indicators under the Goal for each district. Equal
weight was assigned to each indicator.
Where Iij= Goal score for district i under SDG j
Nij= number of non-null indicators for district I
under SDG j
Iijk= normalised value for district i of indicator k
under SDG j
The Goal score Iij for district i under Goal j was then
computed. Based on the Goal score, the districts
were classified into four categories under each
Goal. Achiever: when the Index score equals 100;
Front Runner: when the Index score is between
65 and 100, excluding 100; Performer: when the
Index score is between 50 and 65, excluding 65;
Aspirant: when the Index score is less than 50.
2.7. Computation of composite score
The next step was the computation of composite
score for every district. The composite score is the
arithmetic mean of the Goal score for 14 Goals
1
,
for each district, assigning equal weight to each
Goal. This score is indicative of the overall position
of a district in its journey towards achieving the
SDGs. The districts were again classified into the
four categories based on their composite score
according to the following formula:
Where Ii= composite SDG index score of district i
Ni = number of Goal scores for which district I
has non-null data
Iij= goal score for district i under SDG j
Iijk= normalised value for district i of indicator k
under SDG j
2.8. Categorisation of districts
Given the reach of SDGs across a multitude of
social, political and economic spheres of life as
well as the depth of each Goal through the numer-
ous varying targets and the complex inter-relation
and interdependencies between each Goal, it is
an extremely complicated task to set up scien-
tific classes of performance for each Goal and
to tie them together. Hence, a clean and simple
mechanism of classification was adopted based
on the score of each district across the SDGs. The
districts were classified into the four categories
namely, Achiever, Front Runner, Performer and
Aspirant in accordance with their distance from
target and the category-specific score range
given above.
METHODOLOGY & RESULTS
15
1
Only districts with an Urban Local Body/Administration were considered for computing scores in Goal 11. As a result, Goal 11 scores were generated for
only 79 of the 131 districts; therefore, this Goal is not part of the computation of the overall composite score of a district. The index is guided by India's
National Indicator Framework (NIF) on SDGs. The NIF indicators on SDG 17 at present are relevant only at the national and state levels. Therefore, Goal 17
is not part of this quantitative exercise to measure district performance. Goal 14 pertains only to the marine ecosystem and is therefore not applicable.
2.9. Limitations of the Index
While the SDG NER Index is a useful instrument to
measure the progress of NER districts in adopting
and implementing the SDG agenda, the Index has
the following limitations:
i.
There is limited comparability to the SDG India
Index. The indicator sets used for the two indi-
ces are necessarily different since some indi-
cators used in the NER index are specific to
the region and are not highly relevant to other
states of the country.
ii.
The indicators and data from non-government
sources have not been included in the interest
of data comparability and uniformity. Of the
84 indicators considered for computation-
49 percent have been sourced from Union
Ministries and national-level surveys, and 51
percent from State sources.
iii.
For some indicators, data for all districts are
not available or applicable. In computing the
Index, "null" value has been assigned to these
indicators, which have not been included in
the computation.
iv.
Some recently created districts in some states
could not be included in the analysis due to
the unavailability of data for most identified
indicators.
v. If district level data was furnished for at least
80 percent of State sourced indicators, it was
considered for computation. Therefore, 121
districts out of 131 were considered for ranking
(Refer to the next page for the complete list of
districts considered for ranking).
vi.
Only districts with an Urban Local Body/
Administration were considered for comput-
ing scores in Goal 11. As a result, Goal 11 scores
were generated for only 79 of the 131 districts;
therefore, this Goal is not part of the compu-
tation of the overall composite score of a
district. The index is guided by India's National
Indicator Framework (NIF) on SDGs. The NIF
indicators on SDG 17 at present are relevant
only at the national and state levels. Therefore,
Goal 17 is not part of this quantitative exercise
to measure district performance.
2.10 Policy relevance and utility of the index
• The NER District SDG Index underscores the
importance of embedding data-backed find-
ings and analysis in the planning and deci-
sion-making processes at the level of states
and districts for targeting geographies in clos-
ing sectoral developmental gaps.
•The index provide a tool for integrating data-
based decision making by providing infor-
mation and insights which is horizontally
expansive in terms of sectors (SDGs 1–16) and
disaggregated at the level of the district to
push for balanced regional planning.
•
The index also brings focus to outcome-based
targeting, which goes beyond measuring
performance only as a function of the capacity 2023-24NER DISTRICT SDG INDEX Identified indicators fr om NIF/SD G India Inde x based on
state-wise acceptability and data availability
Rescaled each indicator; 0 denoting the lowest performance
and 100 denoting target achievement
Adopted equal weights for each indicator in line with the
internationally accepted practices
Computed each Districtss aggregate score by calculating
arithmetic mean of normalised values of all indicators
Aggregated Districts overall SDG Index score by
averaging all Goal Scores
1
2
3
4
5
Iden W L F D W L R Q
Normalisation
Weightage
Individual Goal Score
Composite Score
Figure D. Methodology -5 Steps of Computation
16
to spend allocated budgets for schemes. This
would encourage the mapping of expendi -
ture to identified gaps, and desired outcomes
to plug those gaps in order to reach out to
districts in need of budgetary allocation in a
particular sector.
•
The granular analysis provided by the NER
District SDG Index enables states to identify
specific sectors in which immediate improve-
ments can be made. By leveraging existing
government schemes and programmes, state
administrations can address the challenges
highlighted by the Index effectively. The Index
can thus act as a critical tool to guide states
in prioritising resources and directing their
efforts towards reaching out to populations in
need. States may take a regional approach to
integrate the Index into their planning process,
and identify which districts are performing
well and which are lagging behind. This can
help in devising targeted strategies to improve
outcomes across the region.
•
As a first step, at the NER or State level, the
bottom performing districts (bottom 30
percent) can be filtered for further analysis.
The goal level scores of districts, especially
those in the Aspirant (0-49) category, would
be critical to identify the broad sectors, for
example, a score of 41 in Goal 4 would neces-
sitate a closer look in the education sector for
a district. In other words, identifying the goals
in which a district has not performed well and
then following it up with a deep dive analysis
of individual indicators to truly show the gap.
This approach can help in gaining a deeper
understanding of the challenges faced by
districts and enable targeted interventions to
address the root cause of underperformance.
• By mapping the performance at the indica-
tor level to existing government schemes and
programmes, policymakers can assess the
effectiveness of these programmes and chart
a course of implementation-related action.
This approach can help in identifying the gaps
between the intended impact of government
schemes and their actual outcomes on the
ground. By addressing these gaps, policy-
makers can improve the effectiveness of the
programmes and accelerate progress.
17
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Arunachal
Pradesh (25)
Anjaw
Changlang
Dibang Valley
East Kameng
East Siang
Kamle
Kra Daadi
Kurung Kumey
Leparada
Lohit
Longding
Lower Dibang Valley
Lower Siang
Lower Subansiri
Namsai
Pakke Kessang
Papum Pare
Shi Yomi
Siang
Tawang
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam (33)
Baksa
Barpeta
Biswanath
Bongaigaon
Cachar
Charaideo
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Hojai
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Majuli
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
South Salmara Mankachar
Tinsukia
Udalguri
West Karbi Anglong
Manipur (16)
Bishnupur
Chandel
Churachandpur
Imphal East
Imphal West
Jiribam
Kakching
Kamjong
Kangpokpi
Noney
Pherzawl
Senapati
Tamenglong
Tengnoupal
Thoubal
Ukhrul
Tripura (8)
Dhalai
Gomati
Khowai
North Tripura
Sepahijala
South Tripura
Unakoti
West Tripura
Sikkim (6)
Gangtok
Gyalshing
Mangan
Namchi
Pakyong
Soreng
Nagaland (11)
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Meghalaya (11)
East Garo Hills
East Jaintia Hills
East Khasi Hills
North Garo Hills
Ri Bhoi
South Garo Hills
South West Garo Hills
South West Khasi Hills
West Garo Hills
West Jaintia Hills
West Khasi Hills
Mizoram (11)
Aizawl
Champhai
Hnahthial
Khawzawl
Kolasib
Lawngtlai
Lunglei
Mamit
Saitual
Serchhip
Siaha
TABLE A. 121 OUT OF 131 DISTRICTS CONSIDERED FOR COMPUTATION AND RANKING
Arunachal
Pradesh (2)
Bichom
Keyi Panyor
Assam (2)
Bajali
Tamulpur
Nagaland (5)
Chumoukedima
Niuland
Shamator
Tseminyu
Noklak
Meghalaya (1)
Eastern West Khasi
Hills
Manipur
All districts included
in computation and
ranking
Sikkim
All districts included
in computation and
ranking
Tripura
All districts included
in computation and
ranking
Mizoram
All districts included
in computation and
ranking
10 OUT OF 131 DISTRICTS NOT CONSIDERED FOR COMPUTATION
METHODOLOGY & RESULTS
19
Table B. Goal-wise Top* Districts
SDG 5 Gender Equality
Saitual [MZ], Wokha [NL], Mokokchung
[NL], Longleng [NL], Zunheboto [NL]
SDG 6 Clean Water and Sanitation
Saitual [MZ], Serchhip [MZ], Champhai
[MZ], Lower Dibang Valley [AR], Soreng
[SK], Lohit [AR], Leparada [AR]
SDG 8 Decent Work and Economic Growth
Lower Siang [AR], Kamrup Metropolitan [AS],
Lower Subansiri [AR], Gangtok [SK], Dimapur [NL]
SDG 7 Affordable and Clean Energy
Saitual [MZ], Soreng [SK], Leparada [AR],
Pakyong [SK], Khawzawl [MZ], Hnahthial [MZ],
Kakching [MN], Lower Siang [AR], Tengnoupal
[MN], Noney [MN], Kangpokpi [MN], Kamjong
[MN], Jiribam [MN], Pherzawl [MN]
SDG 13 Climate Action
Hnahthial [MZ], Mokokchung [NL], Khawzawl
[MZ], Phek [NL], Senapati [MN]
SDG 15 Life on Land
Hnahthial [MZ], Lower Dibang Valley [AR], Saitual
[MZ], Khawzawl [MZ], Longleng [NL], Peren [NL],
Jiribam [MN], Dima Hasao [AS], Gyalshing [SK],
Charaideo [AS], Tengnoupal [MN], Upper Siang
[AR], West Jaintia Hills [ML], Dibang Valley [AR],
Leparada [AR], Upper Subansiri [AR], Kamjong
[MN], Kiphire [NL], Kamle [AR], Kangpokpi [MN],
West Karbi Anglong [AS], Noney [MN], Lower Siang
[AR], Anjaw [AR], Siang [AR], Pherzawl [MN]
SDG 16 Peace, Justice and Strong Institutions
Kamjong [MN], Noney [MN], Hnahthial
[MZ], Pherzawl [MN], Kangpokpi [MN]
SDG 2 Zero Hunger
Champhai [MZ], Phek [NL], Kakching [MN],
South Tripura [TR], Lohit [AR], Siang [AR]
SDG 1 No Poverty
Mokokchung [NL], Gangtok [SK], Thoubal
[MN], West Tripura [TR], Saitual [MZ],
Imphal East [MN], South Tripura [TR]
SDG 4 Quality Education
West Tripura [TR], Dimapur [NL],
Gangtok [SK], Soreng [SK], East Siang
[AR], Kohima [NL], Pakyong [SK]
SDG 3 Good Health and Well-being
Upper Siang [AR], East Siang [AR],
West Siang [AR], Champhai [MZ],
Hnahthial [MZ], East Kameng [AR]
*Districts classified as "Top" are those that fall within top five rankings or have attained a score of 100.
SDG 10 Reduced Inequalities
South West Khasi Hills [ML], Pakke Kessang
[AR], East Kameng [AR], Dibang Valley [AR],
Kra Daadi [AR], East Jaintia Hills [ML]
SDG 9 Industry, Innovation and Infrastructure
Hnahthial [MZ], Champhai [MZ], West Tripura
[TR], Sepahijala [TR], Unakoti [TR], Nagaon [AS]
SDG 11 Sustainable Cities and Communities
Not considered in the composite ranking
SDG 12 Responsible Consumption
and Production
South Tripura [TR], Unakoti [TR], Gomati
[TR], Shi Yomi [AR], Kohima [NL]
202023-24NER DISTRICT SDG INDEX
All districts in Mizoram, Sikkim and Tripura fall in the Front Runner category, and there are no districts
in the Aspirant or Achiever category.
CHAPTER 3
The composite score for each district was computed
by aggregating its performance across the Goals
by taking the arithmetic mean of individual Goal
scores. The composite score ranges from 0 to 100
and denotes the district's overall achievement
in realising the targets under the Goals. A score
of 100 implies that the district has achieved the
targets set for identified indicators; a score of
0 implies that the district is at the bottom. Based on the
score, each district is categorised into one of the four
categories: i) Achiever: when the Index score equals
100; ii) Front Runner: when the Index score is between
65 and 100, excluding 100; iii) Performer: when the
Index score is between 50 and 65, excluding 65; iv)
Aspirant: when the Index score is less than 50.
3.1. Overall Performance
The index is computed for 121 districts – of which
103 districts are in the Front Runner category, and 18
districts are in the Performer category in the compos-
ite score and ranking.
•The score for the 121 districts ranges from 58.71 in
Longding [AR] to 81.43 in Hnahthial [MZ].
•Top 5 districts of the SDG NER Index are:
»Hnahthial [MZ] (score of 81.43),
»Champhai [MZ] (score of 79.86),
»Gomati [TR] (score of 78.79),
»Mokokchung [NL] (score of 78.43) and
»West Tripura [TR] (score of 77.64).
COMPOSITE RESULTS:
NER DISTRICT SDG
INDEX 2023-24
METHODOLOGY & RESULTS
Figure E. District Score Ranges among NER States
Mizoram
Nagaland
Arunachal Pradesh
Assam
Manipur
Meghalaya
Sikkim
Tripura
All Front Runner
Districts
Mixed Category
SDG Score
55 60 65
70 75 80 85
63.36
67.71 81.43
72.29 78.79
78.43
73.36
76.6471.14
58.71
59.71
74.29
73.0063.00
59.71
73.21
21
3.2. Key Insights
• Mizoram has the highest-scoring district in the
entire Northeast region (Hnahthial at 81.43)
and Arunachal Pradesh has the lowest scor-
ing district in the entire region (Longding
at 58.71).
• Nagaland exhibits widest range (15.07 points
between its highest and lowest performing
districts) indicating the significant intra-state
disparity. Sikkim has the narrowest range (5.5
points), showing the most consistent perfor-
mance across its districts.
• Tripura has the distinction of having some of
the highest-scoring districts with minimum
intra-state disparities (6.5 points).
•
Mizoram and Nagaland have some of the high-
est-scoring districts but also show significant
intra-state variation (ranges of 13.72 and 15.07,
respectively).
The districts with the highest and lowest ranks in each State are as follows:
•Arunachal Pradesh: Lower Dibang Valley
(Rank 23), Longding (Rank 121)
•
Assam: Dibrugarh (Rank 17), South Salmara-
Mankachar (Rank 118)
•
Manipur: Imphal West (Rank 24), Pherzawl
(Rank 118)
•
Meghalaya: East Khasi Hills (Rank 26), East
Jaintia Hills (Rank 114)
•Mizoram: Hnahthial (Rank 1),
Lawngtlai (Rank 86)
•
Nagaland: Mokokchung (Rank 4), Zunheboto
(Rank 110)
•
Sikkim: Gangtok (Rank 8), Gyalshing (Rank 49)
•Tripura: Gomati (Rank 3), Dhalai (Rank 33)
The top 10 districts have continued to perform well across SDG 9 (Industry, Innovation and Infrastructure)
, SDG 4 (Quality Education), SDG 15 (Life on Land), SDG 12 (Responsible Consumption and Production),
SDG 8 (Decent Work and Economic Growth), and SDG 5 (Gender Equality), with opportunities to accel-
erate further in SDG 3 (Good Health and Well-being) and SDG 10 (Reduced Inequalities).
Top 10 Districts
State District Score Rank
Mizoram Hnahthial 81.43 1
Mizoram Champhai 79.86 2
Tripura Gomati 78.79 3
Nagaland Mokokchung 78.43 4
Tripura West Tripura 77.64 5
Nagaland Kohima 76.93 6
Tripura South Tripura 76.71 7
Sikkim Gangtok 76.64 8
Mizoram Kolasib 76.50 9
Nagaland Dimapur 76.29 10
Table C. Top 10 Districts in NER District SDG Index 2023-24
222023-24NER DISTRICT SDG INDEX
The challenges among the bottom 10 districts pertain to SDG 9 (Industry, Innovation and Infrastructure),
SDG 10 (Reduced Inequalities), SDG 12 (Responsible Consumption and Production) and SDG 13
(Climate Change).
Bottom 10 Districts
State District Score Rank
Arunachal Pradesh Pakke Kessang 63.14 112
Arunachal Pradesh Anjaw 63.07 113
Meghalaya East Jaintia Hills 63.00 114
Manipur Tamenglong 62.07 115
Arunachal Pradesh Tirap 61.93 116
Arunachal Pradesh Siang 61.71 117
Assam South Salmara-Mankachar 59.71 118
Manipur Pherzawl 59.71 118
Arunachal Pradesh Kamle 58.86 120
Arunachal Pradesh Longding 58.71 121
• While the index summarises SDG-wise rela-
tive performance results, a closer look at key
indicators provides an in-depth view of the
challenges.
»The NER falls behind the national average in
the indicator on percentage of students in
grade 8 achieving the minimum proficiency
level in terms of nationally defined learning
outcomes as per the National Achievement
Survey (NAS) 2021. In the NER, 66 percent
of the districts have reported values less
than the national average (77 percent).
»Annual average dropout rate is an area
which requires attention. As many as 100
districts have an annual average dropout
rate at secondary level (Class 9–10) higher
than the India average of 14.1 percent as
per Unified- District Information System
for Education (UDISE) 2023–24. School
infrastructure remains a priority area with
significant scope for improvement.
»The NER has experienced a continuous
decline in forest area over the years, raising
significant environmental concerns. As per
the India State of Forest Report (ISFR)
2023, 72 districts reported a reduction
in forest cover compared to the previous
assessment in 2021.
Despite the challenges, significant improvements
have been observed in the indicators linked to the
National Family Health Survey (NFHS), such as
access to clean cooking fuel, housing, electricity,
sanitation, drinking water, bank accounts, child and
maternal health services, schooling and attend-
ance, birth registration, unmet need for family
planning, health insurance, among others. This
momentum will be key to closing the gap with the
national average in the short and medium term and
for states to feature among the top states in the
long term. An Increase in the proportion of districts
in the Front Runner category (overall score 65–99)
from 62 percent in the last edition to 85 percent in
this edition signifies the effect of national flagship
schemes and overall momentum and direction of
progress across goals and indicators in the NER.
In this context, indicator-level analysis is crucial
for identifying gaps and accelerating progress
at par and in the long term beyond the national
average, especially for targeting intra-region/state
disparities among districts.
»Access to clean cooking fuel as primary
source of energy for households has signif-
icantly improved in the region, however
about 75 percent of the districts fare below
the national average.
METHODOLOGY & RESULTS
Table D. Bottom 10 Districts in NER District SDG Index 2023-24
23
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE E: COMPOSITE SCORE AND RANK OF DISTRICTS IN THE NORTH EASTERN REGION
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100)
0 2010 4030 50 60 908070 100
District StateRank
Hnahthial MZ 1 81.43
Champhai MZ 2 79.86
Gomati TR 3 78.79
Mokokchung NL 4 78.43
West TR TR 5 7 7. 6 4
Kohima NL 6 76.93
South TR TR 7 76.71
Gangtok SK 8 76.64
Kolasib MZ 9 76.50
Dimapur NL 10 76.29
Aizawl MZ 11 76.07
Serchhip MZ 12 75.64
Saitual MZ 13 75.36
Namchi SK 14 75.21
Sepahijala TR 15 75.07
Khowai TR 16 74 . 6 4
Dibrugarh AS 17 74 . 29
Khawzawl MZ 17 74 . 29
North TR TR 17 74 . 29
Sivasagar AS 20 74 .0 0
Jorhat AS 21 73.79
Unakoti TR 22 73.71
Lower Dibang Valley AR 23 73.36
Imphal West MN 24 73.21
Phek NL 25 73.14
East Khasi Hills ML 26 73.00
Imphal East MN 27 72.93
Nalbari AS 28 72.86
Longleng NL 28 72.86
Goalpara AS 30 72.79
Mangan SK 31 72.50
Hojai AS 32 72.36
Dhalai TR 33 72.29
Siaha MZ 34 72.14
Peren NL 34 72.14
Tawa n g AR 36 72.07
Pakyong SK 37 72.00
Kamrup Metropolitan AS 38 71.86
Kakching MN 38 71.86
Soreng SK 38 71.86
Tinsukia AS 41 71.79
South West Garo Hills ML 41 71.79
Jiribam MN 43 71.64
Golaghat AS 44 71.50
West Garo Hills ML 44 71.50
Wokha NL 44 71.50
Lakhimpur AS 47 71.43
Thoubal MN 48 71.29
Gyalshing SK 49 71.14
Dima Hasao AS 50 70.93
East Siang AR 51 70.79
Lunglei MZ 51 70.79
Charaideo AS 53 70.71
Karimganj AS 54 70.64
Karbi Anglong AS 55 70.57
Morigaon AS 55 70.57
Tengnoupal MN 57 70.43
Dhemaji AS 58 70.21
Papum Pare AR 59 70.14
Sonitpur AS 59 70.14
Kamrup AS 61 70.07
Mon NL 62 70.00
Changlang AR 63 69.93
West Kameng AR 64 69.86
Cachar AS 65 69.79
Bishnupur MN 66 69.43
242023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE E: COMPOSITE SCORE AND RANK OF DISTRICTS IN THE NORTH EASTERN REGION
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100)
0 2010 4030 50 60 908070 100
District StateRank
Bongaigaon AS 67 69.36
Hailakandi AS 67 69.36
Ri Bhoi ML 69 69.29
Nagaon AS 70 69.21
Kurung Kumey AR 71 69.00
Namsai AR 72 68.93
Senapati MN 73 68.71
West Jaintia Hills ML 73 68.71
Ukhrul MN 75 68.64
Biswanath AS 76 68.50
Chirang AS 77 68.29
East Kameng AR 78 68.21
Mamit MZ 79 68.14
West Siang AR 80 68.07
Lohit AR 81 68.00
East Garo Hills ML 81 68.00
Dibang Valley AR 83 67. 93
Dhubri AS 84 67. 8 6
Upper Siang AR 85 67.79
Lawngtlai MZ 86 67.7 1
Darrang AS 87 67. 4 3
Leparada AR 88 67. 3 6
Majuli AS 88 67. 3 6
West Khasi Hills ML 88 67. 3 6
Upper Subansiri AR 91 67.1 4
Kokrajhar AS 91 67.1 4
South West Khasi Hills ML 93 67. 0 0
Barpeta AS 94 66.79
North Garo Hills ML 95 66.64
Kamjong MN 96 66.43
Baksa AS 97 66.29
Kiphire NL 98 66.07
Chandel MN 99 65.93
Lower Subansiri AR 100 65.86
South Garo Hills ML 101 65.79
Udalguri AS 102 65.71
Churachandpur MN 103 65.36
Kangpokpi MN 104 64.86
Tuensang NL 105 64.57
Noney MN 106 64.43
Lower Siang AR 107 64.14
West Karbi Anglong AS 108 63.86
Shi Yomi AR 109 63.43
Zunheboto NL 110 63.36
Kra Daadi AR 111 63.21
Pakke Kessang AR 112 63.14
Anjaw AR 113 63.07
East Jaintia Hills ML 114 63.00
Tamenglong MN 115 62.07
Tirap AR 116 61.93
Siang AR 117 61.71
South Salmara-Mankachar AS 118
Pherzawl MN 118 59.71
Kamle AR 120
Longding AR 121
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Niuland NL NA
Noklak NL NA
Shamator NL NA
Tseminyu NL NA
59.71
59.71
58.86
58.71
25
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A)
FIGURE F: PERFORMANCE OF DISTRICTS IN THE NORTH EASTERN REGION
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100) Not Available (N/A)
2023-24
2021-22
262023-24NER DISTRICT SDG INDEX
7.41%
(2 Districts)
5.71%
(2 Districts)
8.33%
(1 District)
33.33%
(9 Districts)
5.71%
(2 Districts)
59.26%
(16 Districts)
88.57%
(31 Districts)
25%
(4 Districts)
75%
(12 Districts)
83.33%
(10 Districts)
100%
(11 Districts)
100%
(6 Districts)
100%
(8 Districts)
8.33%
(1 District)
31.25%
(5 Districts)
56.25%
(9 Districts)
12.5%
(2 Districts)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim Tripura
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
Composite
Score
14.88%
2.48%
0.83%
4.96%
9.09%
0.83%
5.79%
6.61%
91.74%
14.05%
27.27%
14.88%
40.50%
1.65%
4.13%21.49% 74.38%
4.96% 71.90% 21.49%
7.44% 48.76% 3.31%
42.98% 42.15%
35.54%37.19%
0.83%
0.83%
9.09% 76.03%
7.44%
33.88% 47.93% 11.57%
94.21%
6.61% 92.56%
24.79% 66.12%
55.37% 39.67%
30.58% 68.60%
67.77% 29.75%
85.12%
Figure G. State-Wise Percentage of Districts in Each Performance Category
Figure H. Goal-Wise Percentage of Districts in Each Category
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100) Not Available (N/A)
METHODOLOGY & RESULTS
27
Goal 1 encompasses the aim of eradicating
poverty - not only in monetary terms but in all
forms and dimensions by 2030. This involves
targeting the most vulnerable, increasing
basic resources and services, and supporting
communities affected by conflict and
climate-related disasters. It calls for continuous
monitoring of progress in social protection and
implementing nationally appropriate social
protection systems. The importance of mobilizing
resources from a variety of sources, including
through enhanced development cooperation, is
also emphasized in this goal.
Targets
1.1 By 2030, eradicate extreme poverty for all
people everywhere, currently measured as
people living on less than USD 1.25 a day
1.2 By 2030, reduce at least by half the
proportion of men, women and children of
all ages living in poverty in all its dimensions
according to national definitions
1.3 Implement nationally appropriate social
protection systems and measures for all,
including floors, and by 2030 achieve
substantial coverage of the poor and the
vulnerable
1.4 By 2030, ensure that all men and women,
in particular the poor and the vulnerable,
have equal rights to economic resources, as
well as access to basic services, ownership
and control over land and other forms of
property, inheritance, natural resources,
appropriate new technology and financial
services, including microfinance
1.5 By 2030, build the resilience of the poor
and those in vulnerable situations and
reduce their exposure and vulnerability to
climate-related extreme events and other
economic, social and environmental shocks
and disasters
1.a Ensure significant mobilization of resources
from a variety of sources, including through
enhanced development cooperation, in
order to provide adequate and predictable
means for developing countries, in particular
least developed countries, to implement
programmes and policies to end poverty in
all its dimensions
1.b Create sound policy frameworks at
the national, regional and international
levels, based on pro-poor and gender-
sensitive development strategies, to
support accelerated investment in poverty
eradication actions
29
CONTEXT & OVERVIEW
SDG 1
NO POVERTY
End poverty in all its forms everywhere
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
The score for Goal 1 ranges between 78 and 47 for the
121 districts included in the ranking and computation.
Mokokchung [NL], Gangtok [SK], and Thoubal [MN]
are the top performing districts. 36 districts fall in the
category of Front Runners and 82 in the category of Performers, while 3 districts are in the category of
Aspirants with scores less than 50.
NER District SDG Index: Goal 1
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
District StateRank
Mokokchung NL 1 78
Gangtok SK 2 77
Thoubal MN 3 74
West Tripura TR 4 73
Imphal East MN 5 72
Saitual MZ 5 72
South Tripura TR 5 72
Kohima NL 8 71
Gomati TR 9 69
East Siang AR 10 68
East Garo Hills ML 10 68
Namchi SK 10 68
Kakching MN 13 67
Ri Bhoi ML 13 67
Dimapur NL 13 67
Mon NL 13 67
Pakyong SK 13 67
Sepahijala TR 13 67
Lower Siang AR 19 66
Upper Siang AR 19 66
Dibrugarh AS 19 66
Hojai AS 19 66
Nalbari AS 19 66
Sivasagar AS 19 66
Imphal West MN 19 66
Jiribam MN 19 66
Tuensang NL 19 66
Wokha NL 19 66
Khowai TR 19 66
West Kameng AR 30 65
Majuli AS 30 65
South West Garo Hills ML 30 65
Gyalshing SK 30 65
Soreng SK 30 65
Dhalai TR 30 65
Unakoti TR 30 65
Tawa n g AR 37 64
Barpeta AS 37 64
Chirang AS 37 64
Ukhrul MN 37 64
South West Khasi Hills ML 37 64
Aizawl MZ 37 64
Kiphire NL 37 64
Longleng NL 37 64
Phek NL 37 64
Mangan SK 37 64
North Tripura TR 37 64
Siang AR 48 63
Charaideo AS 48 63
Noney MN 48 63
East Khasi Hills ML 48 63
West Garo Hills ML 48 63
Serchhip MZ 48 63
Siaha MZ 48 63
Kra Daadi AR 55 62
Jorhat AS 55 62
Lakhimpur AS 55 62
Champhai MZ 55 62
Khawzawl MZ 55 62
Kolasib MZ 55 62
Tirap AR 61 61
FIGURE 1.1: SDG 1 INDEX SCORE OF DISTRICTS
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
302023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
District StateRank
Bongaigaon AS 61 61
Goalpara AS 61 61
Golaghat AS 61 61
Kamrup AS 61 61
Karbi Anglong AS 61 61
Morigaon AS 61 61
Nagaon AS 61 61
Sonitpur AS 61 61
South Salmara-Mankachar AS 61 61
Kamjong MN 61 61
West Jaintia Hills ML 61 61
Mamit MZ 61 61
Zunheboto NL 61 61
Changlang AR 75 60
Kurung Kumey AR 75 60
Lohit AR 75 60
Papum Pare AR 75 60
West Siang AR 75 60
Dhemaji AS 75 60
Kamrup Metropolitan AS 75 60
Kokrajhar AS 75 60
Hnahthial MZ 75 60
Lower Dibang Valley AR 84 59
Karimganj AS 84 59
Tinsukia AS 84 59
Tengnoupal MN 84 59
North Garo Hills ML 84 59
South Garo Hills ML 84 59
Lunglei MZ 84 59
Baksa AS 91 58
Cachar AS 91 58
Dhubri AS 91 58
Udalguri AS 91 58
Churachandpur MN 91 58
East Jaintia Hills ML 91 58
Dibang Valley AR 97 57
Dima Hasao AS 97 57
Hailakandi AS 97 57
Bishnupur MN 97 57
Darrang AS 101 56
Peren NL 101 56
Lower Subansiri AR 103 55
Biswanath AS 103 55
Kamle AR 105 54
Leparada AR 105 54
Upper Subansiri AR 105 54
Senapati MN 105 54
Anjaw AR 109 53
Namsai AR 109 53
Pakke Kessang AR 109 53
Chandel MN 109 53
Kangpokpi MN 109 53
Lawngtlai MZ 114 52
East Kameng AR 115 51
Shi Yomi AR 115 51
Tamenglong MN 115 51
Longding AR 118 50
West Khasi Hills ML 119 49
Pherzawl MN 120 48
West Karbi Anglong MN 121 47
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
FIGURE 1.1: SDG 1 INDEX SCORE OF DISTRICTS
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
31
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 1.2: PERFORMANCE OF DISTRICTS IN SDG 1
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
322023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
1.3
Percentage of beneficiaries covered
under National Food Security Act
(NFSA), 2013
100
NFSA, 2013 is a Government of India Act that aims to provide food
and nutritional security by ensuring access to an adequate quantity
of quality food at affordable prices. It is aimed that all persons
belonging to the eligible population under NFSA, 2013, benefit from
the Act.
1.2
Headcount ratio as per the
Multidimensional Poverty Index (%)
12.43
Global SDG target 1.2 aims to reduce at least by half the proportion
of men, women
and children of all ages living in poverty in all its dimensions
according to national
definitions. According to NITI Aayog's National MPI : A Progress Review
2023, the incidence of multidimensional poverty in India was 24.85%
for the year 2015-16.
Therefore, half of this value has been taken as the target.
1.3
Persons offered employment as a
percentage of persons who demanded
employment under Mahatma Gandhi
National Rural Employment Guarantee
Act (MGNREGA)
100
The mandate of the MGNREG Act is to provide at least 100 days
of guaranteed wage employment in a financial year to every rural
household whose adult members volunteer to do unskilled work
at the time and place provided by a Program Officer. Taking into
consideration possible attrition in the labour turnout due to reasons
such as ill-health, availability of alternate employment, climatic
factors etc., the target has been fixed to be the average of the 5 best
performing districts.
1.3
Percentage of Self-Help Groups
(SHGs) provided credit linkage
100
This target corresponds to global SDG targets 1.3 and 1.4 that
aims to implement nationally appropriate social protection systems
and measures for all, in particular the poor and the vulnerable, and
ensure equal rights to economic and financial resources including
microfinance.
1.3
Percentage of women receiving
benefits under Pradhan Mantri
Matru Vandana Yojana (PMMVY) or
any other maternity related State
schemes against target
100
PMMVY is a maternity benefit programme implemented in all districts
of the country since 2017 for the welfare of pregnant women and
lactating mothers. It is aimed that all persons belonging to the eligible
population under PMMVY and other maternity related State schemes,
benefit from the programme.
1.4
Percentage of affordable houses
completed against sanctioned (rural
+urban) under Pradhan Mantri Awas
Yojana (PMAY) and related State
schemes
100
This target corresponds to the global SDG target 1.4 that aims to
ensure that all men and women, in particular the poor and the
vulnerable, have equal rights to economic resources, as well as
access to basic services.
1.3
Percentage of households with any
usual member covered by a health
scheme or health insurance
100
This target corresponds to the global SDG target 1.3 which aims
to implement nationally appropriate social protection systems and
measures for all. Worldwide, the provision of some form of universal
health coverage is regarded as a basic component of social security.
1.3
Hospital beds empanelled under
Pradhan Mantri Jan Arogya Yojana
(PMJAY) or related State schemes per
10,000 eligible population
196.89
This target corresponds to the global SDG target 1.3 which aims
to implement nationally appropriate social protection systems and
measures for all. The target has been set as the average of the best
five scores
33
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
34Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 1.3 1.2 1.3 1.3 1.3 1.4 1.3 1.3
District
Percentage of
beneficiaries
covered under
NFSA
Head count ratio
as per the Multi-
Dimensional
Poverty Index
Persons offered
employment as
a percentage
of persons who
demanded
employment
under MGNREGA
Percentage
of Self-Help
Groups (SHGs)
provided credit
linkage
Percentage of
women receiving
benefits under PM-
MVY or any other
maternity related
State schemes
against target
Percentage of
affordable houses
completed against
sanctioned (rural
+urban) under
PMAY and related
State schemes
Percentage of
households with
any usual mem-
ber covered by a
health scheme or
health insurance
Hospital beds
empanelled
under PMJAY or
related State
schemes per
10,000 eligible
population
SDG 1
Arunachal Pradesh
Anjaw 100.00 13.09 99.98 1.20 9.17 100.00 17.5 8.23 53
Bichom Null Null Null Null Null Null Null Null *
Changlang 100.00 14.39 99.97 2.17 42.42 99.71 40.5 10.49 60
Dibang Valley 100.00 10.11 99.99 14.29 4.90 100.00 28.7 33.62 57
East Kameng 100.00 22.05 100.00 5.47 0.00 99.94 25.1 12.00 51
East Siang 100.00 8.11 100.00 8.33 96.00 100.00 30.5 30.49 68
Kamle 100.00 Null 99.99 1.19 21.43 99.23 Null 2.95 54
Keyi Panyor Null Null Null Null Null Null Null Null *
Kra Daadi 100.00 18.91 100.00 20.36 69.05 98.97 24.0 3.33 62
Kurung Kumey 100.00 11.14 99.98 8.85 60.58 99.07 13.4 14.01 60
Leparada 100.00 Null 100.00 7.74 9.20 99.23 Null 20.16 54
Lohit 100.00 12.39 100.00 14.78 31.25 100.00 31.9 15.24 60
Longding 100.00 20.97 99.98 0.00 3.87 97.42 23.8 7.95 50
Lower Dibang Valley 100.00 9.08 99.99 8.94 21.51 99.56 36.8 15.87 59
Lower Siang 100.00 Null 100.00 7.51 85.10 99.83 Null 8.44 66
Lower Subansiri 100.00 6.39 95.77 12.11 117.72 99.84 24.5 19.94 55
Namsai 100.00 22.11 99.99 7.32 6.82 99.25 30.9 12.48 53
Pakke Kessang 100.00 Null 100.00 8.37 0.00 100.00 Null 16.18 53
Papum Pare 100.00 13.76 99.99 3.99 33.19 99.70 26.9 57.22 60
Shi Yomi 100.00 Null 100.00 4.32 0.00 99.68 Null 6.18 51
Siang 100.00 9.15 99.89 4.13 84.38 85.61 26.1 27.06 63
Tawang 100.00 8.46 99.93 2.95 77.33 100.00 33.5 17.63 64
Tirap 100.00 14.78 99.98 1.36 66.67 99.75 30.8 4.51 61
Upper Siang 100.00 8.74 99.96 0.75 89.08 99.27 34.6 16.98 66
Upper Subansiri 100.00 19.71 100.00 3.72 26.28 99.35 21.5 5.69 54
West Kameng 100.00 4.74 99.93 7.23 73.61 100.00 38.3 15.81 65
West Siang 100.00 13.85 99.93 9.55 45.98 99.66 26.6 18.86 60
Assam
Bajali Null Null Null Null Null Null Null Null *
Baksa 94.11 15.60 99.89 18.32 47.96 81.43 69.0 4.05 58
Barpeta 94.62 19.12 99.92 39.87 70.78 98.00 58.9 12.17 64
Biswanath 88.50 22.09 99.91 34.74 66.17 78.62 68.4 7.15 55
Bongaigaon 92.81 17.39 99.95 31.72 69.38 96.51 57.6 12.99 61
Cachar 92.60 30.58 99.84 44.43 67.43 89.76 57.9 22.77 58
Charaideo 92.46 20.10 99.97 40.64 78.31 92.90
64.9 4.17 63
Chirang 94.22 16.79 99.88 40.15 84.83 82.05 61.5 4.04 64
Darrang 92.07 23.65 99.97 34.79 46.27 96.78 53.7 8.42 56
Dhemaji 93.63 13.73 99.99 38.48 46.35 78.56 66.8 9.53 60
Dhubri 94.17 26.02 99.91 35.94 49.71 96.38 59.4 11.78 58
Dibrugarh 90.72 12.26 99.94 48.36 77.97 91.28 58.8 53.33 66
Dima Hasao 90.02 13.62 99.69 22.17 60.32 84.14 61.9 25.27 57
Goalpara 92.27 18.34 99.88 44.09 51.93 94.41 71.1 12.69 61
Golaghat 91.19 14.60 99.96 40.15 60.02 82.79 69.3 15.40 61
Hailakandi 94.68 36.22 99.92 37.76 72.78 91.05 53.6 5.37 57
Hojai 93.63 14.13 99.89 44.77 72.05 93.29 67.4 17.49 66
Jorhat 92.07 11.49 99.85 43.36 65.53 86.14 60.1 16.83 62
Kamrup 92.50 12.71 99.96 37.21 58.05 93.96 47.0 18.81 61
Kamrup Metropolitan 88.49 5.63 99.89 34.11 46.69 67.12 45.5 156.82 60
Karbi Anglong 91.59 16.20 99.98 41.90 67.65 89.36 54.1 28.51 61
Karimganj 93.06 32.93 99.99 35.81 80.42 91.44 64.4 9.55 59
Kokrajhar 92.20 18.92 99.99 33.45 76.44 88.84 50.2 17.01 60
Lakhimpur 91.83 14.06 99.92 40.56 69.40 83.28 67.0 15.49 62
Majuli 91.79 14.41 99.93 47.61 100.90 78.52 60.8 8.67 65
Morigaon 94.49 22.46 99.96 30.88 75.57 87.14 62.5 4.42 61
Nagaon 93.58 20.84 99.83 40.16 64.18 93.64 59.4 14.25 61
Nalbari 93.27 11.24 99.96 39.35 91.09 90.70 52.5 18.22 66
Sivasagar 92.45 10.28 99.97 43.19 89.24 85.22 60.7 12.41 66
Sonitpur 88.32 19.94 99.91 39.24 92.96 85.11 66.9 22.03 61
South Salmara-Mankachar 95.69 28.24 99.74 14.93 82.54 97.82 68.2 3.68 61
Tamulpur Null Null Null Null Null Null Null Null *
Tinsukia 91.25 17.66 99.97 37.83 62.50 82.80 60.0 12.95 59
Udalguri 92.47 19.16 99.86 25.84 71.40 74.94 70.6 6.05 58
West Karbi Anglong 86.37 24.09 99.88 34.06 30.75 80.09 63.1 12.71 47
Manipur
Bishnupur 100.00 6.91 99.97 50.97 73.57 2.69 9.3 55.71 57
Chandel 100.00 14.74 99.51 1.32 7.78 17.82 16.1 750.85 53
Churachandpur 100.00 15.35 99.97 16.11 28.88 11.72 18.2 1928.35 58
Imphal East 100.00 5.19 99.92 97.43 70.98 8.35 7.0 548.90 72
Imphal West 100.00 2.12 100.00 9.01 98.68 8.30 15.7 516.60 66
Jiribam 100.00 Null 100.00 76.92 16.28 1.54 Null 2906.98 66
Kakching 100.00 Null 99.98 28.44 73.04 1.26 Null 688.51 67
Kamjong 100.00 Null 99.90 3.60 3.40 Null Null 369.69 61
Kangpokpi 100.00 Null 99.81 14.29 21.72 0.00 Null 166.26 53
Noney 100.00 Null 99.67 21.11 2.34 Null Null 322.06 63
Pherzawl 100.00 Null 98.99 0.00 1.73 10.93 Null 1302.08 48
Senapati 100.00 15.60 99.99 20.00 8.82
0.00 15.4 485.27 54
Tamenglong 100.00 18.50 100.00 8.28 3.34 2.97 16.8 493.10 51
Tengnoupal 100.00 Null 99.84 34.20 8.30 12.22 Null 404.17 59
Thoubal 100.00 7.46 99.99 70.33 86.25 19.35 19.1 206.60 74
Ukhrul 100.00 17.87 99.95 40.32 11.69 Null 17.0 632.41 64
TABLE 1.1: PERFORMANCE OF DISTRICTS ON SDG 1
35Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 1.3 1.2 1.3 1.3 1.3 1.4 1.3 1.3
District
Percentage of
beneficiaries
covered under
NFSA
Head count ratio
as per the Multi-
Dimensional
Poverty Index
Persons offered
employment as
a percentage
of persons who
demanded
employment
under MGNREGA
Percentage
of Self-Help
Groups (SHGs)
provided credit
linkage
Percentage of
women receiving
benefits under PM-
MVY or any other
maternity related
State schemes
against target
Percentage of
affordable houses
completed against
sanctioned (rural
+urban) under
PMAY and related
State schemes
Percentage of
households with
any usual mem-
ber covered by a
health scheme or
health insurance
Hospital beds
empanelled
under PMJAY or
related State
schemes per
10,000 eligible
population
SDG 1
Meghalaya
East Garo Hills 100.00 14.96 99.92 34.75 166.76 38.07 71.9 25.58 68
East Jaintia Hills100.00 43.79 100.00 59.66 73.02 27.59 74.1 16.19 58
East Khasi Hills 100.00 24.10 100.00 56.95 72.50 23.90 47.1 71.66 63
Eastern West Khasi Hills Null Null Null Null Null Null Null Null *
North Garo Hills 100.00 13.26 99.96 40.72 42.26 29.16 60.8 11.67 59
Ri Bhoi 100.00 31.67 99.95 76.46 113.86 34.28 66.8 20.13 67
South Garo Hills 100.00 9.77 100.00 58.16 14.03 12.64 79.5 20.48 59
South West Garo Hills 100.00 18.27 99.98 41.74 95.67 22.97 75.1 12.36 65
South West Khasi Hills 100.00 40.98 99.99 64.26 216.44 37.57 72.3 19.52 64
West Garo Hills 100.00 8.00 99.98 37.89 47.88 30.17 77.9 30.97 63
West Jaintia Hills100.00 52.08 99.99 74.53 236.31 34.47 65.6 26.35 61
West Khasi Hills 100.00 52.48 99.98 69.71 6.17 47.15 60.1 21.79 49
Mizoram
Aizawl 100.00 0.87 100.00 7.74 59.55 95.65 37.5 39.25 64
Champhai 100.00 1.51 99.90 16.52 35.64 79.40 64.9 15.24 62
Hnahthial 100.00 Null 100.00 4.17 0.00 83.73 Null 141.19 60
Khawzawl 100.00 Null 100.00 15.14 16.98 59.66 Null 160.43 62
Kolasib 100.00 5.25 99.98 12.72 22.79 95.18 61.1 17.27 62
Lawngtlai 100.00 21.63 100.00 5.42 11.98 80.02 31.3 23.65 52
Lunglei 100.00 5.15 99.98 4.87 18.21 93.01 46.5 22.91 59
Mamit 100.00 9.29 100.00 12.87 33.74 72.55 61.7 13.65 61
Saitual 100.00 Null 100.00 19.82 38.39 75.29 Null 216.88 72
Serchhip 99.12 3.30 99.99 16.18 46.74 82.91 58.8 21.15 63
Siaha 99.92 6.90 100.00 10.94 49.58 89.51 44.2 28.91 63
Nagaland
Chumoukedima Null Null Null Null Null Null Null Null *
Dimapur 100.00 7.23 99.35 92.54 104.98 19.86 5.7 80.06 67
Kiphire 100.00 28.19 99.30 95.55 100.00 51.23 8.8 41.65 64
Kohima 100.00 6.50 99.65 100.00 124.14 13.38 26.7 82.45 71
Longleng 100.00 26.90 99.91 96.62 95.61 7.66 38.3 28.08 64
Mokokchung 100.00 7.22 99.93 100.00 146.90 87.26 22.3 47.34 78
Mon 100.00 22.95 99.85 85.54 75.43 59.35 39.3 21.59 67
Noklak Null Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null *
Peren 100.00 17.46 98.85 77.20 79.90 12.98 5.4 34.67 56
Phek 100.00 17.28 99.30 96.33 100.80
11.59 24.9 32.07 64
Shamator Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null *
Tuensang 100.00 29.21 99.89 100.00 78.37 62.14 22.0 38.12 66
Wokha 100.00 11.99 100.00 100.00 80.43 16.01 20.6 40.06 66
Zunheboto 100.00 20.31 99.97 91.44 77.95 16.88 18.1 22.90 61
Sikkim
Gangtok 100.00 2.12 99.98 15.09 Null 96.20 29.9 592.12 77
Gyalshing 100.00 2.77 99.99 19.73 Null 98.88 19.9 44.52 65
Mangan 100.00 5.17 99.87 12.59 Null 100.00 24.5 33.14 64
Namchi 100.00 2.90 99.99 29.16 Null 94.85 20.8 66.50 68
Pakyong 100.00 Null 100.00 27.72 Null 95.74 Null 20.79 67
Soreng 100.00 Null 99.99 26.28 Null 99.75 Null 4.36 65
Tripura
Dhalai 100.00 21.89 99.99 63.34 34.72 94.15 44.2 29.89 65
Gomati 100.00 9.06 100.00 71.08 50.68 91.96 29.9 20.65 69
Khowai 100.00 17.27 99.99 53.25 41.58 93.39 44.1 23.12 66
North Tripura 100.00 17.85 99.99 52.93 45.14 97.59 28.7 20.06 64
Sepahijala 100.00 12.27 99.99 55.42 53.25 95.70 31.6 16.35 67
South Tripura 100.00 11.89 99.99 80.52 55.31 90.22 37.3 28.32 72
Unakoti 100.00 24.92 99.99 68.99 50.58 98.00 28.0 20.54 65
West Tripura 100.00 6.00 99.99 58.02 65.24 94.98 28.1 84.79 73
Target 100 12.43 100.00 100.00 100 100.00 100 196.89 100
TABLE 1.1: PERFORMANCE OF DISTRICTS ON SDG 1
The SDGs aim to end all forms of hunger and
malnutrition by 2030, making sure all people
- especially children - have sufficient and nutritious
food all year. This involves promoting sustainable
agriculture, supporting small-scale farmers, and
equal access to land, technology and markets. It
also requires international cooperation to ensure
investment in infrastructure and technology to
improve agricultural productivity. The goal also
focuses at - doubling agricultural productivity,
maintaining genetic diversity of seeds, plants and
farmed animals, and strengthening capacity for
climate change adaptive agriculture.
Targets
2.1 By 2030, end hunger and ensure access by
all people, in particular the poor and people
in vulnerable situations, including infants,
to safe, nutritious and sufficient food all
year round
2.2 By 2030, end all forms of malnutrition,
including achieving, by 2025, the
internationally agreed targets on stunting
and wasting in children under 5 years of
age, and address the nutritional needs of
adolescent girls, pregnant and lactating
women and older persons
2.3 By 2030, double the agricultural productivity
and incomes of small-scale food producers,
in particular women, indigenous peoples,
family farmers, pastoralists and fishers,
including through secure and equal access to
land, other productive resources and inputs,
knowledge, financial services, markets
and opportunities for value addition and
non-farm employment
2.4 By 2030, ensure sustainable food production
systems and implement resilient agricultural
practices that increase productivity and
production, that help maintain ecosystems,
that strengthen capacity for adaptation
to climate change, extreme weather,
drought, flooding and other disasters and
progressively improve land and soil quality
2.5 By 2020, maintain the genetic diversity of
seeds, cultivated plants and farmed and
domesticated animals and their related wild
species, including through soundly managed
and diversified seed and plant banks at
the national, regional and international
levels, and promote access to and fair
and equitable sharing of benefits arising
from the utilization of genetic resources
and associated traditional knowledge, as
internationally agreed
2.a Increase investment, including through
enhanced international cooperation, in rural
infrastructure, agricultural research and
extension services, technology development
and plant and livestock gene banks in order
to enhance agricultural productive capacity
in developing countries, in particular least
developed countries
2.b Correct and prevent trade restrictions and
distortions in world agricultural markets,
including through the parallel elimination of
all forms of agricultural export subsidies and
all export measures with equivalent effect, in
accordance with the mandate of the Doha
Development Round
2.c Adopt measures to ensure the proper
functioning of food commodity markets and
their derivatives and facilitate timely access
to market information, including on food
reserves, in order to help limit extreme food
price volatility
37
CONTEXT & OVERVIEW
SDG 2
ZERO HUNGER
End hunger, achieve food security, improve nutrition and
promote sustainable agriculture
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 2
The score for Goal 2 ranges between 83 and 40 for the
121 districts included in the ranking and computation.
Champhai [MZ], Phek [NL] and Kakching [MN] are the
top performing districts. 83 districts fall in the category
of Front Runners and 37 in the category of Performers,
while 1 district is in the category of Aspirant with scores
less than 50.
FIGURE 2.1: SDG 2 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Champhai MZ 1 83
Phek NL 2 82
Kakching MN 3 80
Lohit AR 4 79
Siang AR 4 79
South Tripura TR 4 79
Serchhip MZ 7 78
Kohima NL 7 78
East Siang AR 9 77
Thoubal MN 9 77
North Garo Hills ML 9 77
Lower Dibang Valley AR 12 76
West Kameng AR 12 76
Gomati TR 12 76
West Tripura TR 12 76
Papum Pare AR 16 75
Upper Siang AR 16 75
Aizawl MZ 16 75
Longleng NL 16 75
North Tripura TR 16 75
West Siang AR 21 74
South West Garo Hills ML 21 74
Peren NL 21 74
Sepahijala TR 21 74
Barpeta AS 25 73
Sivasagar AS 25 73
Imphal East MN 25 73
Lunglei MZ 25 73
Kiphire NL 25 73
Mokokchung NL 25 73
Mon NL 25 73
Wokha NL 25 73
Anjaw AR 33 72
Lower Subansiri AR 33 72
Dibrugarh AS 33 72
Imphal West MN 33 72
Ukhrul MN 33 72
Hnahthial MZ 33 72
Namchi SK 33 72
Longding AR 40 71
Kamrup AS 40 71
Senapati MN 40 71
Kolasib MZ 40 71
Mamit MZ 40 71
Kra Daadi AR 45 70
Goalpara AS 45 70
Majuli AS 45 70
Morigaon AS 45 70
South Salmara-Mankachar AS 45 70
Hojai AS 50 69
Kamrup Metropolitan AS 50 69
East Garo Hills ML 50 69
Mangan SK 50 69
Unakoti TR 50 69
Pakke Kessang AR 55 68
Sonitpur AS 55 68
Bishnupur MN 55 68
Tamenglong MN 55 68
West Garo Hills ML 55 68
Gangtok SK 55 68
Tirap AR 61 67
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
382023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
FIGURE 2.1: SDG 2 INDEX SCORE OF DISTRICTS
District StateRank
Karbi Anglong AS 61 67
Nalbari AS 61 67
Chandel MN 61 67
South Garo Hills ML 61 67
Dimapur NL 61 67
Soreng SK 61 67
Khowai TR 61 67
Changlang AR 69 66
Dibang Valley AR 69 66
Charaideo AS 69 66
Dima Hasao AS 69 66
Golaghat AS 69 66
Churachandpur MN 69 66
Siaha MZ 69 66
Pakyong SK 69 66
Leparada AR 77 65
Darrang AS 77 65
Jorhat AS 77 65
Karimganj AS 77 65
Nagaon AS 77 65
Tuensang NL 77 65
Gyalshing SK 77 65
Bongaigaon AS 84 64
Cachar AS 84 64
Jiribam MN 84 64
East Khasi Hills ML 84 64
Lawngtlai MZ 84 64
Kamle AR 89 63
Namsai AR 89 63
Tawa n g AR 89 63
Kurung Kumey AR 92 62
Shi Yomi AR 92 62
Tinsukia AS 92 62
Kangpokpi MN 92 62
Tengnoupal MN 92 62
Zunheboto NL 92 62
East Kameng AR 98 61
Upper Subansiri AR 98 61
Dhemaji AS 98 61
Dhubri AS 98 61
West Karbi Anglong AS 98 61
West Khasi Hills ML 98 61
Hailakandi AS 104 60
Dhalai TR 104 60
Biswanath AS 106 59
Kamjong MN 106 59
Khawzawl MZ 106 59
Pherzawl MN 109 58
Lower Siang AR 110 57
Lakhimpur AS 110 57
Noney MN 110 57
East Jaintia Hills ML 110 57
South West Khasi Hills ML 110 57
West Jaintia Hills ML 110 57
Udalguri AS 116 56
Kokrajhar AS 117 55
Ri Bhoi ML 117 55
Baksa AS 119 54
Chirang AS 119 54
Saitual MZ 121 40
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
39
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) © 2022 Mapbox © Op enStreetMap
FIGURE 2.2: PERFORMANCE OF DISTRICTS IN SDG 2
2023-24
2021-22
402023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
2.1
Percentage of Fair Price Shops (FPS)
covered under online transaction
system for PDS in the district
100
Global SDG target 2.1 aims to end hunger and ensure access to
safe, nutritious and sufficient food all year round, by all. The Public
Distribution System in India facilitates the supply of food grains
and essential commodities at subsidized price to a large number
of poor people through a network of FPS. Automation of FPS is
critical for having greater transparency in the overall PDS value
chain. To encourage FPS automation, the target has been set to be
the average of the best five scores, rounded to the nearest whole
number.
2.2
Percentage of anganwadi centres
in the district with anthropometric
measurement devices (height, weight
measurement)
100
Global SDG target 2.2 aims to end all forms of malnutrition,
including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age. Availability of
anthropometric measurement devices is important to identify cases
of stunting and wasting in children under 5 years of age.
2.2
Percentage of anganwadis with own
buildings
100
Under the ICDS scheme, anganwadis function as the centre for
health, nutrition and early learning. To carry out their activities
effectively, all anganwadis must necessarily have their own buildings
that meet the guidelines specified by the Ministry of Women and
Child Development.
2.2
Percentage of children under age 5
years who are stunted
23.7
The target has been set to 23.7 percent as per the WHO Global
Nutrition Targets tracking tool
2.2
Percentage of children under age 5
years who are underweight
2.6
The target has been set to 2.6 per cent as this the corresponding
percentage of children under five years who are underweight in
upper middle-income countries as per the 2019 database of the
World Bank.
2.2
Percentage of pregnant women aged
15-49 years who are anaemic (<11.0
g/dl)
25.2
The WHO targets a 50 percent reduction of anaemia in women of
reproductive age by 2025 (Global Nutrition Targets 2025, Policy
Brief Series). Hence, 50 percent reduction from base year (2015-
16) has been set to be the target.
2.2
Percentage of children aged 6-59
months who are anaemic (<11.0 g/dl)
21
The target has been set to 21 per cent as this is the corresponding
prevalence of anaemia in children aged 6-59 months in upper
middle-income countries as per the 2019 database of the World
Bank.
2.3 Average yield of rice (kg/ha) 4114
Global SDG target 2.3 aims to double the agricultural productivity
by 2030. Hence, target is to double the agricultural productivity of
the North Eastern Region from the base year (2015-16).
2.3
Productivity of fruits and vegetables
(kg/ha)
16919.3
Global SDG target 2.3 aims to double the agricultural productivity
by 2030. The target has been set as the average of the 5 best
scores, after removing the outliers.
41
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
42Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 2.1 2.2 2.2 2.2 2.2 2.2 2.2 2.3 2.3
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage
of anganwadi
centres in the
district with
anthropometric
measurement
devices
(height, weight
measurement)
Percentage of
anganwadis
with own
buildings
Percentage of
children under
age 5 years who
are stunted
Percentage of
children under
age 5 years who
are underweight
Percentage of
pregnant wom-
en aged 15-49
years who are
anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who are
anaemic
(<11.0 g/dl)
Average yield of
rice (kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Arunachal Pradesh
Anjaw 100.00 100.00 77.84 23.6 16.0 19.7 57.1 1683.89 3705.05 72
Bichom Null Null Null Null Null Null Null Null Null *
Changlang 98.06 100.00 70.70 26.3 25.0 60.6 65.3 3368.05 6139.40 66
Dibang Valley 100.00 100.00 94.12 16.9 16.0 39.0 88.6 1800.94 3885.71 66
East Kameng 53.81 100.00 53.93 35.7 14.2 13.1 51.7 2024.78 4502.53 61
East Siang 95.70 100.00 86.10 24.6 10.3 32.8 51.5 2783.91 5573.62 77
Kamle 82.61 100.00 57.69 Null Null Null Null 2900.90 3681.61 63
Keyi Panyor Null Null Null Null Null Null Null Null Null *
Kra Daadi 82.61 100.00 62.92 28.8 14.5 2.0 62.0 3005.98 3777.14 70
Kurung Kumey 66.67 100.00 53.85 29.2 13.9 Null 62.4 3000.00 3651.01 62
Leparada 97.44 100.00 54.79 Null Null Null Null 2514.31 4373.24 65
Lohit 100.00 100.00 88.24 24.5 12.9 33.2 52.5 3199.41 5920.86 79
Longding 82.81 100.00 46.88 15.8 13.8 19.1 38.4 2639.53 1932.37 71
Lower Dibang Valley 90.91 100.00 79.89 14.3 9.7 19.6 51.5 2472.24 5121.27 76
Lower Siang 74.36 100.00 47.39 Null Null Null Null 2358.63 4992.58 57
Lower Subansiri 85.19 100.00 54.95 30.7 8.1 22.1 52.4 3098.48 4777.39 72
Namsai 85.19 100.00 61.88 28.7 17.7 52.6 59.2 3418.56 662.69 63
Pakke Kessang 100.00 100.00 80.18 Null Null Null Null 2046.63 4379.12 68
Papum Pare 97.70 100.00 68.77 29.7 15.6 18.6 53.4 3028.31 5366.88 75
Shi Yomi 92.00 100.00 53.96 Null Null Null Null 2501.28 3435.48 62
Siang 74.26 100.00 63.01 21.3 8.8 15.4 24.9 3220.38 5343.79 79
Tawang 100.00 100.00 68.53 30.4 9.0 57.4 89.6 2966.39 5002.20 63
Tirap 91.89 100.00 61.60 38.6 16.0 24.1 48.4 2189.17 4322.86 67
Upper Siang 97.06 100.00 71.79 30.4 12.0 22.4 51.0 2947.19 4673.12 75
Upper Subansiri 74.65 100.00 56.18 36.8 19.2 37.9 60.4 3164.85 2704.78 61
West Kameng 89.33 100.00 100.00 24.2 13.4 18.2 66.6 2775.30 5041.80 76
West Siang 88.44 100.00 69.92 24.5 16.2 16.8 45.6 2529.14 4750.00 74
Assam
Bajali Null Null Null Null Null Null Null Null Null *
Baksa 100.00 100.00 41.25 41.2 34.0 65.3 78.6 2575.83 11695.27 54
Barpeta 100.00 100.00 86.74 29.8 26.2 47.6 63.5 2812.09 13548.74 73
Biswanath 100.00 100.00 58.51 42.7 41.0 45.1
79.8 2549.22 13290.68 59
Bongaigaon 100.00 100.00 96.13 46.2 35.3 51.2 77.2 2845.85 12922.07 64
Cachar 100.00 100.00 46.33 28.7 38.2 44.0 61.8 2094.97 13818.73 64
Charaideo 100.00 100.00 90.87 39.0 34.8 61.6 69.7 2539.76 16601.31 66
Chirang 100.00 100.00 16.50 42.7 39.7 54.1 70.4 2715.01 12335.75 54
Darrang 100.00 100.00 79.52 42.0 33.1 51.6 66.8 2872.11 12639.94 65
Dhemaji 100.00 100.00 67.44 37.2 25.7 61.7 73.1 2176.94 13281.69 61
Dhubri 100.00 100.00 93.44 48.5 37.8 69.7 73.1 3102.67 14978.67 61
Dibrugarh 100.00 100.00 96.51 27.3 32.0 47.2 66.4 2762.68 12054.57 72
Dima Hasao 100.00 100.00 34.26 30.6 21.7 43.3 73.1 2258.64 16296.44 66
Goalpara 100.00 100.00 98.47 38.9 35.4 49.2 60.7 2949.61 13992.90 70
Golaghat 100.00 100.00 83.04 26.3 25.5 76.7 75.1 2764.54 14632.76 66
Hailakandi 100.00 100.00 52.98 42.9 42.4 58.7 59.5 2728.63 15746.56 60
Hojai 100.00 100.00 60.26 39.3 28.4 51.4 56.8 3407.33 14419.93 69
Jorhat 100.00 100.00 76.98 38.7 33.2 56.4 74.1 2911.88 15206.28 65
Kamrup 100.00 100.00 85.44 22.6 19.7 66.5 72.9 2959.47 13682.38 71
Kamrup Metropolitan 100.00 100.00 65.89 25.4 25.0 56.4 80.4 2988.20 14834.21 69
Karbi Anglong 100.00 100.00 40.31 31.6 28.2 42.1 67.5 2577.77 15147.70 67
Karimganj 100.00 100.00 81.77 29.1 52.9 41.9 64.1 2050.85 13836.29 65
Kokrajhar 100.00 100.00 26.44 34.6 35.2 59.5 74.7 2120.06 13083.62 55
Lakhimpur 100.00 100.00 30.76 38.5 34.4 42.3 69.3 1962.78 10865.45 57
Majuli 100.00 100.00 79.26 35.4 22.2 Null 73.0 2523.87 12931.75 70
Morigaon 100.00 100.00 88.54 43.2 30.5 48.0 53.3 2853.50 14410.95 70
Nagaon 100.00 100.00 99.73 38.9 32.4 62.4 68.6 2515.29 13193.33 65
Nalbari 100.00 100.00 59.23 27.5 26.7 53.2 71.0 2681.43 12661.17 67
Sivasagar 100.00 100.00 90.72 26.1 25.9 54.3 67.5 2644.51 15750.14 73
Sonitpur 100.00 100.00 73.67 36.7 21.9 47.3 69.4 2940.93 10301.63 68
South Salmara-Mankachar 100.00 100.00 73.45 38.9 27.9 37.6 69.6 3012.01 13865.11 70
Tamulpur Null Null Null Null Null Null Null Null Null *
Tinsukia 100.00 100.00 91.29 32.8 32.2 71.7 66.4 1805.51 12559.03 62
Udalguri 100.00 100.00 30.73 33.8 32.5 63.9 77.6 2594.00 11806.95 56
West Karbi Anglong 100.00 100.00 39.79 40.9 31.1 38.8 79.0 2523.54 14336.27 61
Manipur
Bishnupur 100.00 100.00 32.92 15.5 11.7 39.0 42.4 1983.48 5260.54 68
Chandel 100.00 100.00 13.47 34.0 14.7 20.3 42.4 1621.35 9914.79 67
Churachandpur 100.00 100.00 27.53 25.1 9.8 51.8 41.1 1208.40 10859.68 66
Imphal East 100.00 100.00 19.55 18.4 14.4 27.4 50.3 2208.89 13080.38 73
Imphal West 100.00 100.00 26.62 15.6 10.2 39.5 41.8 1646.39 12573.50
72
Jiribam 100.00 100.00 10.61 Null Null Null Null 1528.74 19490.64 64
Kakching 100.00 100.00 41.48 Null Null Null Null 4642.79 10839.97 80
Kamjong 100.00 100.00 15.83 Null Null Null Null 1517.41 11494.34 59
Kangpokpi 100.00 100.00 17.89 Null Null Null Null 1772.37 12411.14 62
Noney 100.00 100.00 35.16 Null Null Null Null 798.67 9397.21 57
Pherzawl 100.00 100.00 18.06 Null Null Null Null 1285.84 11664.23 58
Senapati 100.00 100.00 27.80 27.3 12.9 18.3 48.5 1771.54 10814.56 71
Tamenglong 100.00 100.00 31.77 27.1 19.3 31.4 37.0 783.92 11224.13 68
Tengnoupal 100.00 100.00 23.87 Null Null Null Null 1620.33 11441.45 62
Thoubal 100.00 100.00 26.29 31.5 14.9 32.0 39.7 4561.63 11236.48 77
Ukhrul 100.00 100.00 26.57 27.1 16.0 25.7 34.6 1528.23 10433.22 72
TABLE 2.1: PERFORMANCE OF DISTRICTS ON SDG 2
43Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 2.1 2.2 2.2 2.2 2.2 2.2 2.2 2.3 2.3
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage
of anganwadi
centres in the
district with
anthropometric
measurement
devices
(height, weight
measurement)
Percentage of
anganwadis
with own
buildings
Percentage of
children under
age 5 years who
are stunted
Percentage of
children under
age 5 years who
are underweight
Percentage of
pregnant wom-
en aged 15-49
years who are
anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who are
anaemic
(<11.0 g/dl)
Average yield of
rice (kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Meghalaya
East Garo Hills 99.68 100.00 29.61 39.7 26.5 29.1 28.0 1939.82 13378.64 69
East Jaintia Hills100.00 100.00 46.55 49.8 23.6 46.5 47.2 2201.00 5071.60 57
East Khasi Hills 90.20 100.00 52.80 44.6 23.8 43.7 39.0 1947.01 12177.38 64
Eastern West Khasi Hills Null Null Null Null Null Null Null Null Null *
North Garo Hills100.00 100.00 67.56 35.6 15.8 40.8 30.2 2741.71 12229.38 77
Ri Bhoi 25.00 100.00 64.23 42.5 29.6 65.0 45.7 3369.22 12465.73 55
South Garo Hills 76.62 100.00 31.72 29.8 20.8 33.7 33.6 2174.54 9537.71 67
South West Garo Hills100.00 100.00 49.53 32.2 26.4 37.8 35.5 3345.28 10163.92 74
South West Khasi Hills100.00 100.00 70.95 51.4 27.6 63.2 61.3 1870.11 12106.56 57
West Garo Hills 51.68 100.00 64.18 39.5 26.3 26.7 30.2 3018.02 9266.21 68
West Jaintia Hills98.67 100.00 75.23 48.7 28.3 64.6 54.6 1885.88 9414.23 57
West Khasi Hills100.00 100.00 75.49 59.0 31.1 49.6 56.2 1910.90 18165.16 61
Mizoram
Aizawl 99.31 100.00 100.00 25.3 9.6 33.4 44.0 1216.48 5895.38 75
Champhai 100.00 100.00 100.00 27.2 13.1 15.7 38.3 2994.00 5689.78 83
Hnahthial 100.00 Null Null Null Null Null Null 1283.55 35993.36 72
Khawzawl 100.00 Null Null Null Null Null Null 1792.29 8034.36 59
Kolasib 100.00 100.00 100.00 30.4 12.6 43.8 53.8 1865.34 4783.73 71
Lawngtlai 89.93 100.00 100.00 32.7 16.9 46.5 55.3 1775.52 418.94 64
Lunglei 89.19 100.00 100.00 26.5 11.1 27.5 45.7 1521.99 2729.03 73
Mamit 100.00 100.00 100.00 26.4 13.9 29.9 45.5 1279.82 47.22 71
Saitual 100.00 Null Null Null Null Null Null 1417.27 3.11 40
Serchhip 100.00 100.00 100.00 31.8 14.4 43.4 43.2 1667.22 14927.13 78
Siaha 92.31 100.00 100.00 43.8 17.6 30.0 46.4 1504.39 2306.73 66
Nagaland
Chumoukedima Null Null Null Null Null Null Null Null Null *
Dimapur 100.00 100.00 51.62 28.3 29.8 32.9 48.9 3063.15 1274.50 67
Kiphire 100.00 100.00 82.84 36.9 25.0 19.5 55.2 2354.49 10058.10 73
Kohima 100.00 100.00 64.97 28.3 22.1 3.9 38.4 2922.86 8920.65 78
Longleng 100.00 100.00 60.49 34.1 25.7 30.5 40.4 2375.19 14054.25 75
Mokokchung 100.00 100.00 52.00 31.4 22.9 11.5 35.5 2462.85 7945.12 73
Mon 100.00 100.00 63.03 35.5 23.3 27.0 39.4 2286.04 9398.80 73
Noklak Null Null Null Null Null
Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null Null *
Peren 100.00 100.00 61.83 34.9 20.7 26.4 51.0 2825.79 10968.16 74
Phek 100.00 100.00 74.49 28.0 15.6 18.2 44.9 2981.26 11699.58 82
Shamator Null Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null Null *
Tuensang 100.00 100.00 59.56 37.1 34.2 20.0 38.8 2413.69 1805.22 65
Wokha 100.00 100.00 51.68 26.3 28.0 29.8 45.4 2554.75 10163.72 73
Zunheboto 100.00 100.00 60.57 44.0 44.5 40.8 34.9 2412.06 7469.68 62
Sikkim
Gangtok 97.44 100.00 61.24 17.8 13.0 Null 49.8 1817.76 3581.95 68
Gyalshing 97.47 100.00 71.60 25.2 19.3 Null 67.1 1974.68 4089.92 65
Mangan 94.52 100.00 91.05 31.8 15.3 26.9 53.5 1511.38 3314.35 69
Namchi 99.42 100.00 79.52 24.8 7.2 Null 56.5 1968.03 4116.24 72
Pakyong 95.81 100.00 83.02 Null Null Null Null 1872.17 3614.61 66
Soreng 95.63 100.00 85.06 Null Null Null Null 1971.43 3674.09 67
Tripura
Dhalai 100.00 100.00 87.21 45.7 27.6 75.4 81.2 2882.80 14227.35 60
Gomati 100.00 100.00 94.88 22.7 29.0 52.8 70.7 3334.59 15358.73 76
Khowai 100.00 100.00 91.61 47.0 24.7 63.7 73.4 3314.31 16965.56 67
North Tripura 100.00 100.00 88.88 26.2 32.2 55.3 52.5 3011.20 15956.84 75
Sepahijala 100.00 100.00 93.35 34.5 21.0 55.8 72.1 3497.02 15611.76 74
South Tripura 100.00 100.00 94.63 25.5 21.6 57.1 59.6 3455.88 16590.63 79
Unakoti 100.00 100.00 91.78 31.8 32.0 76.7 62.8 3263.63 17362.30 69
West Tripura 100.00 100.00 86.05 30.3 21.2 56.2 54.5 3386.43 14992.47 76
Target 100 100 100 23.7 2.6 25.2 21 4114 16919.32 100
TABLE 2.1: PERFORMANCE OF DISTRICTS ON SDG 2
Good health is essential to sustainable development
and the 2030 Agenda reflects the complexity
and interconnectedness of the two. It takes into
account widening economic and social inequalities,
rapid urbanization, threats to the climate and the
environment, the continuing burden of HIV and
other infectious diseases, and emerging challenges
such as non-communicable diseases. It calls for
a renewed focus on mental health issues as well.
Universal health coverage, including financial risk
protection, access to quality essential health care
services and access to safe, effective, quality, and
affordable medicines are integral to this goal.
Targets
3.1 By 2030, reduce the global maternal mortality
ratio to less than 70 per 100,000 live births
3.2 By 2030, end preventable deaths of newborns
and children under 5 years of age, with all
countries aiming to reduce neonatal mortality
to at least as low as 12 per 1,000 live births and
under-5 mortality to at least as low as 25 per
1,000 live births
3.3 By 2030, end the epidemics of AIDS,
tuberculosis, malaria and neglected tropical
diseases and combat hepatitis, water-borne
diseases and other communicable diseases
3.4 By 2030, reduce by one third premature
mortality from non-communicable diseases
through prevention and treatment and
promote mental health and well-being
3.5 Strengthen the prevention and treatment
of substance abuse, including narcotic drug
abuse and harmful use of alcohol
3.6 By 2020, halve the number of global deaths
and injuries from road traffic accidents
3.7 By 2030, ensure universal access to sexual and
reproductive health-care services, including for
family planning, information and education,
and the integration of reproductive health into
national strategies and programmes
3.8 Achieve universal health coverage, including
financial risk protection, access to quality
essential health-care services and access to
safe, effective, quality and affordable essential
medicines and vaccines for all
3.9 By 2030, substantially reduce the number
of deaths and illnesses from hazardous
chemicals and air, water and soil pollution and
contamination
3.a Strengthen the implementation of the World
Health Organization Framework Convention on
Tobacco Control in all countries, as appropriate
3.b Support the research and development of
vaccines and medicines for the communicable
and non‑communicable diseases that primarily
affect developing countries, provide access to
affordable essential medicines and vaccines,
in accordance with the Doha Declaration on
the TRIPS Agreement and Public Health, which
affirms the right of developing countries to use
to the full the provisions in the Agreement on
Trade-Related Aspects of Intellectual Property
Rights regarding flexibilities to protect public
health, and, in particular, provide access to
medicines for all
3.c Substantially increase health financing and
the recruitment, development, training and
retention of the health workforce in developing
countries, especially in least developed
countries and small island developing States
3.d Strengthen the capacity of all countries, in
particular developing countries, for early
warning, risk reduction and management of
national and global health risks
45
CONTEXT & OVERVIEW
SDG 3
GOOD HEALTH AND WELL-BEING
Ensure healthy lives and promote well-being for all at all
ages
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) The score for Goal 3 ranges between 84 and 39 for the
121 districts included in the ranking and computation.
Upper Siang [AR], East Siang [AR] and West Siang
[AR] are the top performing districts. 48 districts fall in
the category of Front Runners and 67 in the category
of Performers, while 6 districts are in the category of
Aspirants with scores less than 50.
NER District SDG Index: Goal 3
FIGURE 3.1: SDG 3 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Upper Siang AR 1 84
East Siang AR 2 80
West Siang AR 3 77
East Kameng AR 4 76
Champhai MZ 4 76
Hnahthial MZ 4 76
Imphal West MN 7 75
Serchhip MZ 7 75
Kolasib MZ 9 74
West Khasi Hills ML 10 73
Kamrup Metropolitan AS 11 72
Longleng NL 11 72
Lohit AR 13 71
East Garo Hills ML 13 71
South West Garo Hills ML 13 71
Thoubal MN 16 70
Lower Subansiri AR 17 69
Imphal East MN 17 69
Mamit MZ 17 69
Dibang Valley AR 20 68
Tawa n g AR 20 68
West Kameng AR 20 68
Aizawl MZ 20 68
Siaha MZ 20 68
Anjaw AR 25 67
Lower Dibang Valley AR 25 67
Dhemaji AS 25 67
Nalbari AS 25 67
Bishnupur MN 25 67
East Khasi Hills ML 25 67
Ri Bhoi ML 25 67
Kiphire NL 25 67
Leparada AR 33 66
Cachar AS 33 66
Goalpara AS 33 66
Lakhimpur AS 33 66
Lunglei MZ 33 66
Gangtok SK 33 66
Kurung Kumey AR 39 65
Hailakandi AS 39 65
Jorhat AS 39 65
Kamrup AS 39 65
Karimganj AS 39 65
Majuli AS 39 65
Tinsukia AS 39 65
North Garo Hills ML 39 65
South Garo Hills ML 39 65
Saitual MZ 39 65
Upper Subansiri AR 49 64
Barpeta AS 49 64
Darrang AS 49 64
Karbi Anglong AS 49 64
Kokrajhar AS 49 64
East Jaintia Hills ML 49 64
West Garo Hills ML 49 64
Mokokchung NL 49 64
Dhalai TR 49 64
Gomati TR 49 64
Sepahijala TR 49 64
South Tripura TR 49 64
Namsai AR 61 63
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
462023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
FIGURE 3.1: SDG 3 INDEX SCORE OF DISTRICTS
District StateRank
Papum Pare AR 61 63
Tirap AR 61 63
Dhubri AS 61 63
Dibrugarh AS 61 63
Golaghat AS 61 63
Nagaon AS 61 63
Peren NL 61 63
Wokha NL 61 63
Biswanath AS 70 62
Dima Hasao AS 70 62
Sonitpur AS 70 62
Churachandpur MN 70 62
West Jaintia Hills ML 70 62
Phek NL 70 62
Zunheboto NL 70 62
Mangan SK 70 62
West Tripura TR 70 62
Bongaigaon AS 79 61
Chirang AS 79 61
Hojai AS 79 61
Morigaon AS 79 61
Chandel MN 79 61
Gyalshing SK 79 61
Khowai TR 79 61
Changlang AR 86 60
Pakke Kessang AR 86 60
Baksa AS 86 60
Kakching MN 86 60
Senapati MN 86 60
Kohima NL 86 60
Tuensang NL 86 60
Lower Siang AR 93 59
Udalguri AS 93 59
Mon NL 93 59
North Tripura TR 93 59
Siang AR 97 58
Sivasagar AS 97 58
South West Khasi Hills ML 97 58
Unakoti TR 97 58
Charaideo AS 101 57
Noney MN 101 57
Namchi SK 101 57
Khawzawl MZ 104 56
Shi Yomi AR 105 55
West Karbi Anglong AS 105 55
Lawngtlai MZ 105 55
South Salmara-Mankachar AS 108 53
Ukhrul MN 108 53
Longding AR 110 52
Tamenglong MN 110 52
Kra Daadi AR 112 51
Dimapur NL 112 51
Kamle AR 114 50
Tengnoupal MN 114 50
Pherzawl MN 116 49
Pakyong SK 117 48
Jiribam MN 118 47
Kangpokpi MN 119 45
Kamjong MN 120 40
Soreng SK 121 39
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
47
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 3.2: PERFORMANCE OF DISTRICTS IN SDG 3
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
482023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
3.1
Percentage of pregnant women
who completed 4 Antenatal Cares
(ANC) in the district
100
This target corresponds to global SDG target 3.1 that aims to reduce maternal
mortality. The antenatal period presents opportunities for reaching pregnant
women with interventions that may be vital to their health and wellbeing and that
of their infants. The WHO recommends receiving antenatal care at least four times
to increase the likelihood of receiving effective maternal health interventions
during the antenatal period.
3.1
Percentage of births attended by
skilled health personnel
100
This target corresponds to global SDG target 3.1 that aims to reduce maternal
mortality. All women should have access to skilled care during pregnancy and
childbirth to ensure prevention, detection and management of complications.
Assistance by competent health personnel working within an enabling
environment is key to lowering maternal and newborn deaths.
3.2
Percentage of children aged 9-11
months fully immunized
100
This target corresponds to the global SDG target 3.2 which aims to end
preventable deaths of newborns and children under 5 years of age. 100 percent
immunization coverage (BCG, measles, and 3 doses each of polio and DPT) is a
prerequisite to achieve this global target.
3.2 Infant Mortality Rate 11
The target has been set to 11 per cent as this is the corresponding rate of infant
mortality in upper middle-income countries as per the 2019 database of the
World Bank.
3.8
Number of functional new born
facilities (SNCU, NBSU, NBCC) per
10,000 population
3.13
Global SDG target 3.8 aims to achieve universal health coverage, including
financial risk protection, access to quality essential health-care services and
access to safe, effective, quality and affordable essential medicines and vaccines
for all. The target has been set as the average of the 5 best scores.
3.3
Number of new HIV infections per
1,000 uninfected population
0
The target is aligned with the global SDG target 3.3 that aims to end the epidemic
of AIDS by 2030.
3.8
Percentage of TB cases successfully
treated among TB cases notified to
the national health authorities
100
The target is aligned with the global SDG target 3.8 that aims to provide access
to quality essential health-care services and access to safe, effective, quality and
affordable essential medicines and vaccines for all. It is also aligned to global
SDG target 3.3.
3.4
Number of suicide deaths reported
per 1,00,000 population
3.5
Global SDG target 3.4 aims to reduce by one third premature mortality from non-
communicable diseases through prevention and treatment and promote mental
health and well-being, by 2030. Hence, the target has been set to reduce by a
third from the base year (2015) figures.
3.5
Number of de-addiction centres
(public and private) per 10,000
population
5.7
Global SDG target 3.5 aims to strengthen the prevention and treatment of
substance abuse, including narcotic drug abuse and harmful use of alcohol. The
target has been set as the average of the 5 best scores.
3.8
First Referral Units (FRUs) per
10,000 population
3.7
The target is aligned with the global SDG target 3.8 that aims to provide access
to quality essential health-care services and access to safe, effective, quality and
affordable essential medicines and vaccines for all. The target has been set as the
average of the 5 best scores.
3.c
Total physicians, nurses and
midwives per 10,000 population
45
Global SDG target 3.c aims to substantially increase health financing and the
recruitment, development, training and retention of the health workforce. The WHO,
in its report “Monitoring Health in the Sustainable Development Goals: 2017,
World Health Organization, Regional Office for South East Asia”, lays out a target
to have a skilled health professionals density (physicians/nurses/midwives per
10,000 population) of 44.5.
49
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
50Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 3.1 3.1 3.2 3.2 3.8 3.3 3.8 3.4 3.5 3.8 3.c
District
Percentage
of pregnant
women who
completed
4 ANCs in
the district
Percentage
of births
attended
by skilled
health
personnel
Percentage
of children
aged 9-11
months fully
immunized
Infant
Mortality
Rate
Number of
functional new
born facilities
(SNCU, NBSU,
NBCC) per
10,000
population
Number of
new HIV
infections
per 1,000
uninfected
population
Percentage of
TB cases suc-
cessfully treated
among TB cases
notified to the
national health
authorities
Number
of suicide
deaths
reported per
1,00,000
population
Number of
de-addiction
centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs) per
1,00,000
population
Total
physicians,
nurses and
midwives
per 10,000
population
SDG 3
Arunachal Pradesh
Anjaw 41.91 78.33 65.85 0.00 1.89 0.00 Null 4.72 4.72 0.00 28.35 67
Bichom Null Null Null Null Null Null Null Null Null Null Null *
Changlang 43.91 90.87 83.64 0.97 1.01 0.51 120.72 8.77 0.67 0.00 12.55 60
Dibang Valley 3.03 93.75 76.74 0.00 3.75 0.00 102.74 12.49 0.00 0.00 66.22 68
East Kameng 111.39 99.39 93.18 0.00 2.06 0.08 179.52 1.59 0.00 1.59 19.38 76
East Siang 86.86 100.00 98.7212.35 1.95 0.49 88.10 30.62 1.39 2.78 47.88 80
Kamle 23.53 76.12 38.78 0.00 1.80 0.00 Null 9.02 0.00 0.00 21.20 50
Keyi Panyor Null Null Null Null Null Null Null Null Null Null Null *
Kra Daadi 70.55 80.46 31.61 0.00 0.86 0.00 Null 0.00 0.00 0.00 13.70 51
Kurung Kumey 72.36 100.00 90.77 0.00 0.88 0.00 425.00 0.00 0.00 0.00 13.44 65
Leparada 41.76 98.96 89.37 0.00 2.48 0.05 Null 4.96 0.00 0.00 28.78 66
Lohit 76.87 99.15 98.7419.13 1.61 1.05 83.10 20.09 2.01 2.01 21.50 71
Longding 36.76 75.49 87.51 5.25 0.53 0.00 Null 1.77 0.00 0.00 12.89 52
Lower Dibang Valley51.50 99.30 86.99 2.16 1.48 0.52 Null 7.40 0.00 1.85 24.78 67
Lower Siang 32.00 98.99 61.9012.66 2.30 0.14 Null 27.57 0.00 0.00 36.76 59
Lower Subansiri38.08 98.04 32.2710.91 1.89 0.02 102.70 2.36 0.00 2.36 40.14 69
Namsai 80.43 97.92 105.11 7.61 0.83 3.76 96.67 6.25 1.04 1.04 13.76 63
Pakke Kessang 15.00 100.00 36.04 0.00 3.31 0.00 Null 16.53 0.00 0.00 41.33 60
Papum Pare 45.88 99.96 113.06 4.62 1.81 1.57 54.17 31.71 0.57 0.57 41.40 63
Shi Yomi 18.79 84.21 83.0222.22 1.50 0.00 Null 7.51 0.00 0.00 23.29 55
Siang 21.90 78.33 70.44 0.00 2.19 0.00 Null 9.40 0.00 0.00 32.89 58
Tawang 44.85 81.37 72.6015.22 2.20 0.02 115.15 2.00 0.00 2.00 22.60 68
Tirap 64.46 81.02 80.66 0.00 0.90 0.52 89.51 7.23 1.81 0.00 21.86 63
Upper Siang 67.61 99.22 85.5811.17 2.27 0.06 90.24 0.00 2.83 2.83 40.77 84
Upper Subansiri71.85 100.00 39.12 0.001.04 0.29 194.34 10.45 0.00 1.31 24.17 64
West Kameng 68.78 99.08 79.75 2.60 1.53 0.09 118.18 12.75 0.00 1.27 20.14 68
West Siang 74.44 99.74 89.66 8.22 1.52 0.17 113.27 1.90 1.90 1.90 26.47 77
Assam
Bajali Null Null Null Null Null Null Null Null Null Null Null *
Baksa 87.16 99.98 68.6528.66 0.59 0.00 116.07 5.89 0.00 0.11 8.14 60
Barpeta 91.49 99.76 85.11 9.92 0.35 0.03 111.60 6.55 0.18 0.18 8.44 64
Biswanath 95.01 99.96 100.84 9.10 0.59 0.01 Null 21.22 0.00 0.49 10.53 62
Bongaigaon 90.96 99.93 72.78 7.61 0.69 0.09 112.72 25.04 0.14 0.27 7.35 61
Cachar 91.06 99.72 106.97 4.16 0.40 0.02 112.22 4.66 0.63 0.12 7.22 66
Charaideo 92.22 100.00 66.7313.35 0.35 0.01 Null 16.57 0.44 0.22 7.92 57
Chirang 84.41 91.32 78.43 9.06 0.83 0.04 106.93 18.25 0.00 0.21 8.15 61
Darrang 95.08 99.99 77.27 6.70 0.59 0.06 110.34 13.46 0.65 0.32 9.99 64
Dhemaji 90.36 99.96 82.40 7.50 0.64 0.03 111.24 10.06 1.46 0.44 9.11 67
Dhubri 92.52 85.33 95.21 9.72 0.49 0.01 107.10 11.33 0.14 0.14 7.66 63
Dibrugarh 91.57 99.96 81.23 5.85 0.34 0.05 115.61 10.56 0.23 0.15 8.60 63
Dima Hasao 62.32 83.89 68.32 8.39 0.98 0.01 112.74 2.34 0.47 0.47 17.33 62
Goalpara 92.35 99.92 86.12 9.07 0.78 0.07 113.75 8.23 0.20 0.30 8.90 66
Golaghat 93.17 99.94 72.9816.98 0.52 0.06 114.13 6.47 0.28 0.28 8.45 63
Hailakandi 90.10 98.57 99.74 6.65 0.65 0.05 116.07 9.86 0.15 0.15 7.95 65
Hojai 96.07 97.24 96.83 4.87 0.35 0.03 Null 8.70 0.21 0.32 4.08 61
Jorhat 84.22 99.99 93.7311.62 0.48 0.05 117.04 8.00 0.22 0.22 10.68 65
Kamrup 93.51 99.95 87.4110.83 0.49 0.12 119.28 18.19 0.59 0.66 9.68 65
Kamrup Metropolitan132.48 99.78 121.98 4.39 0.26 0.31 121.44 24.48 5.26 0.32 9.72 72
Karbi Anglong 71.85 97.01 93.93 6.61 0.86 0.05 112.20 0.00 0.15 0.00 9.20 64
Karimganj 92.37 97.31 88.91 7.10 0.47 0.05 119.83 3.42 0.49 0.08 6.44 65
Kokrajhar 86.44 99.03 76.5710.81 0.56 0.04 112.38 1.69 0.00 0.23 10.26 64
Lakhimpur 94.91 99.99 84.67 6.68 0.58 0.02 111.52 5.66 1.06 0.10 8.89 66
Majuli 92.96 99.29 108.4817.05 0.78 0.02 Null 4.78 0.00 0.60 14.29 65
Morigaon 82.90 98.50 85.12 9.12 0.61 0.06 111.23 25.28 0.10 0.10 8.18 61
Nagaon 89.44 98.44 80.10 5.24 0.41 0.24 107.67 6.13 0.21 0.21 8.60 63
Nalbari 91.99 100.00 91.23 7.67 0.48 0.06 110.23 1.30 0.13 0.39 12.23 67
Sivasagar
92.73 99.97 65.4214.16 0.35 0.13 113.69 38.13 0.29 0.43 11.65 58
Sonitpur 83.89 98.11 73.46 4.97 0.27 0.03 112.83 0.00 0.46 0.15 5.79 62
South Salmara-Mankachar83.19 75.34 70.60 8.76 0.34 0.00 Null 3.06 0.18 0.00 3.73 53
Tamulpur Null Null Null Null Null Null Null Null Null Null Null *
Tinsukia 95.82 99.45 79.29 6.44 0.48 0.01 120.15 7.61 1.05 0.38 6.21 65
Udalguri 86.28 99.72 65.3222.29 0.57 0.02 112.38 14.43 0.00 0.24 8.39 59
West Karbi Anglong62.27 69.45 87.29 7.25 0.95 0.01 Null 3.05 0.00 0.34 7.89 55
TABLE 3.1: PERFORMANCE OF DISTRICTS ON SDG 3
51Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 3.1 3.1 3.2 3.2 3.8 3.3 3.8 3.4 3.5 3.8 3.c
District
Percentage
of pregnant
women who
completed
4 ANCs in
the district
Percentage
of births
attended
by skilled
health
personnel
Percentage
of children
aged 9-11
months fully
immunized
Infant
Mortality
Rate
Number of
functional new
born facilities
(SNCU, NBSU,
NBCC) per
10,000
population
Number of
new HIV
infections
per 1,000
uninfected
population
Percentage of
TB cases suc-
cessfully treated
among TB cases
notified to the
national health
authorities
Number
of suicide
deaths
reported per
1,00,000
population
Number of
de-addiction
centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs) per
1,00,000
population
Total
physicians,
nurses and
midwives
per 10,000
population
SDG 3
Manipur
Bishnupur 118.63 98.04 94.99 3.03 0.29 0.09 61.54 2.53 2.53 0.42 10.07 67
Chandel 23.42 96.80 83.2316.00 0.48 0.36 80.49 0.00 1.20 1.20 20.70 61
Churachandpur 50.38 95.66 118.6434.97 0.17 0.76 87.69 0.00 1.29 1.72 13.01 62
Imphal East 27.11 99.89 84.25 4.85 0.29 0.33 84.90 0.73 5.09 0.97 23.09 69
Imphal West135.12 99.93 81.62 3.52 0.15 0.47 62.33 1.93 5.60 1.35 26.29 75
Jiribam 3.25 68.75 27.05 0.00 0.46 0.07 95.45 4.56 2.28 0.00 6.16 47
Kakching 43.38 82.84 84.28 0.00 0.27 0.05 79.81 0.69 2.06 0.69 12.48 60
Kamjong 40.55 57.07 43.5020.73 0.21 0.08 11.11 0.00 2.07 0.00 6.01 40
Kangpokpi 22.21 74.87 39.90 2.68 0.26 0.10 70.50 0.52 0.52 0.00 5.88 45
Noney 64.39 66.86 65.14 0.00 0.59 0.02 81.82 0.00 1.97 0.00 11.20 57
Pherzawl 60.92 85.50 20.8915.38 0.24 0.00 Null 0.00 2.42 0.00 6.05 49
Senapati 38.28 88.65 201.65 0.49 0.35 0.16 90.73 0.00 0.70 0.35 8.97 60
Tamenglong 35.39 62.36 94.3929.98 0.45 0.01 68.75 0.00 0.00 1.11 10.03 52
Tengnoupal 34.12 92.67 30.72 0.00 0.00 0.00 67.57 3.30 1.65 0.00 13.53 50
Thoubal 73.92 99.30 94.13 0.00 0.25 0.08 81.87 0.36 3.26 0.36 23.70 70
Ukhrul 37.72 84.09 63.61 0.00 0.22 0.49 70.83 0.00 0.74 0.74 11.42 53
Meghalaya
East Garo Hills71.41 77.97 101.7316.43 0.89 0.05 87.01 2.06 0.00 6.86 19.14 71
East Jaintia Hills43.34 82.16 110.3522.99 0.73 1.70 92.82 4.07 0.00 6.51 14.15 64
East Khasi Hills90.68 81.59 76.5528.81 0.44 0.85 85.04 6.42 0.61 4.60 18.50 67
Eastern West Khasi HillsNull Null Null Null Null Null Null Null Null Null Null *
North Garo Hills84.65 66.74 85.6125.14 0.76 0.01 81.88 2.32 0.00 6.97 10.81 65
Ri Bhoi 83.42 65.13 95.6420.86 0.58 0.31 89.50 7.34 0.77 5.02 10.74 67
South Garo Hills64.25 55.58 104.3220.24 0.91 0.02 88.15 7.03 0.00 5.62 13.77 65
South West Garo Hills92.67 87.75 109.0429.16 0.68 0.02 92.61 9.01 0.00 6.20 12.50 71
South West Khasi Hills60.54 39.09 104.94
33.91 0.50 0.06 81.55 14.12 0.00 17.14 14.52 58
West Garo Hills72.94 68.41 85.1624.31 0.45 0.07 88.11 7.52 0.21 4.08 12.65 64
West Jaintia Hills34.38 74.26 124.6917.55 0.51 1.66 87.00 9.92 0.37 6.25 16.24 62
West Khasi Hills91.22 70.23 106.8119.98 1.37 0.14 92.99 11.12 0.65 5.89 17.73 73
Mizoram
Aizawl 89.72 99.92 135.2617.61 0.33 1.49 85.55 16.87 1.91 0.54 34.78 68
Champhai 77.01 98.28 97.0910.32 2.78 0.77 91.72 5.56 1.39 1.39 22.39 76
Hnahthial 75.98 97.91 99.7016.74 2.81 0.35 Null 28.08 0.00 3.51 29.14 76
Khawzawl 66.88 98.51 77.5818.59 1.36 0.49 Null 32.55 0.00 0.00 22.78 56
Kolasib 69.12 97.07 99.2314.23 0.95 0.18 93.33 9.53 2.38 2.38 19.53 74
Lawngtlai 46.14 73.30 74.2017.31 1.70 0.14 71.43 13.57 0.00 0.85 11.62 55
Lunglei 62.54 82.97 87.9310.42 1.59 0.08 88.81 4.55 0.00 0.76 23.76 66
Mamit 60.11 79.08 85.92 7.85 1.85 0.09 225.58 8.11 0.00 2.32 19.57 69
Saitual 64.15 99.74 92.5212.79 0.99 0.26 Null 15.81 0.00 1.98 19.17 65
Serchhip 61.39 99.76 97.8011.93 0.61 0.18 88.89 6.12 1.53 3.06 27.53 75
Siaha 51.64 87.68 91.1025.29 2.83 0.46 95.20 14.14 0.00 1.77 19.09 68
Nagaland
Chumoukedima Null Null Null Null Null Null Null Null Null Null Null *
Dimapur 36.09 95.86 106.5413.15 0.88 4.72 Null 22.02 1.96 0.98 14.29 51
Kiphire 53.39 89.04 42.63 6.56 1.89 0.47 Null 1.35 2.70 2.70 19.05 67
Kohima 36.06 97.50 74.5513.64 1.47 1.32 Null 5.21 1.89 0.47 18.61 60
Longleng 25.44 95.00 47.42 3.01 1.58 0.32 98.04 0.00 7.92 1.98 20.40 72
Mokokchung 53.86 98.53 64.43 7.83 1.23 0.54 57.82 1.54 3.60 0.51 18.24 64
Mon 17.99 77.15 57.86 1.23 1.92 0.32 83.28 0.00 2.80 0.40 10.83 59
Noklak Null Null Null Null Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null Null Null Null *
Peren 19.74 74.66 48.78 6.17 1.68 0.60 75.40 0.00 4.20 2.10 14.91 63
Phek 23.44 89.31 46.40 4.53 1.41 0.39 96.64 0.61 3.06 0.61 18.48 62
Shamator Null Null Null Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null Null Null Null *
Tuensang 15.44 94.65 47.68 4.02 1.31 1.84 79.52 9.33 4.67 0.93 19.69 60
Wokha 29.25 97.89 50.04 3.91 0.96 0.30 93.65 0.60 3.01 1.20 14.25 63
Zunheboto 25.05 96.89 46.08 1.20 0.71 0.23 92.00 0.00 3.55 0.71 16.70
62
Sikkim
Gangtok 70.10 99.84 73.65 2.51 0.68 0.15 92.72 37.82 2.28 0.00 60.29 66
Gyalshing 85.75 99.49 59.3035.71 2.09 0.07 88.74 53.02 0.00 1.40 28.74 61
Mangan 81.05 96.55 48.0886.21 1.83 0.09 86.08 16.02 0.00 2.29 41.41 62
Namchi 85.38 99.32 63.3218.06 0.75 0.03 82.69 48.35 0.68 0.00 26.22 57
Pakyong Null Null Null0.00 0.00 0.11 86.15 63.93 3.12 1.56 0.78 48
Soreng Null Null Null0.00 0.00 0.03 82.97 46.32 0.00 0.00 0.15 39
Tripura
Dhalai 71.07 94.48 106.59 9.35 0.69 0.57 119.15 16.13 0.00 0.53 16.21 64
Gomati 85.21 99.32 93.14 7.63 0.42 0.33 153.27 15.61 0.00 0.47 15.47 64
Khowai 82.53 98.51 84.68 6.79 0.34 0.44 92.58 19.23 0.00 0.61 12.00 61
North Tripura91.86 97.62 121.60 6.77 0.48 0.28 41.69 11.98 0.00 0.24 10.85 59
Sepahijala 80.69 98.14 111.62 3.17 0.44 0.27 269.23 17.08 0.00 0.42 13.29 64
South Tripura79.21 99.49 92.55 3.92 0.65 0.14 93.96 19.25 0.00 0.45 16.25 64
Unakoti 75.52 93.61 112.9110.65 0.40 0.24 49.69 14.47 0.00 0.36 14.10 58
West Tripura134.55 99.91 83.3521.98 0.39 0.94 111.45 26.03 0.11 0.33 24.52 62
Target 100 100 100 11 3.13 0 100 3.5 5.7 3.70 45 100
TABLE 3.1: PERFORMANCE OF DISTRICTS ON SDG 3
Achieving inclusive and quality education for all
reaffirms the belief that education is one of the
most powerful and proven vehicles for sustainable
development. This goal is aimed at ensuring that
all girls and boys complete primary and secondary
schooling by 2030 and are provided equal access
to affordable vocational training, to eliminate
gender and wealth disparities, and achieve universal
access to a quality higher education. Additionally,
it emphasizes on lifelong learning opportunities,
so as to achieve substantial adult literacy and
numeracy, and on building and upgrading existing
education facilities that are child, disability and
gender-sensitive.
Targets
4.1 By 2030, ensure that all girls and boys
complete free, equitable and quality primary
and secondary education leading to relevant
and effective learning outcomes
4.2 By 2030, ensure that all girls and boys have
access to quality early childhood development,
care and pre‑primary education so that they
are ready for primary education
4.3 By 2030, ensure equal access for all women
and men to affordable and quality technical,
vocational and tertiary education, including
university
4.4 By 2030, substantially increase the number
of youth and adults who have relevant
skills, including technical and vocational
skills, for employment, decent jobs and
entrepreneurship
4.5 By 2030, eliminate gender disparities in
education and ensure equal access to all levels
of education and vocational training for the
vulnerable, including persons with disabilities,
indigenous peoples and children in vulnerable
situations
4.6 By 2030, ensure that all youth and a substantial
proportion of adults, both men and women,
achieve literacy and numeracy
4.7 By 2030, ensure that all learners acquire the
knowledge and skills needed to promote
sustainable development, including, among
others, through education for sustainable
development and sustainable lifestyles, human
rights, gender equality, promotion of a culture
of peace and non-violence, global citizenship
and appreciation of cultural diversity and
of culture’s contribution to sustainable
development
4.a Build and upgrade education facilities that
are child, disability and gender sensitive
and provide safe, non-violent, inclusive and
effective learning environments for all
4.b By 2020, substantially expand globally the
number of scholarships available to developing
countries, in particular, least developed
countries, small island developing States and
African countries, for enrolment in higher
education, including vocational training and
information and communications technology,
technical, engineering and scientific
programmes, in developed countries and other
developing countries
4.c By 2030, substantially increase the supply
of qualified teachers, including through
international cooperation for teacher
training in developing countries, especially
least developed countries and small island
developing States
53
CONTEXT & OVERVIEW
SDG 4
QUALITY EDUCATION
Ensure inclusive and equitable quality education and
promote lifelong learning opportunities for all.
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 4
The score for Goal 4 ranges between 88 and 38 for the
121 districts included in the ranking and computation.
West Tripura [TR], Dimapur [NL] and Gangtok [SK]
are the top performing districts. 80 districts fall in the
category of Front Runners and 30 in the category of Performers, while 11 districts are in the category of
Aspirants with scores less than 50.
FIGURE 4.1: SDG 4 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
West Tripura TR 1 88
Dimapur NL 2 86
Gangtok SK 2 86
Soreng SK 4 85
East Siang AR 5 83
Kohima NL 5 83
Pakyong SK 5 83
Imphal West MN 8 82
Aizawl MZ 8 82
Gyalshing SK 8 82
Namchi SK 8 82
Tawa n g AR 12 81
Kamrup Metropolitan AS 12 81
Mokokchung NL 14 79
Mangan SK 14 79
Dibang Valley AR 16 78
Sivasagar AS 16 78
Khowai TR 16 78
South Tripura TR 16 78
West Siang AR 20 77
Saitual MZ 20 77
Gomati TR 20 77
Leparada AR 23 75
Lower Dibang Valley AR 23 75
Kolasib MZ 23 75
Phek NL 23 75
Sepahijala TR 23 75
Unakoti TR 23 75
Charaideo AS 29 74
Darrang AS 29 74
Dhemaji AS 29 74
Dibrugarh AS 29 74
Jorhat AS 29 74
Dima Hasao AS 34 73
Kamrup AS 34 73
Champhai MZ 34 73
North Tripura TR 34 73
Morigaon AS 38 72
Thoubal MN 38 72
Siaha MZ 38 72
Lohit AR 41 71
Papum Pare AR 41 71
Golaghat AS 41 71
Nalbari AS 41 71
Senapati MN 41 71
Longleng NL 41 71
West Kameng AR 47 70
Baksa AS 47 70
Lakhimpur AS 47 70
Tinsukia AS 47 70
Udalguri AS 47 70
Imphal East MN 47 70
Hnahthial MZ 47 70
Tuensang NL 47 70
Lower Subansiri AR 55 69
Upper Subansiri AR 55 69
Zunheboto NL 55 69
Kurung Kumey AR 58 68
Siang AR 58 68
Sonitpur AS 58 68
Changlang AR 61 67
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
542023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
FIGURE 4.1: SDG 4 INDEX SCORE OF DISTRICTS
District StateRank
Lower Siang AR 61 67
Biswanath AS 61 67
Cachar AS 61 67
Goalpara AS 61 67
Kokrajhar AS 61 67
Khawzawl MZ 61 67
Wokha NL 61 67
Dhalai TR 61 67
Chirang AS 70 66
Hojai AS 70 66
Karbi Anglong AS 70 66
Bishnupur MN 70 66
Kamjong MN 70 66
East Kameng AR 75 65
Kamle AR 75 65
Tirap AR 75 65
Barpeta AS 75 65
Nagaon AS 75 65
Serchhip MZ 75 65
Kra Daadi AR 81 64
Longding AR 81 64
Upper Siang AR 81 64
Karimganj AS 81 64
Majuli AS 81 64
Lunglei MZ 81 64
Mamit MZ 81 64
Namsai AR 88 63
Pakke Kessang AR 88 63
Bongaigaon AS 88 63
Dhubri AS 88 63
Hailakandi AS 88 63
West Karbi Anglong AS 88 63
Chandel MN 88 63
Kiphire NL 88 63
Peren NL 88 63
Kakching MN 97 62
Ukhrul MN 97 62
East Khasi Hills ML 97 62
Mon NL 97 62
Shi Yomi AR 101 61
South Salmara-Mankachar AS 101 61
Churachandpur MN 101 61
Tamenglong MN 101 61
Jiribam MN 105 60
Kangpokpi MN 106 57
Tengnoupal MN 106 57
East Garo Hills ML 108 51
Ri Bhoi ML 108 51
Anjaw AR 110 50
West Jaintia Hills ML 111 47
East Jaintia Hills ML 112 46
Lawngtlai MZ 112 46
Pherzawl MN 114 45
South West Garo Hills ML 115 43
South West Khasi Hills ML 115 43
West Garo Hills ML 115 43
Noney MN 118 42
South Garo Hills ML 119 41
North Garo Hills ML 120 38
West Khasi Hills ML 120 38
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
55
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 4.2: PERFORMANCE OF DISTRICTS IN SDG 4
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
562023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
4.1
Average annual dropout rate at
secondary level (Class 9-10)
3.21
This target corresponds to the global SDG target 4.1 which aims to
ensure that all girls and boys complete free, equitable and quality
primary and secondary education. The National Education Policy,
2020 also aims to curtail drop-out rates with a goal to achieve 100
per cent Gross Enrolment Ratio in preschool to secondary level by
2030. Average of the 5 best scores has been set as the target.
4.5
Ratio of female to male enrolment at
secondary level (Class 9-10)
1
This target is aligned with the global SDG target 4.5 which aims to
eliminate gender disparities in education.
4.1
Percentage of students in grade
VIII achieving at least a minimum
proficiency level in terms of nationally
defined learning outcomes to be
attained at the end of the grade
100
This target corresponds to the global SDG target 4.1 which aims to
ensure that all girls and boys complete free, equitable and quality
primary and secondary education with relevant and effective learning
outcomes.
4.a
Percentage of schools with computers
available
100
The National Education Policy 2020 aims to provide effective and
sufficient infrastructure so that all students have access to safe and
engaging school education at all levels from pre-primary school
to Grade 12. It aims to take special care to ensure that no school
remains deficient on infrastructure support.
4.a
Percentage of schools with access to
electricity
100
The National Education Policy 2020 aims to provide effective and
sufficient infrastructure so that all students have access to safe and
engaging school education at all levels from pre-primary school
to Grade 12. It aims to take special care to ensure that no school
remains deficient on infrastructure support.
4.c
Percentage of trained teachers at
secondary level (Class 9-10)
100
This target is aligned with global SDG target 4.c which aims to
substantially increase the supply of qualified teachers.
4.c
Pupil Teacher Ratio at secondary level
(Class 9-10)
30
The National Education Policy 2020 proposes to ensure a pupil-tea-
cher ratio (PTR) of under 30:1 at each level of school education.
57
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
58Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 4.1 4.5 4.1 4.a 4.a 4.c 4.c
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of female to
male enrolment
at secondary level
(Class 9-10)
Percentage of students in grade 8
achieving at least a minimum pro-
ficiency level in terms of nationally
defined learning outcomes to be
attained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary level
(Class 9-10)
Pupil Teacher Ratio
at secondary level
(Class 9-10)
SDG 4
Arunachal Pradesh
Anjaw 35.62 0.85 69.5 16.22 91.89 91.67 7.70 50
Bichom Null Null Null Null Null Null Null *
Changlang 27.33 1.09 60 35.84 88.55 89.11 13.72 67
Dibang Valley 17.14 1.18 81.5 34.78 86.96 100.00 3.24 78
East Kameng 20.93 1.01 66.5 33.53 45.29 95.80 9.04 65
East Siang 10.22 1.01 83.5 51.85 97.53 93.37 7.97 83
Kamle 27.49 1.36 85 22.78 39.24 97.96 9.07 65
Keyi Panyor Null Null Null Null Null Null Null *
Kra Daadi 20.75 1.29 74.5 18.80 48.87 91.44 7.24 64
Kurung Kumey 34.99 1.03 69 36.36 88.89 94.81 4.74 68
Leparada 11.81 1.04 73 42.86 63.49 97.32 5.77 75
Lohit 17.25 1.20 68 49.06 69.81 88.06 11.58 71
Longding 14.37 1.02 57.5 36.79 42.45 90.39 12.98 64
Lower Dibang Valley 20.65 0.96 81 67.00 79.00 94.26 8.04 75
Lower Siang 20.62 0.98 70 50.00 59.46 89.96 5.49 67
Lower Subansiri 16.79 0.91 82 56.52 87.68 87.17 6.26 69
Namsai 21.08 0.95 75.5 28.44 69.19 88.14 10.47 63
Pakke Kessang 27.52 1.84 70 20.75 43.40 100.00 10.61 63
Papum Pare 29.31 1.08 80 51.68 63.03 94.73 8.38 71
Shi Yomi 23.16 1.50 64.5 28.21 33.33 95.45 12.17 61
Siang 16.85 1.05 80 25.00 50.93 91.86 5.22 68
Tawang 15.26 1.76 80 71.19 79.66 92.58 10.37 81
Tirap 20.39 0.96 72.5 40.28 61.11 92.49 10.37 65
Upper Siang 19.41 0.89 77 37.80 76.38 95.45 7.58 64
Upper Subansiri 8.09 1.08 70.5 41.60 29.20 94.62 13.74 69
West Kameng 26.02 1.11 71.5 52.92 67.92 92.65 9.94 70
West Siang 18.92 1.06 79 38.78 97.28 92.84 5.94 77
Assam
Bajali Null Null Null Null Null Null Null *
Baksa 25.39 1.06 78.5 84.84 88.35 62.12 7.82 70
Barpeta 29.42 1.30 79 58.71 83.89 65.32 12.12 65
Biswanath 31.45 1.18 69 59.26 88.21 78.59 14.10 67
Bongaigaon 31.96 1.24 65 65.36 88.19 65.61 14.67 63
Cachar 27.06 1.13 64.5 67.19 90.20 69.97 18.03 67
Charaideo 23.29 1.19 79 95.20 98.44 61.98 9.22 74
Chirang 27.24 1.16 64 61.43 83.87 73.70 13.07 66
Darrang 18.87 1.26 70 80.66 90.68 73.12 10.63 74
Dhemaji 11.24 1.06 76 59.05 90.83 72.29 10.00 74
Dhubri 24.55 1.29 72.5 49.60 68.92 69.59 18.15 63
Dibrugarh 19.43 1.08 69.5 75.74 97.23 74.57 10.34 74
Dima Hasao 14.94 1.03 77 55.37 89.37 72.48 8.30
73
Goalpara 29.02 1.40 67.5 64.17 89.13 72.86 15.91 67
Golaghat 23.57 1.09 67.5 77.33 91.25 71.00 9.45 71
Hailakandi 22.71 1.25 69 49.95 69.99 68.96 15.08 63
Hojai 28.25 1.48 62 79.34 91.07 63.53 15.17 66
Jorhat 22.65 1.04 80.5 63.69 95.68 76.05 7.64 74
Kamrup 34.85 1.13 79.5 83.31 92.70 79.47 10.02 73
Kamrup Metropolitan 13.82 1.02 85 70.85 96.53 80.26 8.24 81
Karbi Anglong 25.78 1.07 63.5 76.02 86.41 65.99 10.77 66
Karimganj 26.72 1.43 60.5 64.43 82.74 69.57 17.16 64
Kokrajhar 20.28 1.08 71.5 67.36 68.32 69.28 13.89 67
Lakhimpur 21.39 1.10 73.5 58.54 88.49 71.99 7.71 70
Majuli 16.59 0.90 79.5 69.86 89.64 67.88 5.97 64
Morigaon 29.39 1.39 73.5 79.88 90.22 76.33 14.32 72
Nagaon 30.05 1.53 68.5 64.25 88.18 69.36 10.16 65
Nalbari 18.80 1.10 84.5 53.67 87.99 67.84 7.91 71
Sivasagar 20.02 1.03 86 94.63 97.73 65.19 6.22 78
Sonitpur 31.51 1.26 69 73.63 85.58 75.99 13.50 68
South Salmara-Mankachar 27.24 1.55 73.5 55.28 73.93 62.01 14.03 61
Tamulpur Null Null Null Null Null Null Null *
Tinsukia 30.68 1.13 69 73.30 94.88 75.48 13.25 70
Udalguri 16.89 1.17 71 67.28 90.51 63.97 11.85 70
West Karbi Anglong 33.80 1.13 62 58.68 88.08 72.07 12.30 63
TABLE 4.1: PERFORMANCE OF DISTRICTS ON SDG 4
59Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 4.1 4.5 4.1 4.a 4.a 4.c 4.c
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of female to
male enrolment
at secondary level
(Class 9-10)
Percentage of students in grade 8
achieving at least a minimum pro-
ficiency level in terms of nationally
defined learning outcomes to be
attained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary level
(Class 9-10)
Pupil Teacher Ratio
at secondary level
(Class 9-10)
SDG 4
Manipur
Bishnupur 20.01 0.96 74.5 40.92 75.25 83.79 10.80 66
Chandel 25.92 1.09 80.5 14.35 93.48 69.64 9.12 63
Churachandpur 33.43 1.02 84 30.37 67.56 76.38 10.94 61
Imphal East 18.17 0.98 82 43.95 77.34 83.27 7.22 70
Imphal West 0.00 1.00 85.5 55.56 86.48 83.51 7.73 82
Jiribam 21.78 1.19 52.5 29.63 100.00 67.39 14.34 60
Kakching 30.47 0.94 80 50.60 76.79 80.04 9.39 62
Kamjong 1.92 1.08 78 9.94 27.95 93.18 10.82 66
Kangpokpi 24.64 0.97 80.5 20.75 56.98 74.66 9.81 57
Noney 32.22 0.91 71 18.57 36.43 70.23 11.70 42
Pherzawl 41.93 0.95 76 17.69 23.08 81.88 5.62 45
Senapati 4.92 0.98 81 26.70 73.86 81.92 9.56 71
Tamenglong 16.88 1.09 70.5 16.61 36.90 89.55 9.83 61
Tengnoupal 29.75 1.02 72 21.71 69.74 69.42 9.18 57
Thoubal 8.18 0.96 74.5 49.11 77.22 86.26 11.21 72
Ukhrul 22.51 1.07 78 42.73 51.98 73.71 9.55 62
Meghalaya
East Garo Hills 14.57 1.15 43.5 24.44 23.04 76.86 17.05 51
East Jaintia Hills 38.61 1.46 59.5 16.43 30.26 76.36 11.33 46
East Khasi Hills 11.16 1.26 72 34.26 53.69 68.58 9.33 62
Eastern West Khasi Hills Null Null Null Null Null Null Null *
North Garo Hills 44.01 1.26 43 14.43 21.53 75.68 13.42 38
Ri Bhoi 16.93 1.39 61.5 20.24 34.38 65.39 10.82 51
South Garo Hills 30.70 1.22 46 9.80 13.76 76.11 8.82 41
South West Garo Hills 29.25 1.13 50 12.71 14.38 73.67 10.01 43
South West Khasi Hills 26.30 1.29 53 10.43 21.59 66.50 7.46 43
West Garo Hills 25.36 1.20 53 15.23 24.08 61.70 9.77 43
West Jaintia Hills 20.56 1.50 63.5 17.81 28.02 60.96 11.88 47
West Khasi Hills 32.13 1.30 38 10.32 17.02 69.97 11.97 38
Mizoram
Aizawl 0.00 1.11 78.5 67.34 99.21 78.36 10.64 82
Champhai 20.26 1.13 62.5 79.03 98.13 74.81 10.27 73
Hnahthial 32.50 1.21 Null 46.38 93.48 83.20 8.43 70
Khawzawl 24.73 1.14 Null 41.35 95.49 67.36 8.53 67
Kolasib 23.34 1.15 66.5 45.04 98.58 95.28 9.22 75
Lawngtlai 29.45 0.92 57 16.44 56.40 78.44 10.76 46
Lunglei 24.57 1.02 63.5 40.45 78.47 78.50 6.51 64
Mamit 39.96 1.06 68 40.16 79.53 92.59 7.07 64
Saitual 29.85 1.10 Null 63.05 99.51 87.21 7.15 77
Serchhip 23.13 0.92 69 43.04 96.96 87.68 8.12 65
Siaha 0.00 0.98 63 27.99 95.90 82.08 10.18 72
Nagaland
Chumoukedima Null Null Null Null Null
Null Null *
Dimapur 0.37 1.05 80 94.83 96.49 74.98 8.78 86
Kiphire 27.88 1.15 66.5 72.18 72.93 65.61 10.99 63
Kohima 0.00 1.04 80 86.91 89.09 74.86 7.05 83
Longleng 14.63 1.22 71.5 94.50 44.04 73.77 7.10 71
Mokokchung 14.22 0.96 82.5 92.19 94.14 79.33 5.35 79
Mon 26.68 1.16 66.5 82.84 69.97 57.36 9.91 62
Noklak Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null *
Peren 15.99 0.92 75 69.36 75.72 69.06 8.34 63
Phek 25.52 1.10 78 88.46 91.88 74.24 5.45 75
Shamator Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null *
Tuensang 21.88 1.21 64.5 87.24 68.31 77.50 9.07 70
Wokha 33.56 1.07 77 72.97 57.84 82.35 6.05 67
Zunheboto 26.74 1.08 77 67.28 81.99 71.74 5.93 69
Sikkim
Gangtok 14.40 1.03 79 91.77 100.00 88.44 7.22 86
Gyalshing 19.66 1.01 69 94.30 96.37 88.03 4.58 82
Mangan 22.41 1.05 76 80.00 97.27 85.49 5.33 79
Namchi 18.83 1.03 71 91.44 99.17 87.03 5.54 82
Pakyong 24.07 0.98 Null 93.72 98.95 89.63 4.72 83
Soreng 22.86 1.02 Null 96.13 100.00 84.34 3.69 85
Tripura
Dhalai 11.89 1.05 62 28.02 57.29 91.82 11.77 67
Gomati 11.98 0.99 76 42.67 94.95 90.16 13.86 77
Khowai 14.12 1.01 76 53.89 96.61 85.46 9.67 78
North Tripura 13.86 1.14 72.5 44.65 68.82 89.66 10.78 73
Sepahijala 13.21 1.00 77.5 50.31 71.23 88.36 9.03 75
South Tripura 11.60 1.00 84.5 40.75 82.84 91.34 12.60 78
Unakoti 13.33 1.10 70.5 55.17 81.96 86.66 14.94 75
West Tripura 3.52 1.00 81.5 86.69 91.03 88.64 10.30 88
Target 3.21 1 100 100 100 100 30 100
TABLE 4.1: PERFORMANCE OF DISTRICTS ON SDG 4
Ending all discrimination against women and
girls is a basic human right and is a prerequisite
for sustainable development. Goal 5 calls
for ending all forms of violence, trafficking
and sexual exploitation of women and girls.
Recognising and valuing unpaid care and
domestic work is a key component of this goal,
with emphasis on the importance of full and
effective participation and equal opportunities
for leadership at all levels of decision-making in
political, economic and public life for women.
Targets
5.1 End all forms of discrimination against all
women and girls everywhere
5.2 Eliminate all forms of violence against all
women and girls in the public and private
spheres, including trafficking and sexual
and other types of exploitation
5.3 Eliminate all harmful practices, such as
child, early and forced marriage and
female genital mutilation
5.4 Recognize and value unpaid care and
domestic work through the provision of
public services, infrastructure and social
protection policies and the promotion of
shared responsibility within the household
and the family as nationally appropriate
5.5 Ensure women’s full and effective
participation and equal opportunities for
leadership at all levels of decision-making
in political, economic and public life
5.6 Ensure universal access to sexual and
reproductive health and reproductive
rights as agreed in accordance with the
Programme of Action of the International
Conference on Population and
Development and the Beijing Platform
for Action and the outcome documents
of their review conferences
5.a Undertake reforms to give women equal
rights to economic resources, as well
as access to ownership and control
over land and other forms of property,
financial services, inheritance and
natural resources, in accordance with
national laws
5.b Enhance the use of enabling
technology,
in particular information
and
communications technology, to
promote the empowerment of women
5.c Adopt and strengthen sound policies and
enforceable legislation for the promotion
of gender equality and the empowerment
of all women and girls at all levels
61
CONTEXT & OVERVIEW
SDG 5
GENDER EQUALITY
Achieve gender equality and empower all women and girls
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) The score for Goal 5 ranges between 98 and 45 for the
121 districts included in the ranking and computation.
Saitual [MZ], Wokha [NL] and Longleng [NL] are the
top performing districts. 112 districts fall in the category
of Front Runners and 8 in the category of Performers,
while 1 district is in the category of Aspirant with scores
less than 50.
NER District SDG Index: Goal 5
0 2010 4030 50 60 908070 100
FIGURE 5.1: SDG 5 INDEX SCORE OF DISTRICTS
District StateRank
Saitual MZ 1 98
Wokha NL 1 98
Longleng NL 3 96
Mokokchung NL 3 96
Zunheboto NL 5 95
Mon NL 6 94
West Tripura TR 7 91
Tawa n g AR 8 90
Karbi Anglong AS 8 90
Tuensang NL 8 90
Champhai MZ 11 88
Khowai TR 11 88
Kurung Kumey AR 13 87
Biswanath AS 13 87
Golaghat AS 13 87
Dhalai TR 13 87
West Karbi Anglong AS 17 86
Hnahthial MZ 17 86
Kolasib MZ 17 86
Kohima NL 17 86
Baksa AS 21 85
Charaideo AS 21 85
Dhemaji AS 21 85
Dima Hasao AS 21 85
Sivasagar AS 21 85
Lunglei MZ 21 85
North Tripura TR 21 85
Dibrugarh AS 28 84
Karimganj AS 28 84
Sepahijala TR 28 84
Chirang AS 31 83
Lakhimpur AS 31 83
Peren NL 31 83
Barpeta AS 34 82
Udalguri AS 34 82
Jiribam MN 34 82
Phek NL 34 82
Gyalshing SK 34 82
Gomati TR 34 82
Kokrajhar AS 40 81
Nagaon AS 40 81
South Salmara-Mankachar AS 40 81
Tinsukia AS 40 81
South Tripura TR 40 81
Unakoti TR 40 81
Dhubri AS 46 80
Hailakandi AS 46 80
Morigaon AS 46 80
Noney MN 46 80
Khawzawl MZ 46 80
Serchhip MZ 46 80
Dimapur NL 46 80
Dibang Valley AR 53 79
Shi Yomi AR 53 79
Bongaigaon AS 53 79
Jorhat AS 53 79
Kamle AR 57 78
Lower Subansiri AR 57 78
Namsai AR 57 78
Tengnoupal MN 57 78
Aizawl MZ 57 78
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
622023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 5.1: SDG 5 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Goalpara AS 62 77
Sonitpur AS 62 77
South West Garo Hills ML 62 77
East Kameng AR 65 76
Majuli AS 65 76
Nalbari AS 65 76
Kamjong MN 65 76
Kiphire NL 65 76
Siang AR 70 75
Upper Subansiri AR 70 75
Cachar AS 70 75
Hojai AS 70 75
Imphal East MN 70 75
Thoubal MN 70 75
Lawngtlai MZ 70 75
Changlang AR 77 74
Longding AR 77 74
Tirap AR 77 74
West Kameng AR 77 74
Tamenglong MN 77 74
Namchi SK 77 74
Lower Dibang Valley AR 83 73
Upper Siang AR 83 73
Kamrup Metropolitan AS 83 73
West Jaintia Hills ML 83 73
Mamit MZ 83 73
Chandel MN 88 72
East Garo Hills ML 88 72
Ri Bhoi ML 88 72
Soreng SK 88 72
Lohit AR 92 71
Siaha MZ 92 71
East Siang AR 94 70
Lower Siang AR 94 70
Darrang AS 94 70
Ukhrul MN 94 70
West Garo Hills ML 94 70
Gangtok SK 94 70
South West Khasi Hills ML 100 69
Leparada AR 101 68
Mangan SK 101 68
Churachandpur MN 103 67
Kakching MN 103 67
East Khasi Hills ML 103 67
West Khasi Hills ML 103 67
Pakyong SK 103 67
Anjaw AR 108 66
Kamrup AS 108 66
Senapati MN 108 66
South Garo Hills ML 108 66
West Siang AR 112 65
Pakke Kessang AR 113 64
Imphal West MN 114 63
Kangpokpi MN 114 63
Bishnupur MN 116 59
North Garo Hills ML 116 59
Papum Pare AR 118 58
East Jaintia Hills ML 119 57
Kra Daadi AR 120 55
Pherzawl MN 121 45
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
63
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 5.2: PERFORMANCE OF DISTRICTS IN SDG 5
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
642023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
5.2
Crimes against women per 10,000
female population
0
This target is aligned with the global SDG target 5.2 that aims to
eliminate all forms of violence against women and girls in the public
and private spheres.
5.1 Sex ratio at birth 950
The 2019 UNFPA report on ‘‘Sex Ratio at Birth in India: Recent
trends and patterns’’ observes that in the absence of sex selection
the Sex Ratio at Birth (SRB) is around 105 male births per 100
female births or around 950 female births per 1,000 male births.
5.2
Percentage of sexual crimes against
women to total crimes against women
0
This target is aligned with the global SDG target 5.2 that aims to
eliminate all forms of violence against women and girls in the public
and private spheres, including trafficking and sexual and other types
of exploitation.
5.6
Unmet need for family planning for
currently married women aged 15-49
years
0
This target corresponds to the global SDG target 5.6 that aims
ensure universal access to sexual and reproductive health and
reproductive rights.
5.a
Exclusive women Self Help Groups
(SHGs) in bank linked SHGs
99.4
Global SDG target 5.a aims to undertake reforms to give women
equal rights to economic resources, as well as access to financial
services. Average of the 5 best scores has been set as the target.
65
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
66Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 5.2 5.1 5.2 5.6 5.a
District
Crimes against women per
10,000 female population
Sex ratio at birth
Percentage of sexual crimes
against women to total crimes
against women
Unmet need for family
planning for currently married
women aged 15-49 years
Exclusive women SHGs in
bank linked SHGs
SDG 5
Arunachal Pradesh
Anjaw 4.14 818 50.00 6.8 47.4 66
Bichom Null Null Null Null Null *
Changlang 2.24 962 68.75 6.7 45.3 74
Dibang Valley 0.00 778 0.00 4.6 61.9 79
East Kameng 4.37 1189 100.00 9.7 91.4 76
East Siang 6.74 931 80.95 17.6 94.2 70
Kamle 0.90 1161 100.00 Null 78.6 78
Keyi Panyor Null Null Null Null Null *
Kra Daadi 0.42 636 100.00 16.5 87.7 55
Kurung Kumey 0.00 971 0.00 16.4 86.3 87
Leparada 8.18 920 80.00 Null 77.1 68
Lohit 5.98 992 64.29 14.6 70.8 71
Longding 1.42 867 50.00 7.3 55.6 74
Lower Dibang Valley 4.23 901 90.91 4.9 74.5 73
Lower Siang 5.62 923 66.67 Null 58.4 70
Lower Subansiri 3.33 966 71.43 8.5 Null 78
Namsai 1.52 1002 80.00 8.7 71.4 78
Pakke Kessang 6.51 833 100.00 Null 89.7 64
Papum Pare 17.74 980 34.67 20.3 72.8 58
Shi Yomi 3.08 1192 100.00 Null 94.2 79
Siang 1.96 871 100.00 5.0 86.0 75
Tawang 1.44 1029 0.00 14.6 99.3 90
Tirap 0.38 934 100.00 10.6 66.4 74
Upper Siang 4.21 1056 85.71 11.9 77.6 73
Upper Subansiri 2.62 895 33.33 17.3 80.2 75
West Kameng 2.28 910 50.00 17.0 78.6 74
West Siang 9.87 914 72.00 15.5 83.4 65
Assam
Bajali Null Null Null Null Null *
Baksa 2.65 929 24.19 12.5 100.0 85
Barpeta 7.15 965 23.35 12.3 100.0 82
Biswanath 6.34 961 19.90 5.3 100.0 87
Bongaigaon 7.77 943 19.86 16.1 99.9 79
Cachar 11.92 969 20.02 15.6 100.0 75
Charaideo 6.78 949 22.37 8.3 100.0 85
Chirang 6.83 962 24.07 9.8 99.7 83
Darrang 16.53 953 21.63 14.8 100.0 70
Dhemaji 5.97 966 32.50 7.1 99.8 85
Dhubri 9.04 971 23.00 11.5 100.0 80
Dibrugarh 6.08 918 16.20 8.7 100.0 84
Dima Hasao 2.90 924 33.33 9.7 100.0 85
Goalpara 13.60 941 19.47 7.4 100.0 77
Golaghat 3.82 939 13.00 10.9 100.0 87
Hailakandi 9.40 944 33.11 8.6 100.0 80
Hojai 13.13 959 16.92 13.2 99.9 75
Jorhat 7.54 914 34.50 10.4 100.0 79
Kamrup 16.47 967 38.13 17.6 100.0 66
Kamrup Metropolitan 16.15 935 24.41 8.8 100.0 73
Karbi Anglong 1.80 976 20.69 9.3 100.0 90
Karimganj 7.90 953 17.02 8.6 99.5 84
Kokrajhar 7.99 961 31.12 10.0 99.9 81
Lakhimpur 7.79 950 18.55 9.8 100.0 83
Majuli 8.20 890 28.36 11.6 100.0 76
Morigaon 11.64 961 21.72 6.5 99.9 80
Nagaon 8.39 969 20.26 12.3 100.0 81
Nalbari
9.69 923 30.49 13.2 100.0 76
Sivasagar 6.69 980 18.14 8.3 99.3 85
Sonitpur 12.71 905 17.61 5.8 100.0 77
South Salmara-Mankachar 10.40 953 17.25 8.0 99.6 81
Tamulpur Null Null Null Null Null *
Tinsukia 6.98 941 28.98 11.0 100.0 81
Udalguri 6.27 956 17.12 14.6 100.0 82
West Karbi Anglong 2.77 901 25.00 7.1 99.4 86
TABLE 5.1: PERFORMANCE OF DISTRICTS ON SDG 5
67Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 5.2 5.1 5.2 5.6 5.a
District
Crimes against women per
10,000 female population
Sex ratio at birth
Percentage of sexual crimes
against women to total crimes
against women
Unmet need for family
planning for currently married
women aged 15-49 years
Exclusive women SHGs in
bank linked SHGs
SDG 5
Manipur
Bishnupur 1.69 808 65.00 20.0 51.0 59
Chandel 0.25 931 0.00 11.0 1.3 72
Churachandpur 0.87 949 80.00 8.7 16.1 67
Imphal East 2.11 908 75.00 16.7 97.4 75
Imphal West 3.27 930 55.81 12.5 9.0 63
Jiribam 1.41 1196 66.67 Null 76.9 82
Kakching 2.33 1096 82.35 Null 28.4 67
Kamjong 0.00 1193 0.00 Null 3.6 76
Kangpokpi 0.11 976 100.00 Null 14.3 63
Noney 0.00 988 0.00 Null 21.1 80
Pherzawl 0.98 781 100.00 Null 0.0 45
Senapati 0.15 934 100.00 8.5 20.0 66
Tamenglong 0.23 914 0.00 8.4 8.3 74
Tengnoupal 1.69 962 20.00 Null 34.2 78
Thoubal 2.82 881 69.23 6.0 70.3 75
Ukhrul 0.76 1005 80.00 12.7 40.3 70
Meghalaya
East Garo Hills 4.35 890 36.84 21.0 87.8 72
East Jaintia Hills 6.97 1050 146.67 26.0 92.2 57
East Khasi Hills 4.84 937 37.18 33.0 89.1 67
Eastern West Khasi Hills Null Null Null Null Null *
North Garo Hills 2.81 998 166.67 25.2 88.8 59
Ri Bhoi 5.15 954 32.14 27.0 87.3 72
South Garo Hills 3.47 926 92.31 25.3 87.6 66
South West Garo Hills 1.17 955 25.00 30.4 99.7 77
South West Khasi Hills 3.06 980 75.00 26.2 85.5 69
West Garo Hills 6.27 916 41.76 19.7 79.6 70
West Jaintia Hills 3.86 974 27.78 29.3 92.4 73
West Khasi Hills 7.47 956 68.42 25.8 93.9 67
Mizoram
Aizawl 3.25 967 35.48 24.0 99.8 78
Champhai 2.51 972 21.05 11.2 100.0 88
Hnahthial 2.10 889 37.50 Null 97.1 86
Khawzawl 6.05 906 50.00 Null 100.0 80
Kolasib 2.68 1040 12.50 15.6 99.8 86
Lawngtlai 2.86 967 90.91 17.3 100.0 75
Lunglei 1.73 970 33.33 15.4 100.0 85
Mamit 2.89 923 100.00 17.0 99.9 73
Saitual 1.60 1037 0.00 Null 100.0 98
Serchhip 3.72 1096 50.00 15.9 100.0 80
Siaha 2.14 838 50.00 22.5 99.9 71
Nagaland
Chumoukedima Null Null Null Null Null *
Dimapur 0.72 902 54.55 14.3 92.5 80
Kiphire 0.28 887 66.67 17.3 95.5 76
Kohima 0.97 915 40.00 9.1 100.0 86
Longleng 0.85 971 0.00 4.3 96.6 96
Mokokchung 0.32 973 0.00 6.4 100.0 96
Mon 0.51 967 0.00 3.7 85.5 94
Noklak Null Null Null Null Null *
Niuland Null Null Null Null Null *
Peren 0.70 976 66.67 6.2 77.2 83
Phek 0.38 841 50.00 6.5 96.3 82
Shamator Null Null Null Null Null *
Tseminyu Null Null Null Null Null *
Tuensang 0.51 930 0.00 12.9 100.0 90
Wokha 0.12 996 0.00 3.2 100.0
98
Zunheboto 0.43 930 0.00 2.8 91.4 95
Sikkim
Gangtok 6.92 964 94.74 17.7 100.0 70
Gyalshing 5.51 1018 75.00 4.3 100.0 82
Mangan 6.32 871 100.00 12.8 100.0 68
Namchi 5.98 852 78.57 5.2 100.0 74
Pakyong 7.11 Null 100.00 Null 100.0 67
Soreng 4.42 Null 100.00 Null 100.0 72
Tripura
Dhalai 3.59 925 40.91 4.0 100.0 87
Gomati 5.90 977 33.87 12.1 100.0 82
Khowai 2.37 943 50.00 4.1 100.0 88
North Tripura 5.42 1001 46.85 6.1 100.0 85
Sepahijala 3.25 1013 23.68 15.3 100.0 84
South Tripura 3.75 948 36.59 17.3 100.0 81
Unakoti 7.85 954 38.32 9.7 100.0 81
West Tripura 3.25 987 33.33 2.5 100.0 91
Target 0 950 0 0 99.4 100
TABLE 5.1: PERFORMANCE OF DISTRICTS ON SDG 5
Goal 6 calls for access to safe and affordable
drinking water, sanitation facilities, and hygiene
for all by 2030. Water resources are also critical
for agriculture and industrial use, and therefore
protecting and restoring water-related ecosystems
is essential. The goal is aimed at -improving
water quality by reducing pollution, substantially
increasing water-use efficiency across all sectors,
and strengthening the participation of local
communities in improving water and sanitation
management.
Targets
6.1 By 2030, achieve universal and equitable
access to safe and affordable drinking
water for all
6.2 By 2030, achieve access to adequate and
equitable sanitation and hygiene for all
and end open defecation, paying special
attention to the needs of women and girls
and those in vulnerable situations
6.3 By 2030, improve water quality by reducing
pollution, eliminating dumping and
minimizing release of hazardous chemicals
and materials, halving the proportion of
untreated wastewater and substantially
increasing recycling and safe reuse globally
6.4 By 2030, substantially increase water-use
efficiency across all sectors and ensure
sustainable withdrawals and supply of
freshwater to address water scarcity and
substantially reduce the number of people
suffering from water scarcity
6.5 By 2030, implement integrated water
resources management at all levels, including
through transboundary cooperation as
appropriate
6.6 By 2020, protect and restore water-related
ecosystems, including mountains, forests,
wetlands, rivers, aquifers and lakes
6.a By 2030, expand international cooperation
and capacity-building support to developing
countries in water- and sanitation-related
activities and programmes, including water
harvesting, desalination, water efficiency,
wastewater treatment, recycling and reuse
technologies
6.b Support and strengthen the participation of
local communities in improving water and
sanitation management
69
CONTEXT & OVERVIEW
SDG 6
CLEAN WATER AND SANITATION
Ensure availability and sustainable management of water
and sanitation for all
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 6
The score for Goal 6 ranges between 94 and 52 for the
121 districts included in the ranking and computation.
Saitual [MZ] and Serchhip [MZ] are the top performing
districts. 114 districts fall in the category of Front
Runners and 7 in the category of Performers, while
no district is in the category of Aspirants with scores
less than 50.
0 2010 4030 50 60 908070 100
FIGURE 6.1: SDG 6 INDEX SCORE OF DISTRICTS
District StateRank
Saitual MZ 1 94
Serchhip MZ 1 94
Leparada AR 3 92
Lohit AR 3 92
Lower Dibang Valley AR 3 92
Champhai MZ 3 92
Soreng SK 3 92
Shi Yomi AR 8 91
Aizawl MZ 8 91
Mamit MZ 8 91
Pakyong SK 8 91
Anjaw AR 12 90
Dibang Valley AR 12 90
Lower Subansiri AR 12 90
Khawzawl MZ 12 90
Kolasib MZ 12 90
Lunglei MZ 12 90
Siaha MZ 12 90
Mokokchung NL 12 90
Gyalshing SK 12 90
Kra Daadi AR 21 89
West Siang AR 21 89
Hnahthial MZ 21 89
Longleng NL 21 89
Gangtok SK 21 89
Mangan SK 21 89
Upper Siang AR 27 88
West Kameng AR 27 88
Mon NL 27 88
Peren NL 27 88
Wokha NL 27 88
Namchi SK 27 88
Changlang AR 33 87
Tawa n g AR 33 87
Kakching MN 33 87
Lawngtlai MZ 33 87
Lower Siang AR 37 86
Tirap AR 37 86
Sivasagar AS 37 86
Churachandpur MN 37 86
Dimapur NL 37 86
Kohima NL 37 86
East Siang AR 43 85
Pakke Kessang AR 43 85
Tamenglong MN 43 85
Namsai AR 46 84
Dima Hasao AS 46 84
Kiphire NL 46 84
Longding AR 49 83
Upper Subansiri AR 49 83
Chandel MN 49 83
Senapati MN 49 83
Papum Pare AR 53 82
Tengnoupal MN 53 82
Phek NL 53 82
Kamle AR 56 81
Kurung Kumey AR 56 81
Dibrugarh AS 56 81
South Garo Hills ML 56 81
Tuensang NL 56 81
Siang AR 61 80
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
702023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 6.1: SDG 6 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Kamrup Metropolitan AS 61 80
Kangpokpi MN 61 80
Noney MN 61 80
East Kameng AR 65 79
Baksa AS 65 79
Kamjong MN 65 79
West Khasi Hills ML 65 79
Golaghat AS 69 78
Jorhat AS 69 78
Lakhimpur AS 69 78
Majuli AS 69 78
South West Khasi Hills ML 69 78
Cachar AS 74 77
East Garo Hills ML 74 77
East Khasi Hills ML 74 77
Charaideo AS 77 76
Goalpara AS 77 76
Karbi Anglong AS 77 76
Udalguri AS 77 76
Chirang AS 81 75
Karimganj AS 81 75
Kokrajhar AS 81 75
North Garo Hills ML 81 75
Ri Bhoi ML 81 75
Zunheboto NL 81 75
Dhemaji AS 87 74
Hojai AS 87 74
Imphal East MN 87 74
Thoubal MN 87 74
Nalbari AS 91 73
Sonitpur AS 91 73
South Salmara-Mankachar AS 91 73
Tinsukia AS 91 73
Imphal West MN 95 72
Jiribam MN 95 72
Pherzawl MN 95 72
Ukhrul MN 95 72
West Jaintia Hills ML 95 72
Bongaigaon AS 100 71
Hailakandi AS 100 71
West Karbi Anglong AS 100 71
West Garo Hills ML 100 71
Barpeta AS 104 70
Bishnupur MN 104 70
Biswanath AS 106 69
East Jaintia Hills ML 106 69
Kamrup AS 108 68
Sepahijala TR 109 67
Dhubri AS 110 66
Nagaon AS 110 66
West Tripura TR 110 66
Morigaon AS 113 65
Gomati TR 113 65
North Tripura TR 115 64
Khowai TR 116 63
Unakoti TR 117 59
South West Garo Hills ML 118 58
Dhalai TR 119 57
South Tripura TR 119 57
Darrang AS 121 52
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
71
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 6.2: PERFORMANCE OF DISTRICTS IN SDG 6
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
722023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
6.1
Percentage of rural population using
an improved drinking water source
100
Global SDG target 6.1 aims to achieve universal and equitable
access to safe and affordable drinking water for all by 2030.
6.1
Percentage of rural population getting
safe and adequate drinking water
within premises through Piped Water
Supply (PWS)
100
The Jal Jeevan Mission aims to provide piped water supply to the
entire rural population by 2024.
6.2
Percentage of population living in
households that use an improved
sanitation facility
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030.
6.2
Percentage of individual household
toilets constructed against target
(SBM(G))
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030. This is also in line with the objectives of the Government
of India’s Swachh Bharat Mission (Gramin).
6.2
Percentage of schools with functional
toilet facility for girls
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030.
6.2
Percentage of GPs/villages verified as
ODF (SBM(G)) in the district
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030. This is also in line with the objectives of the Government
of India’s Swachh Bharat Mission (Gramin).
6.4 Stage of groundwater extraction (%)0.06
Global SDG target 6.4 that aims to substantially increase water-use
efficiency across all sectors and ensure sustainable withdrawals to
address water scarcity. Average of the 5 best scores has been set
as the target.
73
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
74Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 6.1 6.1 6.2 6.2 6.2 6.2 6.4
District
Percentage of rural
population using an
improved drinking
water source
Percentage of rural
population getting
safe and adequate
drinking water within
premises through
Piped Water Supply
(PWS)
Percentage of
population living
in households that
use an improved
sanitation facility
Toilets constructed
against
target - SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of GPs/
Villages verified as
ODF in the district
Stage of
groundwater
extraction (%)
SDG 6
Arunachal Pradesh
Anjaw 100.00 89.84 86.8 100.00 90.54 100.00 Null 90
Bichom Null Null Null Null Null Null Null *
Changlang 100.00 89.97 82.3 100.00 76.81 100.00 0.66 87
Dibang Valley 100.00 91.77 95.0 100.00 73.91 100.00 Null 90
East Kameng 100.00 95.34 75.6 100.00 46.15 100.00 2.63 79
East Siang 100.00 90.87 83.9 100.00 62.35 100.00 0.88 85
Kamle 100.00 92.00 Null 100.00 45.57 100.00 Null 81
Keyi Panyor Null Null Null Null Null Null Null *
Kra Daadi 100.00 92.83 89.3 100.00 78.95 100.00 Null 89
Kurung Kumey 100.00 92.76 78.3 100.00 61.62 100.00 Null 81
Leparada 100.00 92.92 Null 100.00 79.37 100.00 Null 92
Lohit 100.00 92.13 83.7 100.00 95.28 100.00 0.73 92
Longding 100.00 92.58 83.5 100.00 61.32 100.00 Null 83
Lower Dibang Valley 100.00 91.15 89.9 100.00 88.00 100.00 0.33 92
Lower Siang 100.00 94.02 Null 100.00 58.11 100.00 Null 86
Lower Subansiri 100.00 92.89 82.8 100.00 87.59 100.00 2.33 90
Namsai 100.00 90.67 75.1 100.00 81.99 100.00 Null 84
Pakke Kessang 100.00 92.14 Null 100.00 58.49 100.00 Null 85
Papum Pare 100.00 93.11 75.7 100.00 59.66 100.00 1.28 82
Shi Yomi 100.00 93.20 Null 100.00 76.92 100.00 Null 91
Siang 100.00 93.47 91.2 100.00 37.96 100.00 Null 80
Tawang 100.00 89.05 81.7 100.00 85.34 100.00 Null 87
Tirap 100.00 90.24 86.7 100.00 64.34 100.00 1.75 86
Upper Siang 100.00 95.74 91.8 100.00 68.25 100.00 Null 88
Upper Subansiri 100.00 94.20 80.9 100.00 56.00 100.00 0.61 83
West Kameng 100.00 89.75 88.9 100.00 69.58 100.00 0.11 88
West Siang 100.00 93.78 87.7 100.00 72.79 100.00 1.03 89
Assam
Bajali Null Null Null Null Null Null Null *
Baksa 100.00 73.93 68.9 93.83 86.65 100.00 3.49 79
Barpeta 99.43 76.14 63.7 95.63 90.09 100.00 29.68 70
Biswanath 87.66 63.64 76.6 93.64 85.53 100.00 Null 69
Bongaigaon 95.91 71.02 72.5 93.30 90.58 100.00 25.76 71
Cachar 100.00 74.24 57.6 95.55 91.82 100.00 3.29 77
Charaideo 94.98 63.12 75.9 93.05 97.96 100.00 Null 76
Chirang 97.10 51.81 77.1 96.24 83.21 100.00 2.75 75
Darrang 72.72 72.47 67.9 93.66 90.25 100.00 42.71 52
Dhemaji 89.35 65.46 70.8 94.38 93.05 100.00 4.05 74
Dhubri 99.66 66.26 61.8 94.77 84.51 100.00 29.72 66
Dibrugarh 99.17 70.06 75.3 95.19 95.94 100.00 7.63 81
Dima Hasao 100.00 74.03 83.8 94.82
81.11 100.00 1.01 84
Goalpara 100.00 70.70 75.3 95.17 91.39 100.00 20.82 76
Golaghat 95.05 69.29 73.1 94.73 93.65 100.00 5.42 78
Hailakandi 100.00 64.27 60.0 96.41 67.68 100.00 3.62 71
Hojai 99.85 65.62 63.1 94.08 93.29 100.00 Null 74
Jorhat 96.71 57.69 80.4 94.94 96.48 100.00 9.35 78
Kamrup 99.02 61.26 68.7 94.25 96.29 100.00 33.91 68
Kamrup Metropolitan 100.00 77.17 65.2 95.65 96.32 100.00 Null 80
Karbi Anglong 99.01 57.89 75.2 92.45 84.14 100.00 2.48 76
Karimganj 100.00 68.10 61.5 96.17 81.21 100.00 2.94 75
Kokrajhar 97.13 71.18 72.2 95.64 75.64 100.00 5.63 75
Lakhimpur 99.87 72.86 74.2 94.15 87.23 100.00 10.26 78
Majuli 100.00 81.12 65.6 93.68 88.03 100.00 Null 78
Morigaon 99.77 49.88 62.3 94.68 87.36 100.00 25.21 65
Nagaon 96.41 64.78 66.1 93.83 89.19 100.00 28.86 66
Nalbari 99.98 72.35 68.1 94.31 92.76 100.00 24.11 73
Sivasagar 99.12 80.86 82.3 94.53 94.89 100.00 4.19 86
Sonitpur 92.74 67.67 72.2 94.61 87.78 100.00 10.44 73
South Salmara-Mankachar 100.00 74.14 59.0 94.68 82.18 100.00 Null 73
Tamulpur Null Null Null Null Null Null Null *
Tinsukia 87.94 72.77 66.7 94.39 95.97 100.00 6.67 73
Udalguri 96.86 63.82 73.8 94.72 90.76 100.00 8.90 76
West Karbi Anglong 100.00 46.18 76.7 92.49 82.07 100.00 Null 71
TABLE 6.1: PERFORMANCE OF DISTRICTS ON SDG 6
75Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 6.1 6.1 6.2 6.2 6.2 6.2 6.4
District
Percentage of rural
population using an
improved drinking
water source
Percentage of rural
population getting
safe and adequate
drinking water within
premises through
Piped Water Supply
(PWS)
Percentage of
population living
in households that
use an improved
sanitation facility
Toilets constructed
against
target - SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of GPs/
Villages verified as
ODF in the district
Stage of
groundwater
extraction (%)
SDG 6
Manipur
Bishnupur 100.00 69.86 52.6 100.00 68.65 100.00 5.67 70
Chandel 100.00 67.67 85.2 100.00 88.26 100.00 Null 83
Churachandpur 100.00 79.05 81.2 100.00 94.01 100.00 6.18 86
Imphal East 100.00 77.20 59.5 100.00 71.76 100.00 7.98 74
Imphal West 100.00 68.46 58.7 100.00 80.11 100.00 10.97 72
Jiribam 100.00 39.89 Null 100.00 74.53 100.00 Null 72
Kakching 100.00 77.81 Null 100.00 81.55 100.00 Null 87
Kamjong 100.00 67.20 Null 100.00 65.84 100.00 Null 79
Kangpokpi 100.00 80.58 Null 100.00 53.40 100.00 Null 80
Noney 100.00 66.52 Null 100.00 69.29 100.00 Null 80
Pherzawl 100.00 48.09 Null 100.00 64.62 100.00 Null 72
Senapati 100.00 70.87 84.4 100.00 87.22 100.00 Null 83
Tamenglong 100.00 73.58 77.9 100.00 99.63 100.00 Null 85
Tengnoupal 100.00 86.66 Null 100.00 53.95 100.00 Null 82
Thoubal 100.00 76.14 61.3 100.00 72.49 100.00 9.84 74
Ukhrul 100.00 71.70 81.4 100.00 44.93 100.00 Null 72
Meghalaya
East Garo Hills 100.00 81.52 83.9 71.84 69.83 100.00 6.93 77
East Jaintia Hills 100.00 52.07 83.6 76.33 57.20 100.00 2.28 69
East Khasi Hills 100.00 63.84 80.9 84.58 78.91 100.00 2.58 77
Eastern West Khasi Hills Null Null Null NUll Null Null Null *
North Garo Hills 100.00 74.81 84.9 66.47 68.27 100.00 3.59 75
Ri Bhoi 100.00 78.08 85.3 59.72 72.85 100.00 6.17 75
South Garo Hills 100.00 80.10 88.4 76.96 71.25 100.00 1.59 81
South West Garo Hills 100.00 76.94 71.4 37.57 51.73 100.00 17.65 58
South West Khasi Hills 100.00 71.35 89.6 57.66 85.02 100.00 1.71 78
West Garo Hills 100.00 65.99 86.3 64.58 58.89 100.00 4.15 71
West Jaintia Hills 100.00 64.89 75.1 83.20 64.95 100.00 4.45 72
West Khasi Hills 100.00 74.30 87.8 74.48 72.06 100.00 1.74 79
Mizoram
Aizawl 100.00 89.99 96.1 100.00 94.69 100.00 14.06 91
Champhai 100.00 91.79 98.3 100.00 80.52 100.00 3.03 92
Hnahthial 100.00 87.62 Null 100.00 75.36 100.00 Null 89
Khawzawl 100.00 92.09 Null 100.00 76.69 100.00 Null 90
Kolasib 100.00 91.72 96.8 100.00 66.31 100.00 1.30 90
Lawngtlai 100.00 89.62 90.3 100.00 67.99 100.00 3.62 87
Lunglei 100.00 90.43 95.6 100.00 74.65 100.00 4.10 90
Mamit 100.00 91.40 92.7 100.00 78.68 100.00 2.06 91
Saitual 100.00 90.25 Null 100.00 89.16 100.00 Null 94
Serchhip 100.00 92.13 98.2 100.00 92.61 100.00 6.19 94
Siaha 100.00 91.83 91.5 100.00 84.70 100.00 5.78 90
Nagaland
Chumoukedima Null Null
Null Null Null Null Null *
Dimapur 100.00 77.50 81.1 100.00 92.80 100.00 3.98 86
Kiphire 100.00 89.36 83.1 100.00 72.18 100.00 6.43 84
Kohima 100.00 79.41 87.4 100.00 93.09 100.00 10.51 86
Longleng 100.00 83.20 86.6 100.00 88.99 100.00 1.33 89
Mokokchung 100.00 74.69 96.7 100.00 89.06 100.00 0.62 90
Mon 100.00 79.01 86.4 100.00 92.08 100.00 5.11 88
Noklak Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null *
Peren 100.00 79.97 89.4 100.00 83.24 100.00 0.90 88
Phek 100.00 81.37 90.1 100.00 58.12 100.00 6.43 82
Shamator Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null *
Tuensang 100.00 76.64 92.0 100.00 65.02 100.00 10.09 81
Wokha 100.00 82.34 88.5 100.00 79.46 100.00 1.38 88
Zunheboto 100.00 80.76 88.9 100.00 32.35 100.00 8.06 75
Sikkim
Gangtok 100.00 85.99 85.0 100.00 99.55 100.00 9.29 89
Gyalshing 100.00 81.17 88.9 100.00 97.83 100.00 4.63 90
Mangan 100.00 79.82 83.8 100.00 98.95 100.00 2.58 89
Namchi 100.00 77.34 91.7 100.00 96.77 100.00 9.78 88
Pakyong 100.00 74.23 Null 100.00 96.67 100.00 3.60 91
Soreng 100.00 77.50 Null 100.00 100.00 100.00 5.41 92
Tripura
Dhalai 97.87 63.68 67.6 25.51 64.58 100.00 6.73 57
Gomati 96.78 69.37 77.4 36.92 71.66 100.00 5.42 65
Khowai 97.99 65.82 67.8 42.30 78.04 100.00 8.67 63
North Tripura 100.00 72.60 74.1 33.58 78.48 100.00 13.26 64
Sepahijala 99.52 67.59 75.4 54.85 74.54 100.00 11.91 67
South Tripura 95.14 67.01 68.6 26.75 64.33 100.00 6.45 57
Unakoti 94.52 76.06 61.8 30.10 78.51 100.00 8.37 59
West Tripura 99.11 80.15 80.2 23.94 90.26 100.00 20.20 66
Target 100 100 100 100 100 100 0.06 100
TABLE 6.1: PERFORMANCE OF DISTRICTS ON SDG 6
Energy security is a prerequisite for socio-
economic development. Access to energy
enables people to augment their income and
productivity, enhance access to healthcare, water
and education, and improve their overall well-
being. Goal 7 is aimed at ensuring universal access
to affordable, reliable and efficient energy services
by 2030. Expanding infrastructure and upgrading
technology to provide clean and efficient energy
is critical to this endeavour.
Targets
7.1 By 2030, ensure universal access to affordable,
reliable and modern energy services
7.2 By 2030, increase substantially the share of
renewable energy in the global energy mix
7.3 By 2030, double the global rate of improvement
in energy efficiency
7.a By 2030, enhance international cooperation
to facilitate access to clean energy research
and technology, including renewable
energy, energy efficiency and advanced and
cleaner fossil-fuel technology, and promote
investment in energy infrastructure and
clean energy technology
7.b By 2030, expand infrastructure and upgrade
technology for supplying modern and
sustainable energy services for all in developing
countries, in particular least developed
countries, small island developing States and
landlocked developing countries, in accordance
with their respective programmes of support
SDG 7
AFFORDABLE AND CLEAN ENERGY
Ensure access to affordable, reliable, sustainable
and modern energy for all
77
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 7.1: SDG 7 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Leparada AR 1 100
Lower Siang AR 1 100
Jiribam MN 1 100
Kakching MN 1 100
Kamjong MN 1 100
Kangpokpi MN 1 100
Noney MN 1 100
Pherzawl MN 1 100
Tengnoupal MN 1 100
Hnahthial MZ 1 100
Khawzawl MZ 1 100
Saitual MZ 1 100
Pakyong SK 1 100
Soreng SK 1 100
Aizawl MZ 15
95
West Kameng AR 16
94
Imphal West MN 16 94
Tawa n g AR 18 93
Kolasib MZ 18 93
Gangtok SK 18 93
Kamrup Metropolitan AS 21 91
Siaha MZ 21 91
Dimapur NL 21 91
Serchhip MZ 24 90
Papum Pare AR 25 89
Imphal East MN 25 89
Champhai MZ 25 89
Thoubal MN 28 86
Bishnupur MN 29 84
Gyalshing SK 30 83
Namchi SK 31 82
Mangan SK 32 81
West Tripura TR 32 81
Lunglei MZ 34 80
Churachandpur MN 35 79
Kohima NL 35 79
Kamrup AS 37 76
East Siang AR 38 74
Chandel MN 38 74
Tirap AR 40 73
Bongaigaon AS 40 73
Hojai AS 40 73
Nalbari AS 40 73
Senapati MN 40 73
Dibang Valley AR 45 72
Mamit MZ 45 72
West Siang AR 47 71
East Khasi Hills ML 47 71
Mokokchung NL 47 71
Gomati TR 47 71
Dibrugarh AS 51 70
Dima Hasao AS 51 70
Jorhat AS 51 70
Sivasagar AS 51 70
Sonitpur AS 51 70
West Garo Hills ML 51 70
Kurung Kumey AR 57 69
Chirang AS 57 69
Kokrajhar AS 57 69
Cachar AS 60 68
Tinsukia AS 60 68
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
NER District SDG Index: Goal 7
The score for Goal 7 ranges between 100 and 5 for the
121 districts included in the ranking and computation.
14 districts Leparada [AR], Lower Siang [AR], Jiribam
[MN], Kakching [MN], Kamjong [MN], Kangpokpi
[MN], Noney [MN], Tengnoupal [MN], Pherzawl [MN],
Hnahthial [MZ], Khawzawl [MZ], Saitual [MZ], Pakyong
[SK], Soreng [SK] have scored a 100 in this Goal and
fall in the category of Achievers. 58 districts fall in the
category of Front Runners and 41 in the category of
Performers, while 8 districts are in the category of
Aspirants with scores less than 50.
782023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 7.1: SDG 7 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Wokha NL 60 68
Khowai TR 60 68
North Tripura TR 60 68
Dhubri AS 65 67
Karimganj AS 65 67
Barpeta AS 67 66
Morigaon AS 67 66
Nagaon AS 67 66
Sepahijala TR 67 66
Baksa AS 71 65
Goalpara AS 71 65
Biswanath AS 73 64
Hailakandi AS 73 64
Udalguri AS 73 64
Dhalai TR 73 64
Upper Subansiri AR 77 63
Golaghat AS 77 63
Lakhimpur AS 77 63
South West Garo Hills ML 77 63
Karbi Anglong AS 81 62
Tamenglong MN 81 62
Peren NL 81 62
Namsai AR 84 61
South Salmara-Mankachar AS 84 61
South Tripura TR 84 61
Unakoti TR 84 61
Changlang AR 88 60
Charaideo AS 88 60
East Garo Hills ML 90 59
Phek NL 90 59
Longding AR 92 58
Upper Siang AR 92 58
Ukhrul MN 92 58
Darrang AS 95 57
East Jaintia Hills ML 95 57
North Garo Hills ML 95 57
East Kameng AR 98 56
Lower Dibang Valley AR 98 56
Dhemaji AS 98 56
Majuli AS 98 56
Tuensang NL 98 56
Zunheboto NL 103 55
West Karbi Anglong AS 104 54
Kiphire NL 104 54
Anjaw AR 106 53
Ri Bhoi ML 106 53
Lawngtlai MZ 106 53
Kra Daadi AR 109 52
Siang AR 109 52
West Jaintia Hills ML 109 52
Longleng NL 109 52
Mon NL 109 52
South Garo Hills ML 114 49
South West Khasi Hills ML 115 47
West Khasi Hills ML 115 47
Lower Subansiri AR 117 46
Pakke Kessang AR 118 41
Lohit AR 119 30
Shi Yomi AR 120 11
Kamle AR 121 5
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
79
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 7.2: PERFORMANCE OF DISTRICTS IN SDG 7
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
802023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
7.1 Percentage of villages/GPs electrified100
This target corresponds to global SDG target 7.1 that aims to ensure
universal access to affordable, reliable and modern energy services.
7.1
Percentage of households using clean
fuel for cooking
100
This target corresponds to global SDG target 7.1 that aims to ensure
universal access to affordable, reliable and modern energy services.
81
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
82Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 7.1: PERFORMANCE OF DISTRICTS ON SDG 7
SDG Target 7.1 7.1
District Percentage of villages/GPs electrified
Percentage of households
using clean fuel for cooking
SDG 7
Arunachal Pradesh
Anjaw 93.77 29.0 53
Bichom Null Null *
Changlang 96.69 34.1 60
Dibang Valley 100.00 49.3 72
East Kameng 87.32 49.5 56
East Siang 177.38 52.4 74
Kamle 62.34 Null 5
Keyi Panyor Null Null *
Kra Daadi 71.51 78.3 52
Kurung Kumey 94.18 57.3 69
Leparada 105.56 Null 100
Lohit 60.16 63.9 30
Longding 100.00 22.4 58
Lower Dibang Valley 83.44 57.4 56
Lower Siang 108.08 Null 100
Lower Subansiri 74.14 60.8 46
Namsai 127.68 28.7 61
Pakke Kessang 76.54 Null 41
Papum Pare 99.18 81.3 89
Shi Yomi 64.66 Null 11
Siang 93.62 27.6 52
Tawang 99.57 88.1 93
Tirap 166.67 50.4 73
Upper Siang 94.64 36.3 58
Upper Subansiri 112.40 32.8 63
West Kameng 106.92 88.9 94
West Siang 95.24 57.1 71
Assam
Bajali Null Null *
Baksa 100.00 35.2 65
Barpeta 99.66 38.7 66
Biswanath 99.47 35.0 64
Bongaigaon 100.00 49.8 73
Cachar 99.62 43.0 68
Charaideo 99.43 27.3 60
Chirang 99.80 44.5 69
Darrang 96.43 30.1 57
Dhemaji 98.86 21.6 56
Dhubri 99.54 40.7 67
Dibrugarh 99.85 44.7 70
Dima Hasao 98.99 48.2 70
Goalpara 99.64 36.3 65
Golaghat 99.91 33.1 63
Hailakandi 99.40 35.2 64
Hojai 99.29 52.0 73
Jorhat 98.43 48.3 70
Kamrup 99.72 57.4 76
Kamrup Metropolitan 99.07 85.1 91
Karbi Anglong 98.80 33.4 62
Karimganj 99.79 39.6 67
Kokrajhar 99.91 43.3 69
Lakhimpur 98.48 36.1 63
Majuli 100.00 19.3 56
Morigaon 99.84 37.6 66
Nagaon 99.41 38.6 66
Nalbari 100.00 51.1 73
Sivasagar 99.62 45.5 70
Sonitpur 99.38 45.8 70
South Salmara-Mankachar 99.77 28.5 61
Tamulpur Null Null *
Tinsukia 100.00 40.9 68
Udalguri 100.00 34.0 64
West Karbi Anglong 98.89 17.7 54
Manipur
Bishnupur 100.00 71.3 84
Chandel 100.00 52.0 74
Churachandpur 100.00 62.3 79
Imphal East 100.00 79.0 89
Imphal West 100.00 88.6 94
83Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 7.1: PERFORMANCE OF DISTRICTS ON SDG 7
SDG Target 7.1 7.1
District Percentage of villages/GPs electrified
Percentage of households
using clean fuel for cooking
SDG 7
Manipur
Jiribam 100.00 Null 100
Kakching 100.00 Null 100
Kamjong 100.00 Null 100
Kangpokpi 100.00 Null 100
Noney 100.00 Null 100
Pherzawl 100.00 Null 100
Senapati 100.00 50.0 73
Tamenglong 100.00 30.5 62
Tengnoupal 100.00 Null 100
Thoubal 100.00 74.7 86
Ukhrul 100.00 22.9 58
Meghalaya
East Garo Hills 98.05 29.1 59
East Jaintia Hills 97.93 26.5 57
East Khasi Hills 99.61 47.4 71
Eastern West Khasi Hills Null Null *
North Garo Hills 98.60 24.4 57
Ri Bhoi 97.29 21.0 53
South Garo Hills 93.60 22.3 49
South West Garo Hills 99.45 33.9 63
South West Khasi Hills 96.19 11.6 47
West Garo Hills 98.54 47.6 70
West Jaintia Hills 96.12 20.7 52
West Khasi Hills 97.44 8.6 47
Mizoram
Aizawl 98.39 95.4 95
Champhai 100.00 79.4 89
Hnahthial 100.00 Null 100
Khawzawl 100.00 Null 100
Kolasib 100.00 87.5 93
Lawngtlai 81.76 56.3 53
Lunglei 92.68 79.9 80
Mamit 89.66 73.3 72
Saitual 100.00 Null 100
Serchhip 100.00 81.8 90
Siaha 100.00 83.7 91
Nagaland
Chumoukedima Null Null *
Dimapur 100.00 84.2 91
Kiphire 100.00 16.4 54
Kohima 100.00 61.7 79
Longleng 100.00 11.8 52
Mokokchung 100.00 46.2 71
Mon 100.00 13.0 52
Noklak Null Null *
Niuland Null Null *
Peren 100.00 31.4 62
Phek 100.00 24.2 59
Shamator Null Null *
Tseminyu Null Null *
Tuensang 100.00 19.7 56
Wokha 100.00 41.2 68
Zunheboto 100.00 18.6 55
Sikkim
Gangtok 100.00 87.6 93
Gyalshing 100.00 69.8 83
Mangan 100.00 65.9 81
Namchi 100.00 66.5 82
Pakyong 100.00 Null 100
Soreng 100.00 Null 100
Tripura
Dhalai 100.00 34.0 64
Gomati 100.00 47.7 71
Khowai 100.00 41.5 68
North Tripura 100.00 41.6 68
Sepahijala 100.00 37.1 66
South Tripura 100.00 29.4 61
Unakoti 100.00 29.2 61
West Tripura 100.00 65.2 81
Target 100 100 100
Goal 8 promotes sustained economic growth, higher
levels of productivity and technological innovation.
Encouraging entrepreneurship and job creation
are crucial to this, as are effective measures to
eradicate forced labour, modern slavery and human
trafficking. It also seeks to protect labour rights and
promote policies which support decent job creation
and safe and secure working environments. With
these targets in mind, the goal is to achieve full and
productive employment, and decent work, for all
women and men by 2030.
Targets
8.1 Sustain per capita economic growth in
accordance with national circumstances and,
in particular, at least 7 percent gross domestic
product growth per annum in the least
developed countries
8.2 Achieve higher levels of economic productivity
through diversification, technological
upgrading and innovation, including through
a focus on high-value added and labour-
intensive sectors
8.3 Promote development-oriented policies that
support productive activities, decent job
creation, entrepreneurship, creativity and
innovation, and encourage the formalization
and growth of micro-, small- and medium-
sized enterprises, including through access to
financial services
8.4 Improve progressively, through 2030, global
resource efficiency in consumption and
production and endeavour to decouple
economic growth from environmental
degradation, in accordance with the 10‑ Year
Framework of Programmes on Sustainable
Consumption and Production, with developed
countries taking the lead
8.5 By 2030, achieve full and productive
employment and decent work for all women
and men, including for young people and
persons with disabilities, and equal pay for
work of equal value
8.6 By 2020, substantially reduce the proportion of
youth not in employment, education or training
8.7 Take immediate and effective measures
to eradicate forced labour, end modern
slavery and human trafficking and secure the
prohibition and elimination of the worst forms
of child labour, including recruitment and use
of child soldiers, and by 2025 end child labour
in all its forms
8.8 Protect labour rights and promote safe and
secure working environments for all workers,
including migrant workers, in particular women
migrants, and those in precarious employment
8.9 By 2030, devise and implement policies to
promote sustainable tourism that creates jobs
and promotes local culture and products
8.10 Strengthen the capacity of domestic financial
institutions to encourage and expand access to
banking, insurance and financial services for all
8.a Increase Aid for Trade support for developing
countries, in particular least developed
countries, including through the Enhanced
Integrated Framework for Trade related
Technical Assistance to Least Developed
Countries
8.b By 2020, develop and operationalize a global
strategy for youth employment and implement
the Global Jobs Pact of the International
Labour Organization
SDG 8
DECENT WORK AND
ECONOMIC GROWTH
Promote sustained, inclusive and sustainable economic growth,
full and productive employment and decent work for all
85
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
FIGURE 8.1: SDG 8 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Lower Siang AR 1 100
Lower Subansiri AR 2 99
Kamrup Metropolitan AS 2 99
Gangtok SK 4 98
Dimapur NL 5 97
Kohima NL 6 96
Papum Pare AR 7 95
Anjaw AR 8 92
East Siang AR 8 92
Imphal West MN 8 92
West Tripura TR 8 92
Sivasagar AS 12 91
West Kameng AR 13 90
Jorhat AS 13 90
Pakyong SK 13 90
Bongaigaon AS 16 89
Imphal East MN 16 89
Namchi SK 16 89
North Tripura TR 16 89
Lower Dibang Valley AR 20 88
Dibrugarh AS 20 88
Golaghat AS 20 88
Dima Hasao AS 23 87
Nalbari AS 23 87
Thoubal MN 23 87
Gomati TR 23 87
Lohit AR 27 86
Dhubri AS 27 86
Goalpara AS 27 86
Hailakandi AS 27 86
Lakhimpur AS 27 86
Tinsukia AS 27 86
Bishnupur MN 27 86
Dhalai TR 27 86
Sepahijala TR 27 86
South Tripura TR 27 86
Barpeta AS 37 85
Cachar AS 37 85
Chirang AS 37 85
Dhemaji AS 37 85
Karimganj AS 37 85
Kurung Kumey AR 42 84
Darrang AS 42 84
Karbi Anglong AS 42 84
Nagaon AS 42 84
Aizawl MZ 42 84
Mangan SK 42 84
Khowai TR 42 84
Majuli AS 49 83
Ukhrul MN 49 83
Lawngtlai MZ 49 83
Siaha MZ 49 83
Unakoti TR 49 83
Shi Yomi AR 54 82
Upper Siang AR 54 82
Charaideo AS 54 82
Kokrajhar AS 54 82
Sonitpur AS 54 82
East Khasi Hills ML 54 82
Kolasib MZ 54 82
East Kameng AR 61 81
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
NER District SDG Index: Goal 8
The score for Goal 8 ranges between 100 and 52 for the
121 districts included in the ranking and computation.
Lower Siang [AR] is the Achiever district. 111 districts
fall in the category of Front Runners and 9 in the
category of Performers, with no district in the category
of Aspirants with scores less than 50.
862023-24NER DISTRICT SDG INDEX
0 2010 4030 50 60 908070 100
FIGURE 8.1: SDG 8 INDEX SCORE OF DISTRICTS
District StateRank
West Siang AR 61 81
Champhai MZ 61 81
Lunglei MZ 61 81
Mamit MZ 61 81
Changlang AR 66 80
Leparada AR 66 80
Tawa n g AR 68 79
Kamle AR 69 78
Namsai AR 69 78
Tirap AR 69 78
Mokokchung NL 69 78
Morigaon AS 73 77
Kakching MN 73 77
Senapati MN 73 77
West Khasi Hills ML 73 77
Mon NL 73 77
Gyalshing SK 73 77
Siang AR 79 75
Upper Subansiri AR 79 75
Hojai AS 79 75
Udalguri AS 79 75
Chandel MN 79 75
Khawzawl MZ 79 75
Kiphire NL 79 75
Longleng NL 79 75
Peren NL 79 75
Longding AR 88 74
Jiribam MN 88 74
Wokha NL 88 74
Baksa AS 91 73
Kamrup AS 91 73
Tengnoupal MN 91 73
East Jaintia Hills ML 91 73
Biswanath AS 95 72
West Karbi Anglong AS 95 72
Ri Bhoi ML 95 72
Zunheboto NL 95 72
South Salmara-Mankachar AS 99 71
Tamenglong MN 99 71
South West Garo Hills ML 99 71
Phek NL 99 71
Churachandpur MN 103 70
Serchhip MZ 103 70
Tuensang NL 103 70
Dibang Valley AR 106 68
South Garo Hills ML 107 67
Saitual MZ 108 66
Soreng SK 108 66
Kangpokpi MN 110 65
Noney MN 110 65
West Garo Hills ML 110 65
Hnahthial MZ 113 63
Kra Daadi AR 114 62
Pakke Kessang AR 114 62
East Garo Hills ML 114 62
Kamjong MN 117 61
North Garo Hills ML 117 61
South West Khasi Hills ML 117 61
West Jaintia Hills ML 120 60
Pherzawl MN 121 52
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
87
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 8.2: PERFORMANCE OF DISTRICTS IN SDG 8
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
882023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
8.3
Percentage of loans disbursed to
MSMEs against sanctioned
100
This target corresponds to Global SDG target 8.3 that aims to
promote development oriented policies that support productive
activities, decent job creation, entrepreneurship, creativity and
innovation, and encourage the formalization and growth of micro,
small-and medium-sized enterprises, including through access to
financial services.
8.7
Number of victims of human
trafficking per 10,000 population
0
Global SDG target 8.7 aims to take immediate and effective
measures to eradicate forced labour, and end modern slavery and
human trafficking.
8.10
Percentage of households covered
with a bank account under Pradhan
Mantri Jan Dhan Yojana (PMJDY)
against target
100
The Pradhan Mantri Jan Dhan Yojana aims to provide at least one
basic savings banking account to every household.
8.10
Number of bank branches including
Business Correspondents (BCs) in
Urban, Semi-urban and Rural areas
per 10,000 population
8.58
Global SDG target 8.10 aims to strengthen the capacity of
domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all. Average of the 5
best scores has been set as the target.
8.10
Automated Teller Machines (ATMs)
per 10,000 population
5.65
Global SDG target 8.10 aims to strengthen the capacity of
domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all. Average of the 5
best scores has been set as the target.
8.10
Percentage of women account
holders in Pradhan Mantri Jan Dhan
Yojana (PMJDY)
50
This target corresponds to the global SDG target 5.a that aims
to undertake reforms to give women equal rights to economic
resource and access to financial services, and to the global SDG
target 8.10 that aims to expand access to banking, insurance and
financial services for all.
89
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
90Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 8.1: PERFORMANCE OF DISTRICTS ON SDG 8
SDG Target 8.3 8.7 8.10 8.10 8.10 8.10
District
Percentage of loans
disbursed to MSMEs
against sanctioned
Number of victims of
human trafficking per
10,000 population
Percentage of households
covered with a bank account
under PMJDY against target
Number of bank branches including Business
Correspondents (BCs) in Urban, Semi-urban
and Rural areas per 10,000 population
Automated Teller
Machines (ATMs) per
10,000 population
Percentage of
women account
holders in PMJDY
SDG 8
Arunachal Pradesh
Anjaw 100.00 0.00 100.00 5.20 Null 55.08 92
Bichom Null Null Null Null Null Null *
Changlang 100.00 0.00 100.00 5.94 0.94 54.80 80
Dibang Valley 100.00 0.00 100.00 3.75 Null 41.43 68
East Kameng 100.00 0.00 100.00 6.19 0.95 54.66 81
East Siang 100.00 0.00 100.00 18.10 3.06 52.32 92
Kamle 100.00 0.00 Null 1.35 Null 58.95 78
Keyi Panyor Null Null Null Null Null Null *
Kra Daadi 100.00 0.00 Null 0.43 0.64 62.20 62
Kurung Kumey 100.00 0.00 100.00 1.98 Null 58.67 84
Leparada 100.00 0.00 Null 7.44 0.99 53.87 80
Lohit 100.00 0.00 100.00 6.43 2.61 60.20 86
Longding 100.00 0.00 100.00 3.88 0.35 62.75 74
Lower Dibang Valley 100.00 0.00 100.00 14.61 1.66 53.80 88
Lower Siang 100.00 0.00 Null 21.60 Null 53.19 100
Lower Subansiri 100.00 0.00 100.00 11.10 5.19 54.79 99
Namsai 100.00 0.00 Null 6.46 0.94 52.05 78
Pakke Kessang 100.00 0.00 Null 1.65 0.83 48.25 62
Papum Pare 100.00 0.11 100.00 47.06 7.82 56.26 95
Shi Yomi 100.00 0.00 Null 8.26 0.75 53.55 82
Siang 100.00 0.00 Null 4.07 Null 46.21 75
Tawang 100.00 0.20 100.00 7.20 2.20 51.61 79
Tirap 100.00 0.00 100.00 5.06 0.72 57.37 78
Upper Siang 100.00 0.00 100.00 5.66 1.70 54.93 82
Upper Subansiri 100.00 0.00 100.00 3.13 1.18 55.32 75
West Kameng 100.00 0.00 100.00 7.14 3.44 53.87 90
West Siang 100.00 0.19 100.00 9.14 2.67 48.74 81
Assam
Bajali Null Null Null Null Null Null *
Baksa 100.00 0.08 100.00 4.73 0.47 61.56 73
Barpeta 100.00 0.02 100.00 13.21 1.03 56.16 85
Biswanath 100.00 0.21 Null 8.75 0.80 59.96 72
Bongaigaon 100.00 0.00 100.00 11.53 2.11 58.78 89
Cachar 100.00 0.00 99.62 14.27 1.45 56.28 85
Charaideo 100.00 0.00 Null 8.50 0.85 63.13 82
Chirang 100.00 0.00 100.00 8.13 0.87 61.51 85
Darrang 100.00 0.05 100.00 16.68 1.11 57.10 84
Dhemaji 100.00 0.04 100.00 17.50 1.33 57.53 85
Dhubri 100.00 0.01 100.00 17.79 1.09 57.39 86
Dibrugarh 100.00 0.07 100.00 12.18 2.47 61.18 88
Dima Hasao 100.00 0.00 100.00 7.89 1.63 55.12 87
Goalpara 100.00 0.01 100.00 16.25 1.06 58.76 86
Golaghat 100.00 0.01 100.00 11.44 1.86 59.21 88
Hailakandi 100.00 0.02 100.00 11.24 1.15 56.45 86
Hojai 100.00 0.05 Null 6.39 0.87 58.44 75
Jorhat 100.00 0.01 99.89 14.10 2.76 60.81 90
Kamrup 100.00 0.41 100.00 12.81 2.31 58.03 73
Kamrup Metropolitan 100.00 0.02
100.00 115.85 6.64 56.13 99
Karbi Anglong 100.00 0.03 100.00 8.41 0.91 59.54 84
Karimganj 100.00 0.00 100.00 8.02 1.06 55.50 85
Kokrajhar 100.00 0.09 100.00 11.95 1.01 57.66 82
Lakhimpur 100.00 0.05 100.00 12.18 1.54 57.74 86
Majuli 100.00 0.00 Null 13.21 1.02 61.40 83
Morigaon 100.00 0.10 99.43 13.42 0.74 58.00 77
Nagaon 100.00 0.08 100.00 27.65 1.40 57.08 84
Nalbari 100.00 0.01 100.00 13.66 1.46 59.24 87
Sivasagar 100.00 0.03 99.97 17.20 3.06 59.51 91
Sonitpur 100.00 0.13 100.00 16.33 1.58 60.27 82
South Salmara-Mankachar 100.00 0.20 Null 13.91 0.20 62.13 71
Tamulpur Null Null Null Null Null Null *
Tinsukia 100.00 0.02 100.00 11.40 1.36 61.71 86
Udalguri 100.00 0.25 100.00 11.06 0.71 59.11 75
West Karbi Anglong 100.00 0.00 Null 5.04 0.27 57.49 72
Manipur
Bishnupur 100.00 0.00 100.00 17.35 1.14 60.47 86
Chandel 100.00 0.00 100.00 3.95 0.36 54.98 75
Churachandpur 100.00 0.00 97.43 15.98 1.33 54.18 70
Imphal East 100.00 0.00 100.00 13.49 1.89 60.08 89
Imphal West 100.00 0.00 100.00 69.92 3.07 60.54 92
91Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 8.1: PERFORMANCE OF DISTRICTS ON SDG 8
SDG Target 8.3 8.7 8.10 8.10 8.10 8.10
District
Percentage of loans
disbursed to MSMEs
against sanctioned
Number of victims of
human trafficking per
10,000 population
Percentage of households
covered with a bank account
under PMJDY against target
Number of bank branches including Business
Correspondents (BCs) in Urban, Semi-urban
and Rural areas per 10,000 population
Automated Teller
Machines (ATMs) per
10,000 population
Percentage of
women account
holders in PMJDY
SDG 8
Jiribam 100.00 0.00 Null 6.16 0.23 56.91 74
Kakching 100.00 0.00 Null 6.65 0.69 57.11 77
Kamjong 100.00 0.00 Null 1.24 0.21 49.52 61
Kangpokpi 100.00 0.00 Null 2.01 0.41 53.75 65
Noney 100.00 0.00 Null 4.52 0.20 47.51 65
Pherzawl 0.00 0.00 Null 1.21 Null 55.56 52
Senapati 100.00 0.00 100.00 4.17 0.84 52.41 77
Tamenglong 100.00 0.00 100.00 4.46 0.11 47.79 71
Tengnoupal 100.00 0.00 Null 4.62 0.83 54.80 73
Thoubal 100.00 0.00 100.00 25.62 1.34 58.50 87
Ukhrul 100.00 0.00 100.00 11.79 0.29 49.61 83
Meghalaya
East Garo Hills 10.64 0.00 100.00 4.60 0.55 58.29 62
East Jaintia Hills 22.73 0.00 100.00 12.53 0.81 61.71 73
East Khasi Hills 33.45 0.00 100.00 11.03 3.40 58.38 82
Eastern West Khasi Hills Null Null Null Null Null Null *
North Garo Hills 13.21 0.06 100.00 5.40 0.29 56.45 61
Ri Bhoi 21.88 0.00 100.00 7.22 1.55 60.53 72
South Garo Hills 36.67 0.00 100.00 5.06 0.42 54.62 67
South West Garo Hills 38.78 0.06 100.00 8.67 0.28 53.10 71
South West Khasi Hills 10.00 0.00 100.00 3.93 0.91 64.47 61
West Garo Hills 16.42 0.17 100.00 13.25 1.14 57.27 65
West Jaintia Hills 16.04 0.00 Null 5.62 1.25 65.79 60
West Khasi Hills 50.00 0.00 100.00 9.09 0.65 54.79 77
Mizoram
Aizawl 100.00 0.00 99.80 5.23 3.18 51.54 84
Champhai 100.00 0.00 100.00 6.26 0.97 52.29 81
Hnahthial 100.00 0.00 Null 4.21 0.35 46.83 63
Khawzawl 100.00 0.00 Null 6.24 0.27 55.97 75
Kolasib 100.00 0.00 100.00 6.31 1.07 57.00 82
Lawngtlai 100.00 0.00 100.00 7.80 0.51 51.43 83
Lunglei 100.00 0.00 100.00 6.15 1.14 50.08 81
Mamit 100.00 0.00 100.00 6.72 0.69 56.36 81
Saitual 100.00 0.00 Null 2.37 0.40 55.37 66
Serchhip 100.00 0.31 100.00 7.34 0.76 54.46 70
Siaha 100.00 0.00 100.00 7.07 0.88 53.40 83
Nagaland
Chumoukedima Null Null Null Null Null Null *
Dimapur 100.00 0.00 99.60 15.47 6.75 54.13 97
Kiphire 100.00 0.00 100.00 4.19 0.27 55.43 75
Kohima 100.00 0.00 100.00 12.93 4.17 59.93 96
Longleng 100.00 0.00 100.00 4.36 0.20 53.93 75
Mokokchung 100.00 0.00 100.00 3.55 1.80 55.21 78
Mon 100.00 0.00 100.00 4.91 0.36 51.80 77
Noklak Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null *
Peren 100.00 0.00 100.00 3.78 0.53 56.32 75
Phek 100.00 0.00 100.00 2.26 0.37 57.74 71
Shamator Null Null Null Null Null Null *
Tseminyu Null
Null Null Null Null Null *
Tuensang 100.00 0.00 100.00 1.77 0.47 52.12 70
Wokha 100.00 0.00 100.00 3.61 0.54 62.92 74
Zunheboto 100.00 0.00 100.00 2.20 0.64 58.01 72
Sikkim
Gangtok 90.09 0.00 100.00 14.31 6.20 51.00 98
Gyalshing 73.51 0.00 100.00 4.88 2.09 58.56 77
Mangan 81.98 0.00 100.00 6.63 3.20 49.40 84
Namchi 91.24 0.00 100.00 7.76 3.00 53.76 89
Pakyong 85.19 0.00 Null 7.33 4.68 53.00 90
Soreng 73.99 0.00 Null 3.71 1.08 54.45 66
Tripura
Dhalai 97.75 0.00 100.00 8.83 1.22 55.32 86
Gomati 97.33 0.00 100.00 10.44 1.63 54.52 87
Khowai 95.06 0.00 100.00 8.49 0.70 55.43 84
North Tripura 98.72 0.02 100.00 13.63 2.23 54.17 89
Sepahijala 98.19 0.00 100.00 9.00 1.04 56.48 86
South Tripura 98.72 0.00 100.00 8.13 1.23 56.05 86
Unakoti 98.34 0.00 100.00 7.59 0.80 58.35 83
West Tripura 97.36 0.00 100.00 8.45 3.37 56.79 92
Target 100 0 100 8.58 5.65 50 100
This goal promotes investment in innovation; and
reliable and resilient infrastructure which are crucial
drivers of economic growth and development.
It further aims at promoting increased resource
use efficiency and greater adoption of clean and
environmentally sound technologies and industrial
processes. It recognizes the importance of promoting
sustainable industries and investing in scientific
research and innovation, which are all important
ways to facilitate sustainable development.
Targets
9.1 Develop quality, reliable, sustainable and
resilient infrastructure, including regional
and transborder infrastructure, to support
economic development and human well-
being, with a focus on affordable and equitable
access for all
9.2 Promote inclusive and sustainable
industrialization and, by 2030, significantly
raise industry’s share of employment and
gross domestic product, in line with national
circumstances, and double its share in least
developed countries
9.3 Increase the access of small-scale industrial and
other enterprises, in particular in developing
countries, to financial services, including
affordable credit, and their integration into
value chains and markets
9.4 By 2030, upgrade infrastructure and retrofit
industries to make them sustainable, with
increased resource-use efficiency and greater
adoption of clean and environmentally sound
technologies and industrial processes, with
all countries taking action in accordance with
their respective capabilities
9.5 Enhance scientific research, upgrade the
technological capabilities of industrial sectors
in all countries, in particular developing
countries, including, by 2030, encouraging
innovation and substantially increasing the
number of research and development workers
per 1 million people and public and private
research and development spending
9.a Facilitate sustainable and resilient infrastructure
development in developing countries through
enhanced financial, technological and technical
support to African countries, least developed
countries, landlocked developing countries
and small island developing States
9.b Support domestic technology development,
research and innovation in developing
countries, including by ensuring a conducive
policy environment for, inter alia, industrial
diversification and value addition to
commodities
9.c Significantly increase access to information
and communications technology and strive to
provide universal and affordable access to the
Internet in least developed countries by 2020
SDG 9
INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Build resilient infrastructure, promote inclusive and
sustainable industrialisation and foster innovation
93
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 9.1: SDG 9 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 9
0 2010 4030 50 60 908070 100
District StateRank
Hnahthial MZ 1 100
Champhai MZ 2 98
Sepahijala TR 2 98
West Tripura TR 2 98
Nagaon AS 5 97
Unakoti TR 5 97
Biswanath AS 7 96
Dibrugarh AS 7 96
Morigaon AS 7 96
Nalbari AS 7 96
Sonitpur AS 7 96
South West Garo Hills ML 7 96
West Garo Hills ML 7 96
Aizawl MZ 7 96
Cachar AS 15 95
Dhubri AS 15 95
Karimganj AS 15 95
Barpeta AS 18 94
Bongaigaon AS 18 94
Darrang AS 18 94
Hailakandi AS 18 94
Kamrup AS 18 94
Kamrup Metropolitan AS 18 94
Sivasagar AS 18 94
Khowai TR 18 94
North Tripura TR 18 94
South Tripura TR 18 94
Baksa AS 28 93
Dhemaji AS 28 93
Goalpara AS 28 93
Hojai AS 28 93
Lakhimpur AS 28 93
Tinsukia AS 28 93
Udalguri AS 28 93
West Jaintia Hills ML 28 93
Gomati TR 28 93
Charaideo AS 37 92
Chirang AS 37 92
Majuli AS 37 92
Dhalai TR 37 92
Jorhat AS 41 91
East Khasi Hills ML 41 91
North Garo Hills ML 41 91
Ri Bhoi ML 41 91
Golaghat AS 45 90
Kolasib MZ 45 90
South Salmara-Mankachar AS 47 89
East Garo Hills ML 47 89
East Jaintia Hills ML 49 88
South West Khasi Hills ML 50 87
Kokrajhar AS 51 86
Dimapur NL 51 86
Karbi Anglong AS 53 84
Imphal East MN 54 83
Kohima NL 54 83
South Garo Hills ML 56 82
Longleng NL 56 82
Papum Pare AR 58 81
Bishnupur MN 58 81
Imphal West MN 58 81
Tawa n g AR 61 80
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 9 ranges between 100 and 11 for the
121 districts included in the ranking and computation.
Hnahthial [MZ], Champhai [MZ], Sepahijala [TR] and
West Tripura [TR] are the top performing districts. 1
district falls in the category of Achiever, 92 districts fall
in the category of Front Runners and 11 in the category
of Performers, while 17 districts are in the category of
Aspirants with scores less than 50.
942023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 9.1: SDG 9 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
West Karbi Anglong AS 61 80
Kakching MN 63 79
West Khasi Hills ML 63 79
Dima Hasao AS 65 78
Changlang AR 66
Mokokchung NL 66
Pherzawl MN 68 74
Saitual MZ 68 74
Thoubal MN 70 73
Lunglei MZ 70 73
Phek NL 70 73
East Kameng AR 73 72
Namsai AR 73 72
Lawngtlai MZ 73 72
Serchhip MZ 73 72
Lohit AR 77 71
Chandel MN 77 71
Tengnoupal MN 77 71
Mangan SK 77 71
East Siang AR 81 70
Mamit MZ 81 70
Mon NL 81 70
Gangtok SK 81 70
Pakyong SK 81 70
Pakke Kessang AR 86 68
Namchi SK 86 68
Peren NL 88 67
Soreng SK 88 67
Kangpokpi MN 90 66
Ukhrul MN 90 66
Khawzawl MZ 90 66
Senapati MN 93 65
Kurung Kumey AR 94 64
Churachandpur MN 94 64
Siaha MZ 94 64
Wokha NL 94 64
Gyalshing SK 94 64
Jiribam MN 99 55
Kamjong MN 99 55
Lower Dibang Valley 101 53
Kiphire NL 101 53
Lower Subansiri AR 103 52
Tamenglong MN 104 51
West Kameng AR 105 49
Tuensang NL 105 49
West Siang AR 107 47
Upper Subansiri AR 108 46
Zunheboto NL 109 45
Dibang Valley AR 110 39
Noney MN 110 39
Kra Daadi AR 112 28
Lower Siang AR 113 27
Tirap AR 113 27
Anjaw AR 115 25
Kamle AR 116 22
Shi Yomi AR 116 22
Longding AR 118 21
Upper Siang AR 119 18
Leparada AR 120 15
Siang AR 121 11
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
77
77
95
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 9.2: PERFORMANCE OF DISTRICTS IN SDG 9
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
962023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
9.1
Percentage of targeted habitations
connected by all-weather roads under
Pradhan Mantri Gram Sadak Yojana
(PMGSY) and other schemes
100
Global SDG Target 9.1 aims to develop quality, reliable, sustainable
and resilient infrastructure to support economic development and
equitable access for all. It is aimed that all targeted unconnected
habitations under PMGSY and related state schemes are connected.
9.1
Surfaced road as a percentage of
total road length
100
Global SDG Target 9.1 aims to develop quality, reliable, sustainable
and resilient infrastructure to support economic development and
equitable access for all.
9.c
Percentage of GPs/villages with
internet connection (broadband or
cellular)
100
This target aligns with global SDG target 9.c which aims to
significantly increase access to information and communications
technology “Digital India Initiative” of the Government of India also
aims to boost universal coverage of internet connectivity.
9.c
Percentage of villages covered by a
mobile network
100
This target aligns with global SDG target 9.c which aims to
significantly increase access to information and communications
technology. One of the pillars of the “Digital India Initiative” is
universal access to mobile connectivity.
97
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
98Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 9.1: PERFORMANCE OF DISTRICTS ON SDG 9
SDG Target 9.1 9.1 9.c 9.c
District
Percentage of habitations with
access to all weather roads under
PMGSY and other State schemes
Surfaced road as a percentage of
total road length
Percentage of GPs/villages with
internet connection (broadband or
cellular)
Percentage of villages covered by a
mobile network.
SDG 9
Arunachal Pradesh
Anjaw 13.95 56.99 15.74 24.26 25
Bichom Null Null Null Null *
Changlang 89.39 66.99 66.57 88.40 77
Dibang Valley 47.62 53.34 26.76 36.62 39
East Kameng 98.00 26.20 69.57 109.06 72
East Siang 8.47 78.55 138.10 158.33 70
Kamle 64.18 28.53 1.30 3.03 22
Keyi Panyor Null Null Null Null *
Kra Daadi 90.00 26.99 0.28 0.56 28
Kurung Kumey 80.22 28.12 67.72 87.04 64
Leparada 29.63 36.19 1.39 1.39 15
Lohit 14.71 77.25 201.63 228.46 71
Longding 70.83 23.00 0.00 0.00 21
Lower Dibang Valley 40.00 40.15 67.52 75.16 53
Lower Siang 82.14 32.13 0.00 1.01 27
Lower Subansiri 33.54 30.10 54.31 115.09 52
Namsai 42.24 62.91 91.53 110.73 72
Pakke Kessang 50.00 31.35 345.68 466.67 68
Papum Pare 138.78 48.86 80.82 99.38 81
Shi Yomi 58.97 28.66 5.17 5.17 22
Siang 26.97 20.74 3.19 3.19 11
Tawang 65.52 58.57 134.47 194.04 80
Tirap 65.22 51.12 0.00 0.00 27
Upper Siang 50.75 32.16 0.00 0.00 18
Upper Subansiri 91.78 20.76 34.30 43.39 46
West Kameng 46.00 53.55 39.23 63.85 49
West Siang 44.09 43.34 44.90 63.27 47
Assam
Bajali Null Null Null Null *
Baksa 98.94 75.80 100.00 100.00 93
Barpeta 99.57 77.18 100.00 100.00 94
Biswanath 99.49 86.03 99.47 99.57 96
Bongaigaon 100.19 77.63 99.11 99.64 94
Cachar 98.70 87.09 97.15 98.10 95
Charaideo 100.26 71.49 100.00 100.00 92
Chirang 99.21 69.94 100.00 100.00 92
Darrang 99.69 77.61 99.82 100.00 94
Dhemaji 99.91 77.11 99.01 99.16 93
Dhubri 97.77 84.01 99.79 100.00 95
Dibrugarh 99.74 87.47 99.41 99.56 96
Dima Hasao 96.41 57.00 81.83 82.66 78
Goalpara 98.57 77.12 99.29 99.52 93
Golaghat 100.00 71.72 96.12 96.38 90
Hailakandi 97.75 82.17 97.89 99.40 94
Hojai 99.13 76.67 99.26 99.26 93
Jorhat 99.12 67.76 99.18 99.67 91
Kamrup 99.55 82.77 98.25 98.44 94
Kamrup Metropolitan 99.57 78.59 100.00 100.00 94
Karbi Anglong 97.85 55.93 93.12 94.64 84
Karimganj 98.44 81.85 99.89 100.00 95
Kokrajhar 100.00 50.93 99.34 99.44 86
Lakhimpur 98.83 77.17 99.91 100.00 93
Majuli 99.56 81.04 94.76 96.37 92
Morigaon 99.87 86.20 99.68 100.00 96
Nagaon 99.83 90.35 99.51 99.51 97
Nalbari 100.00 84.49 99.56 99.56 96
Sivasagar 98.95 83.31 98.03 98.03 94
Sonitpur 99.82 87.53 98.72 99.14 96
South Salmara-Mankachar 93.17 67.92 100.00 100.00 89
Tamulpur Null Null Null Null *
Tinsukia 99.59 75.68 98.81 98.89 93
Udalguri 100.16 76.64 99.63 99.63 93
West Karbi Anglong 95.22 48.95 89.93 90.66 80
Manipur
Bishnupur 100.00 73.68 54.17 100.00 81
Chandel 98.21
32.44 89.14 70.41 71
Churachandpur 86.42 39.86 58.68 76.04 64
Imphal East 100.00 99.48 35.46 96.45 83
Imphal West 100.00 91.14 34.58 100.00 81
99Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 9.1: PERFORMANCE OF DISTRICTS ON SDG 9
SDG Target 9.1 9.1 9.c 9.c
District
Percentage of habitations with
access to all weather roads under
PMGSY and other State schemes
Surfaced road as a percentage of
total road length
Percentage of GPs/villages with
internet connection (broadband or
cellular)
Percentage of villages covered by a
mobile network.
SDG 9
Jiribam 100.00 33.37 0.00 92.00 55
Kakching 100.00 65.37 59.26 96.30 79
Kamjong 82.05 34.69 45.53 66.67 55
Kangpokpi 98.36 36.50 50.47 85.74 66
Noney 86.96 19.15 20.55 36.99 39
Pherzawl 95.24 17.50 95.45 93.94 74
Senapati 95.92 59.34 12.50 96.32 65
Tamenglong 94.92 8.35 38.61 69.31 51
Tengnoupal 100.00 58.60 62.58 67.48 71
Thoubal 100.00 48.12 46.67 101.67 73
Ukhrul 100.00 32.68 47.78 87.78 66
Meghalaya
East Garo Hills 94.74 95.61 82.07 82.97 89
East Jaintia Hills 100.00 88.22 82.38 83.33 88
East Khasi Hills 97.01 92.72 87.48 88.83 91
Eastern West Khasi Hills Null Null Null Null *
North Garo Hills 93.10 88.10 92.30 92.46 91
Ri Bhoi 98.15 90.87 85.98 88.11 91
South Garo Hills 82.61 79.62 82.84 84.14 82
South West Garo Hills 95.83 93.73 97.19 97.94 96
South West Khasi Hills 93.10 86.64 83.92 86.55 87
West Garo Hills 98.13 93.96 96.49 96.58 96
West Jaintia Hills 91.67 91.04 93.94 94.85 93
West Khasi Hills 94.74 82.23 70.35 72.28 79
Mizoram
Aizawl 100.00 89.49 97.10 97.10 96
Champhai 100.00 96.56 98.39 98.39 98
Hnahthial 100.00 100.00 100.00 100.00 100
Khawzawl 7.69 73.49 94.74 94.74 66
Kolasib 100.00 65.00 100.00 100.00 90
Lawngtlai 31.11 76.68 92.35 92.35 72
Lunglei 29.41 93.48 87.61 87.61 73
Mamit 10.53 91.83 91.11 91.11 70
Saitual 15.38 92.46 96.30 96.30 74
Serchhip 5.56 91.10 98.92 98.92 72
Siaha 17.86 83.63 79.55 79.55 64
Nagaland
Chumoukedima Null Null Null Null *
Dimapur 100.00 51.16 98.59 100.00 86
Kiphire 44.23 38.61 59.05 77.14 53
Kohima 84.75 65.88 87.63 95.88 83
Longleng 92.73 47.66 93.48 100.00 82
Mokokchung 90.32 29.02 96.51 97.67 77
Mon 76.60 53.31 73.77 81.97 70
Noklak Null Null Null Null *
Niuland Null Null Null Null *
Peren 63.95 60.34 66.67 81.61 67
Phek 65.22 41.51 95.96 97.98 73
Shamator Null Null Null Null *
Tseminyu Null Null Null Null *
Tuensang 32.84 25.44 74.59 74.59 49
Wokha 69.63 32.18 75.19 85.71 64
Zunheboto 27.75 24.38 64.12 74.12 45
Sikkim
Gangtok 19.70 68.96 100.00 100.00 70
Gyalshing 15.58 48.81 100.00 100.00 64
Mangan 17.47 72.60 100.00 100.00 71
Namchi 13.40 67.11 100.00 100.00 68
Pakyong 13.77 72.95 100.00 100.00 70
Soreng 15.48 59.73 100.00 100.00 67
Tripura
Dhalai 97.46 93.55 86.09 91.39 92
Gomati 100.00 94.06 88.44 89.02 93
Khowai 100.00 89.11 87.10 99.19 94
North Tripura 96.83 90.66 93.02 97.67 94
Sepahijala 100.00 95.58 98.22 100.00 98
South Tripura 100.00 90.91 86.98 97.04 94
Unakoti 99.68 91.63 97.80 100.00 97
West Tripura 100.00 93.30 98.82 100.00 98
Target 100 100 100 100 100
The Goal calls for progressively reducing not only
income inequalities but also inequalities-of-outcome
by ensuring access to equal opportunities and
promoting social, economic and political inclusion of
all, irrespective of age, sex, disability, race, ethnicity,
origin, religion or economic or any other status
relevant within a society. It also aims at enhancing
representation and voice for developing countries
in decision making in international economic and
financial institutions.
Targets
10.1 By 2030, progressively achieve and sustain
income growth of the bottom 40 percent
of the population at a rate higher than the
national average
10.2 By 2030, empower and promote the social,
economic and political inclusion of all,
irrespective of age, sex, disability, race,
ethnicity, origin, religion or economic or
other status
10.3 Ensure equal opportunity and reduce
inequalities of outcome, including by
eliminating discriminatory laws, policies
and practices and promoting appropriate
legislation, policies and action in this regard
10.4 Adopt policies, especially fiscal, wage and
social protection policies, and progressively
achieve greater equality
10.5 Improve the regulation and monitoring of
global financial markets and institutions
and strengthen the implementation of such
regulations
10.6 Ensure enhanced representation and voice
for developing countries in decision-making
in global international economic and financial
institutions in order to deliver more effective,
credible, accountable and legitimate
institutions
10.7 Facilitate orderly, safe, regular and responsible
migration and mobility of people, including
through the implementation of planned and
well-managed migration policies
10.a Implement the principle of special and
differential treatment for developing countries,
in particular least developed countries, in
accordance with World Trade Organization
agreements
10.b Encourage official development assistance
and financial flows, including foreign direct
investment, to States where the need is
greatest, in particular least developed
countries, African countries, small island
developing States and landlocked developing
countries, in accordance with their national
plans and programmes
10.c By 2030, reduce to less than 3 percent the
transaction costs of migrant remittances and
eliminate remittance corridors with costs
higher than 5 percent
SDG 10
REDUCED INEQUALITIES
Reduce inequality within and among countries
101
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 10.1: SDG 10 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 10
0 2010 4030 50 60 908070 100
District StateRank
South West Khasi Hills ML 1 86
Pakke Kessang AR 2 84
Dibang Valley AR 3 82
East Kameng AR 3 82
Kra Daadi AR 5 81
East Jaintia Hills ML 5 81
Pakyong SK 7 79
Unakoti TR 7 79
Mon NL 9 78
Kurung Kumey AR 10 77
Jiribam MN 10 77
East Garo Hills ML 10 77
Peren NL 10 77
South West Garo Hills ML 14 76
North Tripura TR 14 76
Kamle AR 16 75
East Khasi Hills ML 16 75
Papum Pare AR 18 74
Upper Subansiri AR 18 74
West Jaintia Hills ML 18 74
Dhalai TR 18 74
Lower Dibang Valley AR 22 72
Gomati TR 22 72
Bishnupur MN 24 71
West Garo Hills ML 24 71
Sepahijala TR 24 71
Majuli AS 27 70
Nagaon AS 27 70
Mangan SK 29 69
Khowai TR 29 69
Biswanath AS 31 68
Nalbari AS 31 68
Jorhat AS 33 67
Karimganj AS 33 67
Mokokchung NL 33 67
West Tripura TR 33 67
Leparada AR 37 66
Tawa n g AR 37 66
Darrang AS 39 65
Hojai AS 39 65
Kakching MN 39 65
Ri Bhoi ML 39 65
South Tripura TR 39 65
Lohit AR 44 64
Upper Siang AR 44 64
Dibrugarh AS 44 64
Namsai AR 47 63
Hailakandi AS 47 63
West Khasi Hills ML 47 63
Champhai MZ 47 63
Anjaw AR 51 62
Morigaon AS 51 62
Sivasagar AS 51 62
North Garo Hills ML 51 62
Namchi SK 51 62
Bongaigaon AS 56 61
Dima Hasao AS 56 61
Lunglei MZ 56 61
Saitual MZ 56 61
Charaideo AS 60 60
Lakhimpur AS 60 60
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 10 ranges between 86 and 0 for the
121 districts included in the ranking and computation.
South West Khasi Hills [ML], Pakke Kessang [AR] and
Dibang Valley [AR] are the top performing districts.
43 districts fall in the category of Front Runners and 45 in the category of Performers, while 33 districts are
in the category of Aspirants with scores less than 50.
1022023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 10.1: SDG 10 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Sonitpur AS 60 60
Tinsukia AS 60 60
Cachar AS 64 59
Golaghat AS 64 59
Mamit MZ 66 58
Gyalshing SK 66 58
Goalpara AS 68 57
Kamrup AS 68 57
Imphal East MN 68 57
South Garo Hills ML 68 57
Dhubri AS 72 56
Imphal West MN 72 56
Aizawl MZ 72 56
Siaha MZ 72 56
Soreng SK 72 56
South Salmara-Mankachar AS 77 55
Lawngtlai MZ 77 55
Wokha NL 77 55
Barpeta AS 80 54
Hnahthial MZ 80 54
Khawzawl MZ 80 54
Kolasib MZ 80 54
Gangtok SK 80 54
Kamrup Metropolitan AS 85 53
Kohima NL 86 52
Baksa AS 87 51
West Kameng AR 88 50
Siang AR 89 49
Dhemaji AS 89 49
Thoubal MN 89 49
Chirang AS 92 46
Serchhip MZ 92 46
Dimapur NL 92 46
Karbi Anglong AS 95 45
Lower Subansiri AR 96 44
West Siang AR 96 44
Kokrajhar AS 96 44
Shi Yomi AR 99 43
Phek NL 99 43
Kamjong MN 101 42
Ukhrul MN 101 42
Senapati MN 103 40
Udalguri AS 104 39
West Karbi Anglong AS 104 39
Tengnoupal MN 106 38
Longleng NL 106 38
Chandel MN 108 37
Churachandpur MN 109 36
Changlang AR 110 35
Tamenglong MN 111 34
East Siang AR 112 33
Lower Siang AR 112 33
Longding AR 114 30
Noney MN 115 29
Kiphire NL 115 29
Tuensang NL 117 26
Tirap AR 118 25
Kangpokpi MN 119 16
Zunheboto NL 120 13
Pherzawl MN 121
0
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
103
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 10.2: PERFORMANCE OF DISTRICTS IN SDG 10
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1042023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
10.2
Percentage of women representatives
in PRIs, ULBs, District Autonomous
Councils, VCs, VECs
56.18
This target corresponds to the global SDG target 10.2 that aims to
empower and promote the social, economic and political inclusion
of all, irrespective of age, sex, disability, race, ethnicity, origin,
religion or economic or other status. Average of the 5 best scores
has been set as the target.
10.3
Women offered employment as a
percentage of total employment
demanded by women under
MGNREGA
100
This target corresponds to the global SDG target 10.3 that aims
to ensure equal opportunity and reduce inequalities of outcome,
including by eliminating discriminatory laws, policies and practices
and promoting appropriate legislation, policies and action in this
regard. Average of the 5 best scores has been set as the target.
10.3
Persons with Disability (PwDs) offered
employment as a percentage of total
employment demanded by PwDs
under MGNREGA
78.27
This target corresponds to the global SDG target 10.3 that aims
to ensure equal opportunity and reduce inequalities of outcome,
including by eliminating discriminatory laws, policies and practices
and promoting appropriate legislation, policies and action in this
regard. Average of the 5 best scores has been set as the target.
105
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
106Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 10.1: PERFORMANCE OF DISTRICTS ON SDG 10
SDG Target 10.2 10.3 10.3
District
Percentage of women representatives in PRIs, ULBs,
District Autonomous Councils, VCs, VECs
Women provided employment as a percentage
of total employment demanded by women under
MGNREGA
Persons with Disability (PWDs) provided
employment as a percentage of total employment
demanded by PWDs under MGNREGA
SDG 10
Arunachal Pradesh
Anjaw 44.87 70.16 33.33 62
Bichom Null Null Null *
Changlang 44.35 28.52 11.67 35
Dibang Valley 43.66 74.28 100.00 82
East Kameng 51.00 63.63 93.67 82
East Siang 41.52 39.02 0.00 33
Kamle 44.35 65.41 70.59 75
Keyi Panyor Null Null Null *
Kra Daadi 48.44 64.63 84.62 81
Kurung Kumey 52.08 49.78 78.26 77
Leparada 45.93 33.16 80.00 66
Lohit 59.01 42.66 50.00 64
Longding 36.40 40.61 0.00 30
Lower Dibang Valley 47.66 44.69 100.00 72
Lower Siang 42.00 30.69 8.33 33
Lower Subansiri 52.14 44.64 6.97 44
Namsai 47.04 30.95 70.66 63
Pakke Kessang 45.54 77.22 100.00 84
Papum Pare 44.10 54.38 77.78 74
Shi Yomi 51.52 28.16 20.00 43
Siang 50.00 32.89 33.33 49
Tawang 51.60 45.97 57.89 66
Tirap 37.07 25.96 0.00 25
Upper Siang 39.08 38.18 91.48 64
Upper Subansiri 50.91 45.84 99.61 74
West Kameng 51.83 42.63 23.81 50
West Siang 40.61 31.07 36.00 44
Assam
Bajali Null Null Null *
Baksa Null 75.61 25.61 51
Barpeta 51.20 55.21 21.47 54
Biswanath 51.46 73.15 34.84 68
Bongaigaon 53.54 63.54 25.28 61
Cachar 53.81 71.47 14.24 59
Charaideo 49.89 67.60 24.35 60
Chirang Null 67.45 26.03 46
Darrang 51.37 70.39 32.58 65
Dhemaji 52.10 45.75 17.36 49
Dhubri 45.46 65.94 24.04 56
Dibrugarh 55.40 65.37 29.67 64
Dima Hasao Null 36.69 100.00 61
Goalpara 57.69 60.72 16.39 57
Golaghat 54.07 62.62 22.04 59
Hailakandi 55.36 57.48 34.82 63
Hojai 55.64 73.34 21.97 65
Jorhat 54.32 69.39 33.46 67
Kamrup 53.27 66.23 13.79 57
Kamrup Metropolitan 57.36 64.51 3.45 53
Karbi Anglong Null 67.59 24.29 45
Karimganj 54.40 77.92 25.50 67
Kokrajhar Null 61.92 28.25 44
Lakhimpur 53.59 64.88 22.16 60
Majuli 53.69 55.73 54.72 70
Morigaon 57.12 68.71 20.39 62
Nagaon 55.28 75.90 33.25 70
Nalbari 50.06 78.49 33.14 68
Sivasagar 47.15 67.72 33.96 62
Sonitpur 56.63 64.56 18.58 60
South Salmara-Mankachar 25.65 82.72 31.56 55
Tamulpur Null Null Null *
Tinsukia 54.81 70.33 15.82 60
Udalguri Null 62.71 19.29 39
West Karbi Anglong Null 67.94 13.64 39
Manipur
Bishnupur 56.63 40.97 66.79 71
Chandel 0.00 33.49 73.39 37
Churachandpur 0.00 31.57 72.73 36
Imphal East 19.05 59.15 69.09 57
Imphal West 48.98 35.59 48.63 56
107Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 10.1: PERFORMANCE OF DISTRICTS ON SDG 10
SDG Target 10.2 10.3 10.3
District
Percentage of women representatives in PRIs, ULBs,
District Autonomous Councils, VCs, VECs
Women provided employment as a percentage
of total employment demanded by women under
MGNREGA
Persons with Disability (PWDs) provided
employment as a percentage of total employment
demanded by PWDs under MGNREGA
SDG 10
Jiribam 60.00 43.91 85.00 77
Kakching 53.33 45.87 53.70 65
Kamjong 0.00 39.88 87.30 42
Kangpokpi 0.00 30.15 27.47 16
Noney 0.00 50.07 38.46 29
Pherzawl 0.00 19.82 0.00 0
Senapati 0.00 37.11 77.78 40
Tamenglong 0.00 21.24 83.33 34
Tengnoupal 0.00 31.11 82.14 38
Thoubal 36.51 38.96 46.36 49
Ukhrul 0.00 40.61 87.50 42
Meghalaya
East Garo Hills 41.96 65.03 100.00 77
East Jaintia Hills 45.26 70.15 78.47 81
East Khasi Hills 49.72 67.14 59.74 75
Eastern West Khasi Hills Null Null Null *
North Garo Hills 46.63 50.22 51.85 62
Ri Bhoi 46.05 61.13 47.25 65
South Garo Hills 49.71 43.72 40.64 57
South West Garo Hills 46.20 55.35 88.48 76
South West Khasi Hills 52.28 72.05 88.82 86
West Garo Hills 49.81 44.53 72.37 71
West Jaintia Hills 47.80 64.69 63.49 74
West Khasi Hills 43.49 58.61 48.66 63
Mizoram
Aizawl 27.03 36.55 84.21 56
Champhai 26.60 52.60 96.15 63
Hnahthial 25.76 33.48 100.00 54
Khawzawl 26.92 42.91 66.67 54
Kolasib 25.54 45.40 66.67 54
Lawngtlai 18.09 46.68 100.00 55
Lunglei 27.55 48.07 100.00 61
Mamit 24.37 44.10 100.00 58
Saitual 24.47 52.17 100.00 61
Serchhip 25.83 40.33 51.43 46
Siaha 21.02 45.27 97.14 56
Nagaland
Chumoukedima Null Null Null *
Dimapur Null 45.11 46.86 46
Kiphire 23.02 53.50 4.30 29
Kohima Null 63.75 38.10 52
Longleng Null 39.00 40.00 38
Mokokchung 40.51 44.01 93.33 67
Mon Null 64.92 92.59 78
Noklak Null Null Null *
Niuland Null Null Null *
Peren Null 78.78 62.50 77
Phek Null 46.32 41.24 43
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang Null 49.12 11.81 26
Wokha Null 74.14 33.33 55
Zunheboto Null 34.30 6.90 13
Sikkim
Gangtok 46.10 58.72 23.91 54
Gyalshing 51.76 54.56 30.67 58
Mangan 48.12 47.43 68.18 69
Namchi 48.40 49.79 48.94 62
Pakyong 55.03 61.41 68.42 79
Soreng 51.50 47.40 31.82 56
Tripura
Dhalai 44.72 54.08 77.30 74
Gomati 44.67 59.75 66.74 72
Khowai 44.95 49.08 70.07 69
North Tripura 45.30 65.61 70.69 76
Sepahijala 45.12 59.38 64.49 71
South Tripura 44.99 54.24 56.99 65
Unakoti 45.41 69.01 74.23 79
West Tripura 45.57 52.75 61.66 67
Target 56.18 100 78.27 100
Goal 11 promotes inclusive and sustainable
urbanisation. Making cities sustainable means
creating career and business opportunities, safe
and affordable housing, and building resilient
societies and economies. It involves investment
in public transport, creating green public spaces,
and improving urban planning and management in
participatory and inclusive ways.
Targets
11.1 By 2030, ensure access for all to adequate,
safe and affordable housing and basic services
and upgrade slums
11.2 By 2030, provide access to safe, affordable,
accessible and sustainable transport systems
for all, improving road safety, notably by
expanding public transport, with special
attention to the needs of those in vulnerable
situations, women, children, persons with
disabilities and older persons
11.3 By 2030, enhance inclusive and sustainable
urbanisation and capacity for participatory,
integrated and sustainable human settlement
planning and management in all countries
11.4 Strengthen efforts to protect and safeguard
the world’s cultural and natural heritage
11.5 By 2030, significantly reduce the number of
deaths and the number of people affected and
substantially decrease the direct economic
losses relative to global gross domestic
product caused by disasters, including water-
related disasters, with a focus on protecting
the poor and people in vulnerable situations
11.6 By 2030, reduce the adverse per capita
environmental impact of cities, including by
paying special attention to air quality and
municipal and other waste management
11.7 By 2030, provide universal access to safe,
inclusive and accessible, green and public
spaces, in particular for women and children,
older persons and persons with disabilities
11.a Support positive economic, social and
environmental links between urban, peri-
urban and rural areas by strengthening
national and regional development planning
11.b By 2020, substantially increase the number
of cities and human settlements adopting
and implementing integrated policies and
plans towards inclusion, resource efficiency,
mitigation and adaptation to climate change,
resilience to disasters, and develop and
implement, in line with the Sendai Framework
for Disaster Risk Reduction 2015-2030, holistic
disaster risk management at all levels
11.c Support least developed countries, including
through financial and technical assistance, in
building sustainable and resilient buildings
utilising local materials.
SDG 11
SUSTAINABLE CITIES
AND COMMUNITIES
Make cities and human settlements inclusive,
safe, resilient and sustainable
109
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 11.1: SDG 11 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 11
0 2010 4030 50 60 908070 100
District StateRank
Gomati TR 1 100
North Tripura TR 1 100
Unakoti TR 1 100
Sepahijala TR 4 99
West Tripura TR 4 99
Khowai TR 6 98
Jiribam MN 7 97
Dhalai TR 7 97
South Tripura TR 9 95
Hailakandi AS 10 91
Imphal West MN 11 89
Morigaon AS 12 88
Zunheboto NL 12 88
Jorhat AS 14 87
Kakching MN 14 87
East Khasi Hills ML 14 87
Kohima NL 14 87
Namchi SK 14 87
Kokrajhar AS 19 86
Sivasagar AS 19 86
Imphal East MN 19 86
Wokha NL 19 86
Gangtok SK 19 86
Pakyong SK 19 86
East Siang AR 25 85
Mokokchung NL 25 85
Mon NL 25 85
Dhubri AS 28 84
Tinsukia AS 28 84
West Karbi Anglong AS 28 84
Thoubal MN 28 84
Kiphire NL 28 84
Phek NL 28 84
Barpeta AS 34 83
Dimapur NL 34 83
Cachar AS 36 82
Chirang AS 36 82
Hojai AS 36 82
Karimganj AS 36 82
Gyalshing SK 36 82
Darrang AS 41 81
Dibrugarh AS 41 81
Dima Hasao AS 41 81
Karbi Anglong AS 41 81
Nalbari AS 41 81
Sonitpur AS 41 81
Bishnupur MN 41 81
Longleng NL 41 81
Goalpara AS 49 80
Lakhimpur AS 49 80
Peren NL 49 80
Kamrup AS 52 79
Tuensang NL 52 79
Bongaigaon AS 54 77
Golaghat AS 54 77
Udalguri AS 54 77
Kamrup Metropolitan AS 57 76
Dhemaji AS 58 75
Nagaon AS 58 75
Biswanath AS 60 74
Aizawl MZ 61 73
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 11 ranges between 100 and 42 and
are computed for the 79 districts which have urban
local bodies. Gomati, North Tripura and Unakoti, all
of them in Tripura are the top performing districts.
These three districts fall in the category of Achiever,
66 districts fall in the category of Front Runners and 9
in the category of Performers, while 1 district is in the
category of Aspirant with scores less than 50.
1102023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 11.1: SDG 11 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Mamit MZ 62 72
Mangan SK 62 72
Hnahthial MZ 64 71
Papum Pare AR 65 70
Charaideo AS 66 68
Khawzawl MZ 66 68
Serchhip MZ 68 66
Champhai MZ 69 65
Lunglei MZ 70 64
Lawngtlai MZ 71 63
Kolasib MZ 72 62
Saitual MZ 72 62
Siaha MZ 74 61
West Jaintia Hills ML 75 60
West Garo Hills ML 76 58
East Garo Hills ML 77 57
South Garo Hills ML 78 53
North Garo Hills ML 79 42
Anjaw AR N /A
Bichom AR N /A
Changlang AR N /A
Dibang Valley AR N /A
East Kameng AR N /A
Kamle AR N /A
Keyi Panyor AR N /A
Kra Daadi AR N /A
Kurung Kumey AR N /A
Leparada AR N /A
Lohit AR N /A
Longding AR N /A
Lower Dibang Valley AR N /A
Lower Siang AR N /A
Lower Subansiri AR N /A
Namsai AR N /A
Pakke Kessang AR N /A
Shi Yomi AR N /A
Siang AR N /A
Tawa n g AR N /A
Tirap AR N /A
Upper Siang AR N /A
Upper Subansiri AR N /A
West Kameng AR N /A
West Siang AR N /A
Bajali AS N /A
Baksa AS N /A
Majuli AS N /A
South Salmara-Mankachar AS N /A
Tamulpur AS N /A
Chandel MN N /A
Churachandpur MN N /A
Kamjong MN N /A
Kangpokpi MN N /A
Noney MN N /A
Pherzawl MN N /A
Senapati MN N /A
Tamenglong MN N /A
Tengnoupal MN N /A
Ukhrul MN N /A
East Jaintia Hills ML N /A
Eastern West Khasi Hills ML N /A
Ri Bhoi ML N /A
South West Garo Hills ML N /A
South West Khasi Hills ML N /A
West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Soreng SK N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
111
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 11.2: PERFORMANCE OF DISTRICTS IN SDG 11
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A)
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
Note: Only districts with an Urban Local Body/Administration were considered for computing scores in SDG 11 for
the year 2023-24.
1122023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
11.1
Houses completed under Pradhan
Mantri Awas Yojana (PMAY) and/or
other schemes as a percentage of net
demand assessment (Urban)
100
This target corresponds to the global SDG target 11.1 that aims to
ensure universal access to adequate, safe and affordable housing
and basic services, and upgrade slums, by 2030.
11.2
Deaths due to road accidents per
1,00,000 population
5.8
This target corresponds to the global SDG target 11.2 that focuses
on improving road safety, and also the global SDG target 3.6 which
aims to halve the number of global deaths and injuries from road
traffic accidents. (Base year 2015)
11.6
Percentage of wards with waste
collection
100
Global SDG target 11.6 aims to reduce the adverse per capita en-
vironmental impact of cities, including by paying special attention
to air quality and municipal and other waste management.
11.1
Percentage of individual household
toilets constructed against target
(SBM(U))
100
Swachh Bharat Mission aims to provide universal sanitation
coverage in urban areas through construction of IHHL units and
community toilets. It aims for completion of construction of toilets
targeted and sanctioned.
11.6
Percentage of Municipal Solid Waste
(MSW) treated out of total MSW
generated
100
This target corresponds to the global SDG target 11.6 that aims
to reduce the adverse per capita environmental impact of cities
by 2030, by focusing on municipal and other waste management.
MSW processing is also critical to the success of the SBM (U).
113
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
114Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 11.1: PERFORMANCE OF DISTRICTS ON SDG 11
SDG Target 11.1 11.2 11.6 11.1 11.6
District
Houses completed under
Pradhan Mantri Awas Yojana
(PMAY) and/or other schemes
as a percentage of net
demand assessment (Urban)
Deaths due to road accidents
per 1,00,000 population
Percentage of wards with
waste collection
Percentage of individual
household toilets constructed
against target (SBM(U))
Percentage of Municipal Solid
Waste (MSW) treated out of
total MSW generated (TPD)
SDG 11
Arunachal Pradesh
Anjaw Null Null Null Null Null *
Bichom Null Null Null Null Null *
Changlang Null Null Null Null Null *
Dibang Valley Null Null Null Null Null *
East Kameng Null Null Null Null Null *
East Siang 100.00 20.88 100.00 163.11 50.00 85
Kamle Null Null Null Null Null *
Keyi Panyor Null Null Null Null Null *
Kra Daadi Null Null Null Null Null *
Kurung Kumey Null Null Null Null Null *
Leparada Null Null Null Null Null *
Lohit Null Null Null Null Null *
Longding Null Null Null Null Null *
Lower Dibang Valley Null Null Null Null Null *
Lower Siang Null Null Null Null Null *
Lower Subansiri Null Null Null Null Null *
Namsai Null Null Null Null Null *
Pakke Kessang Null Null Null Null Null *
Papum Pare 86.77 7.93 100.00 52.97 16.38 70
Shi Yomi Null Null Null Null Null *
Siang Null Null Null Null Null *
Tawang Null Null Null Null Null *
Tirap Null Null Null Null Null *
Upper Siang Null Null Null Null Null *
Upper Subansiri Null Null Null Null Null *
West Kameng Null Null Null Null Null *
West Siang Null Null Null Null Null *
Assam
Bajali Null Null Null Null Null *
Baksa Null Null Null Null Null *
Barpeta 74.95 7.79 100.00 100.00 43.40 83
Biswanath 43.82 11.92 100.00 100.00 35.00 74
Bongaigaon 55.82 11.91 100.00 100.00 37.02 77
Cachar 49.56 7.83 100.00 100.00 62.10 82
Charaideo 23.26 5.23 100.00 100.00 16.00 68
Chirang 68.71 10.58 100.00 100.00 49.12 82
Darrang 54.84 6.57 100.00 100.00 50.11 81
Dhemaji 54.16 15.74 100.00 100.00 36.76 75
Dhubri 71.95 6.67 98.25 100.00 53.45 84
Dibrugarh 38.57 8.14 100.00 100.00 69.00 81
Dima Hasao 42.99 7.94 100.00 100.00 63.95 81
Goalpara 60.87 11.51 100.00 100.00 46.25 80
Golaghat 38.06 11.44 100.00 100.00 56.29 77
Hailakandi 85.95 3.19 100.00 100.00 66.67 91
Hojai 59.62 7.52 100.00 100.00 54.44 82
Jorhat 54.56 5.84 100.00 100.00 80.17 87
Kamrup 66.35 13.05 100.00 100.00 38.83 79
Kamrup Metropolitan 87.69 20.18 100.00 100.00 13.91 76
Karbi Anglong 45.81 8.93 100.00 100.00 62.60 81
Karimganj 48.01 5.37 100.00 100.00 61.98 82
Kokrajhar 67.08 9.02 100.00 100.00 70.02 86
Lakhimpur 54.09 12.47 100.00 100.00 58.10 80
Majuli Null Null Null Null Null *
Morigaon 72.50 6.79 100.00 100.00 70.36 88
Nagaon 53.18 12.05
76.71 100.00 63.70 75
Nalbari 60.00 14.51 100.00 100.00 56.07 81
Sivasagar 66.51 9.39 100.00 100.00 71.40 86
Sonitpur 42.11 12.20 130.00 100.00 72.90 81
South Salmara-Mankachar Null Null Null Null Null *
Tamulpur Null Null Null Null Null *
Tinsukia 63.69 6.78 100.00 100.00 57.73 84
Udalguri 48.08 8.90 100.00 100.00 42.76 77
West Karbi Anglong 45.86 3.39 100.00 100.00 71.83 84
Manipur
Bishnupur 79.95 11.79 100.00 100.00 34.66 81
Chandel Null Null Null Null Null *
Churachandpur Null Null Null Null Null *
Imphal East 95.09 2.91 100.00 100.00 34.46 86
115Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 11.1: PERFORMANCE OF DISTRICTS ON SDG 11
SDG Target 11.1 11.2 11.6 11.1 11.6
District
Houses completed under
Pradhan Mantri Awas Yojana
(PMAY) and/or other schemes
as a percentage of net
demand assessment (Urban)
Deaths due to road accidents
per 1,00,000 population
Percentage of wards with
waste collection
Percentage of individual
household toilets constructed
against target (SBM(U))
Percentage of Municipal Solid
Waste (MSW) treated out of
total MSW generated (TPD)
SDG 11
Imphal West 91.28 3.09 100.00 100.00 56.09 89
Jiribam 89.77 9.12 100.00 100.00 100.00 97
Kakching 91.73 9.60 100.00 100.00 50.63 87
Kamjong Null Null Null Null Null *
Kangpokpi Null Null Null Null Null *
Noney Null Null Null Null Null *
Pherzawl Null Null Null Null Null *
Senapati Null Null Null Null Null *
Tamenglong Null Null Null Null Null *
Tengnoupal Null Null Null Null Null *
Thoubal 95.57 6.88 100.00 100.00 25.99 84
Ukhrul Null Null Null Null Null *
Meghalaya
East Garo Hills 85.71 3.43 100.00 7.77 0.00 57
East Jaintia Hills Null Null Null Null Null *
East Khasi Hills 64.97 7.39 100.00 100.00 74.47 87
Eastern West Khasi Hills Null Null Null Null Null *
North Garo Hills 85.78 6.97 30.77 8.68 25.00 42
Ri Bhoi Null Null Null Null Null *
South Garo Hills 45.57 1.41 100.00 24.19 0.00 53
South West Garo Hills Null Null Null Null Null *
South West Khasi Hills Null Null Null Null Null *
West Garo Hills 74.15 8.59 100.00 15.51 10.96 58
West Jaintia Hills 84.02 7.35 100.00 13.37 10.00 60
West Khasi Hills Null Null Null Null Null *
Mizoram
Aizawl 13.49 14.15 100.00 100.00 63.58 73
Champhai 25.37 12.51 100.00 100.00 8.98 65
Hnahthial 0.00 3.51 100.00 100.00 54.13 71
Khawzawl 21.81 8.14 100.00 100.00 22.62 68
Kolasib 17.60 17.87 100.00 100.00 9.10 62
Lawngtlai 6.55 11.03 100.00 100.00 15.70 63
Lunglei 18.43 9.87 100.00 100.00 5.54 64
Mamit 41.22 6.95 100.00 100.00 20.00 72
Saitual 23.81 27.67 100.00 100.00 18.60 62
Serchhip 20.10 6.12 100.00 100.00 12.14 66
Siaha 7.38 15.91 100.00 100.00 13.21 61
Nagaland
Chumoukedima Null Null Null Null Null *
Dimapur 79.44 16.64 100.00 100.00 54.43 83
Kiphire 97.69 0.00 79.31 100.00 54.34 84
Kohima 79.79 1.89 100.00 100.00 54.55 87
Longleng 77.24 0.00 80.00 100.00 54.29 81
Mokokchung 70.56 4.11 100.00 100.00 54.55 85
Mon 87.80 1.60 87.23 100.00 54.41 85
Noklak Null Null Null Null Null *
Niuland Null Null Null Null Null *
Peren 70.63 0.00 81.48 100.00 53.97 80
Phek 64.55 3.67 100.00 100.00 54.47 84
Shamator Null Null Null Null Null *
Tseminyu Null Null Null Null Null *
Tuensang 75.52 0.00 75.00 100.00 54.41 79
Wokha 74.20 1.80 100.00 100.00 54.39 86
Zunheboto 85.59 0.71 100.00 100.00 54.40 88
Sikkim
Gangtok 84.83 8.20 100.00 100.00 49.08 86
Gyalshing 56.96 1.40 100.00 100.00 54.55 82
Mangan
94.44 70.92 100.00 100.00 64.47 72
Namchi 79.86 9.53 100.00 100.00 62.86 87
Pakyong 97.56 26.51 100.00 100.00 65.85 86
Soreng Null Null Null Null Null *
Tripura
Dhalai 100.00 4.76 100.00 86.44 100.00 97
Gomati 100.00 6.29 100.00 134.59 100.00 100
Khowai 100.00 6.11 100.00 91.55 100.00 98
North Tripura 100.00 5.75 100.00 100.00 100.00 100
Sepahijala 100.00 6.25 100.00 95.64 100.00 99
South Tripura 100.00 6.94 100.00 78.56 100.00 95
Unakoti 100.00 5.06 100.00 122.69 100.00 100
West Tripura 100.00 8.39 100.00 123.17 100.00 99
Target 100 5.8 100 100 100 100
The Goal emphasises on “doing more with less” thus
promoting resource efficiency, green economies
and sustainable infrastructure. It also focusses on
reducing degradation and pollution and minimising
waste. The efficient management of our shared
natural resources and the way we dispose of toxic
waste and pollutants are important targets to
achieve this Goal. It calls for awareness generation
and dissemination on sustainable development,
lifestyles and practices.
Targets
12.1 Implement the 10‑ Year Framework of
Programmes on Sustainable Consumption
and Production Patterns, all countries taking
action, with developed countries taking the
lead, taking into account the development and
capabilities of developing countries
12.2 By 2030, achieve the sustainable management
and efficient use of natural resources
12.3 By 2030, halve per capita global food waste at
the retail and consumer levels and reduce food
losses along production and supply chains,
including post-harvest losses
12.4 By 2020, achieve the environmentally sound
management of chemicals and all wastes
throughout their life cycle, in accordance
with agreed international frameworks, and
significantly reduce their release to air, water
and soil in order to minimize their adverse
impacts on human health and the environment
12.5 By 2030, substantially reduce waste generation
through prevention, reduction, recycling
and reuse
12.6 Encourage companies, especially large and
transnational companies, to adopt sustainable
practices and to integrate sustainability
information into their reporting cycle
12.7 Promote public procurement practices that
are sustainable, in accordance with national
policies and priorities
12.8 By 2030, ensure that people everywhere
have the relevant information and awareness
for sustainable development and lifestyles in
harmony with nature
12.a Support developing countries to strengthen
their scientific and technological capacity to
move towards more sustainable patterns of
consumption and production
12.b Develop and implement tools to monitor
sustainable development impacts for
sustainable tourism that creates jobs and
promotes local culture and products
12.c Rationalize inefficient fossil-fuel subsidies
that encourage wasteful consumption by
removing market distortions, in accordance
with national circumstances, including by
restructuring taxation and phasing out those
harmful subsidies, where they exist, to reflect
their environmental impacts, taking fully into
account the specific needs and conditions
of developing countries and minimizing the
possible adverse impacts on their development
in a manner that protects the poor and the
affected communities
SDG 12
RESPONSIBLE CONSUMPTION
AND PRODUCTION
Ensure sustainable consumption and
production patterns
117
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 12.1: SDG 12 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 12
0 2010 4030 50 60 908070 100
District StateRank
South Tripura TR 1 98
Unakoti TR 1 98
Shi Yomi AR 3 96
Gomati TR 3 96
Kohima NL 5 94
South West Garo Hills ML 6 92
Phek NL 6 92
West Khasi Hills ML 8 90
Serchhip MZ 8 90
Sepahijala TR 10 88
Dimapur NL 11 87
Khowai TR 11 87
West Tripura TR 11 87
North Tripura TR 14 86
Champhai MZ 15 85
Mokokchung NL 15 85
Dhalai TR 15 85
Kolasib MZ 18 84
West Jaintia Hills ML 19 79
Zunheboto NL 19 79
West Garo Hills ML 21 78
Saitual MZ 21 78
Peren NL 23 77
Hnahthial MZ 24 76
Mangan SK 24 76
Ri Bhoi ML 26 75
Pakyong SK 26 75
South Garo Hills ML 28 74
Aizawl MZ 28 74
Namchi SK 28 74
Soreng SK 28 74
North Garo Hills ML 32 73
Khawzawl MZ 32 73
West Siang AR 34 72
Wokha NL 34 72
Lower Dibang Valley AR 36 70
East Khasi Hills ML 36 70
Tuensang NL 36 70
Gangtok SK 36 70
Gyalshing SK 36 70
East Siang AR 41 69
Kurung Kumey AR 41 69
Changlang AR 43 68
Kamle AR 43 68
Kra Daadi AR 43 68
Hailakandi AS 43 68
Karbi Anglong AS 47 67
West Karbi Anglong AS 48 66
Longleng NL 48 66
Lohit AR 50 65
Goalpara AS 50 65
Kiphire NL 52 63
Dima Hasao AS 53 62
Bishnupur MN 53 62
Kakching MN 53 62
Lawngtlai MZ 53 62
Darrang AS 57 61
Nagaon AS 57 61
Imphal East MN 57 61
Jiribam MN 57 61
Thoubal MN 57 61
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 12 ranges between 98 and 7 for the
121 districts included in the ranking and computation.
South Tripura [TR], Unakoti [TR] and Shi Yomi [AR]
are the top performing districts. 51 districts fall in the
category of Front Runners and 52 in the category of
Performers, while 18 districts are in the category of
Aspirants with scores less than 50.
1182023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 12.1: SDG 12 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Mon NL 57 61
Lower Siang AR 63 60
Bongaigaon AS 63 60
Ukhrul MN 63 60
Siaha MZ 63 60
Namsai AR 67 59
Siang AR 67 59
Barpeta AS 67 59
East Garo Hills ML 67 59
Tirap AR 71 58
Imphal West MN 71 58
Biswanath AS 73 57
Dhubri AS 73 57
Tawa n g AR 75 56
Kokrajhar AS 75 56
Morigaon AS 75 56
Sonitpur AS 75 56
Udalguri AS 75 56
Lunglei MZ 75 56
Longding AR 81 55
Upper Siang AR 82 54
Dhemaji AS 82 54
Golaghat AS 82 54
Hojai AS 82 54
Anjaw AR 86 53
Kamrup AS 86 53
Lower Subansiri AR 88 52
Charaideo AS 88 52
Chirang AS 88 52
Jorhat AS 88 52
Lakhimpur AS 88 52
Nalbari AS 88 52
Tinsukia AS 88 52
Mamit MZ 88 52
East Kameng AR 96 51
Leparada AR 96 51
Cachar AS 96 51
Dibrugarh AS 96 51
Kamrup Metropolitan AS 96 51
Sivasagar AS 96 51
Karimganj AS 102 50
Senapati MN 102 50
Upper Subansiri AR 104 49
West Kameng AR 105 47
Pakke Kessang AR 106 46
Papum Pare AR 106 46
Pherzawl MN 106 46
Dibang Valley AR 109 44
Kangpokpi MN 109 44
East Jaintia Hills ML 111 42
South West Khasi Hills ML 111 42
Tengnoupal MN 113 41
Chandel MN 114 40
Churachandpur MN 114 40
Noney MN 116 36
Kamjong MN 117 34
Tamenglong MN 118 29
Majuli AS 119 27
South Salmara-Mankachar AS 120 8
Baksa AS 121 7
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
119
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 12.2: PERFORMANCE OF DISTRICTS IN SDG 12
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1202023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
12.3
Area under jhum cultivation as
a percentage of total area under
agriculture
0
Global SDG target 12.2 aims to achieve the sustainable manage-
ment and efficient use of natural resources by 2030. Average
of the 5 best scores, rounded to the nearest whole number, has
been set as the target.
12.3
Percentage of area under micro/
minor irrigation in the district
62.32
Global SDG target 12.2 aims to achieve the sustainable manage-
ment and efficient use of natural resources by 2030. Average of
the 5 best scores, after removing the outliers, has been set as
the target.
12.5
Plastic waste generated per 10,000
population (Tonnes/Annum)
0.04
This target corresponds to the global SDG target 12.5 that aims
to substantially reduce waste generation through prevention,
reduction, recycling and reuse. Average of the 5 best scores has
been set as the target.
121
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
122Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 12.1: PERFORMANCE OF DISTRICTS ON SDG 12
SDG Target 12.3 12.3 12.5
District
Area under jhum cultivation as a
percentage of total area under agriculture
Percentage of area under micro/minor
irrigation in the district
Plastic waste generated
per 10,000 population (Tonnes/Annum)
SDG 12
Arunachal Pradesh
Anjaw 37.71 19.37 168.99 53
Bichom Null Null Null *
Changlang 22.98 30.29 110.56 68
Dibang Valley 39.17 3.90 164.17 44
East Kameng 49.84 19.10 121.73 51
East Siang 6.46 30.01 192.05 69
Kamle 23.67 24.87 44.45 68
Keyi Panyor Null Null Null *
Kra Daadi 15.02 26.86 117.23 68
Kurung Kumey 13.42 25.86 101.36 69
Leparada 32.31 34.15 362.25 51
Lohit 7.35 14.33 102.66 65
Longding 36.75 10.65 67.67 55
Lower Dibang Valley 14.38 26.38 97.86 70
Lower Siang 22.48 27.77 Null 60
Lower Subansiri 24.26 22.72 293.02 52
Namsai 29.72 15.95 87.87 59
Pakke Kessang 35.64 20.04 Null 46
Papum Pare 18.32 36.27 559.57 46
Shi Yomi 7.65 63.07 Null 96
Siang 31.09 29.03 186.39 59
Tawang 8.89 8.78 207.33 56
Tirap 26.09 18.66 145.10 58
Upper Siang 28.05 23.90 253.19 54
Upper Subansiri 28.78 22.79 320.39 49
West Kameng 34.00 3.97 145.16 47
West Siang 26.17 49.45 182.08 72
Assam
Bajali Null Null Null *
Baksa Null 4.30 Null 7
Barpeta Null 11.59 0.61 59
Biswanath Null 8.71 1.35 57
Bongaigaon Null 11.92 0.35 60
Cachar Null 0.81 1.35 51
Charaideo Null 2.91 0.78 52
Chirang Null 2.79 1.31 52
Darrang Null 13.67 0.90 61
Dhemaji Null 4.44 0.37 54
Dhubri Null 9.25 0.53 57
Dibrugarh Null 1.92 1.07 51
Dima Hasao 12.55 0.00 0.64 62
Goalpara Null 19.25 0.90 65
Golaghat Null 5.34 0.32 54
Hailakandi 0.31 2.31 0.16 68
Hojai Null 5.38 0.14 54
Jorhat Null 2.60 1.00 52
Kamrup Null 4.22 0.34 53
Kamrup Metropolitan Null 1.13 1.58 51
Karbi Anglong 2.66 2.17 0.21 67
Karimganj Null 0.64 0.22 50
Kokrajhar Null 7.94 0.97 56
Lakhimpur Null 3.01 0.18 52
Majuli Null 16.72 Null 27
Morigaon Null 8.04 0.65 56
Nagaon Null 14.08 0.20 61
Nalbari Null 3.17 1.47 52
Sivasagar Null 1.47 0.09 51
Sonitpur Null 7.60 0.48 56
South Salmara-Mankachar Null 4.70 Null 8
Tamulpur Null Null Null *
Tinsukia Null 2.36 0.26 52
Udalguri Null 7.65 1.62 56
West Karbi Anglong 6.19 2.82 0.15 66
Manipur
Bishnupur 0.00 5.05 124.43 62
Chandel 59.99 3.81 102.53 40
Churachandpur 61.68 5.01 101.19 40
Imphal East 0.00 7.28 163.31 61
Imphal West 0.00 4.33 192.15 58
123Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 12.1: PERFORMANCE OF DISTRICTS ON SDG 12
SDG Target 12.3 12.3 12.5
District
Area under jhum cultivation as a
percentage of total area under agriculture
Percentage of area under micro/minor
irrigation in the district
Plastic waste generated
per 10,000 population (Tonnes/Annum)
SDG 12
Jiribam 0.00 1.93 111.55 61
Kakching 0.00 3.41 114.99 62
Kamjong 80.07 4.83 95.32 34
Kangpokpi 52.59 6.69 100.75 44
Noney 75.75 3.22 72.72 36
Pherzawl 40.90 1.11 98.50 46
Senapati 45.60 11.93 100.77 50
Tamenglong 88.77 4.68 116.74 29
Tengnoupal 58.77 3.80 98.36 41
Thoubal 0.00 3.00 128.40 61
Ukhrul 21.37 14.63 102.77 60
Meghalaya
East Garo Hills 32.77 11.75 21.34 59
East Jaintia Hills 22.48 5.59 Null 42
East Khasi Hills 1.53 9.94 26.68 70
Eastern West Khasi Hills Null Null Null *
North Garo Hills 12.34 21.03 0.00 73
Ri Bhoi 10.67 22.57 0.00 75
South Garo Hills 16.31 25.04 0.00 74
South West Garo Hills 1.33 52.86 Null 92
South West Khasi Hills 18.89 3.37 Null 42
West Garo Hills 6.93 27.95 19.75 78
West Jaintia Hills 0.52 23.77 1.52 79
West Khasi Hills 26.04 82.37 0.00 90
Mizoram
Aizawl 41.17 43.68 8.46 74
Champhai 39.26 62.87 4.99 85
Hnahthial 57.88 59.14 2.52 76
Khawzawl 38.99 40.51 4.26 73
Kolasib 18.91 45.57 5.58 84
Lawngtlai 29.79 11.84 1.77 62
Lunglei 50.53 16.83 4.67 56
Mamit 53.42 9.44 2.29 52
Saitual 58.14 72.90 3.88 78
Serchhip 25.18 73.94 4.90 90
Siaha 39.90 15.62 4.44 60
Nagaland
Chumoukedima Null Null Null *
Dimapur 2.74 65.18 199.30 87
Kiphire 42.03 21.95 1.01 63
Kohima 14.69 68.06 0.02 94
Longleng 41.74 27.54 0.01 66
Mokokchung 39.83 65.93 0.26 85
Mon 42.78 19.23 0.20 61
Noklak Null Null Null *
Niuland Null Null Null *
Peren 15.12 44.00 Null 77
Phek 14.66 58.71 1.94 92
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang 34.26 30.49 0.05 70
Wokha 34.54 34.97 0.19 72
Zunheboto 43.48 53.97 0.04 79
Sikkim
Gangtok 0.00 7.05 1.77 70
Gyalshing 0.00 6.45 0.20 70
Mangan 0.00 18.01 1.14 76
Namchi 0.00 13.35 0.77 74
Pakyong 0.00 16.55 4.37 75
Soreng 0.00 12.87 0.00 74
Tripura
Dhalai 13.87 44.52 0.30 85
Gomati 3.85 58.14 0.18 96
Khowai 4.05 41.64 0.26 87
North Tripura 10.06 42.57 0.26 86
Sepahijala 0.61 40.82 0.23 88
South Tripura 1.80 59.67 0.44 98
Unakoti 5.63 63.68 0.45 98
West Tripura 2.00 39.06 1.17 87
Target 0 62.32 0.04 100
2023-24
The Goal is aimed at integrating climate change
measures, disaster risk measures and sustainable
natural resource management into national
development strategies. To minimise the human
impact of geophysical disasters, the Goal calls for
strengthening resilience and adaptive capacity,
including human and institutional capacity on
mitigation, adaptation, and early warning. Efforts at
the national level - for adopting green technologies,
promoting the use of clean and modern source
of energy, advocating for behavioural change
for sustainable use of resources, have to be
complemented by international cooperation on
climate change since the causes and effects of
climate change transcend national boundaries.
Targets
13.1 Strengthen resilience and adaptive capacity to
climate-related hazards and natural disasters
in all countries
13.2 Integrate climate change measures into
national policies, strategies and planning
13.3 Improve education, awareness-raising and
human and institutional capacity on climate
change mitigation, adaptation, impact
reduction and early warning
13.a Implement the commitment undertaken by
developed-country parties to the United
Nations Framework Convention on Climate
Change to a goal of mobilising jointly USD
100 billion annually by 2020 from all sources
to address the needs of developing countries
in the context of meaningful mitigation actions
and transparency on implementation and fully
operationalise the Green Climate Fund through
its capitalisation as soon as possible
13.b Promote mechanisms for raising capacity for
effective climate change-related planning and
management in least developed countries
and small island developing States, including
focusing on women, youth and local and
marginalised communities
SDG 13
CLIMATE ACTION
Take urgent action to combat climate
change and its impacts
125
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 13.1: SDG 13 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 13
0 2010 4030 50 60 908070 100
District StateRank
Hnahthial MZ 1 100
Khawzawl MZ 1 100
Mokokchung NL 1 100
Phek NL 1 100
Senapati MN 5 99
Ukhrul MN 6 91
Tengnoupal MN 7 89
South West Khasi Hills ML 8 86
West Garo Hills ML 9 80
Longleng NL 10 79
Majuli AS 11 77
Soreng SK 11 77
East Khasi Hills ML 13 76
Gomati TR 14 75
Charaideo AS 15 74
Ri Bhoi ML 15 74
Baksa AS 17 73
Hojai AS 17 73
Lawngtlai MZ 17 73
Darrang AS 20 72
Jorhat AS 20 72
Morigaon AS 20 72
West Khasi Hills ML 20 72
Dhubri AS 24 71
Goalpara AS 24 71
Sivasagar AS 24 71
South TR TR 24 71
Dibrugarh AS 28 70
Kamrup AS 28 70
Lakhimpur AS 28 70
Nalbari AS 28 70
Champhai MZ 28 70
Serchhip MZ 28 70
Siaha MZ 28 70
Dhemaji AS 35 69
Golaghat AS 35 69
Tinsukia AS 35 69
Upper Subansiri AR 38 68
Karbi Anglong AS 38 68
Changlang AR 40 67
Lower Dibang Valley AR 40 67
Namsai AR 40 67
Shi Yomi AR 40 67
Bishnupur MN 40 67
Chandel MN 40 67
Churachandpur MN 40 67
Imphal East MN 40 67
Imphal West MN 40 67
Jiribam MN 40 67
Kakching MN 40 67
Kangpokpi MN 40 67
Peren NL 40 67
Namchi SK 40 67
Biswanath AS 54 66
Sonitpur AS 54 66
Thoubal MN 54 66
West Jaintia Hills ML 54 66
Dimapur NL 54 66
Kohima NL 54 66
Mon NL 54 66
Wokha NL 54 66
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 13 ranges between 100 and 12 for the
121 districts included in the ranking and computation.
Phek [NL], Mokokchung [NL], Khawzawl [MZ] and
Hnahthial [MZ] are the top performing districts.
4 districts fall in the category of Achiever, 59 districts fall
in the category of Front Runners and 9 in the category
of Performers, while 49 districts are in the category of
Aspirants with scores less than 50.
1262023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 13.1: SDG 13 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Zunheboto NL 54 66
Tuensang NL 63 65
Tamenglong MN 64 64
Kiphire NL 65 63
Gangtok SK 66 61
Kamjong MN 67 60
Noney MN 68 58
Mangan SK 68 58
Upper Siang AR 70 55
Pherzawl MN 71 54
Saitual MZ 72 50
South Garo Hills ML 73 49
South West Garo Hills ML 74 47
North Garo Hills ML 75 46
East Jaintia Hills ML 76 45
Kolasib MZ 77 44
West TR TR 78 43
Khowai TR 79 42
Hailakandi AS 80 41
East Garo Hills ML 80 41
Bongaigaon AS 82 40
Lower Subansiri AR 83 39
Kamrup Metropolitan AS 83 39
Leparada AR 85 38
Tirap AR 85 38
Barpeta AS 85 38
Chirang AS 85 38
Nagaon AS 85 38
Udalguri AS 85 38
Sepahijala TR 85 38
Lower Siang AR 92 37
Kokrajhar AS 92 37
Aizawl MZ 92 37
Mamit MZ 92 37
Dhalai TR 92 37
East Kameng AR 97 36
West Siang AR 97 36
West Karbi Anglong AS 97 36
Lunglei MZ 97 36
North TR TR 97 36
Unakoti TR 97 36
Kamle AR 103 35
Kra Daadi AR 103 35
Longding AR 103 35
Cachar AS 103 35
Dima Hasao AS 103 35
East Siang AR 108 34
Kurung Kumey AR 108 34
Lohit AR 108 34
Pakke Kessang AR 108 34
Papum Pare AR 108 34
Siang AR 108 34
West Kameng AR 108 34
Anjaw AR 115 33
Dibang Valley AR 115 33
Tawa n g AR 115 33
Karimganj AS 115 33
South Salmara-Mankachar AS 115 33
Gyalshing SK 120 30
Pakyong SK 121 12
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
127
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 13.2: PERFORMANCE OF DISTRICTS IN SDG 13
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1282023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
13.1
Number of human lives lost due
to natural calamity per 10,000
population
0
This target corresponds to the global SDG target 13.1 which aims
to strengthen resilience and adaptive capacity to climate-related
hazards and natural disasters. The target has been set to 0 to
imply that all States/UTs must be adequately prepared to ensure
that no human life is lost due to natural calamities.
13.2 Change in forest area
This target corresponds to the global SDG targets 13.2 that aim
to integrate climate change measures into national policies,
strategies and planning and 15.2 that aim to promote the
implementation of sustainable management of all types of forests,
halt deforestation, restore degraded forests and substantially
increase afforestation and reforestation. Districts with an
increase/no change in area under forests have been awarded a
score of 100 while districts with a decrease in area under forests
have been assigned a score of 0.
13.1
Area under watershed management
as a percentage of total geographical
area
16.46
This target corresponds to the global SDG target 13.1 that aims
to strengthen resilience and adaptive capacity to climate-related
hazards and natural disasters in all countries. Average of the 5
best scores, after removing the outliers, has been set as the target.
129
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
130Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 13.1: PERFORMANCE OF DISTRICTS ON SDG 13
SDG Target 13.1 13.2 13.1
District
Number of human lives lost
due to natural calamity per 10,000 population
Change in forest area
Area under watershed management
as a percentage of total geographical area
SDG 13
Arunachal Pradesh
Anjaw 0.00 -8.00 0.07 33
Bichom Null Null Null *
Changlang 0.00 50.16 0.32 67
Dibang Valley 0.00 -7.44 0.04 33
East Kameng 0.00 -29.33 1.28 36
East Siang 0.00 -1.75 0.46 34
Kamle 0.00 -5.63 0.59 35
Keyi Panyor Null Null Null *
Kra Daadi 0.00 -4.27 0.69 35
Kurung Kumey 0.22 -21.70 1.19 34
Leparada 0.00 -10.66 2.45 38
Lohit 0.00 -2.54 0.14 34
Longding 0.00 -9.80 0.92 35
Lower Dibang Valley 0.00 12.66 0.36 67
Lower Siang 0.00 -9.02 1.80 37
Lower Subansiri 0.00 -14.99 2.57 39
Namsai 0.00 7.84 0.31 67
Pakke Kessang 0.00 -11.46 0.43 34
Papum Pare 0.00 -5.40 0.55 34
Shi Yomi 0.00 35.45 0.00 67
Siang 0.00 -1.75 0.14 34
Tawang 0.00 -6.84 0.00 33
Tirap 0.00 -37.78 2.39 38
Upper Siang 1.70 2.54 0.00 55
Upper Subansiri 0.00 16.23 0.51 68
West Kameng 0.00 -9.43 0.23 34
West Siang 0.00 -20.01 1.35 36
Assam
Bajali Null Null Null *
Baksa 0.01 7.43 2.99 73
Barpeta 0.02 -0.77 2.19 38
Biswanath 0.03 5.21 0.00 66
Bongaigaon 0.04 -1.47 3.33 40
Cachar 0.01 -16.77 0.90 35
Charaideo 0.00 0.47 3.72 74
Chirang 0.08 -14.38 2.72 38
Darrang 0.03 2.61 2.84 72
Dhemaji 0.04 15.36 1.29 69
Dhubri 0.02 1.94 2.28 71
Dibrugarh 0.02 0.64 1.48 70
Dima Hasao 0.05 -93.27 0.92 35
Goalpara 0.05 11.60 2.10 71
Golaghat 0.02 36.06 1.25 69
Hailakandi 0.02 -16.60 3.77 41
Hojai 0.01 0.52 2.97 73
Jorhat 0.00 18.79 2.82 72
Kamrup 0.01 6.30 1.51 70
Kamrup Metropolitan 0.02 -2.11 2.63 39
Karbi Anglong 0.02 22.88 0.77 68
Karimganj 0.02 -2.70 0.00 33
Kokrajhar 0.02 -3.16 1.81 37
Lakhimpur 0.01 11.05 1.72 70
Majuli 0.06 4.24 5.23 77
Morigaon 0.01 3.25 2.82 72
Nagaon 0.02 -0.02 2.19 38
Nalbari 0.03 0.08 1.69 70
Sivasagar 0.12 3.90 2.64 71
Sonitpur 0.03 -2.02 24.08 66
South Salmara-Mankachar 0.02 -1.94 0.00 33
Tamulpur Null Null Null *
Tinsukia 0.02 3.65 1.32 69
Udalguri 0.00 -3.33 2.43 38
West Karbi Anglong 0.00 -9.20 1.45 36
Manipur
Bishnupur 0.00 -1.17 28.81 67
Chandel 0.00 -22.32 19.33 67
Churachandpur 0.00 -78.00 17.90 67
Imphal East 0.00 -5.26 31.82 67
131Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 13.1: PERFORMANCE OF DISTRICTS ON SDG 13
SDG Target 13.1 13.2 13.1
District
Number of human lives lost
due to natural calamity per 10,000 population
Change in forest area
Area under watershed management
as a percentage of total geographical area
SDG 13
Imphal West 0.00 -1.49 29.12 67
Jiribam 0.00 -1.93 53.80 67
Kakching 0.00 -2.90 56.04 67
Kamjong 0.00 -21.29 13.00 60
Kangpokpi 0.00 -31.57 17.17 67
Noney 0.00 -16.79 12.00 58
Pherzawl 0.00 -59.89 10.07 54
Senapati 0.07 81.61 16.18 99
Tamenglong 0.00 -38.43 15.36 64
Tengnoupal 0.00 1.55 11.10 89
Thoubal 0.00 -0.95 16.03 66
Ukhrul 0.00 144.00 12.01 91
Meghalaya
East Garo Hills 0.07 -28.09 4.23 41
East Jaintia Hills 0.00 -20.76 5.85 45
East Khasi Hills 0.16 13.69 5.08 76
Eastern West Khasi Hills Null Null Null *
North Garo Hills 0.00 -15.37 6.29 46
Ri Bhoi 0.04 0.56 3.78 74
South Garo Hills 0.00 -5.28 7.57 49
South West Garo Hills 0.11 -4.59 7.30 47
South West Khasi Hills 0.10 10.10 10.07 86
West Garo Hills 0.04 12.72 6.65 80
West Jaintia Hills 0.15 -8.03 17.72 66
West Khasi Hills 0.46 12.11 4.09 72
Mizoram
Aizawl 0.05 -33.64 2.04 37
Champhai 0.00 86.69 1.58 70
Hnahthial 0.00 114.67 Null 100
Khawzawl 0.00 12.89 Null 100
Kolasib 0.00 -37.58 5.41 44
Lawngtlai 0.00 50.17 2.98 73
Lunglei 0.00 -30.66 1.09 36
Mamit 0.00 -21.96 1.69 37
Saitual 0.00 -17.56 Null 50
Serchhip 0.00 14.17 1.69 70
Siaha 0.00 104.54 1.77 70
Nagaland
Chumoukedima Null Null Null *
Dimapur 0.05 -3.48 44.42 66
Kiphire 0.54 -0.54 36.37 63
Kohima 0.09 -4.15 32.57 66
Longleng 0.00 5.26 6.27 79
Mokokchung 0.00 14.88 32.15 100
Mon 0.08 -18.30 23.96 66
Noklak Null Null Null *
Niuland Null Null Null *
Peren 0.00 -8.48 22.50 67
Phek 0.06 0.88 46.68 100
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang 0.19 -14.28 23.26 65
Wokha 0.06 -7.99 31.67 66
Zunheboto 0.07 -15.69 40.39 66
Sikkim
Gangtok 0.87 4.46 0.00 61
Gyalshing 0.42 -1.66 0.00 30
Mangan 1.37 1.45 0.62 58
Namchi 0.48 0.94 1.93 67
Pakyong 4.83 Null 4.08 12
Soreng 0.00 Null 8.82 77
Tripura
Dhalai 0.11 -44.58 2.32 37
Gomati 0.14 6.86 4.62 75
Khowai 0.21 -23.16 5.18 42
North Tripura 0.00 -18.88 1.14 36
Sepahijala 0.08 -7.35 2.62 38
South Tripura 0.04 11.60 2.43 71
Unakoti 0.18 -13.52 2.16 36
West Tripura 0.03 -6.28 4.77 43
Target 0 16.46 100
The Goal is aimed at protecting, restoring and
promoting sustainable use of terrestrial ecosystems;
sustainable management of forests; combating
desertification; and halting and reversing land
degradation in conjunction with integrating
ecosystems and biodiversity into national and local
planning. It also seeks to promote fair and equitable
sharing of the benefits arising from the utilisation
of genetic resources, and prevent poaching and
trafficking of protected species of flora and fauna.
Targets
15.1 By 2020, ensure the conservation, restoration
and sustainable use of terrestrial and inland
freshwater ecosystems and their services,
in particular forests, wetlands, mountains
and drylands, in line with obligations under
international agreements
15.2 By 2020, promote the implementation of
sustainable management of all types of forests,
halt deforestation, restore degraded forests
and substantially increase afforestation and
reforestation globally
15.3 By 2030, combat desertification, restore
degraded land and soil, including land
affected by desertification, drought and floods,
and strive to achieve a land degradation-
neutral world
15.4 By 2030, ensure the conservation of mountain
ecosystems, including their biodiversity, in
order to enhance their capacity to provide
benefits that are essential for sustainable
development
15.5 Take urgent and significant action to reduce
the degradation of natural habitats, halt the
loss of biodiversity and, by 2020, protect and
prevent the extinction of threatened species
15.6 Promote fair and equitable sharing of the
benefits arising from the utilisation of genetic
resources and promote appropriate access to
such resources, as internationally agreed
15.7 Take urgent action to end poaching and
trafficking of protected species of flora and
fauna and address both demand and supply
of illegal wildlife products
15.8 By 2020, introduce measures to prevent the
introduction and significantly reduce the
impact of invasive alien species on land and
water ecosystems and control or eradicate the
priority species
15.9 By 2020, integrate ecosystem and biodiversity
values into national and local planning,
development processes, poverty reduction
strategies and accounts
15.a Mobilize and significantly increase financial
resources from all sources to conserve and
sustainably use biodiversity and ecosystems
15.b Mobilize significant resources from all sources
and at all levels to finance sustainable forest
management and provide adequate incentives
to developing countries to advance such
management, including for conservation and
reforestation
15.c Enhance global support for efforts to combat
poaching and trafficking of protected species,
including by increasing the capacity of local
communities to pursue sustainable livelihood
opportunities
SDG 15
LIFE ON LAND
Protect, restore and promote sustainable use of
terrestrial ecosystems, sustainably manage forests,
combat desertification, and halt and reverse land
degradation and halt biodiversity loss
133
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 15
FIGURE 15.1: SDG 15 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Anjaw AR 1 100
Dibang Valley AR 1 100
Kamle AR 1 100
Leparada AR 1 100
Lower Dibang Valley AR 1 100
Lower Siang AR 1 100
Siang AR 1 100
Upper Siang AR 1 100
Upper Subansiri AR 1 100
Charaideo AS 1 100
Dima Hasao AS 1 100
West Karbi Anglong AS 1 100
Jiribam MN 1 100
Kamjong MN 1 100
Kangpokpi MN 1 100
Noney MN 1 100
Pherzawl MN 1 100
Tengnoupal MN 1 100
West Jaintia Hills ML 1 100
Hnahthial MZ 1 100
Khawzawl MZ 1 100
Saitual MZ 1 100
Kiphire NL 1 100
Longleng NL 1 100
Peren NL 1 100
Gyalshing SK 1 100
Changlang AR 27 99
East Kameng AR 27 99
Kra Daadi AR 27 99
Kurung Kumey AR 27 99
Lohit AR 27 99
Namsai AR 27 99
Pakke Kessang AR 27 99
Chirang AS 27 99
Gangtok SK 27 99
Namchi SK 27 99
Soreng SK 27 99
Shi Yomi AR 38 98
West Siang AR 38 98
Cachar AS 38 98
Karimganj AS 38 98
Tinsukia AS 38 98
Pakyong SK 38 98
Papum Pare AR 44 97
Mangan SK 44 97
Unakoti TR 44 97
Hojai AS 47 96
Jorhat AS 47 96
Gomati TR 47 96
South Tripura TR 47 96
East Siang AR 51 95
East Khasi Hills ML 51 95
Khowai TR 51 95
North Tripura TR 51 95
Kamrup Metropolitan AS 55 94
Sepahijala TR 55 94
West Kameng AR 57 93
Hailakandi AS 57 93
Kamrup AS 57 93
Dhalai TR 57 93
East Garo Hills ML 61 92
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 15 ranges between 100 and 36
for the 121 districts included in the ranking and
computation. 26 districts fall in the category of Achiever,
87 districts fall in the category of Front Runners and
6 in the category of Performers, while 2 districts are
in the category of Aspirants with scores less than 50.
1342023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 15.1: SDG 15 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
North Garo Hills ML 61 92
South Garo Hills ML 61 92
Lower Subansiri AR 64 91
Kokrajhar AS 65 88
Dimapur NL 65 88
Dibrugarh AS 67 87
South West Garo Hills ML 67 87
South West Khasi Hills ML 67 87
West Garo Hills ML 67 87
West Khasi Hills ML 67 87
Wokha NL 67 87
West Tripura TR 67 87
Kolasib MZ 74 86
Sivasagar AS 75 85
Ri Bhoi ML 75 85
Lawngtlai MZ 75 85
Bongaigaon AS 78 84
Tamenglong MN 78 84
Ukhrul MN 78 84
Kohima NL 78 84
Baksa AS 82 83
Chandel MN 82 83
Aizawl MZ 82 83
East Jaintia Hills ML 85 82
Lunglei MZ 85 82
Longding AR 87 81
Tirap AR 87 81
Karbi Anglong AS 87 81
Goalpara AS 90 80
Serchhip MZ 90 80
Phek NL 90 80
Tawa n g AR 93 78
Lakhimpur AS 93 78
Udalguri AS 93 78
Sonitpur AS 96 77
Mokokchung NL 96 77
Nagaon AS 98 76
Senapati MN 98 76
Siaha MZ 98 76
Nalbari AS 101 75
Churachandpur MN 101 75
Champhai MZ 101 75
Dhemaji AS 104 74
Tuensang NL 104 74
Golaghat AS 106 73
Biswanath AS 107 72
Morigaon AS 107 72
Zunheboto NL 109 71
Mamit MZ 110 70
Imphal East MN 111 68
Imphal West MN 111 68
Mon NL 113 67
Kakching MN 114 56
Thoubal MN 114 56
Dhubri AS 116 55
Bishnupur MN 116 55
South Salmara-Mankachar AS 118 52
Majuli AS 119 50
Darrang AS 120 49
Barpeta AS 121 36
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
135
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 15.2: PERFORMANCE OF DISTRICTS IN SDG 15
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1362023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
15.1
Forest cover as a percentage of total
geographical area
33
National Afforestation and Eco-Development Board aims to achieve
33 percent of the geographical area in the country under forest
and tree cover.
15.3
Percentage of wasteland over total
geographical area
1.41
Global SDG target 15.3 aims to combat desertification, restore
degraded land and soil, including land affected by desertification,
drought and floods, and strives to achieve a land degradation-
neutral world by 2030. Average of the 5 best scores has been set
as the target.
15.7
Number of wildlife crime cases
reported per 1,000 sq kms of forest area
0
Global SDG target 15.7 calls for urgent action to end poaching
and trafficking of protected species of flora and fauna and address
both demand and supply of illegal wildlife products. The target
value has been set to 0 to imply that all crimes against wildlife
need to end.
137
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
138Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 15.1: PERFORMANCE OF DISTRICTS ON SDG 15
SDG Target 15.1 15.3 15.7
District
Forest cover as a percentage of
total geographical area
Percentage of wasteland over
total geographical area
Number of wildlife crime cases
reported per 1,000 sq kms of forest area
SDG 15
Arunachal Pradesh
Anjaw 68.62 Null 0.00 100
Bichom Null Null Null *
Changlang 84.49 2.22 0.00 99
Dibang Valley 66.51 Null 0.15 100
East Kameng 86.28 2.29 0.00 99
East Siang 86.24 8.39 0.00 95
Kamle 98.38 Null 0.00 100
Keyi Panyor Null Null Null *
Kra Daadi 69.59 3.33 0.00 99
Kurung Kumey 77.47 3.33 0.00 99
Leparada 88.07 Null 0.00 100
Lohit 75.26 2.41 0.00 99
Longding 65.37 25.71 0.00 81
Lower Dibang Valley 70.03 1.33 0.00 100
Lower Siang 88.69 Null 0.00 100
Lower Subansiri 89.91 13.32 0.00 91
Namsai 63.81 2.41 0.00 99
Pakke Kessang 90.44 2.29 0.00 99
Papum Pare 92.06 5.14 0.00 97
Shi Yomi 74.56 4.06 0.00 98
Siang 86.24 Null 0.00 100
Tawang 46.98 30.78 0.00 78
Tirap 79.53 25.71 0.00 81
Upper Siang 80.69 2.06 0.00 100
Upper Subansiri 92.67 1.62 0.00 100
West Kameng 85.62 10.8 0.00 93
West Siang 73.58 4.06 0.00 98
Assam
Bajali Null Null Null *
Baksa 24 Null 7.11 83
Barpeta 5.24 1.95 135.94 36
Biswanath 16.11 Null 0.00 72
Bongaigaon 20.76 3.21 3.99 84
Cachar 57.79 3.66 0.00 98
Charaideo 35.54 Null 0.00 100
Chirang 37.02 Null 1.42 99
Darrang 7.18 3.28 85.03 49
Dhemaji 11.7 1.72 8.41 74
Dhubri 5.42 5.21 46.88 55
Dibrugarh 22.57 1.93 5.27 87
Dima Hasao 82.68 Null 0.00 100
Goalpara 22.73 9.02 12.36 80
Golaghat 20.55 16.07 10.38 73
Hailakandi 58.22 10.84 0.00 93
Hojai 30.73 Null 0.00 96
Jorhat 32.09 3.29 7.07 96
Kamrup 31.43 5.65 7.24 93
Kamrup Metropolitan 48.51 Null 15.12 94
Karbi Anglong 76.85 26.39 0.13 81
Karimganj 46.38 3.99 1.17 98
Kokrajhar 36.73 16.23 2.57 88
Lakhimpur 14.56 2.15 3.22 78
Majuli 2.72 Null 0.00 50
Morigaon 12.94 1.48 22.67 72
Nagaon 18.93 9.89 8.75 76
Nalbari 10.81 2.35 0.00 75
Sivasagar 20.77 3.89 0.00 85
Sonitpur 23.86 11.47 21.47 77
South Salmara-Mankachar 3.99 Null 0.00 52
Tamulpur Null Null Null *
Tinsukia 41.11 4.03 0.63 98
Udalguri 20.46 Null 2.42 78
West Karbi Anglong 70.15 Null 0.00 100
Manipur
Bishnupur 4.42 2.06 51.33 55
Chandel 86.23 23.75 0.00 83
Churachandpur 79.01 33.59 0.00 75
Imphal East 13.67 15.97 0.00 68
Imphal West 7.24 5.85 0.00 68
139Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 15.1: PERFORMANCE OF DISTRICTS ON SDG 15
SDG Target 15.1 15.3 15.7
District
Forest cover as a percentage of
total geographical area
Percentage of wasteland over
total geographical area
Number of wildlife crime cases
reported per 1,000 sq kms of forest area
SDG 15
Jiribam 74.6 Null 0.00 100
Kakching 7.92 Null 7.22 56
Kamjong 86.8 Null 0.00 100
Kangpokpi 56.08 Null 0.00 100
Noney 87.38 Null 0.00 100
Pherzawl 86.53 Null 0.00 100
Senapati 75.27 33.27 0.00 76
Tamenglong 84.94 22.45 0.00 84
Tengnoupal 77.66 Null 0.00 100
Thoubal 3.07 16.33 0.00 56
Ukhrul 77.5 22.17 0.75 84
Meghalaya
East Garo Hills 93.76 11.82 0.00 92
East Jaintia Hills 65.14 25.5 0.00 82
East Khasi Hills 63.85 8.16 0.00 95
Eastern West Khasi Hills Null Null Null *
North Garo Hills 90.96 11.82 0.00 92
Ri Bhoi 85.1 20.79 0.00 85
South Garo Hills 86.68 11.81 0.00 92
South West Garo Hills 69.77 18.55 0.00 87
South West Khasi Hills 64.37 18.66 0.00 87
West Garo Hills 74.22 18.55 0.00 87
West Jaintia Hills 65.81 Null 0.00 100
West Khasi Hills 80.9 18.66 0.00 87
Mizoram
Aizawl 85.83 21.83 5.23 83
Champhai 83.17 31.52 9.57 75
Hnahthial 86.37 Null Null 100
Khawzawl 75.64 Null Null 100
Kolasib 85.62 11.83 22.98 86
Lawngtlai 80.09 17.72 10.16 85
Lunglei 88.42 18.3 19.20 82
Mamit 89.3 11.51 89.16 70
Saitual 82.35 Null Null 100
Serchhip 83.77 26.44 3.48 80
Siaha 90.76 22.7 Null 76
Nagaland
Chumoukedima Null Null Null *
Dimapur 50.04 16.71 0.00 88
Kiphire 71.85 Null 0.00 100
Kohima 74.5 22.09 0.00 84
Longleng 68.58 Null 0.00 100
Mokokchung 83.02 31.38 0.00 77
Mon 75.91 45 0.00 67
Noklak Null Null Null *
Niuland Null Null Null *
Peren 90.84 Null 0.00 100
Phek 73.66 27.01 0.00 80
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang 53.6 35.9 0.00 74
Wokha 79.46 18.65 0.00 87
Zunheboto 90.01 38.79 0.00 71
Sikkim
Gangtok 74.99 2.86 0.00 99
Gyalshing 67.72 2.06 0.00 100
Mangan 30.53 0.88 0.00 97
Namchi 75.07 3.11 0.00 99
Pakyong 74.99 2.86 Null 98
Soreng 67.72 2.06 Null 99
Tripura
Dhalai 79.19 10.62 0.54 93
Gomati 74.95 6.57 0.00 96
Khowai 70.07 7.7 0.00 95
North Tripura 77.37 7.28 1.18 95
Sepahijala 62.22 8.99 0.00 94
South Tripura 73.11 7.12 0.00 96
Unakoti 62.9 5.68 0.00 97
West Tripura 63.11 14.47 13.98 87
Target 33 1.41 0 100
Peace, stability and effective governance based
on rule-of-law and upholding the principles of
equality, human rights and justice are prerequisites
for sustainable development. The 2030 Agenda
aims to significantly reduce all forms of violence,
and work with governments and communities to
end conflict and insecurity. Promoting rule-of-law
and human rights are key to this process, as are
reducing the flow of illicit arms and strengthening
the participation of developing countries in the
institutions of global governance. Goal 16 also
focuses on ending abuse, exploitation, trafficking,
corruption and bribery, and in the development of
accountable and transparent institutions.
Targets
16.1 Significantly reduce all forms of violence and
related death rates everywhere
16.2 End abuse, exploitation, trafficking and
all forms of violence against and torture
of children
16.3 Promote the rule of law at the national and
international levels and ensure equal access
to justice for all
16.4 By 2030, significantly reduce illicit financial
and arms flows, strengthen the recovery and
return of stolen assets and combat all forms
of organized crime
16.5 Substantially reduce corruption and bribery
in all their forms
16.6 Develop effective, accountable and
transparent institutions at all levels
16.7 Ensure responsive, inclusive, participatory
and representative decision-making at
all levels
16.8 Broaden and strengthen the participation
of developing countries in the institutions of
global governance
16.9 By 2030, provide legal identity for all,
including birth registration
16.10 Ensure public access to information and
protect fundamental freedoms, in accordance
with national legislation and international
agreements
16.a Strengthen relevant national institutions,
including through international cooperation,
for building capacity at all levels, in particular
in developing countries, to prevent violence
and combat terrorism and crime
16.b Promote and enforce non-discriminatory laws
and policies for sustainable development
SDG 16
PEACE, JUSTICE AND
STRONG INSTITUTIONS
Promote peaceful and inclusive societies for sustainable
development, provide access to justice for all and build
effective, accountable and inclusive institutions at all levels
METHODOLOGY & RESULTS
141
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 16.1: SDG 16 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 16
0 2010 4030 50 60 908070 100
District StateRank
Kamjong MN 1 97
Noney MN 2 96
Hnahthial MZ 3 94
Pherzawl MN 4 93
Kangpokpi MN 5 90
Tengnoupal MN 6 86
Lawngtlai MZ 6 86
Serchhip MZ 6 86
Barpeta AS 9 85
Goalpara AS 9 85
South West Garo Hills ML 9 85
Lunglei MZ 9 85
Mamit MZ 9 85
Churachandpur MN 14 84
Ukhrul MN 14 84
Tamenglong MN 16 83
Champhai MZ 16 83
Khowai TR 16 83
Dhemaji AS 19 82
Karimganj AS 19 82
Lakhimpur AS 19 82
Aizawl MZ 19 82
Darrang AS 23 81
Dhalai TR 23 81
West Kameng AR 25 80
Kolasib MZ 25 80
Saitual MZ 25 80
Siaha MZ 25 80
Gomati TR 25 80
Changlang AR 30 79
Lower Dibang Valley AR 30 79
Cachar AS 30 79
Golaghat AS 30 79
Nalbari AS 30 79
Bishnupur MN 30 79
Imphal West MN 30 79
Sepahijala TR 30 79
Morigaon AS 38 78
Jiribam MN 38 78
Thoubal MN 38 78
North Garo Hills ML 38 78
Baksa AS 42 77
Chandel MN 42 77
Kakching MN 42 77
Senapati MN 42 77
Kokrajhar AS 46 76
Nagaon AS 46 76
Udalguri AS 46 76
North Tripura TR 46 76
West Tripura TR 46 76
Dibang Valley AR 51 75
West Garo Hills ML 51 75
Longding AR 53 74
Dibrugarh AS 53 74
Imphal East MN 53 74
Unakoti TR 53 74
Leparada AR 57 73
Dima Hasao AS 57 73
Hojai AS 57 73
Karbi Anglong AS 57 73
South West Khasi Hills ML 57 73
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 16 ranges between 97 and 36 for the
121 districts included in the ranking and computation.
Kamjong [MN], Noney [MN] and Hnahthial [MZ] are the
top performing districts. 90 districts fall in the category
of Front Runners and 26 in the category of Performers,
while 5 district is in the category of Aspirants with
scores less than 50.
1422023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 16.1: SDG 16 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Chirang AS 62 72
Dhubri AS 62 72
Jorhat AS 62 72
South Garo Hills ML 62 72
Gangtok SK 62 72
South Tripura TR 62 72
Tawa n g AR 68 71
Tirap AR 68 71
Bongaigaon AS 68 71
Namchi SK 68 71
East Kameng AR 72 70
Shi Yomi AR 72 70
Majuli AS 72 70
Dimapur NL 72 70
Kra Daadi AR 76 69
Tinsukia AS 76 69
Gyalshing SK 76 69
Upper Siang AR 79 68
South Salmara-Mankachar AS 79 68
Ri Bhoi ML 79 68
Anjaw AR 82 67
Lower Subansiri AR 83 66
Hailakandi AS 83 66
Sivasagar AS 83 66
Sonitpur AS 83 66
West Jaintia Hills ML 83 66
Mon NL 83 66
Biswanath AS 89 65
East Garo Hills ML 89 65
West Karbi Anglong AS 91 64
East Jaintia Hills ML 92 63
Mokokchung NL 92 63
Namsai AR 94 62
West Siang AR 94 62
East Khasi Hills ML 94 62
Tuensang NL 94 62
Zunheboto NL 94 62
Pakyong SK 94 62
East Siang AR 100 61
Siang AR 100 61
Kamrup AS 100 61
West Khasi Hills ML 100 61
Kiphire NL 100 61
Longleng NL 100 61
Wokha NL 106 60
Lohit AR 107 59
Upper Subansiri AR 107 59
Kohima NL 107 59
Phek NL 107 59
Khawzawl MZ 111 58
Peren NL 111 58
Pakke Kessang AR 113 57
Papum Pare AR 113 57
Kamle AR 115 50
Kamrup Metropolitan AS 115 50
Charaideo AS 117 49
Mangan SK 118 48
Kurung Kumey AR 119 47
Soreng SK 119 47
Lower Siang AR 121 36
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
143
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 16.2: PERFORMANCE OF DISTRICTS IN SDG 16
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1442023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
16.1
Reported murders per 10,000
population
0.07
Global SDG target 16.1 aims to significantly reduce all forms of
violence and related death rates everywhere. Average of the 5
best scores has been set as the target.
16.2
Cognizable crimes against children
per 10,000 child population
0
Global SDG target 16.2 aims to end abuse, exploitation,
trafficking and all forms of violence against and torture of
children.
16.2
Number of missing children per
10,000 child population
0
Global SDG target 16.2 aims to end abuse, exploitation,
trafficking and all forms of violence against and torture of
children.
16.3
Ratio of working strength to
sanctioned strength of Judges
(District & Subordinate courts)
1
Global SDG target 16.3 aims to promote the rule of law at the
national and international levels and ensure equal access to
justice for all.
16.6
Common Service Centres providing
online services per 10,000
population
11.88
Global SDG target 16.6 aims to develop effective, accountable
and transparent institutions at all levels. Average of the 5 best
scores has been set as the target.
16.9 Percentage of births registered100
Global SDG target 16.9 aims to provide legal identity for all,
including birth registration by 2030.
16.9
Percentage of population covered
under Aadhaar
100
Global SDG target 16.9 aims to provide legal identity for all,
including birth registration by 2030.
16.9 Percentage of deaths registered100
Global SDG target 16.9 aims to provide legal identity for all,
including birth registration by 2030.
145
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
146Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 16.1: PERFORMANCE OF DISTRICTS ON SDG 16
SDG Target 16.1 16.2 16.2 16.3 16.6 16.9 16.9 16.9
District
Reported murders
per 10,000
population
Cognizable crimes
against children
per 10,000
population
Number of
missing children
per 10,000
population
Ratio of working strength
to sanctioned strength
of Judges (District &
Subordinate courts)
Common Service
Centres providing
online services per
10,000 population
Percentage of
births registered
Percentage
of population
covered under
Aadhaar
Percentage
of deaths
registered
SDG 16
Arunachal Pradesh
Anjaw 0.47 0.94 0.00 1.00 0.94 94.4 88 34.6 67
Bichom Null Null Null Null Null Null Null Null *
Changlang 0.54 1.08 0.40 1.00 10.05 97.6 112 56.5 79
Dibang Valley 0.00 0.00 0.00 1.00 0.00 96.5 92 28.9 75
East Kameng 0.64 0.79 0.00 1.00 15.72 81.3 84 22.2 70
East Siang 0.56 1.39 0.00 1.00 0.42 83.9 95 26.1 61
Kamle 0.45 0.45 0.00 0.00 0.45 Null Null Null 50
Keyi Panyor Null Null Null Null Null Null Null Null *
Kra Daadi 0.21 0.43 0.00 1.00 0.00 92.7 Null 30.7 69
Kurung Kumey 0.44 0.22 0.44 0.50 0.22 93.4 47 8.3 47
Leparada 0.00 1.49 0.00 1.00 0.50 Null Null Null 73
Lohit 0.40 1.61 0.00 1.00 3.01 93.0 42 50.8 59
Longding 0.35 0.35 0.00 1.00 3.53 88.7 Null 57.2 74
Lower Dibang Valley 0.00 1.66 0.00 1.00 4.81 92.6 107 53.6 79
Lower Siang 0.92 1.38 0.00 0.00 1.84 Null Null Null 36
Lower Subansiri 0.24 0.47 0.47 1.00 2.60 90.0 77 30.3 66
Namsai 0.94 0.42 0.21 1.00 3.02 89.8 Null 57.5 62
Pakke Kessang 0.00 0.83 0.00 0.00 0.83 Null Null Null 57
Papum Pare 0.57 2.78 0.00 1.00 2.94 75.4 114 21.6 57
Shi Yomi 0.00 0.75 0.00 0.00 Null Null Null Null 70
Siang 0.31 0.94 0.00 1.00 0.31 79.9 Null 23.2 61
Tawang 0.00 0.20 0.00 0.50 1.20 95.3 84 51.2 71
Tirap 0.18 0.00 0.36 1.00 4.70 91.1 49 64.8 71
Upper Siang 0.28 1.13 0.00 1.00 3.40 79.5 107 18.4 68
Upper Subansiri 0.39 0.52 0.00 1.00 0.65 78.9 78 10.5 59
West Kameng 0.13 0.64 0.00 1.00 3.70 97.3 98 48.5 80
West Siang 0.38 1.33 0.00 1.00 1.14 81.9 92 17.7 62
Assam
Bajali Null Null Null Null Null Null Null Null *
Baksa 0.16 0.78 0.17 0.89 5.68 97.9 Null 50.1 77
Barpeta 0.18 0.76 0.00 0.86 7.29 96.0 118 74.3 85
Biswanath 0.57 2.01 0.00 0.67 5.62 98.7 Null 62.5 65
Bongaigaon 0.28 1.80 0.53 1.00 7.73 95.2 69 69.1 71
Cachar 0.35 0.84 0.00 0.92 3.56 96.0 101 72.4 79
Charaideo 0.72 1.40 1.57 0.63 3.92 94.4 Null 50.6 49
Chirang 0.29 1.78 0.58 0.92 5.10 99.3 Null 72.7 72
Darrang 0.33 0.88 0.19 0.91 6.79 96.9 103 69.2
81
Dhemaji 0.25 1.30 0.31 1.00 10.71 98.4 106 47.2 82
Dhubri 0.25 1.92 1.49 0.94 7.98 96.4 108 73.1 72
Dibrugarh 0.42 1.10 0.05 0.89 3.97 93.9 92 72.3 74
Dima Hasao 0.23 0.61 0.00 0.78 2.85 95.0 Null 60.3 73
Goalpara 0.23 0.55 0.00 0.90 6.58 98.8 106 73.3 85
Golaghat 0.22 0.59 0.10 0.93 5.43 90.9 100 55.2 79
Hailakandi 0.20 1.44 2.06 1.00 4.25 96.6 104 60.3 66
Hojai 0.29 2.10 0.00 0.70 5.85 98.7 Null 79.7 73
Jorhat 0.40 0.70 0.35 0.92 4.92 92.8 86 57.2 72
Kamrup 0.33 1.34 1.14 0.93 6.36 91.4 63 52.4 61
Kamrup Metropolitan 0.59 3.37 1.67 0.98 2.54 95.2 Null 77.4 50
Karbi Anglong 0.38 1.06 0.00 0.90 4.10 93.0 89 60.7 73
Karimganj 0.26 0.59 0.00 1.00 3.10 98.2 104 72.6 82
Kokrajhar 0.42 1.03 0.30 1.00 5.66 97.1 92 69.5 76
Lakhimpur 0.34 1.15 0.00 1.00 6.62 98.7 103 67.1 82
Majuli 0.24 1.08 0.42 0.50 6.87 98.1 Null 59.3 70
Morigaon 0.31 2.58 0.00 1.00 7.14 96.8 111 74.3 78
Nagaon 0.31 0.87 0.41 0.94 5.57 99.2 88 66.0 76
Nalbari 0.25 1.11 0.00 1.00 6.30 97.1 93 55.0 79
Sivasagar 0.40 1.26 0.00 0.77 6.56 97.1 56 57.9 66
Sonitpur 0.47 1.56 0.00 0.93 4.26 96.0 55 77.9 66
South Salmara-Mankachar 0.29 1.48 0.50 0.57 5.49 97.6 Null 71.1 68
Tamulpur Null Null Null Null Null Null Null Null *
Tinsukia 0.44 1.38 0.21 0.94 3.29 92.1 88 64.3 69
Udalguri 0.30 0.66 0.20 1.00 5.45 96.1 Null 51.2 76
West Karbi Anglong 0.24 0.91 0.24 0.50 3.11 95.4 Null 43.5 64
Manipur
Bishnupur 0.13 0.38 0.13 0.75 11.46 83.6 112 24.4 79
Chandel 0.24 0.24 0.00 1.00 6.10 91.4 78 53.7 77
Churachandpur 0.39 0.47 0.00 1.00 13.53 87.4 101 52.5 84
Imphal East 0.19 0.49 0.36 0.63 9.36 86.1 114 32.8 74
147Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 16.1: PERFORMANCE OF DISTRICTS ON SDG 16
SDG Target 16.1 16.2 16.2 16.3 16.6 16.9 16.9 16.9
District
Reported murders
per 10,000
population
Cognizable crimes
against children
per 10,000
population
Number of
missing children
per 10,000
population
Ratio of working strength
to sanctioned strength
of Judges (District &
Subordinate courts)
Common Service
Centres providing
online services per
10,000 population
Percentage of
births registered
Percentage
of population
covered under
Aadhaar
Percentage
of deaths
registered
SDG 16
Imphal West 0.10 0.64 0.27 0.86 7.37 86.8 113 49.6 79
Jiribam 0.23 0.46 0.46 1.00 4.79 Null Null Null 78
Kakching 0.21 0.69 1.10 1.00 8.57 Null Null Null 77
Kamjong 0.00 0.00 0.00 1.00 10.36 Null Null Null 97
Kangpokpi 0.15 0.15 0.00 1.00 7.85 Null Null Null 90
Noney 0.20 0.20 0.00 1.00 11.99 Null Null Null 96
Pherzawl 0.00 0.00 0.00 1.00 7.50 Null Null Null 93
Senapati 0.04 0.07 0.00 0.67 3.36 94.5 79 75.4 77
Tamenglong 0.00 0.00 0.00 1.00 9.13 90.4 78 51.8 83
Tengnoupal 0.17 0.83 0.00 1.00 7.43 Null Null Null 86
Thoubal 0.29 0.62 0.36 0.75 11.98 87.2 112 40.4 78
Ukhrul 0.15 0.37 0.00 1.00 12.45 87.3 86 49.1 84
Meghalaya
East Garo Hills 0.00 1.44 0.07 0.43 8.71 81.4 68 45.9 65
East Jaintia Hills 0.73 2.11 0.49 0.80 18.79 83.0 86 43.5 63
East Khasi Hills 0.17 1.74 0.00 0.43 5.04 77.4 79 55.3 62
Eastern West Khasi Hills Null Null Null Null Null Null Null Null *
North Garo Hills 0.00 1.05 0.00 0.80 19.87 79.5 Null 43.8 78
Ri Bhoi 0.39 2.12 0.42 0.71 12.63 85.9 81 51.1 68
South Garo Hills 0.49 1.26 0.00 0.83 13.14 92.0 68 53.8 72
South West Garo Hills 0.17 0.45 0.11 0.80 20.67 87.7 Null 71.4 85
South West Khasi Hills 0.20 1.31 0.10 0.60 15.13 80.3 Null 49.5 73
West Garo Hills 0.15 1.78 0.00 0.75 7.17 92.9 87 65.8 75
West Jaintia Hills 0.48 1.84 0.15 0.63 9.55 81.7 86 55.7 66
West Khasi Hills 0.33 3.14 0.00 0.63 23.03 79.2 66 49.0 61
Mizoram
Aizawl 0.38 1.31 0.00 0.86 7.08 99.3 116 86.2 82
Champhai 0.28 1.39 0.00 0.44 9.87 100.0 113 98.3 83
Hnahthial 0.00 0.70 0.00 Null 11.23 Null Null Null 94
Khawzawl 0.54 2.98 0.00 Null 7.87 Null Null Null 58
Kolasib 0.60 1.55 0.12 0.50 12.27 99.8 115 96.3 80
Lawngtlai 0.25 0.59 0.00 0.40 12.13 99.3 115 85.4 86
Lunglei 0.15 0.91 0.00 0.31 12.37 100.0 113 86.6 85
Mamit 0.12 1.51 0.00 0.40 15.17 99.1 129 88.4 85
Saitual 0.20 0.79 0.00 Null 6.72 Null Null Null 80
Serchhip 0.15 1.68 0.00 0.50 12.54 100.0 103 93.4 86
Siaha 0.00 0.71 0.00 0.60 4.07 97.5 118 75.3 80
Nagaland
Chumoukedima Null Null Null Null Null Null Null
Null *
Dimapur 0.59 0.64 0.15 0.67 6.85 80.2 116 61.6 70
Kiphire 0.00 0.14 0.00 0.50 4.59 72.3 64 28.1 61
Kohima 0.14 0.24 1.75 1.00 2.13 78.3 78 42.8 59
Longleng 0.20 0.00 0.00 0.50 6.54 67.5 76 12.7 61
Mokokchung 0.10 0.15 0.00 0.67 1.18 85.6 68 29.7 63
Mon 0.00 0.12 0.00 0.67 4.52 71.4 64 50.9 66
Noklak Null Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null *
Peren 0.21 0.11 0.00 0.50 5.99 78.7 49 19.3 58
Phek 0.06 0.18 0.00 0.50 2.14 70.3 67 31.2 59
Shamator Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null *
Tuensang 0.00 0.28 0.00 0.50 5.60 66.0 76 26.5 62
Wokha 0.00 0.06 0.00 0.50 2.04 78.9 52 47.5 60
Zunheboto 0.00 0.14 0.07 1.00 1.49 51.6 67 51.0 62
Sikkim
Gangtok 0.09 2.73 0.18 1.00 1.00 95.9 107 68.4 72
Gyalshing 0.42 2.37 0.00 0.67 1.67 97.6 116 83.1 69
Mangan 0.23 3.66 1.83 0.25 1.14 98.1 93 76.3 48
Namchi 0.07 2.52 0.20 0.60 1.02 96.8 102 87.2 71
Pakyong 0.16 2.18 0.16 0.80 0.78 Null Null Null 62
Soreng 0.15 2.32 0.00 0.00 0.77 Null Null Null 47
Tripura
Dhalai 0.45 0.45 0.11 0.92 5.76 94.2 117 81.0 81
Gomati 0.16 0.82 0.26 0.90 7.27 92.9 Null 70.8 80
Khowai 0.34 0.52 0.00 1.00 6.62 94.8 Null 83.9 83
North Tripura 0.43 0.77 0.24 0.89 5.27 93.5 86 85.9 76
Sepahijala 0.25 0.33 0.29 0.89 6.19 95.3 Null 67.4 79
South Tripura 0.34 0.51 0.63 0.80 6.22 91.7 79 75.2 72
Unakoti 0.22 1.23 0.47 0.88 5.89 91.7 Null 71.1 74
West Tripura 0.25 0.50 0.50 0.90 4.16 94.9 82 88.1 76
Target 0.07 0 0 1 11.88 100 100 100 100
THE WAY FORWARD:
With less than five years remaining to achieve the
Sustainable Development Goals (SDGs), expediting
focused efforts to ensure inclusive development for
all is imperative. The North Eastern Region District
SDG Index and Dashboard serves as a valuable tool
to identify critical areas of development needs and
prioritise those farthest behind. It aims to enhance
analytical understanding of sectoral issues, fill data
gaps, and guide future action plans in the region. This
unique policy tool provides essential insights at the
district level, highlighting critical gaps and informing
resource allocation decisions. The Index serves as
a reliable reference for the NE States to assess the
comparative progress of districts across various SDGs,
including health, education, gender, economic growth,
institutions and environment.
Over the past four years, the North Eastern States have
successfully intensified the momentum of localising
SDGs and measuring progress at the district level
through the first edition of the NER District SDG Index
and Dashboard. A few States have also initiated setting
up SDG cells/coordination centres to institutionalise
these goals. Sustaining this progress is key to bridging
the performance gap in the short term and positioning
districts/states as top Performers in the long run.
It is worth noting that MDoNER has designed a new
scheme, Prime Minister's Development Initiative for
North East Region (PM-DevINE), based on the findings
of the first NER District SDG Index. This scheme
focuses on infrastructure development, industry
promotion, and social development projects while
enhancing livelihood opportunities for youth and
women. It provides targeted support to address
development gaps and accelerate progress on the
SDGs in the North Eastern Region.
Looking ahead, NITI Aayog and MDoNER are
committed to ensure:
a) Institutionalisation of SDGs in NE States through
the whole of the government approach:
The second edition of the index can be used as a tool
by the NE States to
•
Establish SDGCAC with support and guidance
from MDoNER and NITI Aayog to strengthen
governance, implementation, and monitoring of
SDG progress.
•
Develop State SDG Action Plans by leveraging
data from the index to assess district performance,
identify gaps, and set a foundation for targeted
interventions in alignment with national and state
initiatives.
•
Set clear targets and assign responsibilities to
specific departments, ensuring accountability and
a structured approach to addressing SDG-related
challenges.
•
Design and implement targeted interventions
using evidence-based insights to close identified
gaps, improve outcomes, and track progress
effectively.
b) Investment in data infrastructure and capacities
(including for citizen-generated data) to
improve data accessibility, support evidence-
based decision-making and accurate solution
identification. It is essential to integrate emerging
technologies like Big Data, AI, and Machine
Learning with traditional data sources while
ensuring their ethical use. There is a need to
enhance analytics and data capacities to identify
marginalized groups, understand challenges, and
design targeted SDG interventions.
c) Integrating SDG targets into government budgets
to ensure impact-driven and results-oriented
financial planning. SDG costing and financing gap
analyses are needed to assess resource needs and
identify funding shortfalls. Innovative financing
tools such as the SDG Investor Map and CSR
matchmaking platforms to mobilize additional
investments can be explored in this direction.
FROM ANALYSIS TO ACTION
CHAPTER 4
1502023-24NER DISTRICT SDG INDEX
d) Recognise the role of partnerships, including
South-South Cooperation, as a key strategy to
accelerate SDG progress. Fostering cross-learning
among Himalayan states and countries to share
best practices has the potential to address common
implementation challenges. Knowledge exchange
on effective strategies can help policymakers adopt
innovative, region-specific solutions for sustainable
development.
The continued collaboration between NITI Aayog, the
nodal ministry for SDG implementation, MDoNER,
State governments, other development partners,
and the private sector will be crucial in ensuring the
effective implementation and monitoring of SDGs. This
partnership will focus on strengthening institutional
structures at the state and district levels, aligning them
with the SDG agenda, and working towards achieving
the goals outlined in Agenda 2030.
151
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
STATE PROFILE
STATE PROFILES
III
153
© 2022 Mapbox © OpenStreetMap
State_Map
Arunachal Pradesh
Performance Category
Front Runner
Performer
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Arunachal Pradesh.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
59.26%
(16 Districts)
33.33%
(9 Districts)
7.41%
(2 Districts)
FIGURE AR.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORESAspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) ARUNACHAL PRADESH
DISTRICT-WISE PERFORMANCE
FIGURE AR.2: OVERALL PERFORMANCE OF DISTRICTS IN ARUNACHAL PRADESH
1542023-24NER DISTRICT SDG INDEX
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
52.00%
40.00%
16.00%
68.00%
72.00%
64.00%
56.00%84.00%
4.00% 20.00%
44.00%20.00%
88.00%
88.00%
100.00%
32.00%
32.00%12.00%
8.00%
100.00%
8.00%
20.00%
36.00%
20.00%
76.00%
56.00%
48.00%
84.00%
28.00%
12.00%
32.00%
8.00%
4.00%
36.00%
36.00%
36.00%44.00%
FIGURE AR.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE AR.1: OVERALL PERFORMANCE OF DISTRICTS IN ARUNACHAL PRADESH
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Lower Dibang Valley 23 1 73.36 67.67
Tawang 36 2 72.07 68.73
East Siang 51 3 70.79 68.80
Papum Pare 59 4 70.14 68.87
Changlang 63 5 69.93 68.53
West Kameng 64 6 69.86 66.93
Kurung Kumey 71 7 69.00 62.13
Namsai 72 8 68.93 65.60
East Kameng 78 9 68.21 58.27
West Siang 80 10 68.07 68.07
Lohit 81 11 68.00 64.67
Dibang Valley 83 12 67.93 64.80
Upper Siang 85 13 67.79 67.40
Leparada 88 14 67.36 63.80
Upper Subansiri 91 15 67.14 65.40
Lower Subansiri 100 16 65.86 68.47
Lower Siang 107 17 64.14 60.87
Shi Yomi 109 18 63.43 58.60
Kra Daadi 111 19 63.21 55.60
Pakke Kessang 112 20 63.14 59.73
Anjaw 113 21 63.07 63.60
Tirap 116 22 61.93 66.20
Siang 117 23 61.71 64.00
Kamle 120 24 58.86 57.40
Longding 121 25 58.71 66.60
Bichom N/A N/A N/A N/A
Keyi Panyor N/A N/A N/A N/AAspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
155
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) ASSAM
DISTRICT-WISE PERFORMANCE FIGURE AS.2: OVERALL PERFORMANCE OF DISTRICTS IN ASSAM
© 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
ERROR
Front Runner
Performer
Assam
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Assam.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
5.71%
(2 Districts)
88.57%
(31 Districts)
5.71%
(2 Districts)
FIGURE AS.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1562023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE AS.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1 81.82%
63.64%
100.00%
100.00%
57.58% 24.24%
12.12%
9.09%
96.97%
63.64%
9.09%
39.39%
6.06%
60.61%
75.76%
87.88%
78.79%21.21%
3.03%
100.00%
18.18%
100.00%
78.79%
9.09%
9.09%3.03%
36.36%
60.61%
15.15%
36.36%
39.39%
3.03%
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Dibrugarh 17 1 74.29 68.33
Sivasagar 20 2 74.00 68.33
Jorhat 21 3 73.79 69.67
Nalbari 28 4 72.86 69.47
Goalpara 30 5 72.79 69.47
Hojai 32 6 72.36 N/A
Kamrup Metropolitan 38 7 71.86 71.73
Tinsukia 41 8 71.79 67.60
Golaghat 44 9 71.50 67.00
Lakhimpur 47 10 71.43 68.80
Dima Hasao 50 11 70.93 62.67
Charaideo 53 12 70.71 N/A
Karimganj 54 13 70.64 69.47
Karbi Anglong 55 14 70.57 63.87
Morigaon 55 14 70.57 67.40
Dhemaji 58 16 70.21 66.33
Sonitpur 59 17 70.14 68.60
Kamrup 61 18 70.07 69.07
Cachar 65 19 69.79 67.53
Bongaigaon 67 20 69.36 67.47
Hailakandi 67 20 69.36 67.27
Nagaon 70 22 69.21 67.33
Biswanath 76 23 68.50 N/A
Chirang 77 24 68.29 69.07
Dhubri 84 25 67.86 64.33
Darrang 87 26 67.43 N/A
Majuli 88 27 67.36 N/A
Kokrajhar 91 28 67.14 66.00
Barpeta 94 29 66.79 64.00
Baksa 97 30 66.29 65.33
Udalguri 102 31 65.71 66.73
West Karbi Anglong 108 32 63.86 N/A
South Salmara-Mankachar 118 33 59.71 N/A
Bajali N/A N/A N/A N/A
Tamulpur N/A N/A N/A N/A
TABLE AS.1: OVERALL PERFORMANCE OF DISTRICTS IN ASSAM
157
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) MANIPUR
DISTRICT-WISE PERFORMANCE © 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
Front Runner
Performer
Manipur
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Manipur.© 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
Front Runner
Performer
Manipur
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Manipur.
FIGURE MN.2: OVERALL PERFORMANCE OF DISTRICTS IN MANIPUR
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
25%
(4 Districts)
75%
(12 Districts)
FIGURE MN.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1582023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 16.25%
25.00%
12.50%
18.75%6.25%
100.00%
43.75%
6.25%
68.75%
25.00%
18.75%
50.00%
43.75%
68.75%
50.00%
18.75%
37.50%
75.00%
31.25%
62.50%
62.50%
37.50%
50.00%
12.50%
12.50% 87.50%
25.00%
100.00%
43.75%
100.00%
75.00%
50.00%
37.50%
25.00%
12.50%
FIGURE MN.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE MN.1: OVERALL PERFORMANCE OF DISTRICTS IN MANIPUR
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Imphal West 24 1 73.21 72.13
Imphal East 27 2 72.93 70.87
Kakching 38 3 71.86 N/A
Jiribam 43 4 71.64 N/A
Thoubal 48 5 71.29 68.93
Tengnoupal 57 6 70.43 N/A
Bishnupur 66 7 69.43 69.27
Senapati 73 8 68.71 66.93
Ukhrul 75 9 68.64 65.27
Kamjong 96 10 66.43 N/A
Chandel 99 11 65.93 67.47
Churachandpur 103 12 65.36 66.53
Kangpokpi 104 13 64.86 N/A
Noney 106 14 64.43 N/A
Tamenglong 115 15 62.07 64.93
Pherzawl 118 16 59.71 N/A
159
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) MEGHALAYA
DISTRICT-WISE PERFORMANCE FIGURE ML.2: OVERALL PERFORMANCE OF DISTRICTS IN MEGHALAYA
© 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
ERROR
Front Runner
Performer
Null
Meghalaya
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Meghalaya.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
8.33%
(1 District)
83.33%
(10 Districts)
8.33%
(1 District)
FIGURE ML.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1602023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
54.55%
63.64%
54.55%
66.67%
54.55%
18.18%
27.27%
27.27%
45.45%
36.36%
27.27%
16.67%
45.45%
72.73%
72.73%9.09%
72.73%
81.82%
90.91%
63.64%
90.91%
16.67%
18.18%
9.09% 63.64%
18.18%
9.09%
36.36%
27.27%
9.09%
100.00%
72.73%27.27%
TABLE ML.1: OVERALL PERFORMANCE OF DISTRICTS IN MEGHALAYA
FIGURE ML.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
East Khasi Hills 26 1 73.00 66.27
South West Garo Hills 41 2 71.79 63.40
West Garo Hills 44 3 71.50 63.80
Ri Bhoi 69 4 69.29 62.80
West Jaintia Hills 73 5 68.71 64.27
East Garo Hills 81 6 68.00 63.00
West Khasi Hills 88 7 67.36 63.60
South West Khasi Hills 93 8 67.00 61.93
North Garo Hills 95 9 66.64 56.87
South Garo Hills 101 10 65.79 59.20
East Jaintia Hills 114 11 63.00 63.33
Eastern West Khasi Hills N/A N/A N/A N/A
161
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) MIZORAM
DISTRICT-WISE PERFORMANCE OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM
© 2022 Mapbox © Op enStreetMap
State_Map
Performance Category
Front Runner
Mizoram
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Mizoram.
OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM
© 2022 Mapbox © Op enStreetMap
State_Map
Performance Category
Front Runner
Mizoram
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Mizoram.
FIGURE MZ.2: OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM© 2022 Mapbox © Op enStreetMap
State_Map
Performance Category
Front Runner
Mizoram
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Mizoram.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
100.00%
(11 Districts)
Aspirant Performer Front Runner Achiever Not included in computation
FIGURE MZ.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1622023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 190.91%
9.09%
81.82%
18.18% 72.73%
9.09%
72.73%18.18%
100.00%
63.64%
72.73%
9.09% 36.36%36.36%
100.00%
81.82%
90.91%
90.91%
63.64%
9.09%
9.09%
9.09%
9.09%
90.91%
36.36%
18.18%
27.27%
27.27%
9.09%
18.18%
9.09%
54.55%45.45%
9.09%
FIGURE MZ.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE MZ.1: OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Hnahthial 1 1 81.43 N/A
Champhai 2 2 79.86 71.93
Kolasib 9 3 76.50 72.27
Aizawl 11 4 76.07 71.27
Serchhip 12 5 75.64 74.87
Saitual 13 6 75.36 N/A
Khawzawl 17 7 74.29 N/A
Siaha 34 8 72.14 68.27
Lunglei 51 9 70.79 72.87
Mamit 79 10 68.14 71.47
Lawngtlai 86 11 67.71 63.40
163
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) NAGALAND
DISTRICT-WISE PERFORMANCE FIGURE NL.2: OVERALL PERFORMANCE OF DISTRICTS IN NAGALAND
© 2022 Mapbox © O penStreetMap
State_Map
Performance Category
ERROR
Front Runner
Performer
Nagaland
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Nagaland.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
12.5%
(2 Districts)
31.25%
(5 Districts)
56.25%
(9 Districts)
FIGURE NL.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1642023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1 54.55%
9.09%
81.82%
72.73%27.27%
63.64%
18.18%
45.45%
90.91%
54.55%
81.82% 18.18%
18.18%
36.36%
100.00%
100.00%
100.00%
100.00%
72.73%
18.18%
27.27%
27.27%
63.64%18.18%
18.18% 81.82%
9.09% 72.73%
18.18%
FIGURE NL.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE NL.1: OVERALL PERFORMANCE OF DISTRICTS IN NAGALAND
District Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Mokokchung 4 1 78.43 62.27
Kohima 6 2 76.93 64.07
Dimapur 10 3 76.29 63.67
Phek 25 4 73.14 58.27
Longleng 28 5 72.86 59.07
Peren 34 6 72.14 60.53
Wokha 44 7 71.50 59.33
Mon 62 8 70.00 55.93
Kiphire 98 9 66.07 53.00
Tuensang 105 10 64.57 55.87
Zunheboto 110 11 63.36 54.53
Chumoukedima N/A N/A N/A N/A
Niuland N/A N/A N/A N/A
Noklak N/A N/A N/A N/A
Shamator N/A N/A N/A N/A
Tseminyu N/A N/A N/A N/A
165
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) SIKKIM
DISTRICT-WISE PERFORMANCE FIGURE SK.2: OVERALL PERFORMANCE OF DISTRICTS IN SIKKIM
© 2022 Mapbox © OpenStreetMap
State_Map
Sikkim
Performance Category
ERROR
Front Runner
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Sikkim.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
100%
(6 Districts)
FIGURE SK.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1662023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 116.67%
100.00%
33.33% 33.33%
50.00%
100.00%
100.00%
66.67%
83.33%
100.00%
100.00%
100.00%
50.00%33.33%
100.00%
100.00%
16.67%
66.67% 33.33%
33.33%
16.67%
83.33%
33.33% 16.67%
33.33%
16.67%
83.33%
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Gangtok 8 1 76.64 75.87
Namchi 14 2 75.21 74.80
Mangan 31 3 72.50 72.00
Pakyong 37 4 72.00 N/A
Soreng 38 5 71.86 N/A
Gyalshing 49 6 71.14 71.87
FIGURE SK.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE SK.1: OVERALL PERFORMANCE OF DISTRICTS IN SIKKIM
167
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) TRIPURA
DISTRICT-WISE PERFORMANCE FIGURE TR.2: OVERALL PERFORMANCE OF DISTRICTS IN TRIPURA
© 2022 Mapbox © Op enStreetMap
State_Ma p
Tripura
Performance Category
Front Runner
Map bas ed on Longitude (generated) and L ongitude (generated) and L atitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and St ates. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_St ates.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Tripura.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
100%
(8 Districts)
Aspirant Performer Front Runner Achiever Not included in computation
FIGURE TR.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1682023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
87.50%
87.50%
62.50%
37.50%
25.00%75.00%
62.50%
37.50%
12.50%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
62.50%
100.00%
12.50%
12.50%
37.50%
FIGURE TR.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE TR.1: OVERALL PERFORMANCE OF DISTRICTS IN TRIPURA
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Gomati 3 1 78.79 75.73
West Tripura 5 2 77.64 75.67
South Tripura 7 3 76.71 72.40
Sepahijala 15 4 75.07 72.60
Khowai 16 5 74.64 71.93
North Tripura 17 6 74.29 75.73
Unakoti 22 7 73.71 73.47
Dhalai 33 8 72.29 72.60
169
CONTEXT & OVERVIEWSTATE PROFILE
METADATA &
INDICATOR TABLES
IV
GOAL 1: END POVERTY Percentage of beneficiaries covered under National Food Security Act (NFSA), 2013
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people
in vulnerable situations, including infants, to safe, nutritious and sufficient food all year round
Relevant NIF Indicator 2.1.2: Proportion of beneficiaries covered under National Food Security Act 2013
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: END POVERTY Headcount ratio as per the Multi-Dimensional Poverty Index (%)
Indicator Data Source
NITI Aayog
National Multi-Dimensional Poverty Index (Baseline Report based on NFHS-5 (2019–2021))
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity Non-periodic
Relevant Global Target
1.2: By 2030, reduce at least by half the proportion of men, women and children of all ages living
in poverty in all its dimensions according to national definitions
Relevant NIF Indicator
1.2.2: Proportion of men, women and children of all ages living in poverty in all its dimensions
according to national definitions
Relevant Global Indicator
1.2.2: Proportion of men, women and children of all ages living in poverty in all its dimensions
according to national definitions
Indicator Interpretation Higher value means lower performance (–)
GOAL 1: END POVERTY
Persons offered employment as a percentage of persons who demanded employment under
Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)
Indicator Data Source
Ministry of Rural Development
[MGNREGA MIS Report]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant Global Indicator
1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing
children, unemployed persons, older persons, persons with disabilities, pregnant women,
newborns, work-injury victims and the poor and the vulnerable
Relevant NIF Indicator
1.3.3: Persons offered employment as a percentage of persons who demanded employment under
Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)
Indicator Interpretation Higher value means higher performance (+)
× 100
Families/persons identified under NFSA
Accepted no. of persons/families covered under NFSA
× 100
Persons offered employment under MGNREGA
Persons who demanded employment under MGNREGA
1722023-24NER DISTRICT SDG INDEX
GOAL 1: END POVERTY Percentage of Self-Help Groups (SHGs) provided credit linkage
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant NIF Indicator 1.3.4: Number of Self-Help Groups (SHGs) provided bank credit linkage
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: END POVERTY
Percentage of women receiving benefits under Pradhan Mantri Matru Vandana Yojana (PMMVY)
or any other maternity related State schemes against target
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 115
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant Global Indicator
1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing
children, unemployed persons, older persons, persons with disabilities, pregnant women,
newborns, work-injury victims and the poor and the vulnerable
Relevant NIF Indicator
1.3.5: Proportion of the population (out of total eligible population) receiving social protection
benefits under Pradhan Mantri Matru Vandana Yojana (PMMVY)
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: END POVERTY
Percentage of affordable houses completed against sanctioned (rural + urban) under Pradhan
Mantri Awas Yojana (PMAY) and related State schemes
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
1.4: By 2030, ensure that all men and women, in particular the poor and the vulnerable, have
equal rights to economic resources, as well as access to basic services, ownership and control
over land and other forms of property, inheritance, natural resources, appropriate new technology
and financial services, including microfinance
Relevant Global Indicator 1.4.1: Proportion of population living in households with access to basic services
Relevant NIF Indicator 1.4.1: Proportion of population living in households with access to basic services
Indicator Interpretation Higher value means higher performance (+)
× 100
No. of SHGs provided credit linkage in the district
Total no. of SHGs in the district
× 100
No. of beneficiaries paid under PMMVY and other State schemes in the FY 2023–24
No. of beneficiaries enrolled under PMMVY and other State schemes in the FY 2023–24
× 100
No. of houses completed under PMAY and State schemes (rural & urban)
Total no. of houses sanctioned for construction under PMAY & State schemes (rural & urban)
173
METADATA
GOAL 1: NO POVERTY
Percentage of households with any usual member covered by a health scheme or health
insurance
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including floors,
and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant Global Indicator
1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing
children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns,
work-injury victims and the poor and the vulnerable
Relevant NIF Indicator
1.3.1: Percentage of households with any usual member covered by a health scheme or health
insurance
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: NO POVERTY
Hospital beds empanelled under Pradhan Mantri Jan Arogya Yojana (PMJAY) or related State
schemes per 10,000 eligible population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Number per 10,000 eligible population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including floors,
and by 2030 achieve substantial coverage of the poor and the vulnerable
Indicator Interpretation Higher value means higher performance (+)
GOAL 2: ZERO HUNGER Percentage of Fair Price Shops (FPS) covered under online transaction system for PDS in the district
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people in
vulnerable situations, including infants, to safe, nutritious and sufficient food all year round
Indicator Interpretation Higher value means higher performance (+)
× 10,000
No. of beds in the hospitals empanelled under PMJAY or related State schemes in the district
Total no. of people identified as eligible for PMJAY or related State schemes in the district
× 100
No. of FPS covered under online transaction system for PDS in the district
Total no. of FPS for PDS in the district
1742023-24NER DISTRICT SDG INDEX
GOAL 2: ZERO HUNGER
Percentage of Anganwadi centres in the district with anthropometric measurement devices
(height, weight)
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls,
pregnant and lactating women and older persons
Indicator InterpretationHigher value means higher performance (+)
GOAL 2: ZERO HUNGER Percentage of Anganwadis with own buildings
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls,
pregnant and lactating women and older persons
Indicator InterpretationHigher value means higher performance (+)
GOAL 2: ZERO HUNGER Percentage of children under age 5 years who are stunted
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls,
pregnant and lactating women and older persons
Relevant Global Indicator
2.2.1: Prevalence of stunting (height for age ≤2 standard deviation from the median of the World Health
Organization (WHO) Child Growth Standards) among children under 5 years of age
Relevant NIF Indicator2.2.1: Percentage of Children under age 5 years who are stunted
Indicator InterpretationHigher value means lower performance (–)
× 100
No. of Anganwadi centres in the district with anthropometric measurement devices (height, weight)
Total no. of Anganwadi centres in the district
× 100
No. of Anganwadi centres with own buildings
Total no. of Anganwadi centres in the district
175
METADATA
GOAL 2: ZERO HUNGER Percentage of children under age 5 years who are underweight
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally
agreed targets on stunting and wasting in children under 5 years of age, and address the
nutritional needs of adolescent girls, pregnant and lactating women and older persons
Relevant NIF Indicator 2.1.1: Percentage of children aged under 5 years who are underweight
Indicator Interpretation Higher value means lower performance (–)
GOAL 2: ZERO HUNGER Percentage of pregnant women aged 15–49 years who are anaemic (<11.0 g/dL)
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 99
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally
agreed targets on stunting and wasting in children under 5 years of age, and address the
nutritional needs of adolescent girls, pregnant and lactating women and older persons
Relevant Global Indicator 2.2.3: Prevalence of anaemia in women aged 15–49 years, by pregnancy status (percentage)
Relevant NIF Indicator 2.2.3: Prevalence of anaemia in women aged 15–49 years, by pregnancy status (percentage)
Indicator Interpretation Higher value means lower performance (–)
GOAL 2: ZERO HUNGER Percentage of children aged 6–59 months who are anaemic (<11.0 g/dL)
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally
agreed targets on stunting and wasting in children under 5 years of age, and address the
nutritional needs of adolescent girls, pregnant and lactating women and older persons
Relevant NIF Indicator 2.2.5: Percentage of children age 6–59 months who are anaemic (Hb < 11.0 g/dL)
Indicator Interpretation Higher value means lower performance (−)
1762023-24NER DISTRICT SDG INDEX
GOAL 2: ZERO HUNGER Average yield of rice (kg/ha)
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Kg/Hectare
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in
particular women, indigenous peoples, family farmers, pastoralists and fishers, including through
secure and equal access to land, other productive resources and inputs, knowledge, financial
services, markets and opportunities for value addition and non-farm employment
Relevant NIF Indicator 2.3.1: Agriculture productivity of wheat and rice (in kg per hectare)
Indicator Interpretation Higher value means higher performance (+)
GOAL 2: ZERO HUNGER Productivity of fruits and vegetables (kg/ha)
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Kg/Hectare
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in
particular women, indigenous peoples, family farmers, pastoralists and fishers, including through
secure and equal access to land, other productive resources and inputs, knowledge, financial
services, markets and opportunities for value addition and non-farm employment
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of pregnant women who completed 4 (ANCs) in the district
Indicator Data Source Ministry of Health and Family Welfare
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 119
Data Periodicity Annual
Relevant Global Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births
Relevant NIF Indicator
3.1.4: Percentage of women aged 15–49 years with a live birth, for last birth, who received ANC,
four times or more (period for 5 years/1 year)
Indicator Interpretation Higher value means higher performance (+)
Total production of rice (kg)
Area under rice cultivation (Ha)
Total production of fruits and vegetables (kg)
Area under cultivation of fruits and vegetables (Ha)
177
METADATA
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of births attended by skilled health personnel
Indicator Data Source Ministry of Health and Family Welfare
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 119
Data Periodicity Annual
Relevant Global Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births
Relevant Global Indicator 3.1.2: Proportion of births attended by skilled health personnel
Relevant NIF Indicator 3.1.3: Percentage of births attended by skilled health personnel (period 1 year)
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of children aged 9–11 months fully immunized
Indicator Data Source Ministry of Health and Family Welfare
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 119
Data Periodicity Annual
Relevant Global Target
3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all
countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and
under-5 mortality to at least as low as 25 per 1,000 live births
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
Relevant Global Indicator
3.b.1: Proportion of the target population covered by all vaccines included in their national
programme
Relevant NIF Indicator
3.b.1: Percentage of children aged 12–23 months fully immunized (BCG, Measles and three doses
of Pentavalent vaccine)
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Infant Mortality Rate
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Per 1,000 live births
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all
countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and
under-5 mortality to at least as low as 25 per 1,000 live births
Indicator Interpretation Higher value means lower performance (–)
× 1,000
Infant deaths (< 1 year) during the given year
Total live births during the given year
1782023-24NER DISTRICT SDG INDEX
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of functional newborn facilities (SNCU, NBSU, NBCC) per 10,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of new HIV infections per 1,000 uninfected population
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Per 1,000 uninfected population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases
and combat hepatitis, waterborne diseases and other communicable diseases
Relevant Global Indicator
3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key
populations
Relevant NIF Indicator 3.3.1: Number of new HIV infections per 1,000 uninfected population
Indicator Interpretation Higher value means lower performance (–)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of TB cases successfully treated among TB cases notified to the national health
authorities
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 98
Data Periodicity Annual
Relevant Global Target
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases
and combat hepatitis, water-borne diseases and other communicable diseases
Relevant NIF Indicator
3.8.1 (f): Percentage of TB cases successfully treated (cured plus treatment completed) among TB
cases notified to the national health authorities during a specified period
Indicator Interpretation Higher value means higher performance (+)
× 10,000
No. of functional newborn facilities (SNCU, NBSU, NBCC)
Total population of the district (2011)
× 1,000
New HIV infections
Uninfected population
× 100
No. of TB case successfully treated out of the new cases notified in the reference year
Total no. of TB cases notified (Public + Private) in the reference year
179
METADATA
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of suicide deaths reported per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Per 1,00,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through
prevention and treatment and promote mental health and well-being
Relevant Global Indicator 3.4.2: Suicide mortality rate
Relevant NIF Indicator 3.4.2. Suicide mortality rate (per 1,00,000 population)
Indicator Interpretation Higher value means lower performance (–)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of de-addiction centres (public and private) per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–24
Data Unit Per 1,00,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and
harmful use of alcohol
Relevant Global Indicator
3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and
aftercare services) for substance use disorders
Relevant NIF Indicator 3.5.1: Number of persons treated in de-addiction centres
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
First Referral Units (FRUs) per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Per 1,00,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
Indicator Interpretation Higher value means higher performance (+)
No. of suicides reported during reference year in the district
Total population (2011)
× 1,00,000
No. of de-addiction centres (public and private) in the district
Total population (2011)
× 1,00,000
No. of FRUs in the district
Total population (2011)
× 1,00,000
1802023-24NER DISTRICT SDG INDEX
GOAL 3: GOOD HEALTH AND
WELL-BEING
Total physicians, nurses and midwives per 10,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Number per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.c: Substantially increase health financing and the recruitment, development, training and
retention of the health workforce in developing countries, especially in least developed countries
and small island developing States
Relevant Global Indicator 3.c.1: Health worker density and distribution
Relevant NIF Indicator 3.c.1: Health worker density
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Average annual dropout rate at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education - Plus (UDISE+)]
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and
secondary education leading to relevant and effective learning outcomes
Indicator Interpretation Higher value means lower performance (–)
GOAL 4: QUALITY EDUCATION Ratio of female to male enrolment at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education - Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Ratio
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.5: By 2030, eliminate gender disparities in education and ensure equal access to all levels of
education and vocational training for the vulnerable, including persons with disabilities, indigenous
peoples and children in vulnerable situations
Relevant Global Indicator
4.5.1: Parity indices (female/male, rural/urban, bottom/top wealth quintile and others such
as disability status, indigenous peoples and conflict-affected, as data become available) for all
education indicators on this list that can be disaggregated
Relevant NIF Indicator 4.5.1: Gender Parity Indices (GPI) for primary/secondary/higher secondary/tertiary education
Indicator Interpretation Higher value means higher performance (+)
No. of (Registered doctors + AYUSH practitioners + ANM +
Registered nurses and midwives + Lady health volunteers)
Total population (2011)
× 10,000
Female enrolment at secondary level
Male enrolment at secondary level
181
METADATA
GOAL 4: QUALITY EDUCATION
Percentage of students in Grade 8 achieving at least a minimum proficiency level in terms of
nationally defined learning outcomes to be attained at the end of the grade
Indicator Data Source
Ministry of Education
[National Achievement Survey, 2021]
Computation Approach
Data Period (Year) 2021
Data Unit Percentage
Districts Covered 116
Data Periodicity 3 Years
Relevant Global Target
4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and
secondary education leading to relevant and effective learning outcomes
Relevant Global Indicator
4.1.1: Proportion of children and young people (a) in grades 2/3; (b) at the end of primary; and (c)
at the end of lower secondary achieving at least a minimum proficiency level in (i) reading and (ii)
mathematics, by sex
Relevant NIF Indicator
4.1.1: Percentage of students in grade 3, 5, 8 and 10 achieving at least a minimum proficiency
level in terms of nationally defined learning outcomes to be attained by pupils at the end of each
of above grades
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Percentage of schools with computers available
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.a: Build and upgrade education facilities that are child, disability and gender sensitive and
provide safe, non-violent, inclusive and effective learning environments for all
Relevant Global Indicator 4.a.1: Proportion of schools offering basic services, by type of service
Relevant NIF Indicator 4.a.1: Proportion of schools with access to: (b) computers for pedagogical purposes
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Percentage of schools with access to electricity
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.a: Build and upgrade education facilities that are child, disability and gender sensitive and
provide safe, non-violent, inclusive and effective learning environments for all
Relevant Global Indicator 4.a.1: Proportion of schools offering basic services, by type of service
Relevant NIF Indicator 4.a.1: Proportion of schools with access to: (a) electricity
Indicator Interpretation Higher value means higher performance (+)
No. of students of class 8 achieving desired score as per NAS assessment
standards in Maths & Language
Total no. of students of class 8 who participated in NAS
× 100
No. of schools with computers available
Total no. of schools
× 100
No. of schools with electricity
Total no. of schools
× 100
1822023-24NER DISTRICT SDG INDEX
GOAL 4: QUALITY EDUCATION Percentage of trained teachers at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
*Teachers with Basic teacher's training/B.Ed./D.El.Ed./M.Ed or equivalent (not less than two years)/Diploma/degree in special
education at secondary level
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.c: By 2030, substantially increase the supply of qualified teachers, including through
international cooperation for teacher training in developing countries, especially least developed
countries and small island developing States
Relevant Global Indicator 4.c.1: Proportion of teachers with the minimum required qualifications, by education level
Relevant NIF Indicator
4.c.1: Proportion of trained teacher, by education level (primary, upper primary, elementary,
secondary and higher secondary education), (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Pupil Teacher Ratio at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education - Plus (UDISE+)]
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Ratio
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.c: By 2030, substantially increase the supply of qualified teachers, including through
international cooperation for teacher training in developing countries, especially least developed
countries and small island developing States
Indicator Interpretation Higher value means lower performance (–)
GOAL 5: GENDER EQUALITY Crimes against women per 10,000 female population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau, Crime in India 2022]
Computation Approach
Data Period (Year) 2022
Data Unit Number of cases per 10,000 female population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
5.2: Eliminate all forms of violence against all women and girls in the public and private spheres,
including trafficking and sexual and other types of exploitation
Relevant NIF Indicator 5.1.4: Rate of crimes against women per 1,00,000 female population
Indicator Interpretation Higher value means lower performance (–)
No. of trained teachers* at secondary level
Total no. of teachers at secondary level
× 100
No. of cases registered under crime against women during reference year
Female population in the district (Census 2011)
× 10,000
183
METADATA
GOAL 5: GENDER EQUALITY Sex ratio at birth
Indicator Data Source Ministry of Health and Family Welfare [Health Management Information System]
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Female per 1,000 males
Districts Covered 119
Data Periodicity Annual
Relevant Global Target 5.1: End all forms of discrimination against all women and girls everywhere
Relevant NIF Indicator 5.1.3: Sex Ratio at Birth (per 1,000 male live births)
Indicator Interpretation Higher value means higher performance (+)
GOAL 5: GENDER EQUALITY Percentage of sexual crimes against women to total crimes against women
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
5.2: Eliminate all forms of violence against all women and girls in the public and private spheres,
including trafficking and sexual and other types of exploitation
Relevant Global Indicator
5.2.2: Proportion of women and girls aged 15 years and older subjected to sexual violence by
persons other than an intimate partner in the previous 12 months, by age and place of occurrence
Relevant NIF Indicator
5.2.2: Proportion of women and girls aged 18–49 years subjected to sexual violence by persons
other than an intimate partner in the previous 12 months
5.2.3: Per lakh women who have experienced sexual crimes during the year
(per 1,00,000 females)
Indicator Interpretation Higher value means lower performance (-)
GOAL 5: GENDER EQUALITY Unmet need for family planning for currently married women aged 15–49 years
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
5.6: Ensure universal access to sexual and reproductive health and reproductive rights as agreed
in accordance with the Programme of Action of the International Conference on Population and
Development and the Beijing Platform for Action and the outcome documents of their
review conferences
Relevant NIF Indicator
5.6.1: Unmet need for family planning for currently married women aged 15–49 years (in
percentage)
Indicator Interpretation Higher value means lower performance (–)
No. of cases registered under sexual crime against women during reference year
No. of cases registered under crime against women during reference year
× 100
1842023-24NER DISTRICT SDG INDEX
GOAL 5: GENDER EQUALITY Exclusive women Self-Help Groups (SHGs) in bank-linked SHGs
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 120
Data Periodicity Annual
Relevant Global Target
5.a: Undertake reforms to give women equal rights to economic resources, as well as access to
ownership and control over land and other forms of property, financial services, inheritance and
natural resources, in accordance with national laws
Relevant NIF Indicator 5.a.5: Exclusive women SHGs in bank-linked SHGs (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of rural population using an improved drinking water source
Indicator Data Source Department of Drinking Water and Sanitation, Ministry of Jal Shakti
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 6.1: By 2030, achieve universal and equitable access to safe and affordable drinking water for all
Relevant Global Indicator 6.1.1: Proportion of population using safely managed drinking water services
Relevant NIF Indicator 6.1.2: Percentage of population using an improved drinking water source (Rural)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of rural population getting safe and adequate drinking water within premises
through Piped Water Supply (PWS)
Indicator Data Source Department of Drinking Water and Sanitation, Ministry of Jal Shakti
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 6.1: By 2030, achieve universal and equitable access to safe and affordable drinking water for all
Relevant Global Indicator 6.1.1: Proportion of population using safely managed drinking water services
Relevant NIF Indicator
6.1.1: Percentage of households getting safe and adequate drinking water within premises
through Piped Water Supply (PWS)
Indicator Interpretation Higher value means higher performance (+)
No. of bank-linked women SHGs
Total no. of SHGs in the district
× 100
Total population having quality affected drinking water
Total population (Census 2011)
× 1001–((
Population having PWS (fully covered)
Total population (Census 2011)
× 100
185
METADATA
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of population living in households that use an improved sanitation facility
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant Global Indicator 6.2.1: Proportion of population using (a) safely managed sanitation services
Relevant NIF Indicator 6.2.1: Proportion of households having access to toilet facility (Urban & Rural), (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of individual household toilets constructed against target (SBM(G))
Indicator Data Source State
Computation Approach
Data Period (Year) 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant Global Indicator 6.2.1: Proportion of population using (a) safely managed sanitation services
Relevant NIF Indicator 6.2.1: Proportion of households having access to toilet facility (Urban & Rural), (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of schools with functional toilet facility for girls
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant NIF Indicator 6.2.3: Proportion of schools with separate toilet facility for girls
Indicator Interpretation Higher value means higher performance (+)
Number of toilets constructed under SBM(G) during the reference year covered
Number of toilets targeted to be constructed under SBM(G) during the reference year
× 100
No. of school with functional toilet facility for girls
Total no. of schools in the district
× 100
1862023-24NER DISTRICT SDG INDEX
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of GPs/villages verified as ODF (SBM(G)) in the district
Indicator Data Source
Ministry of Jal Shakti
[Swachh Bharat Mission Gramin Dashboard]
Computation Approach Directly from data source
Data Period (Year) As on 31 March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant NIF Indicator 6.2.2: Percentage of Districts achieving Open Defecation Free (ODF) target
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Stage of groundwater extraction (%)
Indicator Data Source
Central Ground Water Board, Ministry of Jal Shakti
[National Compilation on Dynamic Ground Water Resources of India]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Percentage
Districts Covered 86
Data Periodicity Non-periodic
Relevant Global Target
6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure
sustainable withdrawals and supply of fresh-water to address water scarcity and substantially
reduce the number of people suffering from water scarcity
Relevant Global Indicator
6.4.2: Level of water stress: freshwater withdrawal as a proportion of available
freshwater resources
Relevant NIF Indicator 6.4.2: Percentage ground water withdrawal against availability
Indicator Interpretation Higher value means lower performance (–)
GOAL 7: AFFORDABLE AND CLEAN
ENERGY
Percentage of villages/GPs electrified
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 7.1: By 2030, ensure universal access to affordable, reliable and modern energy services
Relevant Global Indicator 7.1.1: Proportion of population with access to electricity
Relevant NIF Indicator 7.1.1: Percentage of households electrified
Indicator Interpretation Higher value means higher performance (+)
No. of village/GPs electrified
Total no. of villages/GPs
× 100
187
METADATA
GOAL 7: AFFORDABLE AND CLEAN
ENERGY
Percentage of households using clean fuel for cooking
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target 7.1: By 2030, ensure universal access to affordable, reliable and modern energy services
Relevant Global Indicator 7.1.2: Proportion of population with primary reliance on clean fuels and technology
Relevant NIF Indicator 7.1.2: Percentage of household using clean cooking fuel
Indicator Interpretation Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Percentage of loans disbursed to MSMEs against sanctioned
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.3: Promote development-oriented policies that support productive activities, decent job creation,
entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-,
small- and medium-sized enterprises, including through access to financial services
Relevant NIF Indicator 8.3.3: Outstanding Credit to MSME (in INR crore)
Indicator Interpretation Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Number of victims of human trafficking per 10,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and
human trafficking and secure the prohibition and elimination of the worst forms of child labour,
including recruitment and use of child soldiers, and by 2025 end child labour in all its forms
Relevant NIF Indicator 8.7.1: Human trafficking cases per 10,00,000 population
Indicator Interpretation Higher value means lower performance (–)
No. of loans disbursed to MSMEs
No. of loans sanctioned to MSMEs
× 100
Total no. of victims trafficked (male and female)
Total population (Census 2011)
× 10,000
1882023-24NER DISTRICT SDG INDEX
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Percentage of households covered with a bank account under Pradhan Mantri Jan Dhan Yojana
(PMJDY) against target
Indicator Data Source
Ministry of Finance
[Pradhan Mantri Jan Dhan Yojana – District-wise Household Report]
Computation Approach Directly from data source
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 94
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all
Relevant Global Indicator
8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution
or with a mobile money service provider
Relevant NIF Indicator
8.10.2: Number of accounts (including deposit and credit accounts) of scheduled commercial banks
per 1,000 population
Indicator Interpretation Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Number of bank branches including Business Correspondents (BCs) in Urban, Semi-urban and Rural
areas per 10,000 population
Indicator Data Source State
Computation
Approach
Data Period (Year) As on 31st March 2024
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage
and expand access to banking, insurance and financial services for all
Relevant Global Indicator 8.10.1: (a) Number of commercial bank branches per 10,000 adults
Relevant NIF Indicator 8.10.1: (a) Number of banking outlets per 100,000 population
Indicator
Interpretation
Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Automated Teller Machines (ATMs) per 10,000 population
Indicator Data Source Reserve Bank of India [Database on Indian Economy]
Computation Approach
Data Period (Year) As on31st March 2024
Data Unit Per 10,000 population
Districts Covered 114
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all
Relevant Global Indicator 8.10.1: (b) Number of ATMs per 100,000 adults
Relevant NIF Indicator 8.10.1: (b) ATMs per 100,000 population
Indicator Interpretation Higher value means higher performance (+)
No. of bank branches including BCs in Urban, Semi-urban and Rural areas
Total population (Census 2011)
× 10,000
Total no. of ATMs
Total population (Census 2011)
× 10,000
189
METADATA
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Percentage of women account holders in Pradhan Mantri Jan Dhan Yojana (PMJDY)
Indicator Data Source Ministry of Finance [Pradhan Mantri Jan Dhan Yojana –District wise Household Report]
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all
Relevant Global Indicator
8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution
or with a mobile money service provider
Relevant NIF Indicator 5.a.7: Percentage of women having an account at a formal financial institution
Indicator Interpretation Higher value means higher performance (+)
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Percentage of habitations with access to all weather roads under PMGSY and other State schemes
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.1: Develop quality, reliable, sustainable and resilient infrastruc-ture, including regional and
transborder infrastructure, to support economic development and human well-being, with a focus on
affordable and equitable access for all
Relevant Global Indicator 9.1.1: Proportion of the rural population who live within 2 km of an all-season road
Relevant NIF Indicator 9.1.1: Proportion of the rural population who live within 2 km of an all-season road
Indicator Interpretation Higher value means higher performance (+)
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Surfaced road as a percentage of total road length
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.1: Develop quality, reliable, sustainable and resilient infrastructure, including regional and
transborder infrastructure, to support economic development and human well-being, with a focus on
affordable and equitable access for all
Indicator Interpretation Higher value means higher performance (+)
PMJDY accounts opened by women
Total no. of PMJDY accounts
× 100
No. of habitations with access to all weather roads under PMGSY and other State schemes
Total no. of habitations
× 100
Total length of surfaced road in the district
Total length of road in the district
× 100
1902023-24NER DISTRICT SDG INDEX
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Percentage of GPs/villages with internet connection (broadband or cellular)
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.c: Significantly increase access to information and communications technology and strive to provide
universal and affordable access to the Internet in least developed countries by 2020
Relevant Global Indicator 9.c.1: Proportion of population covered by a mobile network, by technology
Relevant NIF Indicator 9.c.1: Number of Internet Subscription as percentage of total population
Indicator Interpretation Higher value means higher performance (+)
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Percentage of villages covered by a mobile network
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.c: Significantly increase access to information and communications technology and strive to provide
universal and affordable access to the Internet in least developed countries by 2020
Relevant Global Indicator 9.c.1: Proportion of population covered by a mobile network, by technology
Indicator Interpretation Higher value means higher performance (+)
GOAL 10: REDUCED INEQUALI-
TIES
Percentage of women representatives in PRIs, ULBs, District Autonomous Councils, VCs, VECs
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 105
Data Periodicity Annual
Relevant Global Target
10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective
of age, sex, disability, race, ethnicity, origin, religion or economic or other status
Relevant NIF Indicator 10.2.2: Proportion of seats held by women in (a) national parliaments and (b) local governments,
Indicator Interpretation Higher value means higher performance (+)
No. of GPs/villages with internet connection (broadband or cellular)
Total no. of GPs/villages
× 100
No. of villages covered by a mobile network
Total no. of villages
× 100
No. of women representatives in PRIs, ULBs, District Autonomous Councils, VCs, VECs
Total no. of representatives in PRIs, ULBs, District Autonomous Councils, VCs, VECs
× 100
191
METADATA
GOAL 10: REDUCED IN-
EQUALITIES
Women offered employment as a percentage of total employment demanded by women under MGNREGA
Indicator Data Source Ministry of Rural Development [MGNREGA MIS Report]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory
laws, policies and practices and promoting appropriate legislation, policies and action in this regard
Indicator InterpretationHigher value means higher performance (+)
GOAL 10: REDUCED IN-
EQUALITIES
Persons with Disabilities (PwDs) offered employment as a percentage of total employment demanded by
PwDs under MGNREGA
Indicator Data Source Ministry of Rural Development [MGNREGA MIS Report]
Computation
Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory
laws, policies and practices and promoting appropriate legislation, policies and action in this regard
Indicator
Interpretation
Higher value means higher performance (+)
GOAL 11: SUSTAINABLE
CITIES AND COMMUNITIES
Houses completed under Pradhan Mantri Awas Yojana (PMAY) and/or other schemes as a
percentage of net demand assessment (Urban)
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.1: By 2030, ensure access for all to adequate, safe and affordable housing and basic services and
upgrade slums
Indicator InterpretationHigher value means higher performance (+)
No. of women who were offered employment under MGNREGA during reference period
No. of women who demanded employment under MGNREGA during reference period
× 100
No. of persons with disability who were offered employment under MGNREGA during reference period
No. of persons with disability who demanded employment under MGNREGA during reference period
× 100
No. of houses constructed and completed under PMAY (Urban) and related State schemes
No. of houses sanctioned for construction under PMAY (Urban) and related State schemes
× 100
1922023-24NER DISTRICT SDG INDEX
GOAL 11: SUSTAINABLE
CITIES AND COMMUNITIES
Deaths due to road accidents per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Per 1,00,000 population
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.2: By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all,
improving road safety, notably by expanding public transport, with special attention to the needs of those in
vulnerable situations, women, children, persons with disabilities and older persons
3.6: By 2020, halve the number of global deaths and injuries from road traffic accidents
Relevant Global Indicator3.6.1: Death rate due to road traffic injuries
Relevant NIF Indicator 3.6.1 & 11.2.2: People killed/injured in road accidents (per 100,000 population)
Indicator InterpretationHigher value means lower performance (-)
GOAL 11: SUSTAINABLE
CITIES AND COMMUNITIES
Percentage of wards with waste collection
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special
attention to air quality and municipal and other waste management
Relevant Global Indicator
11.6.1: Proportion of municipal solid waste collected and managed in controlled facilities out of total
municipal waste generated, by cities
Relevant NIF Indicator 11.6.2: Percentage of wards with 100% door-to-door waste collection
Indicator InterpretationHigher value means higher performance (+)
Deaths due to road traffic accidents during reference year
Total population of the district (census 2011)
× 1,00,000
Total no. of wards with waste collection
Total no. of wards
× 100
193
METADATA
GOAL 11: SUSTAINABLE CITIES AND
COMMUNITIES
Percentage of individual household toilets constructed against target (SBM(U))
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.1: By 2030, ensure access for all to adequate, safe and affordable housing and basic services
and upgrade slums
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant Global Indicator 6.2.1: Proportion of population using (a) safely managed sanitation services
Relevant NIF Indicator 6.2.1: Proportion of households having access to toilet facility (Urban and Rural)
Indicator Interpretation Higher value means higher performance (+)
GOAL 11: SUSTAINABLE CITIES AND
COMMUNITIES
Percentage of Municipal Solid Waste (MSW) treated out of total MSW generated
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying
special attention to air quality and municipal and other waste management
Relevant Global Indicator
11.6.1: Proportion of municipal solid waste collected and managed in controlled facilities out of
total municipal waste generated, by cities
Relevant NIF Indicator 11.6.1: Percentage of waste processed
Indicator Interpretation Higher value means higher performance (+)
No. of IHHL units constructed
No. of IHHL units targeted to be constructed
× 100
Total MSW treated (tonnes/day)
Total MSW generated (tonnes/day)
× 100
1942023-24NER DISTRICT SDG INDEX
GOAL 12: SUSTAINABLE
CONSUMPTION AND PRODUCTION
Area under jhum cultivation as a percentage of total area under agriculture
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 92
Data Periodicity Annual
Relevant Global Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources
Indicator Interpretation Higher value means lower performance (–)
GOAL 12: SUSTAINABLE
CONSUMPTION AND PRODUCTION
Percentage of area under micro/minor irrigation in the district
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources
Indicator Interpretation Higher value means higher performance (+)
GOAL 12: SUSTAINABLE
CONSUMPTION AND PRODUCTION
Plastic waste generated per 10,000 population (tonnes/annum)
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Tonnes per 10,000 population per annum
Districts Covered 111
Data Periodicity Annual
Relevant Global Target
12.5: By 2030, substantially reduce waste generation through prevention, reduction, recycling
and reuse
Indicator Interpretation Higher value means lower performance (–)
Area under Jhum cultivation
Area under agriculture
× 100
Area under micro/minor irrigation in the district
Area under agriculture
× 100
Quantity of plastic waste generated during the reference year
Total population of the district (Census 2011)
× 10,000
195
METADATA
GOAL 13: CLIMATE ACTION Number of human lives lost due to natural calamity per 10,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2023
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters
in all countries
Relevant Global Indicator
13.1.1: Number of deaths, missing persons and directly affected persons attributed to disasters
per 1,00,000 population
Relevant NIF Indicator
13.1.1: Number of deaths, missing persons and directly affected persons attributed to disasters
per 1,00,000 population
Indicator Interpretation Higher value means lower performance (–)
GOAL 13: CLIMATE ACTION Change in forest area
Indicator Data Source Ministry of Environment Forest & Climate Change [Forest Survey of India 2023]
Computation Approach Directly from data source
Data Period (Year) 2021-23
Data Unit Square Kilometre
Districts Covered 119
Data Periodicity 2 years
Relevant Global Target
13.2: Integrate climate change measures into national policies, strategies and planning
15.2: By 2020, promote the implementation of sustainable management of all types of forests,
halt deforestation, restore degraded forests and substantially increase afforestation and
reforestation globally
Relevant NIF Indicator 15.2.1: Progress towards sustainable forest management
Indicator Interpretation
Districts with an increase/no change in area under forests have been awarded a score of 100
while districts with a decrease in area under forests have been assigned a score of 0
GOAL 13: CLIMATE ACTION Area under watershed management as a percentage of total geographical area
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters
in all countries
Indicator Interpretation Higher value means higher performance (+)
No. of deaths due to natural calamities during the reference year
Total population of the district (Census 2011)
× 10,000
Area covered under integrated watershed management in the district (sq. km)
Total geographical area of the district (sq. km)
× 100
1962023-24NER DISTRICT SDG INDEX
GOAL 15: LIFE ON LAND Forest cover as a percentage of total geographical area
Indicator Data Source Ministry of Environment, Forest & Climate Change [Forest Survey of India 2023]
Computation Approach Directly from data source
Data Period (Year) 2023
Data Unit Percentage
Districts Covered 121
Data Periodicity 2 years
Relevant Global Target
15.1: By 2020, ensure the conservation, restoration and sustainable use of terrestrial and inland
freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands,
in line with obligations under international agreements
Relevant Global Indicator 15.1.1: Forest area as a proportion of total land area
Relevant NIF Indicator 15.1.1: Forest cover as a percentage of total geographical area
Indicator Interpretation Higher value means higher performance (+)
GOAL 15: LIFE ON LAND Percentage of wasteland over total geographical area
Indicator Data Source
Department of Land Resources, Ministry of Rural Development & National Remote Sensing Centre,
Indian Space Research Organisation [Wastelands Atlas of India 2019]
Computation Approach
Total area under wasteland in the district
Total geographical area of the district
× 100
Total area under wasteland includes the following categories*:
Land with Dense Scrub
Land with Open Scrub
Shifting Cultivation - Current Jhum
Shifting Cultivation - Abandoned Jhum
Under-utilised/degraded forest (Scrub domain)
Under-utilised/degraded forest (Agriculture)
Degraded pastures/grazing land
Degraded land under plantation crop
Mining wastelands
Industrial wastelands
*Those categories (as classified in the Wasteland Atlas) which are predominantly due to human interventions and/or those that are
commonly found in the 8 States of the NER have been considered to estimate the numerator.
Data Period (Year) 2015-16
Data Unit Percentage
Districts Covered 90
Data Periodicity Non-periodic
Relevant Global Target
15.3: By 2030, combat desertification, restore degraded land and soil, including land affected by
desertification, drought and floods, and strive to achieve a land degradation-neutral world
Relevant Global Indicator 15.3.1: Proportion of land that is degraded over total land area
Relevant NIF Indicator 15.3.1: Proportion of land that is degraded over total land area
Indicator Interpretation Higher value means lower performance (–)
197
METADATA
GOAL 15: LIFE ON LAND Number of wildlife crime cases reported per 1,000 sq. km of forest area
Indicator Data Source State
Computation Approach
Data Period (Year) 2023
Data Unit Number per 1,000 sq. km of forest area
Districts Covered 115
Data Periodicity Annual
Relevant Global Target
15.7: Take urgent action to end poaching and trafficking of protected species of flora and fauna
and address both demand and supply of illegal wildlife products
15.c: Enhance global support for efforts to combat poaching and trafficking of protected species,
including by increasing the capacity of local communities to pursue sustainable
livelihood opportunities
Relevant Global Indicator 15.7.1 & 15.c.1: Proportion of traded wildlife that was poached or illicitly trafficked
Relevant NIF Indicator 15.7.1 & 15.c.1: Number of cases registered under the Wildlife Protection Act, 1972
Indicator Interpretation Higher value means lower performance (–)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Reported murders per 10,000 population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau – Crime in India 2022]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 16.1: Significantly reduce all forms of violence and related death rates everywhere
Relevant Global Indicator 16.1.1: Number of victims of intentional homicide per 1,00,000 population, by sex and age
Relevant NIF Indicator 16.1.1: Number of victims of intentional homicide per 1,00,000 population
Indicator Interpretation Higher value means lower performance (−)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Cognizable crimes against children per 10,000 population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau – Crime in India 2022]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Per 10,000 child population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of children
Relevant NIF Indicator 16.2.1: Proportion of crime committed against children during the year (per lakh children)
Indicator Interpretation Higher value means lower performance (–)
No. of wildlife crime cases reported in the district during the reference period
Total forest area in the district (sq. km)
× 1,000
1982023-24NER DISTRICT SDG INDEX
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Number of missing children per 10,000 population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau – Crime in India 2022]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Per 10,000 child population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of children
Relevant Global Indicator
16.2.2: Number of victims of human trafficking per 1,00,000 population by sex, age and form of
exploitation
Relevant NIF Indicator 8.7.2: Number of missing children
Indicator Interpretation Higher value means lower performance (–)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Ratio of working strength to sanctioned strength of Judges (District & Subordinate courts)
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Ratio
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
16.3: Promote the rule of law at the national and international levels and ensure equal access to
justice for all
Relevant NIF Indicator 16.3.3: Number of Judges (all levels) per lakh population
Indicator Interpretation Higher value means higher performance (+)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Common Service Centres (CSCs) providing online services per 10,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Per 10,000 population
Districts Covered 120
Data Periodicity Annual
Relevant Global Target 16.6: Develop effective, accountable and transparent institutions at all levels
Relevant NIF Indicator 16.6.3: Number of government services provided online to citizens
Indicator Interpretation Higher value means higher performance (+)
Working strength of judges in the district court and sub-ordinate courts
Sanctioned strength of judges in the district court and sub-ordinate courts
No. of CSCs in the district
Total population of the district (Census 2011)
× 10,000
199
METADATA
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Percentage of births registered
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target 16.9: By 2030, provide legal identity for all, including birth registration
Relevant Global Indicator
16.9.1: Proportion of children under 5 years of age whose births have been registered with a
civil authority, by age
Relevant NIF Indicator 16.9.1: Percentage of births registered
Indicator Interpretation Higher value means higher performance (+)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Percentage of population covered under Aadhaar
Indicator Data Source Unique Identification Authority of India Dashboard
Computation Approach Directly from data source
Data Period (Year) Data accessed as on July 2024
Data Unit Percentage
Districts Covered 82
Data Periodicity Live data
Relevant Global Target 16.9: By 2030, provide legal identity for all, including birth registration
Relevant NIF Indicator 16.9.2: Proportion of population covered under Aadhaar
Indicator Interpretation Higher value means higher performance (+)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Percentage of deaths registered
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target 16.9: By 2030, provide legal identity for all, including birth registration
Relevant Global Indicator
17.19.2: Proportion of countries that (b) have achieved 100 percent birth registration and 80
percent death registration
Indicator Interpretation Higher value means higher performance (+)
2002023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of bene -
ficiaries
covered
under NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employ -
ment as a
percentage
of persons
who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses
completed
against
sanctioned
(rural +ur -
ban) under
PMAY and
related State
schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds
empanelled
under PM -
JAY or re -
lated State
schemes
per 10,000
eligible
population
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employment
as a per -
centage of
persons who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Arunachal Pradesh
Anjaw100.0013.0999.981.209.17100.0017.58.2310098991910013353
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang100.0014.3999.972.1742.4299.7140.510.49100959924210037460
Dibang Valley100.0010.1199.9914.294.90100.0028.733.62100100100145100251657
East Kameng100.0022.05100.005.470.0099.9425.112.00100761005010021551
East Siang100.008.11100.008.3396.00100.0030.530.49100100100896100271468
Kamle100.00Null99.991.1921.4399.23Null2.95100Null10012199Null054
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi100.0018.91100.0020.3669.0598.9724.03.331008410020699920062
Kurung Kumey100.0011.1499.988.8560.5899.0713.414.01100100100961998660
Leparada100.00Null100.007.749.2099.23Null20.16100Null1008999Null954
Lohit100.0012.39100.0014.7831.25100.0031.915.24100100100153110028660
Longding100.0020.9799.980.003.8797.4223.87.9510079100049719350
Lower Dibang Valley100.009.0899.998.9421.5199.5636.8
15.8710010010092210033759
Lower Siang100.00Null100.007.5185.1099.83Null8.44100Null100885100Null366
Lower Subansiri100.006.3995.7712.11117.7299.8424.519.9410010001210010020955
Namsai100.0022.1199.997.326.8299.2530.912.4810076100779927553
Pakke Kessang100.00Null100.008.370.00100.00Null16.18100Null10080100Null753
Papum Pare100.0013.7699.993.9933.1999.7026.957.2210097100433100232860
Shi Yomi100.00Null100.004.320.0099.68Null6.18100Null10040100Null251
Siang100.009.1599.894.1384.3885.6126.127.061001009848486221263
Tawang100.008.4699.932.9577.33100.0033.517.631001009837710030864
Tirap100.0014.7899.981.3666.6799.7530.84.51100949916710027161
Upper Siang100.008.7499.960.7589.0899.2734.616.98100100991899931766
Upper Subansiri100.0019.71100.003.7226.2899.3521.55.69100821004269917154
West Kameng100.004.7499.937.2373.61100.0038.315.811001009877410035765
West Siang100.0013.8599.939.5545.9899.6626.618.861009698104610022860
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa94.1115.6099.8918.3247.9681.4369.04.0557929718488167158
Barpeta94.6219.1299.9239.8770.7898.0058.912.1761839840719857564
Biswanath88.5022.0999.9134.7466.1778.6268.47.1516769835667967255
Bongaigaon92.8117.3999.9531.7269.3896.5157.612.9947889932699755561
201
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of bene -
ficiaries
covered
under NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employ -
ment as a
percentage
of persons
who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses
completed
against
sanctioned
(rural +ur -
ban) under
PMAY and
related State
schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds
empanelled
under PM -
JAY or re -
lated State
schemes
per 10,000
eligible
population
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employment
as a per -
centage of
persons who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Cachar92.6030.5899.8444.4367.4389.7657.922.77465596446790551058
Charaideo92.4620.1099.9740.6478.3192.9064.94.1745819941789363163
Chirang94.2216.7999.8840.1584.8382.0561.54.0458899740858259164
Darrang92.0723.6599.9734.7946.2796.7853.78.4242729935469751356
Dhemaji93.6313.7399.9938.4846.3578.5666.89.53539710038467965360
Dhubri94.1726.0299.9135.9449.7196.3859.411.7857669836509657558
Dibrugarh90.7212.2699.9448.3677.9791.2858.853.333210099487891562666
Dima Hasao90.0213.6299.6922.1760.3284.1461.925.27279793226084601257
Goalpara92.2718.3499.8844.0951.9394.4171.112.6943859744529469561
Golaghat91.1914.6099.9640.1560.0282.7969.315.4035959940608368661
Hailakandi94.6836.2299.9237.7672.7891.0553.65.3761419838739151157
Hojai93.6314.1399.8944.7772.0593.2967.417.4953969745729366766
Jorhat92.0711.4999.8543.3665.5386.1460.116.83421009643668658762
Kamrup92.5012.7199.9637.2158.0593.9647.018.81
45999937589444861
Kamrup Metropolitan88.495.6399.8934.1146.6967.1245.5156.821610097344767427960
Karbi Anglong91.5916.2099.9841.9067.6589.3654.128.513891100426889511361
Karimganj93.0632.9399.9935.8180.4291.4464.49.55494910036809162359
Kokrajhar92.2018.9299.9933.4576.4488.8450.217.01438410033768947760
Lakhimpur91.8314.0699.9240.5669.4083.2867.015.4940969841698365662
Majuli91.7914.4199.9347.61100.9078.5260.88.67409598481007959365
Morigaon94.4922.4699.9630.8875.5787.1462.54.4260759931768760161
Nagaon93.5820.8499.8340.1664.1893.6459.414.2553799640649457661
Nalbari93.2711.2499.9639.3591.0990.7052.518.22511009939919150866
Sivasagar92.4510.2899.9743.1989.2485.2260.712.41451009943898558566
Sonitpur88.3219.9499.9139.2492.9685.1166.922.03148198399385651061
South Salmara-Mankachar95.6928.2499.7414.9382.5497.8268.23.6868619415839866061
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia91.2517.6699.9737.8362.5082.8060.012.9536879938638358559
Udalguri92.4719.1699.8625.8471.4074.9470.66.0545839726717569258
West Karbi Anglong86.3724.0999.8834.0630.7580.0963.112.710719734318061547
2022023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
men-
sional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual member
covered by a
health scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
Percentage
of bene -
ficiaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
mensional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percent -
age of
Self-
Help
Groups
(SHGs)
provided
credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual mem -
ber covered
by a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Manipur
Bishnupur100.006.9199.9750.9773.572.699.355.71100100995174342757
Chandel100.0014.7499.511.327.7817.8216.1750.85100948818181110053
Churachandpur100.0015.3599.9716.1128.8811.7218.21928.3510093991629121410058
Imphal East100.005.1999.9297.4370.988.357.0548.901001009897718210072
Imphal West100.002.12100.009.0198.688.3015.7516.6010010010099981110066
Jiribam100.00Null100.0076.9216.281.54Null2906.98100Null10077162Null10066
Kakching100.00Null99.9828.4473.041.26Null688.51100Null9928731Null10067
Kamjong100.00Null99.903.603.40NullNull369.69100Null9843NullNull10061
Kangpokpi100.00Null99.8114.2921.720.00Null166.26100Null9614220Null8453
Noney100.00Null99.6721.112.34NullNull322.06100Null92212NullNull10063
Pherzawl100.00Null98.990.001.7310.93Null1302.08100Null760211Null10048
Senapati100.0015.6099.9920.008.820.0015.4485.271009210020901110054
Tamenglong100.0018.50100.008.283.342.9716.8493.10100851008331210051
Tengnoupal100.00Null99.8434.208.3012.22Null404.17
100Null9634812Null10059
Thoubal100.007.4699.9970.3386.2519.3519.1206.601001001007086191410074
Ukhrul100.0017.8799.9540.3211.69Null17.0632.4110086994012Null1210064
Meghalaya
East Garo Hills100.0014.9699.9234.75166.7638.0771.925.5810094983510038701268
East Jaintia Hills100.0043.79100.0059.6673.0227.5974.116.191002210060732873758
East Khasi Hills100.0024.10100.0056.9572.5023.9047.171.6610071100577224443563
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
North Garo Hills100.0013.2699.9640.7242.2629.1660.811.67100989941422959459
Ri Bhoi100.0031.6799.9576.46113.8634.2866.820.131005299761003465967
South Garo Hills100.009.77100.0058.1614.0312.6479.520.4810010010058141378959
South West Garo Hills100.0018.2799.9841.7495.6722.9775.112.361008510042962374565
South West Khasi Hills100.0040.9899.9964.26216.4437.5772.319.5210029100641003871964
West Garo Hills100.008.0099.9837.8947.8830.1777.930.9710010099384830771463
West Jaintia Hills100.0052.0899.9974.53236.3134.4765.626.3510011007510034641261
West Khasi Hills100.0052.4899.9869.716.1747.1560.121.7910009970647581049
Mizoram
Aizawl100.000.87100.007.7459.5595.6537.539.2510010010086096341964
Champhai100.001.5199.9016.5235.6479.4064.915.241001009817367963662
Hnahthial100.00Null100.004.170.0083.73Null141.19100Null1004084Null7160
Khawzawl100.00Null100.0015.1416.9859.66Null160.43100Null100151760Null8162
Kolasib100.005.2599.9812.7222.7995.1861.117.2710010010013239559762
Lawngtlai100.0021.63100.005.4211.9880.0231.323.651007710051280271152
203
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
men-
sional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual member
covered by a
health scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
Percentage
of bene -
ficiaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
mensional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percent -
age of
Self-
Help
Groups
(SHGs)
provided
credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual mem -
ber covered
by a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Lunglei100.005.1599.984.8718.2193.0146.522.911001009951893431059
Mamit100.009.29100.0012.8733.7472.5561.713.6510010010013347360661
Saitual100.00Null100.0019.8238.3975.29Null216.88100Null100203875Null10072
Serchhip99.123.3099.9916.1846.7482.9158.821.159410010016478356963
Siaha99.926.90100.0010.9449.5889.5144.228.9199100100115090411363
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur100.007.2399.3592.54104.9819.865.780.0610010085931002004067
Kiphire100.0028.1999.3095.55100.0051.238.841.651006183961005142064
Kohima100.006.5099.65100.00124.1413.3826.782.451001009210010013234171
Longleng100.0026.9099.9196.6295.617.6638.328.08100649897968351364
Mokokchung100.007.2299.93100.00146.9087.2622.347.341001009810010087182378
Mon100.0022.9599.8585.5475.4359.3539.321.591007496867559361067
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNull
NullNullNullNullNullNullNullNull*
Peren100.0017.4698.8577.2079.9012.985.434.67100877377801301656
Phek100.0017.2899.3096.33100.8011.5924.932.0710088839610012211564
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang100.0029.2199.89100.0078.3762.1422.038.1210058981007862181866
Wokha100.0011.99100.00100.0080.4316.0120.640.061001001001008016161966
Zunheboto100.0020.3199.9791.4477.9516.8818.122.901008099917817131061
Sikkim
Gangtok100.002.1299.9815.09Null96.2029.9592.121001009915Null962610077
Gyalshing100.002.7799.9919.73Null98.8819.944.5210010010020Null99152165
Mangan100.005.1799.8712.59Null100.0024.533.141001009713Null100201664
Namchi100.002.9099.9929.16Null94.8520.866.5010010010029Null95163368
Pakyong100.00Null100.0027.72Null95.74Null20.79100Null10028Null96Null967
Soreng100.00Null99.9926.28Null99.75Null4.36100Null10026Null100Null165
Tripura
Dhalai100.0021.8999.9963.3434.7294.1544.229.8910076100633594411465
Gomati100.009.06100.0071.0850.6891.9629.920.6510010010071519226969
Khowai100.0017.2799.9953.2541.5893.3944.123.1210088100534293411066
North Tripura100.0017.8599.9952.9345.1497.5928.720.061008610053459825964
Sepahijala100.0012.2799.9955.4253.2595.7031.616.3510010010055539628767
South Tripura100.0011.8999.9980.5255.3190.2237.328.32100100100815590341372
Unakoti100.0024.9299.9968.9950.5898.0028.020.541006910069519824965
West Tripura100.006.0099.9958.0265.2494.9828.184.79100100100586595244273
Target10012.43100.00100.00100100.00100196.89100100
100100100100100100100
2042023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of Fair Price
Shop (FPS)
covered
under online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
Percentage
of Fair Price
Shop (FPS)
covered un -
der online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Arunachal Pradesh
Anjaw100.00100.0077.8423.616.019.757.11683.893705.05100100751007310047272272
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang98.06100.0070.7026.325.060.665.33368.056139.40971006793553135783666
Dibang Valley100.00100.0094.1216.916.039.088.61800.943885.711001009310073731312366
East Kameng53.81100.0053.9335.714.213.151.72024.784502.533810048667710055372761
East Siang95.70100.0086.1024.610.332.851.52783.915573.62941008497858556603377
Kamle82.61100.0057.69NullNullNullNull2900.903681.617710053NullNullNullNull642263
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi82.61100.0062.9228.814.52.062.03005.983777.147710059867610040672270
Kurung Kumey66.67100.0053.8529.213.9Null62.43000.003651.0156100488478Null40672262
Leparada97.44100.0054.79NullNullNullNull2514.314373.249710049NullNullNullNull522665
Lohit100.00100.0088.2424.512.933.252.53199.415920.861001008798808454733579
Longding82.81100.0046.8815.813.819.138.42639.531932.3777100411007810075561171
Lower Dibang Valley90.91100.0079.89
14.39.719.651.52472.245121.2788100771008610056513076
Lower Siang74.36100.0047.39NullNullNullNull2358.634992.586610041NullNullNullNull472957
Lower Subansiri85.19100.0054.9530.78.122.152.43098.484777.398010050808910054702872
Namsai85.19100.0061.8828.717.752.659.23418.56662.6980100578670474479463
Pakke Kessang100.00100.0080.18NullNullNullNull2046.634379.1210010078NullNullNullNull382668
Papum Pare97.70100.0068.7729.715.618.653.43028.315366.889710065837410053673275
Shi Yomi92.00100.0053.96NullNullNullNull2501.283435.488910048NullNullNullNull522062
Siang74.26100.0063.0121.38.815.424.93220.385343.7966100591008810094733279
Tawang100.00100.0068.5330.49.057.489.62966.395002.20100100658187370663063
Tirap91.89100.0061.6038.616.024.148.42189.174322.868910057587310060422667
Upper Siang97.06100.0071.7930.412.022.451.02947.194673.129610068818110056652875
Upper Subansiri74.65100.0056.1836.819.237.960.43164.852704.78661005163677543711661
West Kameng89.33100.00100.0024.213.418.266.62775.305041.8086100100997910034603076
West Siang88.44100.0069.9224.516.216.845.62529.144750.008510066987310064522874
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa100.00100.0041.2541.234.065.378.62575.8311695.271001003450382216546954
Barpeta100.00100.0086.7429.826.247.663.52812.0913548.741001008583535738618073
Biswanath100.00100.0058.5142.741.045.179.82549.2213290.681001005446246114537959
Bongaigaon100.00100.0096.1346.235.351.277.22845.8512922.071001009636355018627664
205
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of Fair Price
Shop (FPS)
covered
under online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
Percentage
of Fair Price
Shop (FPS)
covered un -
der online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Cachar100.00100.0046.3328.738.244.061.82094.9713818.731001004086296341398264
Charaideo100.00100.0090.8739.034.861.669.72539.7616601.311001009057362929539866
Chirang100.00100.0016.5042.739.754.170.42715.0112335.75100100746264428587354
Darrang100.00100.0079.5242.033.151.666.82872.1112639.941001007748394933637565
Dhemaji100.00100.0067.4437.225.761.773.12176.9413281.691001006462542924427861
Dhubri100.00100.0093.4448.537.869.773.13102.6714978.671001009330301424708961
Dibrugarh100.00100.0096.5127.332.047.266.42762.6812054.571001009690425734597172
Dima Hasao100.00100.0034.2630.621.743.373.12258.6416296.441001002680626524449666
Goalpara100.00100.0098.4738.935.449.260.72949.6113992.901001009857355342658370
Golaghat100.00100.0083.0426.325.576.775.12764.5414632.76100100819354021598666
Hailakandi100.00100.0052.9842.942.458.759.52728.6315746.561001004746213544589360
Hojai100.00100.0060.2639.328.451.456.83407.3314419.931001005656494948798569
Jorhat100.00100.0076.9838.733.256.474.12911.8815206.281001007458393923649065
Kamrup100.00100.0085.4422.6
19.766.572.92959.4713682.3810010084100662024658171
Kamrup Metropolitan100.00100.0065.8925.425.056.480.42988.2014834.211001006295553913668869
Karbi Anglong100.00100.0040.3131.628.242.167.52577.7715147.701001003378496732549067
Karimganj100.00100.0081.7729.152.941.964.12050.8513836.29100100808506837388265
Kokrajhar100.00100.0026.4434.635.259.574.72120.0613083.621001001869353322407755
Lakhimpur100.00100.0030.7638.534.442.369.31962.7810865.451001002358376730356457
Majuli100.00100.0079.2635.422.2Null73.02523.8712931.75100100776761Null24527670
Morigaon100.00100.0088.5443.230.548.053.32853.5014410.951001008745455653628570
Nagaon100.00100.0099.7338.932.462.468.62515.2913193.3310010010057412831527865
Nalbari100.00100.0059.2327.526.753.271.02681.4312661.171001005489524627577567
Sivasagar100.00100.0090.7226.125.954.367.52644.5115750.141001009093544332569373
Sonitpur100.00100.0073.6736.721.947.369.42940.9310301.631001007163625729656168
South Salmara-Mankachar100.00100.0073.4538.927.937.669.63012.0113865.111001007057507629678270
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia100.00100.0091.2932.832.271.766.41805.5112559.031001009074411034317462
Udalguri100.00100.0030.7333.832.563.977.62594.0011806.951001002371412517547056
West Karbi Anglong100.00100.0039.7940.931.138.879.02523.5414336.271001003351437415528561
2062023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage of
pregnant wom -
en aged 15-49
years who
are anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Average
yield of
rice (kg/
ha)
Produc -
tivity of
fruits and
vegetables
(kg/ha)
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percent -
age of
children
under age
5 years
who are
stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage
of pregnant
women aged
15-49 years
who are anae -
mic (<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Aver -
age
yield
of rice
(kg/
ha)
Produc -
tivity of
fruits
and veg -
etables
(kg/ha)
SDG 2
Manipur
Bishnupur100.00100.0032.9215.511.739.042.41983.485260.5410010025100827369363168
Chandel100.00100.0013.4734.014.720.342.41621.359914.791001003717610069255967
Churachandpur100.00100.0027.5325.19.851.841.11208.4010859.681001001996864871136466
Imphal East100.00100.0019.5518.414.427.450.32208.8913080.3810010010100779657437773
Imphal West100.00100.0026.6215.610.239.541.81646.3912573.5010010018100857270267472
Jiribam100.00100.0010.61NullNullNullNull1528.7419490.641001000NullNullNullNull2210064
Kakching100.00100.0041.48NullNullNullNull4642.7910839.9710010035NullNullNullNull1006480
Kamjong100.00100.0015.83NullNullNullNull1517.4111494.341001006NullNullNullNull226859
Kangpokpi100.00100.0017.89NullNullNullNull1772.3712411.141001008NullNullNullNull307362
Noney100.00100.0035.16NullNullNullNull798.679397.2110010027NullNullNullNull05657
Pherzawl100.00100.0018.06NullNullNullNull1285.8411664.231001008NullNullNullNull156958
Senapati100.00100.0027.8027.312.918.348.51771.5410814.5610010019908010060306471
Tamenglong100.00100.0031.7727.119.331.437.0783.9211224.13100100249067887706668
Tengnoupal100.00100.0023.87NullNullNullNull1620.3311441.45
10010015NullNullNullNull256862
Thoubal100.00100.0026.2931.514.932.039.74561.6311236.4810010018787687731006677
Ukhrul100.00100.0026.5727.116.025.734.61528.2310433.221001001890739980226272
Meghalaya
East Garo Hills99.68100.0029.6139.726.529.128.01939.8213378.641001002155529290357969
East Jaintia Hills100.00100.0046.5549.823.646.547.22201.005071.601001004026585962433057
East Khasi Hills90.20100.0052.8044.623.843.739.01947.0112177.38871004741586474357264
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
North Garo Hills100.00100.0067.5635.615.840.830.22741.7112229.381001006466747087597277
Ri Bhoi25.00100.0064.2342.529.665.045.73369.2212465.7301006047462364787455
South Garo Hills76.62100.0031.7229.820.833.733.62174.549537.71691002483648382425667
South West Garo Hills100.00100.0049.5332.226.437.835.53345.2810163.921001004476537679776074
South West Khasi Hills100.00100.0070.9551.427.663.261.31870.1112106.561001006822502641337257
West Garo Hills51.68100.0064.1839.526.326.730.23018.029266.21361006055539787675568
West Jaintia Hills98.67100.0075.2348.728.364.654.61885.889414.23981007229492351335657
West Khasi Hills100.00100.0075.4959.031.149.656.21910.9018165.161001007304353493410061
Mizoram
Aizawl99.31100.00100.0025.39.633.444.01216.485895.389910010095868466133575
Champhai100.00100.00100.0027.213.115.738.32994.005689.78100100100907910075663483
Hnahthial100.00NullNullNullNullNullNull1283.5535993.36100NullNullNullNullNullNull1510072
Khawzawl100.00NullNullNullNullNullNull1792.298034.36100NullNullNullNullNullNull304759
Kolasib100.00100.00100.0030.412.643.853.81865.344783.7310010010081806452322871
Lawngtlai89.93100.00100.0032.716.946.555.3
1775.52418.94871001007572595030264
Lunglei89.19100.00100.0026.511.127.545.71521.992729.038610010092839664221673
Mamit100.00100.00100.0026.413.929.945.51279.8247.221001001009278916415071
207
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage of
pregnant wom -
en aged 15-49
years who
are anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Average
yield of
rice (kg/
ha)
Produc -
tivity of
fruits and
vegetables
(kg/ha)
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percent -
age of
children
under age
5 years
who are
stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage
of pregnant
women aged
15-49 years
who are anae -
mic (<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Aver -
age
yield
of rice
(kg/
ha)
Produc -
tivity of
fruits
and veg -
etables
(kg/ha)
SDG 2
Saitual100.00NullNullNullNullNullNull1417.273.11100NullNullNullNullNullNull19040
Serchhip100.00100.00100.0031.814.443.443.21667.2214927.1310010010077776568278878
Siaha92.31100.00100.0043.817.630.046.41504.392306.739010010043709163221466
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur100.00100.0051.6228.329.832.948.93063.151274.50100100468746855968867
Kiphire100.00100.0082.8436.925.019.555.22354.4910058.1010010081635510050475973
Kohima100.00100.0064.9728.322.13.938.42922.868920.6510010061876110075645378
Longleng100.00100.0060.4934.125.730.540.42375.1914054.251001005671549072488375
Mokokchung100.00100.0052.0031.422.911.535.52462.857945.1210010046786010079504773
Mon100.00100.0063.0335.523.327.039.42286.049398.801001005967599773455673
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren100.00100.0061.8334.920.726.451.02825.7910968.161001005768649856616574
Phek100.00100.0074.4928.015.618.244.92981.2611699.58
10010071887410065666982
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang100.00100.0059.5637.134.220.038.82413.691805.2210010055623710074491165
Wokha100.00100.0051.6826.328.029.845.42554.7510163.721001004693509164536073
Zunheboto100.00100.0060.5744.044.540.834.92412.067469.681001005642177080494462
Sikkim
Gangtok97.44100.0061.2417.813.0Null49.81817.763581.95971005710079Null58312168
Gyalshing97.47100.0071.6025.219.3Null67.11974.684089.9297100689667Null33362465
Mangan94.52100.0091.0531.815.326.953.51511.383314.35931009077759753222069
Namchi99.42100.0079.5224.87.2Null56.51968.034116.2499100779791Null48362472
Pakyong95.81100.0083.02NullNullNullNull1872.173614.619410081NullNullNullNull332166
Soreng95.63100.0085.06NullNullNullNull1971.433674.099410083NullNullNullNull362267
Tripura
Dhalai100.00100.0087.2145.727.675.481.22882.8014227.35100100863850312638460
Gomati100.00100.0094.8822.729.052.870.73334.5915358.7310010094100484628779176
Khowai100.00100.0091.6147.024.763.773.43314.3116965.5610010091345625247610067
North Tripura100.00100.0088.8826.232.255.352.53011.2015956.841001008893414254679475
Sepahijala100.00100.0093.3534.521.055.872.13497.0215611.761001009369634126819274
South Tripura100.00100.0094.6325.521.657.159.63455.8816590.631001009495623844809879
Unakoti100.00100.0091.7831.832.076.762.83263.6317362.301001009177420397410069
West Tripura100.00100.0086.0530.321.256.254.53386.4314992.471001008481634051788976
Target100100100.0023.72.625.221
411416919.32100100100100100100100100100100
2082023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Arunachal Pradesh
Anjaw41.9178.3365.850.001.890.00Null4.724.720.0028.3540645710060100Null988306367
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang43.9190.8783.640.971.010.51120.728.770.670.0012.554285791003289100911202860
Dibang Valley3.0393.7576.740.003.750.00102.7412.490.000.0066.2209071100100100100850010068
East Kameng111.3999.3993.180.002.060.08179.521.590.001.5919.38100999110066981001000434376
East Siang86.86100.0098.7212.351.950.4988.1030.621.392.7847.8886100989862908755247510080
Kamle23.5376.1238.780.001.800.00Null9.020.000.0021.20216123
10058100Null91004750
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi70.5580.4631.610.000.860.00Null0.000.000.0013.7070681410027100Null100003051
Kurung Kumey72.36100.0090.770.000.880.00425.000.000.000.0013.44711008810028100100100003065
Leparada41.7698.9689.370.002.480.05Null4.960.000.0028.784098871007999Null98006466
Lohit76.8799.1598.7419.131.611.0583.1020.092.012.0121.50769998895178817335544871
Longding36.7675.4987.515.250.530.00Null1.770.000.0012.8935608410017100Null100002852
Lower Dibang Valley51.5099.3086.992.161.480.52Null7.400.001.8524.785099841004789Null940505567
Lower Siang32.0098.9961.9012.662.300.14Null27.570.000.0036.76309852987397Null60008259
Lower Subansiri38.0898.0432.2710.911.890.02102.702.360.002.3640.1436971410060991001000648969
Namsai80.4397.92105.117.610.833.7696.676.251.041.0413.7680971001002720969518283063
Pakke Kessang15.00100.0036.040.003.310.00Null16.530.000.0041.331210019100100100Null78009260
Papum Pare45.8899.96113.064.621.811.5754.1731.710.570.5741.40441001001005867485310159263
Shi Yomi18.7984.2183.0222.221.500.00Null7.510.000.0023.291674798548100Null93005255
Siang21.9078.3370.440.002.190.00Null9.400.000.0032.8919646310070100Null90007358
Tawang44.8581.3772.6015.222.200.02115.152.000.002.0022.6043696594701001001000545068
Tirap64.4681.0280.660.000.900.5289.517.231.810.0021.86636976100298988943204863
Upper Siang67.6199.2285.5811.172.270.06
90.240.002.832.8340.7767998210072998910050779184
Upper Subansiri71.85100.0039.120.001.040.29194.3410.450.001.3124.1771100231003394100880355464
West Kameng68.7899.0879.752.601.530.09118.1812.750.001.2720.146898741004998100850344568
West Siang74.4499.7489.668.221.520.17113.271.901.901.9026.477410087100499610010033515977
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa87.1699.9868.6528.660.590.00116.075.890.000.118.148710060771910010096031860
Barpeta91.4999.7685.119.920.350.03111.606.550.180.188.449110081100119910095351864
Biswanath95.0199.96100.849.100.590.01Null21.220.000.4910.539510010010019100Null710132362
Bongaigaon90.9699.9372.787.610.690.09112.7225.040.140.277.359110066100229810064271661
209
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Cachar91.0699.72106.974.160.400.02112.224.660.630.127.229110010010013100100981131666
Charaideo92.22100.0066.7313.350.350.01Null16.570.440.227.9292100589711100Null78861757
Chirang84.4191.3278.439.060.830.04106.9318.250.000.218.15848673100279910076061861
Darrang95.0899.9977.276.700.590.06110.3413.460.650.329.9995100711001999100841192264
Dhemaji90.3699.9682.407.500.640.03111.2410.061.460.449.11901007810020991008926122067
Dhubri92.5285.3395.219.720.490.01107.1011.330.140.147.669276941001610010087341763
Dibrugarh91.5799.9681.235.850.340.05115.6110.560.230.158.609110076100
119910088441963
Dima Hasao62.3283.8968.328.390.980.01112.742.340.470.4717.33617460100311001001008133862
Goalpara92.3599.9286.129.070.780.07113.758.230.200.308.909210082100259810092381966
Golaghat93.1799.9472.9816.980.520.06114.136.470.280.288.45931006692179910095581863
Hailakandi90.1098.5799.746.650.650.05116.079.860.150.157.959098100100219910089341765
Hojai96.0797.2496.834.870.350.03Null8.700.210.324.089695961001199Null9149961
Jorhat84.2299.9993.7311.620.480.05117.048.000.220.2210.68841009299159910093462365
Kamrup93.5199.9587.4110.830.490.12119.2818.190.590.669.68931008410016981007610182165
Kamrup Metropolitan132.4899.78121.984.390.260.31121.4424.485.260.329.72100100100100893100659292172
Karbi Anglong71.8597.0193.936.610.860.05112.200.000.150.009.207195921002899100100302064
Karimganj92.3797.3188.917.100.470.05119.833.420.490.086.449296861001599100100921465
Kokrajhar86.4499.0376.5710.810.560.04112.381.690.000.2310.268698701001899100100062364
Lakhimpur94.9199.9984.676.680.580.02111.525.661.060.108.89951008110018100100961931966
Majuli92.9699.29108.4817.050.780.02Null4.780.000.6014.2993991009225100Null980163265
Morigaon82.9098.5085.129.120.610.06111.2325.280.100.108.18829881100199910064231861
Nagaon89.4498.4480.105.240.410.24107.676.130.210.218.60899775100139510096461963
Nalbari91.99100.0091.237.670.480.06110.231.300.130.3912.23921008910015991001002112767
Sivasagar92.7399.9765.4214.160.350.13113.69
38.130.290.4311.659310056961197100435122658
Sonitpur83.8998.1173.464.970.270.03112.830.000.460.155.79839766100999100100841362
South Salmara-Mankachar83.1975.3470.608.760.340.00Null3.060.180.003.7383606310011100Null10030853
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia95.8299.4579.296.440.480.01120.157.611.050.386.21969974100151001009318101365
Udalguri86.2899.7265.3222.290.570.02112.3814.430.000.248.398610056851810010082061859
West Karbi Anglong62.2769.4587.297.250.950.01Null3.050.000.347.8961508410030100Null100091755
2102023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully
immu -
nized
Infant
Mortality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by
skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mor-
tality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Manipur
Bishnupur118.6398.0494.993.030.290.0961.542.532.530.4210.0710097941009985710044112267
Chandel23.4296.8083.2316.000.480.3680.490.001.201.2020.702195799315927810021324661
Churachandpur50.3895.66118.6434.970.170.7687.690.001.291.7213.014993100685848610023462962
Imphal East27.1199.8984.254.850.290.3384.900.735.090.9723.0925100801009938310089265169
Imphal West135.1299.9381.623.520.150.4762.331.935.601.3526.29100100771005905810098375875
Jiribam3.2568.7527.050.000.460.0795.454.562.280.006.160498100159995984001347
Kakching43.3882.8484.280.000.270.0579.810.692.060.6912.484272801009997710036192760
Kamjong40.5557.0743.5020.730.210.0811.110.002.070.006.01393029877980
1003601340
Kangpokpi22.2174.8739.902.680.260.1070.500.520.520.005.8820592410089867100901345
Noney64.3966.8665.140.000.590.0281.820.001.970.0011.2063465610019100801003402557
Pherzawl60.9285.5020.8915.380.240.00Null0.002.420.006.0560760948100Null1004201349
Senapati38.2888.65201.650.490.350.1690.730.000.700.358.9736811001001197901001292060
Tamenglong35.3962.3694.3929.980.450.0168.750.000.001.1110.033338937514100651000302252
Tengnoupal34.1292.6730.720.000.000.0067.573.301.650.0013.533288121000100641002903050
Thoubal73.9299.3094.130.000.250.0881.870.363.260.3623.707399931008988010057105370
Ukhrul37.7284.0963.610.000.220.4970.830.000.740.7411.423674541007906710013202553
Meghalaya
East Garo Hills71.4177.97101.7316.430.890.0587.012.060.006.8619.1471641009328998510001004271
East Jaintia Hills43.3482.16110.3522.990.731.7092.824.070.006.5114.154271100842364929901003164
East Khasi Hills90.6881.5976.5528.810.440.8585.046.420.614.6018.509070707614828395111004167
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
North Garo Hills84.6566.7485.6125.140.760.0181.882.320.006.9710.8184458281241008010001002465
Ri Bhoi83.4265.1395.6420.860.580.3189.507.340.775.0210.748343948719938894141002467
South Garo Hills64.2555.58104.3220.240.910.0288.157.030.005.6213.7763271008829100879401003065
South West Garo Hills92.6787.75109.0429.160.680.0292.619.010.006.2012.5092801007622100929101002871
South West Khasi Hills60.5439.09104.9433.910.500.0681.5514.120.00
17.1414.52590100701699798201003258
West Garo Hills72.9468.4185.1624.310.450.0788.117.520.214.0812.65724881821499879341002864
West Jaintia Hills34.3874.26124.6917.550.511.6687.009.920.376.2516.243258100911665858961003662
West Khasi Hills91.2270.23106.8119.981.370.1492.9911.120.655.8917.7391511008844979287111003973
Mizoram
Aizawl89.7299.92135.2617.610.331.4985.5516.871.910.5434.7889100100911068847833157768
Champhai77.0198.2897.0910.322.780.7791.725.561.391.3922.397697961008984919724385076
Hnahthial75.9897.9199.7016.742.810.35Null28.080.003.5129.147597100929093Null590956576
Khawzawl66.8898.5177.5818.591.360.49Null32.550.000.0022.78669872904390Null52005056
Kolasib69.1297.0799.2314.230.950.1893.339.532.382.3819.53689599963096939042644374
Lawngtlai46.1473.3074.2017.311.700.1471.4313.570.000.8511.6244566792549768830232655
Lunglei62.5482.9787.9310.421.590.0888.814.550.000.7623.76617285100519887980215366
211
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully
immu -
nized
Infant
Mortality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by
skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mor-
tality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Mamit60.1179.0885.927.851.850.09225.588.110.002.3219.575966821005998100920634369
Saitual64.1599.7492.5212.790.990.26Null15.810.001.9819.176310091983295Null800534265
Serchhip61.3999.7697.8011.930.610.1888.896.121.533.0627.536010097992096889627836175
Siaha51.6487.6891.1025.292.830.4695.2014.140.001.7719.0950808981909095820484268
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur36.0995.86106.5413.150.884.72Null22.021.960.9814.29349310097280Null6934263251
Kiphire53.3989.0442.636.561.890.47Null1.352.702.7019.055282271006090Null10047734267
Kohima36.0697.5074.5513.641.471.32Null5.211.890.4718.61349668964772Null
9733134160
Longleng25.4495.0047.423.011.580.3298.040.007.921.9820.40239234100519398100100544572
Mokokchung53.8698.5364.437.831.230.5457.821.543.600.5118.2452985510039895310063144064
Mon17.9977.1557.861.231.920.3283.280.002.800.4010.8315624710061938110049112459
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren19.7474.6648.786.171.680.6075.400.004.202.1014.9117583510054877210074573363
Phek23.4489.3146.404.531.410.3996.640.613.060.6118.4821823210045929610054174162
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang15.4494.6547.684.021.311.8479.529.334.670.9319.691391341004261779082254460
Wokha29.2597.8950.043.910.960.3093.650.603.011.2014.2527973710031949310053323163
Zunheboto25.0596.8946.081.200.710.2392.000.003.550.7116.7023953210023959110062193762
Sikkim
Gangtok70.1099.8473.652.510.680.1592.7237.822.280.0060.2969100671002297924340010066
Gyalshing85.7599.4959.3035.712.090.0788.7453.020.001.4028.7485994967679987180386461
Mangan81.0596.5548.0886.211.830.0986.0816.020.002.2941.418094340589884790629262
Namchi85.3899.3263.3218.060.750.0382.6948.350.680.0026.2285995491249981261205857
PakyongNullNullNull0.000.000.1186.1563.933.12
1.560.78NullNullNull1000988405542148
SorengNullNullNull0.000.000.0382.9746.320.000.000.15NullNullNull100099812900039
Tripura
Dhalai71.0794.48106.599.350.690.57119.1516.130.000.5316.2170911001002288100790143664
Gomati85.2199.3293.147.630.420.33153.2715.610.000.4715.478599911001393100800133464
Khowai82.5398.5184.686.790.340.4492.5819.230.000.6112.00829881100119192740172661
North Tripura91.8697.62121.606.770.480.2841.6911.980.000.2410.85929610010015943486062459
Sepahijala80.6998.14111.623.170.440.27269.2317.080.000.4213.2980971001001494100780112964
South Tripura79.2199.4992.553.920.650.1493.9619.250.000.4516.25799991100219793740123664
Unakoti75.5293.61112.9110.650.400.2449.6914.470.000.3614.107590100100139543820103158
West Tripura134.5599.9183.3521.980.390.94111.4526.030.110.3324.521001007985138010063295462
Target100100100113.1301003.55.73.7045100100100100100100100100100100100100
2122023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Arunachal Pradesh
Anjaw35.620.8569.516.2291.8991.677.70210517918010050
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang27.331.096035.8488.5589.1113.72411003529877410067
Dibang Valley17.141.1881.534.7886.96100.003.246610070288510010078
East Kameng20.931.0166.533.5345.2995.809.04571004626379010065
East Siang10.221.0183.551.8597.5393.377.97831007347978410083
Kamle27.491.368522.7839.2497.969.07401007614309510065
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi20.751.2974.518.8048.8791.447.24571005910418010064
Kurung Kumey34.991.036936.3688.8994.814.74221005029878810068
Leparada11.811.047342.8663.4997.325.77791005637589410075
Lohit17.251.206849.0669.8188.0611.58661004844657210071
Longding14.371.0257.536.7942.4590.3912.98731003130337710064
Lower Dibang Valley20.650.968167.0079.0094.268.0457726963768710075
Lower Siang20.620.987050.0059.4689.965.4957885245537610067
Lower Subansiri16.790.918256.5287.6887.176.2667387152867010069
Namsai21.080.9575.528.4469.1988.1410.4756676021647210063
Pakke Kessang27.521.847020.7543.40100.0010.614010052123410010063
Papum Pare29.311.088051.6863.0394.738.38361006846578810071
Shi Yomi23.161.5064.528.2133.3395.4512.1751
1004320238910061
Siang16.851.058025.0050.9391.865.22671006817438110068
Tawang15.261.768071.1979.6692.5810.37701006868768310081
Tirap20.390.9672.540.2861.1192.4910.3758715634558210065
Upper Siang19.410.897737.8076.3895.457.5860306331738910064
Upper Subansiri8.091.0870.541.6029.2094.6213.74881005235188710069
West Kameng26.021.1171.552.9267.9292.659.94441005448638310070
West Siang18.921.067938.7897.2892.845.94611006632978310077
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa25.391.0678.584.8488.3562.127.82461006583861110070
Barpeta29.421.307958.7183.8965.3212.12361006654811910065
Biswanath31.451.186959.2688.2178.5914.10311005055865010067
Bongaigaon31.961.246565.3688.1965.6114.67301004462861910063
213
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Assam
Cachar27.061.1364.567.1990.2069.9718.03421004364893010067
Charaideo23.291.197995.2098.4461.989.22511006695981110074
Chirang27.241.166461.4383.8773.7013.07411004257813810066
Darrang18.871.267080.6690.6873.1210.63621005279893710074
Dhemaji11.241.067659.0590.8372.2910.00801006155893510074
Dhubri24.551.2972.549.6068.9269.5918.15481005644642910063
Dibrugarh19.431.0869.575.7497.2374.5710.34601005173974010074
Dima Hasao14.941.037755.3789.3772.488.30711006351883510073
Goalpara29.021.4067.564.1789.1372.8615.91371004860873610067
Golaghat23.571.0967.577.3391.2571.009.45501004875903210071
Hailakandi22.711.256949.9569.9968.9615.08521005045652710063
Hojai28.251.486279.3491.0763.5315.17391003977901410066
Jorhat22.651.0480.563.6995.6876.057.64521006960954410074
Kamrup34.851.1379.583.3192.7079.4710.02221006781925210073
Kamrup Metropolitan13.821.028570.8596.5380.268.24741007668965410081
Karbi Anglong25.781.0763.576.0286.4165.9910.77451004173842010066
Karimganj26.721.4360.564.4382.7469.5717.16421003661802910064
Kokrajhar20.281.0871.567.3668.3269.2813.89581005464632810067
Lakhimpur21.391.1073.558.5488.4971.997.71551005754873410070
Majuli16.590.9079.569.8689.6467.885.9767
326767882510064
Morigaon29.391.3973.579.8890.2276.3314.32361005778894410072
Nagaon30.051.5368.564.2588.1869.3610.16341004960862810065
Nalbari18.801.1084.553.6787.9967.847.91621007549862510071
Sivasagar20.021.038694.6397.7365.196.22591007794971810078
Sonitpur31.511.266973.6385.5875.9913.50311005071834410068
South Salmara-Mankachar27.241.5573.555.2873.9362.0114.03411005750701110061
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia30.681.136973.3094.8875.4813.25331005070944210070
Udalguri16.891.177167.2890.5163.9711.85661005364891510070
West Karbi Anglong33.801.136258.6888.0872.0712.30251003954863410063
2142023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average
annual
dropout
rate at
secondary
level (Class
9-10)
Ratio of
female
to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency level
in terms of nationally defined
learning outcomes to be at -
tained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage
of trained
teachers at
secondary
level (Class
9-10)
Pupil Teach -
er Ratio at
secondary
level (Class
9-10)
Average annual
dropout rate at
secondary level
(Class 9-10)
Ratio of fe -
male to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency
level in terms of nationally
defined learning outcomes
to be attained at the end of
the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Manipur
Bishnupur20.010.9674.540.9275.2583.7910.8059755935716210066
Chandel25.921.0980.514.3593.4869.649.1244100695922910063
Churachandpur33.431.028430.3767.5676.3810.94261007423624510061
Imphal East18.170.988243.9577.3483.277.2263857138746110070
Imphal West0.001.0085.555.5686.4883.517.731001007751846110082
Jiribam21.781.1952.529.63100.0067.3914.345410023221002410060
Kakching30.470.948050.6076.7980.049.3933646845735310062
Kamjong1.921.08789.9427.9593.1810.82100100650168410066
Kangpokpi24.640.9780.520.7556.9874.669.8147796912504110057
Noney32.220.917118.5736.4370.2311.7029425310263010042
Pherzawl41.930.957617.6923.0881.885.62569619115710045
Senapati4.920.988126.7073.8681.929.5696876919705810071
Tamenglong16.881.0970.516.6136.9089.559.8366100528277610061
Tengnoupal29.751.027221.7169.7469.429.18351005513652810057
Thoubal8.180.9674.549.1177.2286.2611.2188735944746810072
Ukhrul22.511.077842.7351.9873.719.55531006537443810062
Meghalaya
East Garo Hills14.571.1543.524.4423.0476.8617.0572100916114610051
East Jaintia Hills38.611.4659.516.4330.2676.3611.3313100357194510046
East Khasi Hills11.161.267234.2653.6968.589.33811005527462610062
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNull
NullNull*
North Garo Hills44.011.264314.4321.5375.6813.4201008594310038
Ri Bhoi16.931.3961.520.2434.3865.3910.82661003812241910051
South Garo Hills30.701.22469.8013.7676.118.823310013004410041
South West Garo Hills29.251.135012.7114.3873.6710.013610019313810043
South West Khasi Hills26.301.295310.4321.5966.507.464310024192110043
West Garo Hills25.361.205315.2324.0861.709.7746100246121010043
West Jaintia Hills20.561.5063.517.8128.0260.9611.885710041917810047
West Khasi Hills32.131.303810.3217.0269.9711.97291000143010038
Mizoram
Aizawl0.001.1178.567.3499.2178.3610.641001006564994910082
Champhai20.261.1362.579.0398.1374.8110.27581004077984110073
Hnahthial32.501.21Null46.3893.4883.208.4328100Null41926110070
Khawzawl24.731.14Null41.3595.4967.368.5347100Null35952310067
215
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average
annual
dropout
rate at
secondary
level (Class
9-10)
Ratio of
female
to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency level
in terms of nationally defined
learning outcomes to be at -
tained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage
of trained
teachers at
secondary
level (Class
9-10)
Pupil Teach -
er Ratio at
secondary
level (Class
9-10)
Average annual
dropout rate at
secondary level
(Class 9-10)
Ratio of fe -
male to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency
level in terms of nationally
defined learning outcomes
to be attained at the end of
the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Kolasib23.341.1566.545.0498.5895.289.22511004639988910075
Lawngtlai29.450.925716.4456.4078.4410.763647317494910046
Lunglei24.571.0263.540.4578.4778.506.51481004134755010064
Mamit39.961.066840.1679.5392.597.07101004834768310064
Saitual29.851.10Null63.0599.5187.217.1535100Null59997010077
Serchhip23.130.926943.0496.9687.688.1251515037967110065
Siaha0.000.986327.9995.9082.0810.18100894020955810072
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur0.371.058094.8396.4974.988.781001006894964110086
Kiphire27.881.1566.572.1872.9365.6110.99401004669691910063
Kohima0.001.048086.9189.0974.867.051001006885874110083
Longleng14.631.2271.594.5044.0473.777.10721005494353810071
Mokokchung14.220.9682.592.1994.1479.335.3573737291935210079
Mon26.681.1666.582.8469.9757.369.9142100468165010062
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren15.990.927569.3675.7269.068.3469486066722710063
Phek25.521.107888.4691.8874.245.45451006587914010075
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNull
Null*
Tuensang21.881.2164.587.2468.3177.509.07541004386634710070
Sikkim
Gangtok14.401.037991.77100.0088.447.227310066911007310086
Gyalshing19.661.016994.3096.3788.034.58601005094967210082
Mangan22.411.057680.0097.2785.495.33531006178976610079
Namchi18.831.037191.4499.1787.035.54621005391997010082
Pakyong24.070.98Null93.7298.9589.634.724985Null93997610083
Soreng22.861.02Null96.13100.0084.343.6952100Null961006310085
Tripura
Dhalai11.891.056228.0257.2991.8211.77791003920508110067
Gomati11.980.997642.6794.9590.1613.8679956136947710077
Khowai14.121.017653.8996.6185.469.67731006149966610078
North Tripura13.861.1472.544.6568.8289.6610.78741005639647610073
Sepahijala13.211.0077.550.3171.2388.369.03751006445677310075
South Tripura11.601.0084.540.7582.8491.3412.6079987534808010078
Unakoti13.331.1070.555.1781.9686.6614.94751005250796910075
West Tripura3.521.0081.586.6991.0388.6410.3099987085907310088
Target3.2110010010010030100100100100100100100100
2162023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Arunachal Pradesh
Anjaw4.1481850.006.847.4775870794866
BichomNullNullNullNullNullNullNullNullNullNull*
Changlang2.2496268.756.745.38710059804674
Dibang Valley0.007780.004.661.910045100866279
East Kameng4.371189100.009.791.47510040719276
East Siang6.7493180.9517.694.2629451479570
Kamle0.901161100.00Null78.69510040Null7978
Keyi PanyorNullNullNullNullNullNullNullNullNullNull*
Kra Daadi0.42636100.0016.587.798040508855
Kurung Kumey0.009710.0016.486.3100100100508787
Leparada8.1892080.00Null77.1549052Null7868
Lohit5.9899264.2914.670.86610061567171
Longding1.4286750.007.355.6927470785674
Lower Dibang Valley4.2390190.914.974.5768445857573
Lower Siang5.6292366.67Null58.4689160Null5970
Lower Subansiri3.3396671.438.5Null811005774Null78
Namsai1.52100280.008.771.49110052747278
Pakke Kessang6.51833100.00Null89.7636340Null9064
Papum Pare17.7498034.6720.372.8010079387358
Shi Yomi3.081192100.00Null94.28310040Null9579
Siang1.96871100.005.086.0897540858775
Tawang1.4410290.0014.699.3921001005610090
Tirap0.38934100.0010.666.4989540686774
Upper Siang4.21105685.7111.977.67610049647873
Upper Subansiri2.6289533.3317.380.2858380488175
West Kameng2.2891050.0017.078.6878770487974
West Siang9.8791472.0015.583.4448857538465
Assam
BajaliNullNullNullNullNullNullNullNullNullNull*
Baksa2.6592924.1912.5100.08593856210085
Barpeta7.1596523.3512.3100.060100866310082
Biswanath6.3496119.905.3100.064
100888410087
Bongaigaon7.7794319.8616.199.95698885110079
217
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Cachar11.9296920.0215.6100.033100885310075
Charaideo6.7894922.378.3100.062100877510085
Chirang6.8396224.079.899.762100867010083
Darrang16.5395321.6314.8100.07100875510070
Dhemaji5.9796632.507.199.866100817810085
Dhubri9.0497123.0011.5100.049100866510080
Dibrugarh6.0891816.208.7100.06690907410084
Dima Hasao2.9092433.339.7100.08492807110085
Goalpara13.6094119.477.4100.02397887810077
Golaghat3.8293913.0010.9100.07896926710087
Hailakandi9.4094433.118.6100.04798807410080
Hojai13.1395916.9213.299.926100906010075
Jorhat7.5491434.5010.4100.05889796810079
Kamrup16.4796738.1317.6100.07100774710066
Kamrup Metropolitan16.1593524.418.8100.0995857310073
Karbi Anglong1.8097620.699.3100.090100887210090
Karimganj7.9095317.028.699.555100907410084
Kokrajhar7.9996131.1210.099.955100817010081
Lakhimpur7.7995018.559.8100.056100897010083
Majuli8.2089028.3611.6100.05481836510076
Morigaon11.6496121.726.599.934100878010080
Nagaon8.3996920.2612.3100.053100886310081
Nalbari9.6992330.4913.2100.04591826010076
Sivasagar6.6998018.148.399.362100897510085
Sonitpur12.7190517.615.8100.02886898210077
South Salmara-Mankachar10.4095317.258.099.641100907610081
TamulpurNullNullNullNullNullNullNullNullNullNull*
Tinsukia6.9894128.9811.0100.06197836710081
Udalguri6.2795617.1214.6100.065100905610082
West Karbi Anglong2.7790125.007.199.48484857810086
2182023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Manipur
Bishnupur1.6980865.0020.051.0905561395159
Chandel0.259310.0011.01.3999410067172
Churachandpur0.8794980.008.716.19510052741667
Imphal East2.1190875.0016.797.4888755499875
Imphal West3.2793055.8112.59.082946762963
Jiribam1.41119666.67Null76.99210060Null7782
Kakching2.33109682.35Null28.48710051Null2967
Kamjong0.0011930.00Null3.6100100100Null476
Kangpokpi0.11976100.00Null14.39910040Null1463
Noney0.009880.00Null21.1100100100Null2180
Pherzawl0.98781100.00Null0.0944640Null045
Senapati0.15934100.008.520.0999540742066
Tamenglong0.239140.008.48.3998910075874
Tengnoupal1.6996220.00Null34.29010088Null3478
Thoubal2.8288169.236.070.3847858827175
Ukhrul0.76100580.0012.740.39610052624170
Meghalaya
East Garo Hills4.3589036.8421.087.8758178368872
East Jaintia Hills6.971050146.6726.092.26110012219357
East Khasi Hills4.8493737.1833.089.173967809067
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNull*
North Garo Hills2.81998166.6725.288.8841000248959
Ri Bhoi5.1595432.1427.087.37110081188872
South Garo Hills3.4792692.3125.387.6809245238866
South West Garo Hills1.1795525.0030.499.79310085810077
South West Khasi Hills3.0698075.0026.285.58310055218669
West Garo Hills6.2791641.7619.779.6658975408070
West Jaintia Hills3.8697427.7829.392.47810083119373
West Khasi Hills7.4795668.4225.893.95810059229467
Nagaland
Aizawl3.2596735.4824.099.882100792710078
Champhai2.5197221.0511.2100.086100876610088
Hnahthial2.1088937.50Null97.1
888178Null9886
Khawzawl6.0590650.00Null100.0668670Null10080
219
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Kolasib2.68104012.5015.699.885100935310086
Lawngtlai2.8696790.9117.3100.084100454810075
Lunglei1.7397033.3315.4100.090100805310085
Mamit2.89923100.0017.099.98491404810073
Saitual1.6010370.00Null100.091100100Null10098
Serchhip3.72109650.0015.9100.079100705210080
Siaha2.1483850.0022.599.98864703210071
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNull*
Dimapur0.7290254.5514.392.5968567579380
Kiphire0.2888766.6717.395.5988060489676
Kohima0.9791540.009.1100.09589767210086
Longleng0.859710.004.396.695100100879796
Mokokchung0.329730.006.4100.0981001008110096
Mon0.519670.003.785.597100100898694
NoklakNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNull*
Peren0.7097666.676.277.29610060817883
Phek0.3884150.006.596.3986570809782
ShamatorNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNull*
Tuensang0.519300.0012.9100.097941006110090
Wokha0.129960.003.2100.0991001009010098
Zunheboto0.439300.002.891.49894100929295
Sikkim
Gangtok6.9296494.7417.7100.061100434610070
Gyalshing5.51101875.004.3100.069100558710082
Mangan6.32871100.0012.8100.06475406110068
Namchi5.9885278.575.2100.06669538410074
Pakyong7.11Null100.00Null100.060Null40Null10067
Soreng4.42Null100.00Null100.075Null40Null10072
Tripura
Dhalai3.5992540.914.0100.08092758810087
Gomati5.9097733.8712.1100.0
67100806310082
Khowai2.3794350.004.1100.08798708810088
North Tripura5.42100146.856.1100.069100728210085
Sepahijala3.25101323.6815.3100.082100865410084
South Tripura3.7594836.5917.3100.079100784810081
Unakoti7.8595438.329.7100.056100777110081
West Tripura3.2598733.332.5100.082100809210091
Target09500099.4100100100100100100
2202023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Arunachal Pradesh
Anjaw100.0089.8486.8100.0090.54100.00Null100837210086100Null90
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang100.0089.9782.3100.0076.81100.000.661008363100661009987
Dibang Valley100.0091.7795.0100.0073.91100.00Null100868910061100Null90
East Kameng100.0095.3475.6100.0046.15100.002.631009249100201009479
East Siang100.0090.8783.9100.0062.35100.000.881008566100441009885
Kamle100.0092.00Null100.0045.57100.00Null10087Null10020100Null81
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi100.0092.8389.3100.0078.95100.00Null100887710069100Null89
Kurung Kumey100.0092.7678.3100.0061.62100.00Null100885410043100Null81
Leparada100.0092.92Null100.0079.37100.00Null10088Null10069100Null92
Lohit100.0092.1383.7100.0095.28100.000.731008766100931009892
Longding100.0092.5883.5100.0061.32100.00Null100886510043100Null83
Lower Dibang Valley100.0091.1589.9100.0088.00100.000.331008579100821009992
Lower Siang100.0094.02Null100.0058.11100.00Null10090Null10038100Null86
Lower Subansiri100.0092.8982.8100.0087.59100.002.331008864100821009590
Namsai100.0090.6775.1100.0081.99100.00Null100844710073100Null84
Pakke Kessang100.0092.14Null100.0058.49100.00Null10087Null10039100Null85
Papum Pare100.0093.1175.7100.0059.66100.001.281008949100401009782
Shi Yomi100.0093.20Null100.0076.92100.00Null10089Null10066100Null
91
Siang100.0093.4791.2100.0037.96100.00Null10089811008100Null80
Tawang100.0089.0581.7100.0085.34100.00Null100826110078100Null87
Tirap100.0090.2486.7100.0064.34100.001.751008472100471009686
Upper Siang100.0095.7491.8100.0068.25100.00Null100938310053100Null88
Upper Subansiri100.0094.2080.9100.0056.00100.000.611009060100351009983
West Kameng100.0089.7588.9100.0069.58100.000.1110083771005510010088
West Siang100.0093.7887.7100.0072.79100.001.031009074100601009889
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa100.0073.9368.993.8386.65100.003.49100573492801009279
Barpeta99.4376.1463.795.6390.09100.0029.6898602394851003170
Biswanath87.6663.6476.693.6485.53100.00Null5540519279100Null69
Bongaigaon95.9171.0272.593.3090.58100.0025.7685524291861004071
221
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Cachar100.0074.2457.695.5591.82100.003.29100571194881009277
Charaideo94.9863.1275.993.0597.96100.00Null8239499197100Null76
Chirang97.1051.8177.196.2483.21100.002.7589205295751009475
Darrang72.7272.4767.993.6690.25100.0042.71054329286100052
Dhemaji89.3565.4670.894.3893.05100.004.0561433893901009174
Dhubri99.6666.2661.894.7784.51100.0029.7299441993771003066
Dibrugarh99.1770.0675.395.1995.94100.007.6397504894941008281
Dima Hasao100.0074.0383.894.8281.11100.001.01100576693721009884
Goalpara100.0070.7075.395.1791.39100.0020.82100514894871005176
Golaghat95.0569.2973.194.7393.65100.005.4282494393911008778
Hailakandi100.0064.2760.096.4167.68100.003.62100411695521009271
Hojai99.8565.6263.194.0893.29100.00Null9943229290100Null74
Jorhat96.7157.6980.494.9496.48100.009.3588305993951007878
Kamrup99.0261.2668.794.2596.29100.0033.9196363492951002168
Kamrup Metropolitan100.0077.1765.295.6596.32100.00Null10062279495100Null80
Karbi Anglong99.0157.8975.292.4584.14100.002.4896304890771009476
Karimganj100.0068.1061.596.1781.21100.002.94100471995721009375
Kokrajhar97.1371.1872.295.6475.64100.005.6389524194641008775
Lakhimpur99.8772.8674.294.1587.23100.0010.26100554692811007678
Majuli100.0081.1265.693.6888.03100.00Null10069279282100Null78
Morigaon99.7749.8862.394.6887.36100.0025.2199172093811004165
Nagaon96.4164.7866.193.8389.19100.0028.8687412892841003266
Nalbari99.9872.3568.194.3192.76100.0024.11100543393891004473
Sivasagar99.1280.8682.394.5394.89100.004.1997686393921009086
Sonitpur92.7467.6772.294.6187.78100.0010.4473464193821007673
South Salmara-Mankachar100.0074.1459.094.6882.18100.00Null10057149374100Null73
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia87.9472.7766.794.3995.97100.006.6756553093941008573
Udalguri96.8663.8273.894.7290.76100.008.9088404593861007976
West Karbi Anglong100.0046.1876.792.4982.07100.00Null10010519073100Null71
2222023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Percentage
of individual
household toi -
lets constructed
against target
(SBM(G))
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/villages
verified as ODF
(SBM(G)) in the
district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Manipur
Bishnupur100.0069.8652.6100.0068.65100.005.67100500100541008770
Chandel100.0067.6785.2100.0088.26100.00Null100466910083100Null83
Churachandpur100.0079.0581.2100.0094.01100.006.181006560100911008686
Imphal East100.0077.2059.5100.0071.76100.007.981006215100581008174
Imphal West100.0068.4658.7100.0080.11100.0010.971004813100711007472
Jiribam100.0039.89Null100.0074.53100.00Null1000Null10062100Null72
Kakching100.0077.81Null100.0081.55100.00Null10063Null10073100Null87
Kamjong100.0067.20Null100.0065.84100.00Null10045Null10050100Null79
Kangpokpi100.0080.58Null100.0053.40100.00Null10068Null10031100Null80
Noney100.0066.52Null100.0069.29100.00Null10044Null10055100Null80
Pherzawl100.0048.09Null100.0064.62100.00Null10014Null10048100Null72
Senapati100.0070.8784.4100.0087.22100.00Null100526710081100Null83
Tamenglong100.0073.5877.9100.0099.63100.00Null100565310099100Null85
Tengnoupal100.0086.66Null100.0053.95100.00Null10078Null10032100Null82
Thoubal100.0076.1461.3100.0072.49100.009.841006018100591007774
Ukhrul100.0071.7081.4100.0044.93100.00Null100536110019100Null72
Meghalaya
East Garo Hills100.0081.5283.971.8469.83100.006.93100696663551008477
East Jaintia Hills100.0052.0783.676.3357.20100.002.28100206569371009569
East Khasi Hills100.0063.8480.984.5878.91100.002.58100406080691009477
Eastern West Khasi HillsNullNullNullNUllNullNullNullNullNull
NullNullNullNullNull*
North Garo Hills100.0074.8184.966.4768.27100.003.59100586856531009275
Ri Bhoi100.0078.0885.359.7272.85100.006.17100646947601008675
South Garo Hills100.0080.1088.476.9671.25100.001.59100677670581009681
South West Garo Hills100.0076.9471.437.5751.73100.0017.65100624018291005958
South West Khasi Hills100.0071.3589.657.6685.02100.001.71100527844781009678
West Garo Hills100.0065.9986.364.5858.89100.004.15100437153391009071
West Jaintia Hills100.0064.8975.183.2064.95100.004.45100424778481009072
West Khasi Hills100.0074.3087.874.4872.06100.001.74100577466591009679
Mizoram
Aizawl100.0089.9996.1100.0094.69100.0014.061008392100921006791
Champhai100.0091.7998.3100.0080.52100.003.031008696100711009392
Hnahthial100.0087.62Null100.0075.36100.00Null10079Null10064100Null89
Khawzawl100.0092.09Null100.0076.69100.00Null10087Null10066100Null90
Kolasib100.0091.7296.8100.0066.31100.001.301008693100501009790
Lawngtlai100.0089.6290.3100.0067.99100.003.621008380100531009287
Lunglei100.0090.4395.6100.0074.65100.004.101008491100631009190
223
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Percentage
of individual
household toi -
lets constructed
against target
(SBM(G))
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/villages
verified as ODF
(SBM(G)) in the
district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Mamit100.0091.4092.7100.0078.68100.002.061008685100681009591
Saitual100.0090.25Null100.0089.16100.00Null10084Null10084100Null94
Serchhip100.0092.1398.2100.0092.61100.006.191008796100891008694
Siaha100.0091.8391.5100.0084.70100.005.781008682100771008790
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur100.0077.5081.1100.0092.80100.003.981006360100891009186
Kiphire100.0089.3683.1100.0072.18100.006.431008264100591008584
Kohima100.0079.4187.4100.0093.09100.0010.511006673100901007586
Longleng100.0083.2086.6100.0088.99100.001.331007272100841009789
Mokokchung100.0074.6996.7100.0089.06100.000.621005893100841009990
Mon100.0079.0186.4100.0092.08100.005.111006571100881008888
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren100.0079.9789.4100.0083.24100.000.901006778100751009888
Phek100.0081.3790.1100.0058.12100.006.431006979100381008582
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang100.0076.6492.0100.0065.02100.0010.091006183100481007681
Wokha100.0082.3488.5100.0079.46100.001.381007176100701009788
Zunheboto100.0080.7688.9100.0032.35100.008.061006877
10001008175
Sikkim
Gangtok100.0085.9985.0100.0099.55100.009.291007768100991007889
Gyalshing100.0081.1788.9100.0097.83100.004.631006977100971008990
Mangan100.0079.8283.8100.0098.95100.002.581006666100981009489
Namchi100.0077.3491.7100.0096.77100.009.781006282100951007788
Pakyong100.0074.23Null100.0096.67100.003.6010057Null100951009291
Soreng100.0077.50Nu
Copyright@NITI Aayog & MDoNER, 2025
NITI Aayog,
Government of India,
Sansad Marg, New Delhi - 110001, India
Ministry of Development of North Eastern Region
Vigyan Bhawan Annexe,
Maulana Azad Road, New Delhi - 110011
Source of Maps: Survey of India. Boundaries shown in the map
are as per the Political Map of India, Twelfth Edition (Newly
created districts maps provided by respective states and not
to scale).
Cover & Report Design by Rouge Communications
rougecommunications@gmail.com
Photo credits: Biju Boro, Pallav Bhuyan & Andrew Drewzy
Ministry of Development
of North Eastern Region
NORTH EASTERN REGION
DISTRICT SDG INDEX
REPORT 2023–24
II
The collective resolve to address development challenges across social, economic, and
environmental dimensions—while ensuring that no one is left behind—is more urgent today
than ever before. India has demonstrated remarkable resilience and unwavering commit-
ment in its pursuit of the Sustainable Development Goals. In this endeavour, our States
and Union Territories have played an instrumental role, championing SDG initiatives and
advancing a robust localisation model that reaffirms our belief in both cooperative and
competitive federalism.
The States of the North-Eastern Region are central to SDG localisation, given their unique
geography, rich cultural heritage, and intra-regional developmental disparities. Their
commendable efforts have led to the formulation of SDG-aligned vision documents, the
establishment of dedicated institutional frameworks, and the development of state-specific
monitoring systems—ensuring alignment with our broader localisation efforts.
To accelerate SDG progress and promote holistic regional development, NITI Aayog, in
partnership with the Ministry of Development of North Eastern Region and UNDP India,
launched the first-ever District-level SDG Index for the region in 2021. This initiative, shaped
through extensive consultation with all eight North-Eastern States, yielded invaluable insights
into the challenges hindering progress, while also illuminating opportunities to advance
sustainable development across the region. The positive reception of the 2021–2022 edition
has rightfully paved the way for this second iteration.
Shri Suman Bery
Vice Chairperson
National Institution for Transforming India (NITI Aayog)
Government of IndiaMessage
III
July, 2025
New Delhi, India
The North Eastern Region District SDG Index marks a significant step forward in localising
the global goals by translating them into region-specific targets and tracking progress at
the district level. Through data-driven governance, targeted interventions, and the facilita-
tion of peer learning among districts, this Index empowers States to respond more effec-
tively to local development priorities. These collaborative efforts stand as a testament to
India’s unwavering commitment to deepening SDG localisation and accelerating progress
throughout the region.
This initiative epitomises the spirit of cooperative federalism, bringing together the eight
North-Eastern States, NITI Aayog, and MDoNER in a unified pursuit of sustainable and
inclusive development. It also reflects the Honourable Prime Minister’s vision of Sabka
Saath, Sabka Vikas, Sabka Vishwas, Sabka Prayas.
We gratefully acknowledge the valuable contribution of the UNDP team in India, whose
technical expertise, dedication, and consistent support have been integral to the design
and implementation of this initiative. Their partnership has greatly enriched the process
and is deeply appreciated.
Suman Bery
IV
Sustainable Development Goals are at the top of India’s development agenda and their
importance has been repeatedly emphasised by Hon’ble Prime Minister, Shri Narendra Modi.
With this vision, India has accentuated its efforts to realise the SDGs, bouncing back from
the adverse effect the COVID-19 pandemic.
The SDG framework requires effective mechanisms and decentralisation to solve environ-
mental, social and economic challenges. Sub-national entities have utilised the SDG India
Index Report & Dashboard to strengthen their statistical systems and policy formulation.
In the true spirit of cooperative federalism, the Centre and States are working in unison
to realise the Agenda 2030. The first edition of the North East Region District SDG Index
and Dashboard has steered districts of the North East Region towards better monitoring
of achievement of SDGs and this edition would encourage them further.
The North Eastern Region is the country's most socially and ethnically diverse region,
with each State having distinct traditions and cultures. This diversity is its strength and
provides many opportunities for sustainable development. I am delighted that the Ministry
of Development of North Eastern Region has taken the initiative to bring out the NER
District SDG Index and Dashboard in collaboration with NITI Aayog. This monitoring tool
enables States, Ministries and various stakeholders to measure progress and examine the
impact at a granular level.
Shri B.V.R. Subrahmanyam
Chief Executive Officer
National Institution for Transforming India (NITI Aayog)
Government of India
Message
V
NITI Aayog has conducted state-level capacity-building workshops to better understand and
realise SDGs. I applaud the remarkable progress reported by States and districts on SDG
implementation with the development of the State Indicator Framework, District Indicator
Framework, SDG Coordination Cells and review systems at the local level. These steps to
localise SDGs are paramount for achieving the targets.
I compliment the Ministry of Development of North Eastern Region and UNDP India for their
unrelenting support in bringing out this second edition of the NER District SDG Index and
Dashboard. I congratulate the NITI Aayog team for their efforts in preparing this report. I
thank all the State governments of the region for their cooperation and active contribution
to the development of this Index.
B.V.R. Subrahmanyam
July, 2025
New Delhi, India
VI
Message
The North Eastern Region, with its vibrant mosaic of communities, culture, and ecology,
stands at a pivotal moment in its developmental journey. Despite longstanding challenges
such as inadequate connectivity, difficult terrain, and developmental disparities, the region
continues to move forward with resilience and purpose. It is in this context that the NER
District SDG Index & Dashboard 2023–24 becomes a vital instrument of change.
This second edition of the Index, jointly developed by NITI Aayog, Ministry of Development
of North Eastern Region and with technical support from UNDP India, reflects our sustained
commitment to localizing the Sustainable Development Goals at the most granular level.
It builds upon the momentum of the first edition and incorporates feedback, better data
systems, and enhanced district-level coverage, with 121 of the 131 districts of the region now
included. The Index now draws on 84 indicators sourced from both central and state data
systems—a testimony to improved reporting and institutional collaboration.
The findings of this edition are encouraging. A remarkable 85% of districts now fall within
the Front Runner category—a significant leap from 62% in the previous round. This progress
is a direct result of targeted interventions, saturation-based approaches under flagship
national schemes, and robust local efforts in SDG planning and implementation across the
eight NER states. Many districts have shown notable improvement in critical sectors such as
education, health, gender equity, and access to water and energy. The performance on Goal
5 (Gender Equality) and Goal 6 (Clean Water and Sanitation) is particularly commendable.
Shri Chanchal Kumar
Secretary
Ministry of Development of North Eastern Region
Government of India
New Delhi, India
VII
Chanchal Kumar
July, 2025
New Delhi, India
Yet, the journey is far from complete. Certain goals such as Goal 10 (Reduced Inequalities)
and Goal 12 (Responsible Consumption and Production) still show marked disparities across
districts. These require sustained focus and tailored strategies. The Index, by identifying
such gaps, offers actionable insights to guide interventions and resource deployment more
efficiently.
Importantly, the Index continues to foster a spirit of cooperative and competitive federalism
among the States and districts of the NER. Its expanded coverage and methodological rigor
make it not only a tool for benchmarking but also a roadmap for inclusive and sustainable
regional development.
I express my sincere appreciation to NITI Aayog and UNDP India for their unwavering
support in bringing out this updated edition. I also commend the efforts of the eight North
Eastern States for their valuable cooperation in data collection, consultations, and feedback.
VIII
The 17 Sustainable Development Goals lay out a bold agenda—to end poverty in all its
dimensions, drive inclusive economic growth, and protect the planet. These goals offer a
comprehensive framework to address some of the most persistent and emerging challenges
of our time, from climate change and inequality to public health and gender disparities.
For India, the SDGs are not just a global responsibility but a national priority. India’s lead-
ership in localizing the SDGs is a powerful example of translating global aspirations into
local action. Through this approach, states and union territories are tailoring the SDG
framework to their development needs—prioritizing goals, adopting relevant indicators,
and implementing innovative solutions.
A key enabler of this effort is the SDG India Index and Dashboard, developed by NITI Aayog.
It tracks and compares progress across all states and UTs, fostering evidence-based poli-
cymaking, transparency, and healthy competition.
India’s commitment to hyper-local monitoring is equally commendable. The launch of the
North East Region District SDG Index in 2021–22 brought district-level tracking to the eight
northeastern states. By measuring each district’s performance against specific targets,
the Index equips policymakers with the insights needed to focus efforts where they are
needed most.
This collaborative model between central and state governments has delivered meaningful
progress in the region—in areas such as renewable energy, poverty reduction, and digital
inclusion.
Dr. Angela Lusigi
Resident Representative
UNDP India
Message
IX
The latest NER District SDG Index 2023–24 builds on this foundation. It highlights achieve-
ments, uncovers emerging challenges, and provides a roadmap for action. It highlights
progress, identifies new challenges, and offers data-driven insights to accelerate action. By
spotlighting both high-performing districts and those needing more attention, it enables
focused interventions, efficient resource allocation, and inter-district learning. It also rein-
forces how local efforts in the Northeast contribute to the national vision of Viksit Bharat.
We commend the Government of India for its exemplary leadership in advancing
the SDG agenda. In particular, we thank the senior leadership of NITI Aayog and the
Ministry of Development of North Eastern Region for their vision and partnership. We
extend our appreciation to Shri Jyotiraditya M. Scindia, Union Minister for MDoNER;
Shri Suman Bery, Vice Chairperson of NITI Aayog; Shri B.V.R. Subrahmanyam, CEO of NITI
Aayog; and Shri Chanchal Kumar, Secretary of MDoNER.
I sincerely thank Shri Rajib Sen, Adviser to NITI Aayog, for steering this publication, and to the
state governments of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland,
Sikkim, and Tripura for their strong commitment to sustainable development in the region.
At UNDP, we remain a steadfast partner to the Government of India, committed to support-
ing this journey through technical expertise, innovative investment, integrated solutions
and institutionalcapabilities. Together, we can ensure that no district—and no one—is left
behind in India’s SDG journey.
July, 2025
New Delhi, India
Dr. Angela Lusigi
X
Acknowledgements
NITI Aayog has been consistently engaging with States and UTs for the adoption, implemen-
tation, and monitoring of the Sustainable Development Goals at the national and sub-na-
tional levels. The 'Indian Model of SDG Localisation', anchored in the core SDG principle
of ‘leaving no one behind', reflects India's relentless efforts towards the '2030 Agenda'.
NITI Aayog's SDG India Index has become the primary tool for SDG monitoring at the
national and sub-national levels. The North Eastern Region District SDG Index expands
the model to the district level to address the growing needs for reliable and comparable
data and supports evidence-based policymaking and targeted interventions. For a region
with such cultural and socio-economically diversity, as well as disparities, the NER District
SDG Index serves as a tool to fast-track the progress of SDGs at the districts in the region.
The second edition of the NER District SDG Index, developed collaboratively with the Ministry
of Development of North Eastern Region, State Governments of the north eastern region and
UNDP India, covers 15 SDGs and ranks 121 of 131 districts of the region. A notable achieve-
ment is the inclusion of 16 districts that were excluded last time due to data unavailability.
The Index is the first of its kind to measure regional progress through customised meth-
odology and metrics, highlighting significant progress in district-level data reporting. It
enables state-wise, district-wise, and SDG-wise comparisons and serves as a platform for
peer learning, mid-course correction, and better resource allocation.
We extend our deepest gratitude to MDoNER and the State Governments of Arunachal
Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura for their
continuous support, from consultations to data provision. The state-level workshops were
instrumental in refining this edition.
Shri Rajib Kumar Sen
Programme Director (SDGs)
National Institution for Transforming India (NITI Aayog)
Government of India
XI
Rajib Kumar Sen
Our sincere thanks to Shri Suman Bery, Hon’ble Vice Chairman, NITI Aayog, for his inspiring
leadership, and to Shri B.V.R. Subrahmanyam, CEO, NITI Aayog, for his constant encourage-
ment and support for localising efforts in the SDGs.
We are also thankful to Shri Chanchal Kumar, Ministry of Development of North Eastern
Region, for entrusting us with this critical initiative, and to Dr. Angela Lusigi, Resident
Representative, UNDP India, for her team’s strong partnership.
Special acknowledgements are due to the entire SDG team at NITI Aayog for their commit-
ment and dedication towards the development of the Report.
We sincerely hope that the NER District SDG Index will be a catalyst for inclusive and coor-
dinated ground-level implementation of the SDGs in the region.
July, 2025
New Delhi, India
XII
LIST OF ABBREVIATIONS
AIDS Acquired Immunodeficiency Syndrome
ANC Antenatal Care
ANM Auxiliary Nurse Midwifery
ATMs Automated Teller Machines
AYUSH Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homoeopathy
BCG Bacillus Calmette-Guerin
BCs Business Correspondents
BPL Below Poverty Line
CMSGUY Chief Minister's Samagra Gramya Unnayan Yojana
COVID-19 Coronavirus Disease
CSCs Common Service Centres
CSDGs Centre for Sustainable Development Goals
CSOs Civil Society Organisations
CSSEIP Centre for Study of Social Exclusion and Inclusive Policy
DPC District Planning Committee
DPT Diphtheria, Pertussis and Tetanus
FPS Fair Price Shops
FRUs First Referral Units
FSI Forest Survey of India
FY Financial Year
GIZ Deutsche Gesellschaft für Internationale Zusammenarbeit
GPI Gender Parity Indices
GPs Gram Panchayats
Hb Haemoglobin
HIV Human Immunodeficiency Virus
ICDS Integrated Child Development Services
IHHL Individual Household Latrines
IMR Infant Mortality Rate
JJM Jal Jeevan Mission
MDoNER Ministry of Development of North Eastern Region
MGNREGA Mahatma Gandhi National Rural Employment Guarantee Act
MIS Management Information System
MoEFCC Ministry of Environment, Forest and Climate Change
MoHFW Ministry of Health and Family Welfare
MoSPI Ministry of Statistics and Programme Implementation
MPI Multidimensional Poverty Index
MSMEs Micro, Small and Medium Enterprises
MSW Municipal Solid Waste
NAS National Achievement Survey
NBCC Newborn Care Corner
NBSU Newborn Stabilization Unit
NCRB National Crime Records Bureau
NER North Eastern Region
NFHS National Family Health Survey
XIII
NFSA National Food Security Act
NGOs Non-governmental Organisations
NIF National Indicator Framework
NITI National Institution for Transforming India
ODF Open Defecation Free
OPV Oral Polio Vaccine
PDS Public Distribution System
PMAY Pradhan Mantri Awas Yojana
PM-DevINE Prime Minister’s Development Initiative for North East Region
PMGSY Pradhan Mantri Gram Sadak Yojana
PMJAY Pradhan Mantri Jan Arogya Yojana
PMJDY Pradhan Mantri Jan Dhan Yojana
PMMVY Pradhan Mantri Matru Vandana Yojana
PRIs Panchayati Raj Institutions
PTR Pupil-Teacher Ratio
PwD Persons with Disabilities
PWS Piped Water Supply
SBA Skilled Birth Attendant
SBM Swachh Bharat Mission
SBM(G) Swachh Bharat Mission (Gramin)
SDGCAC Sustainable Development Goals Coordination and Acceleration Centre
SDGCC Sustainable Development Goals Coordination Centre
SDGs Sustainable Development Goals
SHGs Self-Help Groups
SIF State Indicator Framework
SNCU Special Newborn Care Unit
SRB Sex Ratio at Birth
SSSG SDG Strategy Support Group
TB Tuberculosis
THR Take Home Ration
TRIPS Trade-Related Aspects of Intellectual Property Rights
U-DISE+ Unified-District Information System for Education - Plus
ULBs Urban Local Bodies
UN United Nations
UNDP United Nations Development Programme
UNFCCC United Nations Framework Convention on Climate Change
UNFPA United Nations Population Fund
USD United States Dollar
U Ts Union Territories
VCs Village Councils
VEC Village Education Committee
WHO World Health Organization
XIV
Contents
Message from Vice Chairperson, NITI Aayog II
Message from CEO, NITI Aayog IV
Message from Secretary, MDoNER VI
Message from Resident Representative, UNDP-India VIII
Acknowledgements by Programme Director (SDGs),
NITI Aayog X
List of Abbreviations XVI
Executive Summary XX
Context & Overview
PAGE 1
1.
Introduction: SDGs and the
North Eastern Region (NER) 3
I
Photo courtesy of Alen John
XV
Metadata 172
Indicator Tables 201
Methodology & Results State Profiles
PAGE 153PAGE 11
PAGE 171
II III
IV
2.
Methodology and Framework of the North
Eastern Region District SDG Index 13
3.
Composite Results: NER District SDG Index
2023-24 21
Progress on Goals:
SDG 1No Poverty
29
SDG 2Zero Hunger 37
SDG 3Good Health and Well-being 45
SDG 4Quality Education 53
SDG 5Gender Equality 61
SDG 6Clean Water and Sanitation 69
SDG 7Affordable and Clean Energy 77
SDG 8Decent Work and Economic Growth 85
SDG 9Industry, Innovation and Infrastructure 93
SDG 10Reduced Inequalities 101
SDG 11Sustainable Cities and Communities 109
SDG 12Responsible Consumption and Production 117
SDG 13Climate Action 125
SDG 15Life on Land 133
SDG 16Peace, Justice and Strong Institutions 141
4.
Way Forward:
From Analysis to Action 150
i.Arunachal Pradesh [AR] 154
ii.Assam [AS] 156
iii.Manipur [MN] 158
iv.Meghalaya [ML] 160
v.Mizoram [MZ] 162
vi. Nagaland [NL] 164
vii.Sikkim [SK] 166
viii.Tripura [TR] 168
Metadata &
Indicator Tables
XVI
1. Overview
The North Eastern Region (NER) District SDG
Index, a collaborative effort by Ministry of
Development of North Eastern Region (MDoNER)
and NITI Aayog – with technical support from
UNDP, is the first of its kind progress tracking tool
for the NER, which is of critical significance to
the country’s development trajectory. The Index
measures the performance of the NER districts
on the Sustainable Development Goals (SDGs).
It is based on the methodology adopted by the
NITI Aayog’s SDG India Index, the principal and
official tool for monitoring progress on the SDGs
at the national and State/Union Territory levels.
The NER District SDG Index is aimed at enhancing
analytical understanding of sectoral issues as well
as data gaps while assisting in designing future
courses of action in the region. The first edition of
the NER District SDG Index Report 2021–22 was
released on 26 August 2021.
2. Introduction to the second edition
Enhanced coverage of districts: While the
first edition of the index covered 103 of 120
(86 percent) districts of the North Eastern Region,
this edition covers 121 out of 131 (92 percent)
districts.
Data: The second edition of the index has 84 indi-
cators. Out of 84 indicators, data for 41 indicators
is from various ministries/departments of Union
Government and data for 43 indicators is from
State sources. A significant improvement in the
district-level reporting to the Union Government
has been noted in the index.
3. Key findings and results obtained from the
second edition
Improvement in the overall performance of
districts: In this edition of the index, 85 percent
of the districts of the NER are in the Front Runner
category (overall score 65–99) compared to the
previous edition, where 62 percent of the districts
were in this category.
District-wise performance: The scores for the 121
districts ranges from 58.71 in Longding [AR] to
81.43 in Hnahthial [MZ].
EXECUTIVE SUMMARY
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
Composite
Score
14.88%
2.48%
0.83%
4.96%
9.09%
0.83%
5.79%
6.61%
91.74%
14.05%
27.27%
14.88%
40.50%
1.65%
4.13%21.49% 74.38%
4.96% 71.90% 21.49%
7.44% 48.76% 3.31%
42.98% 42.15%
35.54%37.19%
0.83%
0.83%
9.09% 76.03%
7.44%
33.88% 47.93% 11.57%
94.21%
6.61% 92.56%
24.79% 66.12%
55.37% 39.67%
30.58% 68.60%
67.77% 29.75%
85.12%
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Figure A. Goal-Wise Percentage of Districts in Each Category
XVII
SDG 8 Decent Work and Economic Growth
There has been a substantial improvement,
with Front Runner districts increasing from
69 (67 percent) to 111 (92 percent).
SDG 7 Affordable and Clean Energy
The number of Achiever districts (score
of 100) has doubled from 7 to 14.
This goal tracks village electrification
and the use of clean cooking fuel.
SDG 15 Life on Land
There has been a significant improvement,
with 26 districts (21.5 percent) achieving
Achiever status, up from 12 districts (12
percent). Similarly, 87 districts (72 percent)
are in the Front Runner category.
SDG 16 Peace, Justice and Strong Institutions
There is a positive trend with Front Runner districts
increasing from 64 (62 percent) to 90 (74 percent).
However, number of Aspirant districts have also
increased from 1 (<1 percent) to 5 (4 percent).
SDG 2 Zero Hunger
There is significant progress, with Front Runner
districts increasing from 49 (47.5 percent) to
83 (69 percent). Number of Aspirant districts
have dropped from 21 (20 percent) to just 1.
SDG 1 No Poverty
There has been an impressive improvement,
with 36 districts (30 percent) in the Front
Runner category (score of 65-99.99), up from
21 districts (20 percent). The Aspirant category
(score of 0–49) has dropped from 20 districts
(19.5 percent) to just 3 districts (2.5 percent).
SDG 5 Gender Equality
The region now has 112 districts (93 percent) in
the Front Runner category, up from 71 districts
(69 percent) in the last edition. The Aspirant
category has nearly disappeared, dropping from
5 districts (5 percent) to just 1 district (<1 percent).
SDG 6 Clean Water and Sanitation
Over 114 districts (94 percent) are now in Front
Runner category up from 81 districts (79 percent),
reflecting the impact of Jal Jeevan Mission -
Har Ghar Nal and Swachh Bharat Mission on access
to piped water and improved sanitation facilities.
SDG 4 Quality Education
There has been a significant growth in the
Front Runner districts rising from 36 (35 percent)
to 80 (66 percent). Only 11 districts (9 percent)
remain in the Aspirant category.
SDG 3 Good Health and Well-being
There is a strong improvement in Front Runner
districts increasing from 14 (14 percent) to 48
(40 percent). The Aspirant category has reduced
from 18 (17.5 percent) to just 6 (5 percent) only.
SDG 10 Reduced Inequalities
The number of Front Runner districts has gone
down from 59 (57 percent) to 43 (35.5 percent).
33 districts (27 percent) remain in the Aspirant
category (score of 0–49), up from 12 (12 percent),
requiring focused attention on relevant indicators.
SDG 9 Industry, Innovation
and Infrastructure
There has been significant progress in
Front Runner districts, increasing from
55 (53 percent) to 92 (76 percent).
SDG 13 Climate Action
4 districts (3.3 percent) have reached Achiever status
(score of 100), and the number of Front Runner
districts have gone up from 36 (35 percent) to 59
(49 percent), However, 49 districts (41 percent) still
remain in the Aspirant category, indicating a need
for targeted action across the North Eastern region.
SDG 12 Responsible Consumption
and Production
There is a decline in Front Runner districts
from 67 (65 percent) to 51 (43 percent).
18 districts (15 percent) remain in the
Aspirant category (score of 0–49).
FIGURE B. PROGRESS BETWEEN NER DISTRICT SDG INDEX 2023-24 AND 2021-22
XVIIIState-wiseoverallperformance
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ArunachalPradesh AssamM anipur MeghalayaM izoram Nagaland Sikkim Tripura
State-wisepercentageofdistrictsin eachperformancecategory
Achiever(100)FrontRunner(65-99)Performer(50-64)Aspirant(0-49) N/A
36%
(9 Districts)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ArunachalPradesh AssamM anipur MeghalayaM izoram Nagaland Sikkim Tripura
31.25%
(5 Districts)
12.5%
(2 Districts)
56.25%
(9 Districts)
100%
(8Districts)100%
(6 Districts)
100%
(11 Districts)
83.33%
(10 Districts)
75%
(12 Districts)
8.33%
(1 District)
8.33%
(1 District)
25%
(4 Districts)
5.71%
(2 Districts)
88.57%
(31 Districts)
59.26%
(16 Districts)
7.41%
(2 Districts)
33.33%
(9 Districts)
5.71%
(2 Districts)
Index
2023-24
Index
2021-22
48%
(12 Districts)
52%
(13Districts)
69.7%
(23 Districts)
12.12%
(4 Districts)
18.18%
(6 Districts)
50%
(8 Districts)
6.25%
(1 District)
43.75%
(7 Districts)
9.09%
(1 District)
90.91%
(10 Districts)
100%
(8 Districts)
100%
(4 Districts)
91.67%
(11 Districts)
8.33%
(1 District)
27.27%
(3 Districts)
63.64%
(7 Districts)
9.09%
(1 District)
Significant improvements have been observed
in the indicators linked to the National Family
Health Survey (NFHS) in sectors such as access to
clean cooking fuel, housing, electricity, sanitation,
drinking water, bank accounts, child and maternal
health services, schooling and attendance, birth
registration, unmet need for family planning,
health insurance, among others. This momentum
will be key to closing the gap with the national
average in the short and medium term and for
states to feature among the top states in the
long term. In this context, indicator level analysis
is crucial for identifying gaps and accelerating
progress in the short term and beyond. It would
also help in addressing intra-regional and inter-dis-
trict disparities to ensure that performance is in
line with or above the national average.
FIGURE C. STATE-WISE OVERALL PERFORMANCE COMPARED TO THE PREVIOUS EDITION
Overall, there has been an increase in the proportion of
districts in the Front Runner category from 62 percent in
the last edition to 85 percent in this edition. This signifies
the impact of the national flagship schemes coupled with
the localisation efforts of the states and saturation of
benefits through initiatives like the Aspirational Districts
Programme. The state wise performance based on the
composite scores of SDGs is provided below:
XIX
CONTEXT
& OVERVIEW
I
CHAPTER 1.1. Importance of SDGs in the NER
The SDG framework represents a comprehensive
global consensus on sustainable development
priorities, encompassing economic, environmen-
tal and social dimensions. It serves as a ready
reckoner for countries to formulate policies for
sustainable development with people and their
quality and ease of living at the centre as priorities.
For India's North Eastern Region, the SDGs hold
particular significance given the region's distinc-
tive ecological, cultural, and demographic char-
acteristics. The eight states comprising the NER
—Arunachal Pradesh, Assam, Manipur, Meghalaya,
Mizoram, Nagaland, Sikkim, and Tripura—feature
unique geographical landscapes and are home
to diverse tribal communities with rich cultural
heritage. The central challenge for this region
lies in fostering development that enhances living
standards while preserving traditional knowl-
edge systems, cultural practices, and indigenous
lifestyles.
The NER District SDG Index measures the
performance of the districts of the eight States on
SDGs and their corresponding targets. The Index
is based on NITI Aayog's SDG India Index – the
principal and official tool for monitoring progress
on the SDGs at the national and State/Union
Territory levels and shares the common ethos of
benchmarking performance and ranking on the
SDGs to foster competition among the districts.
The implementation of the SDGs in the North
Eastern Region faces significant challenges rooted
in the region's unique geographic, economic, and
social landscape. Economic vulnerability stands as
a primary concern, with the incidence of poverty
(National MPI NITI Aayog, 2023) in the region
ranging from 2.6 percent in Sikkim to 27.79 percent
in Meghalaya, while the national average is 24.85
percent. This economic fragility is compounded by
heavy dependence on agriculture, particularly in
states like Nagaland and Arunachal Pradesh, where
a significant proportion of the population depends
on subsistence farming that offers little resilience
against climate shocks. The limited access to
advanced agricultural technology, quality inputs,
and modern farming techniques further constrains
agricultural diversification and productivity.
The geographical characteristics of the region
–mountainous terrain, dense forests, and border
proximity, create natural barriers to industrial
development and infrastructure expansion,
particularly in the eastern regions of Arunachal
Pradesh. These constraints have led to a stagnation
in progress toward SDG 9 (Industry, Innovation and
Infrastructure) and limited employment oppor-
tunities in modern sectors. The interconnected
nature of the SDGs becomes evident as these
infrastructure and economic challenges directly
impact the region's ability to advance on SDGs
2 (Zero Hunger), 3 (Good Health and Wellbeing),
and 4 (Quality Education), areas where states
like Arunachal Pradesh, Assam, Meghalaya, and
Nagaland show substantial room for improvement.
The social dimension reveals how these develop-
ment gaps affect vulnerable populations dispro-
portionately. Women and adolescent girls bear
the heaviest burden of health inequities, with high
rates of malnutrition and anaemia where poor
socioeconomic conditions and difficult living
environments compound health challenges.
These health issues diminish cognitive capa-
bilities and productivity, creating a cycle that
hinders economic participation and advance-
ment. These challenges directly impact progress
on SDGs 3 (Good Health and Well-being) and
5 (Gender Equality). Addressing these gender-spe-
cific health inequities is essential not only for
individual well-being but also for enabling full
economic participation of women in the region's
development.
INTRODUCTION:
SDGs AND THE
NORTHEASTERN
REGION (NER)
CHAPTER 1
3
CONTEXT & OVERVIEW
The environmental aspects of sustainable develop-
ment present perhaps the most nuanced challenge
for the NER. The region represents an ecolog-
ical treasure, accounting for 25 percent of the
country's forest cover despite comprising just 7.98
percent of the geographical area and housing 43
percent of all plant species in India. However, this rich
biodiversity is under increasing threat from unsus-
tainable agricultural practices like Jhum cultivation,
unplanned urbanisation and unscientific extraction
of natural resources. The region is already witnessing
alarming patterns of climate change with intensified
rainfall, frequent floods, emerging resilient pest
variants and steadily rising temperatures. According
to the India State of Forest Report, 2023, the North
Eastern Region recorded a decline of 327.30 square
kilometres in forest cover. These environmental
challenges directly impact the region's progress on
SDG 13 (Climate Action), SDG 15 (Life on Land), and
SDG 12 (Sustainable Consumption and Production).
Preserving the region's unique ecosystems is not
merely an environmental concern but has profound
implications for sustainable livelihoods, water secu-
rity, and disaster resilience. In response, all North
Eastern states have established climate change
monitoring cells, and states like Assam have intro-
duced policy measures such as a "green tax" on old
vehicles to encourage more sustainable practices.
The complexity of these interconnected challenges
underscores why the SDG framework is particularly
valuable for the NER, offering a comprehensive
approach that addresses these multidimensional
issues while recognizing the importance of preserv-
ing the region's unique cultural identity and envi-
ronmental heritage.
1.2. State Initiatives to Accelerate and
Localize SDGs in the North Eastern Region
Arunachal Pradesh
Arunachal Pradesh prepared its draft SDG 2030
vision report in 2016, with targets for most SDGs to
be achieved by 2019, 2022 and 2030. The document
is a comprehensive plan of action to achieve the
targets by setting baseline data and strategies to
achieve the SDGs. Government of Arunachal Pradesh
held its first SDG workshop in December 2018 with
UNDP. The Planning and Investment Division of
Finance, Planning and Investment Department is the
nodal department for implementing and monitoring
SDGs in the State, and the Secretary (Planning and
Investment) is the state nodal officer.
The Arunachal Pradesh SDG Dashboard is an effort
by the Department of Planning and Investment,
Government of Arunachal Pradesh, to track and
monitor the implementation of the different poli-
cies to achieve the SDGs. A geographic map and
heatmap feature have been developed on the dash-
board to facilitate the overall monitoring of the
status of SDGs in each district of the State. The
State has also launched the CM Dashboard with
E-Jan Bhagidari – a web portal and mobile app for
citizens' feedback and real-time monitoring of SDGs
as part of the 2022 budgetary allocation.
The state’s planned budget allocation is linked to
the SDGs, and every year, an effort is made by the
Finance, Planning & Investment Department to
review the outcomes of the plan funds and necessary
corrective measures are being made based on the
outcomes visible in the reports.
42023-24NER DISTRICT SDG INDEX
Assam
Assam was one of India's first states to adopt the SDGs
into its policy processes. In 2016, the Government
of Assam established a Centre for Sustainable
Development Goals (CSDGs), a dedicated think tank
that provides research and technical support while
also promoting awareness of SDGs among the stake-
holders and across all levels of governance. It also
guides all the departments of the State on matters
related to SDGs. In 2016, the state launched "Vision
2030", outlining the state's aspirations for holistic
development, with a strong emphasis on preserving
biodiversity as a foundation for both sustainability
and economic progress. Since May 2016, strategic and
action plans were formulated for each department
under the Transformation & Development Department's
guidance, culminating in the publication of "Assam
Agenda 2030" in April 2018. The document provided
a framework to achieve Assam vision 2030 with the
support of different stakeholders in the State, empha-
sizing the importance of the involvement of public
servants, citizens, communities, different tiers of the
local Government, and members of the civil society.
The Transformation and Development Department
serves as the nodal department for monitoring the
progress of the SDGs. To support this mandate, 10
working groups were constituted. Eventually, 10 work-
ing groups were formed to plan and follow through
with achieving the SDGs within the specified time
period. In February 2020, the state published its
comprehensive State Indicator Framework and District
Indicator Framework.
In January 2023, the T&D Department established
a Project Management Unit (PMU) emphasizing the
state's commitment to effective implementation.
Throughout 2023, sensitization sessions, consultations,
and data cleaning processes were conducted, culmi-
nating in the Assam SDG State Indicator Framework
1.0, offering a comprehensive strategy for monitoring
progress and fostering holistic development aligned
with Target 2030. The report encompasses data for
the baseline year (2019-20) and the current year
(2022-23) for 267 indicators with targets for 2030. It
serves as a vital tool for the state to assess its progress
across 16 out of 17 SDGs (excluding Goal 14) over the
specified time period.
Assam has introduced many innovative schemes at
the local level to accelerate the SDGs. For example,
the Chief Minister's Atmanirbhar Asom Abhiyan aims
to generate employment opportunities in the state
through the setting up of new entrepreneurial ventures.
The Chief Minister's Samagara Gramya Unnayan
Yoajana Samagra Gramya Unnayan Yojana (CMSGUY,
also known as the Integrated Village Development
Programme), is an initiative aimed at the holistic devel-
opment of villages, and the programme is expected
to help the State achieve several of the Global Goals.
The Government of Assam has identified 270 state
indicators and 142 district indicators based on MoSPI's
guidelines. An SDG Strategy Support Group (SSSG)
was set up to support strategic thinking and integrated
implementation and oversee SDG-related activities
such as data collection and analysis. SSSG is chaired
by the Chief Secretary of the State, with key state
Government officials as members.
Manipur
Manipur developed its Vision 2030 document:
"Ensuring no one is left behind", in 2019, by consid-
ering the developmental needs and aspirations of the
State. Preparing the preliminary draft vision document
for Manipur was entrusted to the Centre for Study of
Social Exclusion and Inclusive Policy (CSSEIP) under
Manipur Central University. The Planning Department
is the nodal department for implementing SDGs in the
State. UNDP also collaborated with the Government
of Manipur on finalising the Vision Document.
Three committees have been constituted at the state
and district levels to monitor and implement the poli-
cies and programmes to achieve the SDG vision. The
Chief Secretary chairs the State Committee on SDGs,
and it monitors the targets, goals and achievements
of the SDGs biannually. The inter-departmental work-
ing group is chaired by the Administrative Secretary
(Planning), and its role is to carry out mapping and
re-aligning targets of the various centrally sponsored
schemes in line with the goals of the SDGs, as well
as to develop a suitable State Indicator Framework
in line with the National Indicator Framework. The
district-level working group is the third committee
and is chaired by the Deputy Commissioner of each
district. The function of this committee is to re-align
targets and monitor achievements of the targets and
goals at the field level.
The Planning department of the Government of
Manipur has also developed the State Indicator
Framework, which includes 15 SDGs with 108 indica-
tors. The Government of Manipur has encouraged the
participation of all relevant stakeholders in framing
policies for achieving the vision of the SDGs in the
State. Manipur University has organised state level
consultations involving nodal officers from about 35
departments. Public consultations were also organised
to bring on board members of civil society, academia
and citizens to understand the needs of the people at
the grassroots and to rank the SDGs in order of priority.
5
CONTEXT & OVERVIEW
Meghalaya
The Government of Meghalaya formed an SDG cell at the
State level in 2018 to coordinate the preparation of the
draft "Meghalaya Vision 2030" document and the imple-
mentation of SDGs in the State. The nodal department
for implementation and monitoring of the SDGs is the
Planning Department. Meghalaya has developed its SDG
monitoring framework along the lines of MoSPI's indicator
framework. The State Indicator Framework consists of
195 indicators, of which data for 130 indicators are also
included in the District Indicator Framework and 29 Block
Level Indicators.
In November 2024, an SDG Localisation kick-off work-
shop was conducted in Meghalaya organized by NITI
Aayog, the Government of Meghalaya and GIZ under the
Green and Sustainable Development Partnership (GSDP)
Support Project. The GSDP-NITI project aims to enhance
the implementation and monitoring of SDGs at the sub-
national level through setting up SDG Acceleration Centre
in States. In this event, the Government of Meghalaya has
launched its application and data dashboard to facilitate
sustainable way of data collection. The mobile application
allows stakeholders to easily access and input SDG related
data. Simultaneously, the collected data is available for
further use through a well-designed district-wise dash-
board. Integrated within the Chief Minister’s overarching
dashboard, it reflects progress and composite scores for
all 12 districts. The Hon’ble Chief Minister of Meghalaya
announced, “CM Catalytic Fund Phase 2” in November
2024 building on the success of Phase 1, which saw a
yearly disbursement of INR 10 crores in financial support
to districts for improvement of SDGs.” This fund, designed
to address financial constraints at the grassroots level,
signifies a departure from the traditional tied-fund model.
During phase II, districts that fall into the large and small
district categories would receive a yearly allocation of
₹ 12 crores. This fund comes in the form of ₹ 4 crores in
performance-based incentives and ₹ 8 crores in untied
funds. It empowers DCs to initiate projects and interven-
tions tailored to the needs of the districts. By doing so, the
initiative aims not only to alleviate financial constraints but
also to catalyze a bottom-up approach towards enhancing
SDG performance. In 2022, the Government of Meghalaya
set aside INR 9,182 crores for funding SDGs as part of its
annual budget for 2022–23. The DC Connect platform
has also been launched to track grassroots progress,
address grievances, and monitor key development metrics
through real-time dashboards. Districts are ranked quar-
terly, with top Performers receiving additional incentives
of up to ₹ 25 lakh (large districts) and ₹ 12.5 lakh (small
districts), ensuring accountability and fostering impactful
interventions.
Mizoram
Mizoram adopted State Vision 2030, a document which
outlines the targets, strategies and budgetary allocations
to achieve the SDGs in the State. The vision document
has set targets for 2019–20, 2024–25 and 2029–30. The
Planning & Programme Implementation Department is
the Nodal Department for implementing the SDGs. The
Government has set up different bodies and committees
to monitor the implementation of the policies at different
levels. The Chief Secretary chairs the high-level moni-
toring committee to review and monitor progress. The
technical committee on SDGs is chaired by the Director
of the Economics & Statistics Department to identify indi-
cators and update data on the progress made on SDGs.
All Nodal Officers of Line Departments are members of
this technical committee. An SDG Cell has been set up
in the Research & Development Branch of the Planning
& Programme Implementation Department headed by
the Principal Adviser.
The Government of Mizoram has developed the
Consolidated Indicator Framework (CIF) comprising of
93 indicators to monitor the progress of 11 districts on
SDGs. The District Planning Committee (DPC), chaired
by the Deputy Commissioner, monitors and reviews the
progress of implementation of the SDGs at regular inter-
vals. The Village Level Monitoring Committee, chaired by
the President/Chairperson of the Village Council or Local
council, is the local layer of the monitoring framework
in Mizoram and is responsible for monitoring the SDGs
implementation at the village level.
The SDG website for Mizoram, under the Planning &
Programme Implementation Department, is an online
platform that allows users to access the SDG vision for
the State, essential documents and state policies on SDGs,
the latest state and district indicator frameworks and
the initiatives undertaken by the Government to achieve
the SDGs in the State. The state has released a report
on ‘Localisation of Sustainable Development Goals in
Mizoram’ in August 2023. The state government has part-
nered with UNDP and has developed an SDG Dashboard
for monitoring of SDGs at state, village, ULB and village
levels which was launched in 2024. In November 2024,
the Government of Mizoram, in partnership with UNDP
organised a consultation on accelerating sustainable
development in Mizoram with CSOs and CSR entities in
Bangalore to network and create partnerships with poten-
tial partners for fast-tracking sustainable development
in the state. The Government in partnership with UNDP
is also in the process of creating a CSR Matchmaking
Platform to facilitate the same.
Nagaland
The Government of Nagaland launched the "Nagaland SDG
vision 2030" and "District SDG Localisation and Integration
Manual" in 2021. The document contains state-specific
short, medium and long-term targets with measurable
indicators and strategies that the State should adopt
to meet the developmental aspirations of the State and
62023-24NER DISTRICT SDG INDEX
the needs of the people while embracing sustainability.
It has also finalised the State Indicator Framework with
125 indicators and the District Indicator Framework with
130 indicators.
The Planning & Coordination Department is the nodal
department for SDGs. The State has also established
a High-Level Steering Committee headed by the Chief
Secretary for monitoring, policy review and course correc-
tion. The State has set up a Sustainable Development
Goals Coordination Centre (SDGCC) under the Planning
and Coordination Department, with the support of UNDP,
to streamline and coordinate the different departmental
activities and provide a more holistic environment for
the Government to carry out activities related to the
SDGs. SDG cells have also been created in all the related
departments, and a nodal officer has been nominated to
monitor the progress.
The SDG Coordination Centre (SDGCC), under the
Government of Nagaland has hosted ‘SDG One Stop
Destination’ – an immersive experience for increased
awareness on SDGs at the annual Hornbill Festival since
2021. The inclusion of 'Interaction with Differently Abled
Children' as part Hornbill Festival 2023 significantly
contributed to fostering inclusivity and deepening the
understanding of diverse abilities. The state also hosts SDG
Action Awards. This Award seeks individuals, organisations,
and institutions that inspire, empower and connect people
to drive action towards a more sustainable future through
their actions. The state organises several events like SDG
poster making, essay competitions and online quizzes to
sensitise the youth on SDGs. The SDGCC Nagaland annu-
ally organises SDG Innovation and Participatory Action
Research initiative to scale up grassroot innovations for
strengthening SDG localisation. The SDGCC has also
developed the Nagaland SDG Dashboard to track the
progress of the state and its districts on the indicators
under each SDG. In 2024, the SDGCC Nagaland released
a coffee table book titled “Weaving Dreams-a tribute
to the Inspiring Women of Nagaland”, celebrating the
contributions of 21 pioneering women of the state in
various fields of development, showcasing Nagaland’s
commitment towards Gender Equality.
Sikkim
Sikkim has developed and adopted its SDG Vision 2030,
which has identified the challenges, opportunities, and
strategies to meet the SDGs. The paper draws attention to
sustainable consumption, market expansion and livelihood
development, with a particular emphasis on sustainable
tourism, health and education.
The Planning and Development Department is the nodal
Department for the implementation of the SDGs, and the
Directorate of Economics, Statistics & Monitoring within
the Planning and Development Department is the nodal
Department for monitoring SDG implementation, report-
ing the progress on SDGs and identifying areas which
require mid-course corrections. The State has prepared
its State Indicator Framework based on 14 relevant SDGs.
The Government of Sikkim has involved various stake-
holders in discussions and consultations on SDG policies.
Subsequently, it outlined the concerns of the community
and industrialists and ways to mitigate and address them.
The Government also released "The Sikkim Action Plan
on Climate Change" report, which outlined the threats
to Sikkim's biodiversity and rural communities because
of climate change, and proposed actions to be taken to
address the challenges.
Tripura
In 2019, Tripura adopted its 2030 Vision Document. The
Planning (Economics & Statistics) Department is the
nodal agency in the State for SDG implementation in the
State. Tripura has four Working Groups for SDGs – social;
economic; environmental; peace, justice and partnership.
The State government has accorded highest priority for
development efforts in infrastructure, connectivity, agricul-
ture, safe drinking water, power, health and education. The
Planning Department is tasked to bring all departments
together in achieving the Goals and targets.
Tripura finalised its State Indicator Framework compris-
ing of 172 indicators and District Indicator Framework
comprising of 79 indicators in February 2020. The high-
level monitoring committee chaired by the Chief Secretary
streamlines the activities of all the State departments
of the Government to achieve the SDGs. This reflects a
"whole-of-government" approach for sustainable devel-
opment in the State. The State has spread awareness
about SDGs to the districts and panchayats. The Planning
Department has compiled the best practices covering
all major development sectors to achieve the SDGs.
The State is also taking steps to set aside resources for
SDG-based developmental projects. A vital feature of the
vision document of the State of Tripura is its emphasis on
"leaving no one behind", aligned with the foundational
vision of the SDGs and is creating specific strategies for
the scheduled tribe population in the State.
7
CONTEXT & OVERVIEW
METHODOLOGY
& RESULTS
II
2.1. Introducing the second NER SDG
Index – process, consultations with
the States
The successful uptake of the first edition of
the NER District SDG Index has resulted in the
preparation of the second edition. Following
the consultative process involving government
officials from eight states for the first NER SDG
Index, NITI Aayog took several steps to intensify
engagement from all eight North East States for
the second edition as well. These include:
•
Actively sought feedback and clarifications
on queries on the NER District Indicator
Framework from all eight NER States;
•
Organised eight in-person SDG consulta -
tions in collaboration with UNDP and the
respective State Governments across State
capitals of the NE States to address State
specific challenges and to encourage greater
engagement and discussion with various State
departments; and
•
Supported all the North-Eastern states in
developing capacity to collate information
and progress monitoring.
The consultations were highly participatory and
chaired by the Chief Secretary or Additional Chief
Secretary of the State with representatives from
State Government departments and the district
administration. During these consultations, officials
were briefed on the NER District SDG Index and
their State performance in the previous edition,
highlighting data gaps, resolving data discrep-
ancies and receiving feedback on the proposed
indicators. The state-wise consultations provided
a space for direct interaction and deliberation
between NITI Aayog, UNDP and the concerned
State and district-level officials for fast resolution
of any data-related issues to ensure quality and
reliable data. It provided a space for the resolu-
tion of data issues, addressing State-specific data
challenges, especially definitional challenges and
data periodicity. As a result, States could provide
reliable, timely and quality data.
Consequently, the States shared data, and the
resolution of any challenge that arose was
addressed by coordinating with the concerned
departments of the State Government. Following
this process, Goal-wise and composite district
scores and rankings were computed. Subsequently,
deliberations were held between NITI Aayog and
MDoNER and the report writing, preparation, and
review were undertaken.
The second edition of the NER District SDG
Index adopts a more participatory and inclusive
approach, fostering greater ownership of the SDGs
among State departments and governments. This
process has enabled better data reporting and
timely data collection.
The Index provides an overall view of the social,
economic and environmental aspects of the NER,
while reflecting the progress made by the states
and their districts. Despite a history of under-
development, political uncertainties, insurgency
and emerging ecological concerns, the NER is
striving to do well. The North-East focused SDG
Index will closely monitor the efforts and achieve-
ments and highlight critical gaps in the region and
METHODOLOGY AND FRAMEWORK
OF THE NORTH EASTERN REGION
DISTRICT SDG INDEX
CHAPTER 2
METHODOLOGY & RESULTS
13
serve as a helpful trigger for ramping up targeted
development initiatives by the Central and State
Governments.
2.2. Objectives
The objectives of the NER SDG Index 2.0 are to:
•
Rank the districts of the eight NER States
based on their relative performance across
the 15 SDGs (excluding Goal 14 which is not
applicable and Goal 17 for its limited applica-
bility at the district level).
•
Identify critical gaps and challenges in perfor-
mance and achievements to strategize neces-
sary corrective measures.
•
Highlight intra-state and inter-state disparities
across the eight states, facilitating the design
of suitable interventions.
•
Promote competitive federalism by enabling
state-wise, district-wise, and SDG-wise
comparisons. The ranking system also serves
as a valuable tool for peer learning and perfor-
mance improvement.
•
Create a platform for collaboration and enable
districts to share and adopt best practices
from their peers.
•
Identify data gaps in the statistical system
of the States and the sectors in which robust
and more frequent data collection needs to
be instituted.
2.3. Selection of indicators
As the first step, suitable indicators from the
National Indicator Framework, SDG India Index,
and the State Indicator Framework developed
by each North Eastern State were identified and
mapped with the targets. Guided by these indi-
cator frameworks and based on extensive consul-
tations with all eight NER States, NITI Aayog
prepared a list of 84 indicators, refining them
wherever needed to aid comparison. To determine
suitable metrics for inclusion in the Index, techni-
cally sound indicators based on valid quantitative
criteria were chosen that had:
i. Relevance to the SDG targets
ii. Alignment with the NIF, SDG India Index, and
the SIFs of the NER States
iii.
Data availability at the district level for most
of the 131 districts, from the official statistical
systems
iv.
The consent of the respective State
departments
v.
Data ownership, either administrative minis-
tries/departments at the Centre, survey-de-
rived, or by the line departments in the States
vi.
Due to prevailing data gaps, a threshold of
data availability of at least 80 percent of the
State-reported indicators for any given district
was taken as the benchmark for the computa-
tion of scores. Districts that reported data for
less than this number have been mentioned
but not included in the ranking scheme, to
avoid giving any undue advantage to them.
Therefore, 121 out of the total 131 districts have
been considered for computation and ranking.
All the States, especially with newly created
districts, are encouraged to report the data for
all possible indicators in the future for maxi-
mum utility of the Index.
vii.
Sufficient data coverage, such as data for at
least 70 percent of the districts is available for
any given indicator based on its applicability.
2.4. Target setting
A suitable target value for 2030 was set for each
indicator in one of the following ways:
i.
Identifying a quantifiable national target spec-
ified by the Government of India or
ii.
Selecting a quantifiable target specified under
the SDG framework for 2030 or
iii.
Determining a quantifiable target accepted
scientifically or set by technical standards or
iv.
Computing the average of the values from
the top five scores of the base year (year
2015 or NER SDG Index 2021-22, whichever
is available).
2.5. Normalisation of raw indicator values
Normalising indicator values to a standard scale of
0 to 100 was necessary to ensure comparability,
as different indicators had different ranges of
values. For instance, while Infant Mortality Rate
(IMR) is per 1,000 live births, the poverty rate
is measured as a percentage. In the normalised
range of 0 to 100, where 0 indicates the lowest
142023-24NER DISTRICT SDG INDEX
performance and 100 implies that the target has
been achieved.
For indicators where a higher value means better
performance, for example, the proportion of insti-
tutional deliveries, the following formula was used:
Where, x = raw data value
min(x) = minimum observed value of the indicator
in the dataset
T(x) = target value for the indicator
x’ = normalised value after rescaling
For indicators where the higher value implies
lower performance, for instance, IMR, the following
formula was used:
Where, x = raw data value
max(x) = maximum observed value of the indi-
cator in the dataset
T(x) = target value for the indicator
x’ = normalised value after rescaling
Where the districts had achieved beyond the
target set, the normalised score was capped at 100.
2.6. Computation of district scores
Post normalisation of values, the district-wise
score for each Goal was computed. According to
the following formula, this was estimated as the
arithmetic mean of the normalised values of all
indicators under the Goal for each district. Equal
weight was assigned to each indicator.
Where Iij= Goal score for district i under SDG j
Nij= number of non-null indicators for district I
under SDG j
Iijk= normalised value for district i of indicator k
under SDG j
The Goal score Iij for district i under Goal j was then
computed. Based on the Goal score, the districts
were classified into four categories under each
Goal. Achiever: when the Index score equals 100;
Front Runner: when the Index score is between
65 and 100, excluding 100; Performer: when the
Index score is between 50 and 65, excluding 65;
Aspirant: when the Index score is less than 50.
2.7. Computation of composite score
The next step was the computation of composite
score for every district. The composite score is the
arithmetic mean of the Goal score for 14 Goals
1
,
for each district, assigning equal weight to each
Goal. This score is indicative of the overall position
of a district in its journey towards achieving the
SDGs. The districts were again classified into the
four categories based on their composite score
according to the following formula:
Where Ii= composite SDG index score of district i
Ni = number of Goal scores for which district I
has non-null data
Iij= goal score for district i under SDG j
Iijk= normalised value for district i of indicator k
under SDG j
2.8. Categorisation of districts
Given the reach of SDGs across a multitude of
social, political and economic spheres of life as
well as the depth of each Goal through the numer-
ous varying targets and the complex inter-relation
and interdependencies between each Goal, it is
an extremely complicated task to set up scien-
tific classes of performance for each Goal and
to tie them together. Hence, a clean and simple
mechanism of classification was adopted based
on the score of each district across the SDGs. The
districts were classified into the four categories
namely, Achiever, Front Runner, Performer and
Aspirant in accordance with their distance from
target and the category-specific score range
given above.
METHODOLOGY & RESULTS
15
1
Only districts with an Urban Local Body/Administration were considered for computing scores in Goal 11. As a result, Goal 11 scores were generated for
only 79 of the 131 districts; therefore, this Goal is not part of the computation of the overall composite score of a district. The index is guided by India's
National Indicator Framework (NIF) on SDGs. The NIF indicators on SDG 17 at present are relevant only at the national and state levels. Therefore, Goal 17
is not part of this quantitative exercise to measure district performance. Goal 14 pertains only to the marine ecosystem and is therefore not applicable.
2.9. Limitations of the Index
While the SDG NER Index is a useful instrument to
measure the progress of NER districts in adopting
and implementing the SDG agenda, the Index has
the following limitations:
i.
There is limited comparability to the SDG India
Index. The indicator sets used for the two indi-
ces are necessarily different since some indi-
cators used in the NER index are specific to
the region and are not highly relevant to other
states of the country.
ii.
The indicators and data from non-government
sources have not been included in the interest
of data comparability and uniformity. Of the
84 indicators considered for computation-
49 percent have been sourced from Union
Ministries and national-level surveys, and 51
percent from State sources.
iii.
For some indicators, data for all districts are
not available or applicable. In computing the
Index, "null" value has been assigned to these
indicators, which have not been included in
the computation.
iv.
Some recently created districts in some states
could not be included in the analysis due to
the unavailability of data for most identified
indicators.
v. If district level data was furnished for at least
80 percent of State sourced indicators, it was
considered for computation. Therefore, 121
districts out of 131 were considered for ranking
(Refer to the next page for the complete list of
districts considered for ranking).
vi.
Only districts with an Urban Local Body/
Administration were considered for comput-
ing scores in Goal 11. As a result, Goal 11 scores
were generated for only 79 of the 131 districts;
therefore, this Goal is not part of the compu-
tation of the overall composite score of a
district. The index is guided by India's National
Indicator Framework (NIF) on SDGs. The NIF
indicators on SDG 17 at present are relevant
only at the national and state levels. Therefore,
Goal 17 is not part of this quantitative exercise
to measure district performance.
2.10 Policy relevance and utility of the index
• The NER District SDG Index underscores the
importance of embedding data-backed find-
ings and analysis in the planning and deci-
sion-making processes at the level of states
and districts for targeting geographies in clos-
ing sectoral developmental gaps.
•The index provide a tool for integrating data-
based decision making by providing infor-
mation and insights which is horizontally
expansive in terms of sectors (SDGs 1–16) and
disaggregated at the level of the district to
push for balanced regional planning.
•
The index also brings focus to outcome-based
targeting, which goes beyond measuring
performance only as a function of the capacity 2023-24NER DISTRICT SDG INDEX Identified indicators fr om NIF/SD G India Inde x based on
state-wise acceptability and data availability
Rescaled each indicator; 0 denoting the lowest performance
and 100 denoting target achievement
Adopted equal weights for each indicator in line with the
internationally accepted practices
Computed each Districtss aggregate score by calculating
arithmetic mean of normalised values of all indicators
Aggregated Districts overall SDG Index score by
averaging all Goal Scores
1
2
3
4
5
Iden W L F D W L R Q
Normalisation
Weightage
Individual Goal Score
Composite Score
Figure D. Methodology -5 Steps of Computation
16
to spend allocated budgets for schemes. This
would encourage the mapping of expendi -
ture to identified gaps, and desired outcomes
to plug those gaps in order to reach out to
districts in need of budgetary allocation in a
particular sector.
•
The granular analysis provided by the NER
District SDG Index enables states to identify
specific sectors in which immediate improve-
ments can be made. By leveraging existing
government schemes and programmes, state
administrations can address the challenges
highlighted by the Index effectively. The Index
can thus act as a critical tool to guide states
in prioritising resources and directing their
efforts towards reaching out to populations in
need. States may take a regional approach to
integrate the Index into their planning process,
and identify which districts are performing
well and which are lagging behind. This can
help in devising targeted strategies to improve
outcomes across the region.
•
As a first step, at the NER or State level, the
bottom performing districts (bottom 30
percent) can be filtered for further analysis.
The goal level scores of districts, especially
those in the Aspirant (0-49) category, would
be critical to identify the broad sectors, for
example, a score of 41 in Goal 4 would neces-
sitate a closer look in the education sector for
a district. In other words, identifying the goals
in which a district has not performed well and
then following it up with a deep dive analysis
of individual indicators to truly show the gap.
This approach can help in gaining a deeper
understanding of the challenges faced by
districts and enable targeted interventions to
address the root cause of underperformance.
• By mapping the performance at the indica-
tor level to existing government schemes and
programmes, policymakers can assess the
effectiveness of these programmes and chart
a course of implementation-related action.
This approach can help in identifying the gaps
between the intended impact of government
schemes and their actual outcomes on the
ground. By addressing these gaps, policy-
makers can improve the effectiveness of the
programmes and accelerate progress.
17
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Arunachal
Pradesh (25)
Anjaw
Changlang
Dibang Valley
East Kameng
East Siang
Kamle
Kra Daadi
Kurung Kumey
Leparada
Lohit
Longding
Lower Dibang Valley
Lower Siang
Lower Subansiri
Namsai
Pakke Kessang
Papum Pare
Shi Yomi
Siang
Tawang
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam (33)
Baksa
Barpeta
Biswanath
Bongaigaon
Cachar
Charaideo
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Hojai
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Majuli
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
South Salmara Mankachar
Tinsukia
Udalguri
West Karbi Anglong
Manipur (16)
Bishnupur
Chandel
Churachandpur
Imphal East
Imphal West
Jiribam
Kakching
Kamjong
Kangpokpi
Noney
Pherzawl
Senapati
Tamenglong
Tengnoupal
Thoubal
Ukhrul
Tripura (8)
Dhalai
Gomati
Khowai
North Tripura
Sepahijala
South Tripura
Unakoti
West Tripura
Sikkim (6)
Gangtok
Gyalshing
Mangan
Namchi
Pakyong
Soreng
Nagaland (11)
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Meghalaya (11)
East Garo Hills
East Jaintia Hills
East Khasi Hills
North Garo Hills
Ri Bhoi
South Garo Hills
South West Garo Hills
South West Khasi Hills
West Garo Hills
West Jaintia Hills
West Khasi Hills
Mizoram (11)
Aizawl
Champhai
Hnahthial
Khawzawl
Kolasib
Lawngtlai
Lunglei
Mamit
Saitual
Serchhip
Siaha
TABLE A. 121 OUT OF 131 DISTRICTS CONSIDERED FOR COMPUTATION AND RANKING
Arunachal
Pradesh (2)
Bichom
Keyi Panyor
Assam (2)
Bajali
Tamulpur
Nagaland (5)
Chumoukedima
Niuland
Shamator
Tseminyu
Noklak
Meghalaya (1)
Eastern West Khasi
Hills
Manipur
All districts included
in computation and
ranking
Sikkim
All districts included
in computation and
ranking
Tripura
All districts included
in computation and
ranking
Mizoram
All districts included
in computation and
ranking
10 OUT OF 131 DISTRICTS NOT CONSIDERED FOR COMPUTATION
METHODOLOGY & RESULTS
19
Table B. Goal-wise Top* Districts
SDG 5 Gender Equality
Saitual [MZ], Wokha [NL], Mokokchung
[NL], Longleng [NL], Zunheboto [NL]
SDG 6 Clean Water and Sanitation
Saitual [MZ], Serchhip [MZ], Champhai
[MZ], Lower Dibang Valley [AR], Soreng
[SK], Lohit [AR], Leparada [AR]
SDG 8 Decent Work and Economic Growth
Lower Siang [AR], Kamrup Metropolitan [AS],
Lower Subansiri [AR], Gangtok [SK], Dimapur [NL]
SDG 7 Affordable and Clean Energy
Saitual [MZ], Soreng [SK], Leparada [AR],
Pakyong [SK], Khawzawl [MZ], Hnahthial [MZ],
Kakching [MN], Lower Siang [AR], Tengnoupal
[MN], Noney [MN], Kangpokpi [MN], Kamjong
[MN], Jiribam [MN], Pherzawl [MN]
SDG 13 Climate Action
Hnahthial [MZ], Mokokchung [NL], Khawzawl
[MZ], Phek [NL], Senapati [MN]
SDG 15 Life on Land
Hnahthial [MZ], Lower Dibang Valley [AR], Saitual
[MZ], Khawzawl [MZ], Longleng [NL], Peren [NL],
Jiribam [MN], Dima Hasao [AS], Gyalshing [SK],
Charaideo [AS], Tengnoupal [MN], Upper Siang
[AR], West Jaintia Hills [ML], Dibang Valley [AR],
Leparada [AR], Upper Subansiri [AR], Kamjong
[MN], Kiphire [NL], Kamle [AR], Kangpokpi [MN],
West Karbi Anglong [AS], Noney [MN], Lower Siang
[AR], Anjaw [AR], Siang [AR], Pherzawl [MN]
SDG 16 Peace, Justice and Strong Institutions
Kamjong [MN], Noney [MN], Hnahthial
[MZ], Pherzawl [MN], Kangpokpi [MN]
SDG 2 Zero Hunger
Champhai [MZ], Phek [NL], Kakching [MN],
South Tripura [TR], Lohit [AR], Siang [AR]
SDG 1 No Poverty
Mokokchung [NL], Gangtok [SK], Thoubal
[MN], West Tripura [TR], Saitual [MZ],
Imphal East [MN], South Tripura [TR]
SDG 4 Quality Education
West Tripura [TR], Dimapur [NL],
Gangtok [SK], Soreng [SK], East Siang
[AR], Kohima [NL], Pakyong [SK]
SDG 3 Good Health and Well-being
Upper Siang [AR], East Siang [AR],
West Siang [AR], Champhai [MZ],
Hnahthial [MZ], East Kameng [AR]
*Districts classified as "Top" are those that fall within top five rankings or have attained a score of 100.
SDG 10 Reduced Inequalities
South West Khasi Hills [ML], Pakke Kessang
[AR], East Kameng [AR], Dibang Valley [AR],
Kra Daadi [AR], East Jaintia Hills [ML]
SDG 9 Industry, Innovation and Infrastructure
Hnahthial [MZ], Champhai [MZ], West Tripura
[TR], Sepahijala [TR], Unakoti [TR], Nagaon [AS]
SDG 11 Sustainable Cities and Communities
Not considered in the composite ranking
SDG 12 Responsible Consumption
and Production
South Tripura [TR], Unakoti [TR], Gomati
[TR], Shi Yomi [AR], Kohima [NL]
202023-24NER DISTRICT SDG INDEX
All districts in Mizoram, Sikkim and Tripura fall in the Front Runner category, and there are no districts
in the Aspirant or Achiever category.
CHAPTER 3
The composite score for each district was computed
by aggregating its performance across the Goals
by taking the arithmetic mean of individual Goal
scores. The composite score ranges from 0 to 100
and denotes the district's overall achievement
in realising the targets under the Goals. A score
of 100 implies that the district has achieved the
targets set for identified indicators; a score of
0 implies that the district is at the bottom. Based on the
score, each district is categorised into one of the four
categories: i) Achiever: when the Index score equals
100; ii) Front Runner: when the Index score is between
65 and 100, excluding 100; iii) Performer: when the
Index score is between 50 and 65, excluding 65; iv)
Aspirant: when the Index score is less than 50.
3.1. Overall Performance
The index is computed for 121 districts – of which
103 districts are in the Front Runner category, and 18
districts are in the Performer category in the compos-
ite score and ranking.
•The score for the 121 districts ranges from 58.71 in
Longding [AR] to 81.43 in Hnahthial [MZ].
•Top 5 districts of the SDG NER Index are:
»Hnahthial [MZ] (score of 81.43),
»Champhai [MZ] (score of 79.86),
»Gomati [TR] (score of 78.79),
»Mokokchung [NL] (score of 78.43) and
»West Tripura [TR] (score of 77.64).
COMPOSITE RESULTS:
NER DISTRICT SDG
INDEX 2023-24
METHODOLOGY & RESULTS
Figure E. District Score Ranges among NER States
Mizoram
Nagaland
Arunachal Pradesh
Assam
Manipur
Meghalaya
Sikkim
Tripura
All Front Runner
Districts
Mixed Category
SDG Score
55 60 65
70 75 80 85
63.36
67.71 81.43
72.29 78.79
78.43
73.36
76.6471.14
58.71
59.71
74.29
73.0063.00
59.71
73.21
21
3.2. Key Insights
• Mizoram has the highest-scoring district in the
entire Northeast region (Hnahthial at 81.43)
and Arunachal Pradesh has the lowest scor-
ing district in the entire region (Longding
at 58.71).
• Nagaland exhibits widest range (15.07 points
between its highest and lowest performing
districts) indicating the significant intra-state
disparity. Sikkim has the narrowest range (5.5
points), showing the most consistent perfor-
mance across its districts.
• Tripura has the distinction of having some of
the highest-scoring districts with minimum
intra-state disparities (6.5 points).
•
Mizoram and Nagaland have some of the high-
est-scoring districts but also show significant
intra-state variation (ranges of 13.72 and 15.07,
respectively).
The districts with the highest and lowest ranks in each State are as follows:
•Arunachal Pradesh: Lower Dibang Valley
(Rank 23), Longding (Rank 121)
•
Assam: Dibrugarh (Rank 17), South Salmara-
Mankachar (Rank 118)
•
Manipur: Imphal West (Rank 24), Pherzawl
(Rank 118)
•
Meghalaya: East Khasi Hills (Rank 26), East
Jaintia Hills (Rank 114)
•Mizoram: Hnahthial (Rank 1),
Lawngtlai (Rank 86)
•
Nagaland: Mokokchung (Rank 4), Zunheboto
(Rank 110)
•
Sikkim: Gangtok (Rank 8), Gyalshing (Rank 49)
•Tripura: Gomati (Rank 3), Dhalai (Rank 33)
The top 10 districts have continued to perform well across SDG 9 (Industry, Innovation and Infrastructure)
, SDG 4 (Quality Education), SDG 15 (Life on Land), SDG 12 (Responsible Consumption and Production),
SDG 8 (Decent Work and Economic Growth), and SDG 5 (Gender Equality), with opportunities to accel-
erate further in SDG 3 (Good Health and Well-being) and SDG 10 (Reduced Inequalities).
Top 10 Districts
State District Score Rank
Mizoram Hnahthial 81.43 1
Mizoram Champhai 79.86 2
Tripura Gomati 78.79 3
Nagaland Mokokchung 78.43 4
Tripura West Tripura 77.64 5
Nagaland Kohima 76.93 6
Tripura South Tripura 76.71 7
Sikkim Gangtok 76.64 8
Mizoram Kolasib 76.50 9
Nagaland Dimapur 76.29 10
Table C. Top 10 Districts in NER District SDG Index 2023-24
222023-24NER DISTRICT SDG INDEX
The challenges among the bottom 10 districts pertain to SDG 9 (Industry, Innovation and Infrastructure),
SDG 10 (Reduced Inequalities), SDG 12 (Responsible Consumption and Production) and SDG 13
(Climate Change).
Bottom 10 Districts
State District Score Rank
Arunachal Pradesh Pakke Kessang 63.14 112
Arunachal Pradesh Anjaw 63.07 113
Meghalaya East Jaintia Hills 63.00 114
Manipur Tamenglong 62.07 115
Arunachal Pradesh Tirap 61.93 116
Arunachal Pradesh Siang 61.71 117
Assam South Salmara-Mankachar 59.71 118
Manipur Pherzawl 59.71 118
Arunachal Pradesh Kamle 58.86 120
Arunachal Pradesh Longding 58.71 121
• While the index summarises SDG-wise rela-
tive performance results, a closer look at key
indicators provides an in-depth view of the
challenges.
»The NER falls behind the national average in
the indicator on percentage of students in
grade 8 achieving the minimum proficiency
level in terms of nationally defined learning
outcomes as per the National Achievement
Survey (NAS) 2021. In the NER, 66 percent
of the districts have reported values less
than the national average (77 percent).
»Annual average dropout rate is an area
which requires attention. As many as 100
districts have an annual average dropout
rate at secondary level (Class 9–10) higher
than the India average of 14.1 percent as
per Unified- District Information System
for Education (UDISE) 2023–24. School
infrastructure remains a priority area with
significant scope for improvement.
»The NER has experienced a continuous
decline in forest area over the years, raising
significant environmental concerns. As per
the India State of Forest Report (ISFR)
2023, 72 districts reported a reduction
in forest cover compared to the previous
assessment in 2021.
Despite the challenges, significant improvements
have been observed in the indicators linked to the
National Family Health Survey (NFHS), such as
access to clean cooking fuel, housing, electricity,
sanitation, drinking water, bank accounts, child and
maternal health services, schooling and attend-
ance, birth registration, unmet need for family
planning, health insurance, among others. This
momentum will be key to closing the gap with the
national average in the short and medium term and
for states to feature among the top states in the
long term. An Increase in the proportion of districts
in the Front Runner category (overall score 65–99)
from 62 percent in the last edition to 85 percent in
this edition signifies the effect of national flagship
schemes and overall momentum and direction of
progress across goals and indicators in the NER.
In this context, indicator-level analysis is crucial
for identifying gaps and accelerating progress
at par and in the long term beyond the national
average, especially for targeting intra-region/state
disparities among districts.
»Access to clean cooking fuel as primary
source of energy for households has signif-
icantly improved in the region, however
about 75 percent of the districts fare below
the national average.
METHODOLOGY & RESULTS
Table D. Bottom 10 Districts in NER District SDG Index 2023-24
23
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE E: COMPOSITE SCORE AND RANK OF DISTRICTS IN THE NORTH EASTERN REGION
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100)
0 2010 4030 50 60 908070 100
District StateRank
Hnahthial MZ 1 81.43
Champhai MZ 2 79.86
Gomati TR 3 78.79
Mokokchung NL 4 78.43
West TR TR 5 7 7. 6 4
Kohima NL 6 76.93
South TR TR 7 76.71
Gangtok SK 8 76.64
Kolasib MZ 9 76.50
Dimapur NL 10 76.29
Aizawl MZ 11 76.07
Serchhip MZ 12 75.64
Saitual MZ 13 75.36
Namchi SK 14 75.21
Sepahijala TR 15 75.07
Khowai TR 16 74 . 6 4
Dibrugarh AS 17 74 . 29
Khawzawl MZ 17 74 . 29
North TR TR 17 74 . 29
Sivasagar AS 20 74 .0 0
Jorhat AS 21 73.79
Unakoti TR 22 73.71
Lower Dibang Valley AR 23 73.36
Imphal West MN 24 73.21
Phek NL 25 73.14
East Khasi Hills ML 26 73.00
Imphal East MN 27 72.93
Nalbari AS 28 72.86
Longleng NL 28 72.86
Goalpara AS 30 72.79
Mangan SK 31 72.50
Hojai AS 32 72.36
Dhalai TR 33 72.29
Siaha MZ 34 72.14
Peren NL 34 72.14
Tawa n g AR 36 72.07
Pakyong SK 37 72.00
Kamrup Metropolitan AS 38 71.86
Kakching MN 38 71.86
Soreng SK 38 71.86
Tinsukia AS 41 71.79
South West Garo Hills ML 41 71.79
Jiribam MN 43 71.64
Golaghat AS 44 71.50
West Garo Hills ML 44 71.50
Wokha NL 44 71.50
Lakhimpur AS 47 71.43
Thoubal MN 48 71.29
Gyalshing SK 49 71.14
Dima Hasao AS 50 70.93
East Siang AR 51 70.79
Lunglei MZ 51 70.79
Charaideo AS 53 70.71
Karimganj AS 54 70.64
Karbi Anglong AS 55 70.57
Morigaon AS 55 70.57
Tengnoupal MN 57 70.43
Dhemaji AS 58 70.21
Papum Pare AR 59 70.14
Sonitpur AS 59 70.14
Kamrup AS 61 70.07
Mon NL 62 70.00
Changlang AR 63 69.93
West Kameng AR 64 69.86
Cachar AS 65 69.79
Bishnupur MN 66 69.43
242023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE E: COMPOSITE SCORE AND RANK OF DISTRICTS IN THE NORTH EASTERN REGION
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100)
0 2010 4030 50 60 908070 100
District StateRank
Bongaigaon AS 67 69.36
Hailakandi AS 67 69.36
Ri Bhoi ML 69 69.29
Nagaon AS 70 69.21
Kurung Kumey AR 71 69.00
Namsai AR 72 68.93
Senapati MN 73 68.71
West Jaintia Hills ML 73 68.71
Ukhrul MN 75 68.64
Biswanath AS 76 68.50
Chirang AS 77 68.29
East Kameng AR 78 68.21
Mamit MZ 79 68.14
West Siang AR 80 68.07
Lohit AR 81 68.00
East Garo Hills ML 81 68.00
Dibang Valley AR 83 67. 93
Dhubri AS 84 67. 8 6
Upper Siang AR 85 67.79
Lawngtlai MZ 86 67.7 1
Darrang AS 87 67. 4 3
Leparada AR 88 67. 3 6
Majuli AS 88 67. 3 6
West Khasi Hills ML 88 67. 3 6
Upper Subansiri AR 91 67.1 4
Kokrajhar AS 91 67.1 4
South West Khasi Hills ML 93 67. 0 0
Barpeta AS 94 66.79
North Garo Hills ML 95 66.64
Kamjong MN 96 66.43
Baksa AS 97 66.29
Kiphire NL 98 66.07
Chandel MN 99 65.93
Lower Subansiri AR 100 65.86
South Garo Hills ML 101 65.79
Udalguri AS 102 65.71
Churachandpur MN 103 65.36
Kangpokpi MN 104 64.86
Tuensang NL 105 64.57
Noney MN 106 64.43
Lower Siang AR 107 64.14
West Karbi Anglong AS 108 63.86
Shi Yomi AR 109 63.43
Zunheboto NL 110 63.36
Kra Daadi AR 111 63.21
Pakke Kessang AR 112 63.14
Anjaw AR 113 63.07
East Jaintia Hills ML 114 63.00
Tamenglong MN 115 62.07
Tirap AR 116 61.93
Siang AR 117 61.71
South Salmara-Mankachar AS 118
Pherzawl MN 118 59.71
Kamle AR 120
Longding AR 121
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Niuland NL NA
Noklak NL NA
Shamator NL NA
Tseminyu NL NA
59.71
59.71
58.86
58.71
25
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A)
FIGURE F: PERFORMANCE OF DISTRICTS IN THE NORTH EASTERN REGION
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100) Not Available (N/A)
2023-24
2021-22
262023-24NER DISTRICT SDG INDEX
7.41%
(2 Districts)
5.71%
(2 Districts)
8.33%
(1 District)
33.33%
(9 Districts)
5.71%
(2 Districts)
59.26%
(16 Districts)
88.57%
(31 Districts)
25%
(4 Districts)
75%
(12 Districts)
83.33%
(10 Districts)
100%
(11 Districts)
100%
(6 Districts)
100%
(8 Districts)
8.33%
(1 District)
31.25%
(5 Districts)
56.25%
(9 Districts)
12.5%
(2 Districts)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim Tripura
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
Composite
Score
14.88%
2.48%
0.83%
4.96%
9.09%
0.83%
5.79%
6.61%
91.74%
14.05%
27.27%
14.88%
40.50%
1.65%
4.13%21.49% 74.38%
4.96% 71.90% 21.49%
7.44% 48.76% 3.31%
42.98% 42.15%
35.54%37.19%
0.83%
0.83%
9.09% 76.03%
7.44%
33.88% 47.93% 11.57%
94.21%
6.61% 92.56%
24.79% 66.12%
55.37% 39.67%
30.58% 68.60%
67.77% 29.75%
85.12%
Figure G. State-Wise Percentage of Districts in Each Performance Category
Figure H. Goal-Wise Percentage of Districts in Each Category
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Aspirant (0-49.99) Performer (50.00-64.99) Front Runner (65.00-99.99) Achiever (100) Not Available (N/A)
METHODOLOGY & RESULTS
27
Goal 1 encompasses the aim of eradicating
poverty - not only in monetary terms but in all
forms and dimensions by 2030. This involves
targeting the most vulnerable, increasing
basic resources and services, and supporting
communities affected by conflict and
climate-related disasters. It calls for continuous
monitoring of progress in social protection and
implementing nationally appropriate social
protection systems. The importance of mobilizing
resources from a variety of sources, including
through enhanced development cooperation, is
also emphasized in this goal.
Targets
1.1 By 2030, eradicate extreme poverty for all
people everywhere, currently measured as
people living on less than USD 1.25 a day
1.2 By 2030, reduce at least by half the
proportion of men, women and children of
all ages living in poverty in all its dimensions
according to national definitions
1.3 Implement nationally appropriate social
protection systems and measures for all,
including floors, and by 2030 achieve
substantial coverage of the poor and the
vulnerable
1.4 By 2030, ensure that all men and women,
in particular the poor and the vulnerable,
have equal rights to economic resources, as
well as access to basic services, ownership
and control over land and other forms of
property, inheritance, natural resources,
appropriate new technology and financial
services, including microfinance
1.5 By 2030, build the resilience of the poor
and those in vulnerable situations and
reduce their exposure and vulnerability to
climate-related extreme events and other
economic, social and environmental shocks
and disasters
1.a Ensure significant mobilization of resources
from a variety of sources, including through
enhanced development cooperation, in
order to provide adequate and predictable
means for developing countries, in particular
least developed countries, to implement
programmes and policies to end poverty in
all its dimensions
1.b Create sound policy frameworks at
the national, regional and international
levels, based on pro-poor and gender-
sensitive development strategies, to
support accelerated investment in poverty
eradication actions
29
CONTEXT & OVERVIEW
SDG 1
NO POVERTY
End poverty in all its forms everywhere
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
The score for Goal 1 ranges between 78 and 47 for the
121 districts included in the ranking and computation.
Mokokchung [NL], Gangtok [SK], and Thoubal [MN]
are the top performing districts. 36 districts fall in the
category of Front Runners and 82 in the category of Performers, while 3 districts are in the category of
Aspirants with scores less than 50.
NER District SDG Index: Goal 1
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
District StateRank
Mokokchung NL 1 78
Gangtok SK 2 77
Thoubal MN 3 74
West Tripura TR 4 73
Imphal East MN 5 72
Saitual MZ 5 72
South Tripura TR 5 72
Kohima NL 8 71
Gomati TR 9 69
East Siang AR 10 68
East Garo Hills ML 10 68
Namchi SK 10 68
Kakching MN 13 67
Ri Bhoi ML 13 67
Dimapur NL 13 67
Mon NL 13 67
Pakyong SK 13 67
Sepahijala TR 13 67
Lower Siang AR 19 66
Upper Siang AR 19 66
Dibrugarh AS 19 66
Hojai AS 19 66
Nalbari AS 19 66
Sivasagar AS 19 66
Imphal West MN 19 66
Jiribam MN 19 66
Tuensang NL 19 66
Wokha NL 19 66
Khowai TR 19 66
West Kameng AR 30 65
Majuli AS 30 65
South West Garo Hills ML 30 65
Gyalshing SK 30 65
Soreng SK 30 65
Dhalai TR 30 65
Unakoti TR 30 65
Tawa n g AR 37 64
Barpeta AS 37 64
Chirang AS 37 64
Ukhrul MN 37 64
South West Khasi Hills ML 37 64
Aizawl MZ 37 64
Kiphire NL 37 64
Longleng NL 37 64
Phek NL 37 64
Mangan SK 37 64
North Tripura TR 37 64
Siang AR 48 63
Charaideo AS 48 63
Noney MN 48 63
East Khasi Hills ML 48 63
West Garo Hills ML 48 63
Serchhip MZ 48 63
Siaha MZ 48 63
Kra Daadi AR 55 62
Jorhat AS 55 62
Lakhimpur AS 55 62
Champhai MZ 55 62
Khawzawl MZ 55 62
Kolasib MZ 55 62
Tirap AR 61 61
FIGURE 1.1: SDG 1 INDEX SCORE OF DISTRICTS
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
302023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
District StateRank
Bongaigaon AS 61 61
Goalpara AS 61 61
Golaghat AS 61 61
Kamrup AS 61 61
Karbi Anglong AS 61 61
Morigaon AS 61 61
Nagaon AS 61 61
Sonitpur AS 61 61
South Salmara-Mankachar AS 61 61
Kamjong MN 61 61
West Jaintia Hills ML 61 61
Mamit MZ 61 61
Zunheboto NL 61 61
Changlang AR 75 60
Kurung Kumey AR 75 60
Lohit AR 75 60
Papum Pare AR 75 60
West Siang AR 75 60
Dhemaji AS 75 60
Kamrup Metropolitan AS 75 60
Kokrajhar AS 75 60
Hnahthial MZ 75 60
Lower Dibang Valley AR 84 59
Karimganj AS 84 59
Tinsukia AS 84 59
Tengnoupal MN 84 59
North Garo Hills ML 84 59
South Garo Hills ML 84 59
Lunglei MZ 84 59
Baksa AS 91 58
Cachar AS 91 58
Dhubri AS 91 58
Udalguri AS 91 58
Churachandpur MN 91 58
East Jaintia Hills ML 91 58
Dibang Valley AR 97 57
Dima Hasao AS 97 57
Hailakandi AS 97 57
Bishnupur MN 97 57
Darrang AS 101 56
Peren NL 101 56
Lower Subansiri AR 103 55
Biswanath AS 103 55
Kamle AR 105 54
Leparada AR 105 54
Upper Subansiri AR 105 54
Senapati MN 105 54
Anjaw AR 109 53
Namsai AR 109 53
Pakke Kessang AR 109 53
Chandel MN 109 53
Kangpokpi MN 109 53
Lawngtlai MZ 114 52
East Kameng AR 115 51
Shi Yomi AR 115 51
Tamenglong MN 115 51
Longding AR 118 50
West Khasi Hills ML 119 49
Pherzawl MN 120 48
West Karbi Anglong MN 121 47
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
FIGURE 1.1: SDG 1 INDEX SCORE OF DISTRICTS
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
31
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 1.2: PERFORMANCE OF DISTRICTS IN SDG 1
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
322023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
1.3
Percentage of beneficiaries covered
under National Food Security Act
(NFSA), 2013
100
NFSA, 2013 is a Government of India Act that aims to provide food
and nutritional security by ensuring access to an adequate quantity
of quality food at affordable prices. It is aimed that all persons
belonging to the eligible population under NFSA, 2013, benefit from
the Act.
1.2
Headcount ratio as per the
Multidimensional Poverty Index (%)
12.43
Global SDG target 1.2 aims to reduce at least by half the proportion
of men, women
and children of all ages living in poverty in all its dimensions
according to national
definitions. According to NITI Aayog's National MPI : A Progress Review
2023, the incidence of multidimensional poverty in India was 24.85%
for the year 2015-16.
Therefore, half of this value has been taken as the target.
1.3
Persons offered employment as a
percentage of persons who demanded
employment under Mahatma Gandhi
National Rural Employment Guarantee
Act (MGNREGA)
100
The mandate of the MGNREG Act is to provide at least 100 days
of guaranteed wage employment in a financial year to every rural
household whose adult members volunteer to do unskilled work
at the time and place provided by a Program Officer. Taking into
consideration possible attrition in the labour turnout due to reasons
such as ill-health, availability of alternate employment, climatic
factors etc., the target has been fixed to be the average of the 5 best
performing districts.
1.3
Percentage of Self-Help Groups
(SHGs) provided credit linkage
100
This target corresponds to global SDG targets 1.3 and 1.4 that
aims to implement nationally appropriate social protection systems
and measures for all, in particular the poor and the vulnerable, and
ensure equal rights to economic and financial resources including
microfinance.
1.3
Percentage of women receiving
benefits under Pradhan Mantri
Matru Vandana Yojana (PMMVY) or
any other maternity related State
schemes against target
100
PMMVY is a maternity benefit programme implemented in all districts
of the country since 2017 for the welfare of pregnant women and
lactating mothers. It is aimed that all persons belonging to the eligible
population under PMMVY and other maternity related State schemes,
benefit from the programme.
1.4
Percentage of affordable houses
completed against sanctioned (rural
+urban) under Pradhan Mantri Awas
Yojana (PMAY) and related State
schemes
100
This target corresponds to the global SDG target 1.4 that aims to
ensure that all men and women, in particular the poor and the
vulnerable, have equal rights to economic resources, as well as
access to basic services.
1.3
Percentage of households with any
usual member covered by a health
scheme or health insurance
100
This target corresponds to the global SDG target 1.3 which aims
to implement nationally appropriate social protection systems and
measures for all. Worldwide, the provision of some form of universal
health coverage is regarded as a basic component of social security.
1.3
Hospital beds empanelled under
Pradhan Mantri Jan Arogya Yojana
(PMJAY) or related State schemes per
10,000 eligible population
196.89
This target corresponds to the global SDG target 1.3 which aims
to implement nationally appropriate social protection systems and
measures for all. The target has been set as the average of the best
five scores
33
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
34Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 1.3 1.2 1.3 1.3 1.3 1.4 1.3 1.3
District
Percentage of
beneficiaries
covered under
NFSA
Head count ratio
as per the Multi-
Dimensional
Poverty Index
Persons offered
employment as
a percentage
of persons who
demanded
employment
under MGNREGA
Percentage
of Self-Help
Groups (SHGs)
provided credit
linkage
Percentage of
women receiving
benefits under PM-
MVY or any other
maternity related
State schemes
against target
Percentage of
affordable houses
completed against
sanctioned (rural
+urban) under
PMAY and related
State schemes
Percentage of
households with
any usual mem-
ber covered by a
health scheme or
health insurance
Hospital beds
empanelled
under PMJAY or
related State
schemes per
10,000 eligible
population
SDG 1
Arunachal Pradesh
Anjaw 100.00 13.09 99.98 1.20 9.17 100.00 17.5 8.23 53
Bichom Null Null Null Null Null Null Null Null *
Changlang 100.00 14.39 99.97 2.17 42.42 99.71 40.5 10.49 60
Dibang Valley 100.00 10.11 99.99 14.29 4.90 100.00 28.7 33.62 57
East Kameng 100.00 22.05 100.00 5.47 0.00 99.94 25.1 12.00 51
East Siang 100.00 8.11 100.00 8.33 96.00 100.00 30.5 30.49 68
Kamle 100.00 Null 99.99 1.19 21.43 99.23 Null 2.95 54
Keyi Panyor Null Null Null Null Null Null Null Null *
Kra Daadi 100.00 18.91 100.00 20.36 69.05 98.97 24.0 3.33 62
Kurung Kumey 100.00 11.14 99.98 8.85 60.58 99.07 13.4 14.01 60
Leparada 100.00 Null 100.00 7.74 9.20 99.23 Null 20.16 54
Lohit 100.00 12.39 100.00 14.78 31.25 100.00 31.9 15.24 60
Longding 100.00 20.97 99.98 0.00 3.87 97.42 23.8 7.95 50
Lower Dibang Valley 100.00 9.08 99.99 8.94 21.51 99.56 36.8 15.87 59
Lower Siang 100.00 Null 100.00 7.51 85.10 99.83 Null 8.44 66
Lower Subansiri 100.00 6.39 95.77 12.11 117.72 99.84 24.5 19.94 55
Namsai 100.00 22.11 99.99 7.32 6.82 99.25 30.9 12.48 53
Pakke Kessang 100.00 Null 100.00 8.37 0.00 100.00 Null 16.18 53
Papum Pare 100.00 13.76 99.99 3.99 33.19 99.70 26.9 57.22 60
Shi Yomi 100.00 Null 100.00 4.32 0.00 99.68 Null 6.18 51
Siang 100.00 9.15 99.89 4.13 84.38 85.61 26.1 27.06 63
Tawang 100.00 8.46 99.93 2.95 77.33 100.00 33.5 17.63 64
Tirap 100.00 14.78 99.98 1.36 66.67 99.75 30.8 4.51 61
Upper Siang 100.00 8.74 99.96 0.75 89.08 99.27 34.6 16.98 66
Upper Subansiri 100.00 19.71 100.00 3.72 26.28 99.35 21.5 5.69 54
West Kameng 100.00 4.74 99.93 7.23 73.61 100.00 38.3 15.81 65
West Siang 100.00 13.85 99.93 9.55 45.98 99.66 26.6 18.86 60
Assam
Bajali Null Null Null Null Null Null Null Null *
Baksa 94.11 15.60 99.89 18.32 47.96 81.43 69.0 4.05 58
Barpeta 94.62 19.12 99.92 39.87 70.78 98.00 58.9 12.17 64
Biswanath 88.50 22.09 99.91 34.74 66.17 78.62 68.4 7.15 55
Bongaigaon 92.81 17.39 99.95 31.72 69.38 96.51 57.6 12.99 61
Cachar 92.60 30.58 99.84 44.43 67.43 89.76 57.9 22.77 58
Charaideo 92.46 20.10 99.97 40.64 78.31 92.90
64.9 4.17 63
Chirang 94.22 16.79 99.88 40.15 84.83 82.05 61.5 4.04 64
Darrang 92.07 23.65 99.97 34.79 46.27 96.78 53.7 8.42 56
Dhemaji 93.63 13.73 99.99 38.48 46.35 78.56 66.8 9.53 60
Dhubri 94.17 26.02 99.91 35.94 49.71 96.38 59.4 11.78 58
Dibrugarh 90.72 12.26 99.94 48.36 77.97 91.28 58.8 53.33 66
Dima Hasao 90.02 13.62 99.69 22.17 60.32 84.14 61.9 25.27 57
Goalpara 92.27 18.34 99.88 44.09 51.93 94.41 71.1 12.69 61
Golaghat 91.19 14.60 99.96 40.15 60.02 82.79 69.3 15.40 61
Hailakandi 94.68 36.22 99.92 37.76 72.78 91.05 53.6 5.37 57
Hojai 93.63 14.13 99.89 44.77 72.05 93.29 67.4 17.49 66
Jorhat 92.07 11.49 99.85 43.36 65.53 86.14 60.1 16.83 62
Kamrup 92.50 12.71 99.96 37.21 58.05 93.96 47.0 18.81 61
Kamrup Metropolitan 88.49 5.63 99.89 34.11 46.69 67.12 45.5 156.82 60
Karbi Anglong 91.59 16.20 99.98 41.90 67.65 89.36 54.1 28.51 61
Karimganj 93.06 32.93 99.99 35.81 80.42 91.44 64.4 9.55 59
Kokrajhar 92.20 18.92 99.99 33.45 76.44 88.84 50.2 17.01 60
Lakhimpur 91.83 14.06 99.92 40.56 69.40 83.28 67.0 15.49 62
Majuli 91.79 14.41 99.93 47.61 100.90 78.52 60.8 8.67 65
Morigaon 94.49 22.46 99.96 30.88 75.57 87.14 62.5 4.42 61
Nagaon 93.58 20.84 99.83 40.16 64.18 93.64 59.4 14.25 61
Nalbari 93.27 11.24 99.96 39.35 91.09 90.70 52.5 18.22 66
Sivasagar 92.45 10.28 99.97 43.19 89.24 85.22 60.7 12.41 66
Sonitpur 88.32 19.94 99.91 39.24 92.96 85.11 66.9 22.03 61
South Salmara-Mankachar 95.69 28.24 99.74 14.93 82.54 97.82 68.2 3.68 61
Tamulpur Null Null Null Null Null Null Null Null *
Tinsukia 91.25 17.66 99.97 37.83 62.50 82.80 60.0 12.95 59
Udalguri 92.47 19.16 99.86 25.84 71.40 74.94 70.6 6.05 58
West Karbi Anglong 86.37 24.09 99.88 34.06 30.75 80.09 63.1 12.71 47
Manipur
Bishnupur 100.00 6.91 99.97 50.97 73.57 2.69 9.3 55.71 57
Chandel 100.00 14.74 99.51 1.32 7.78 17.82 16.1 750.85 53
Churachandpur 100.00 15.35 99.97 16.11 28.88 11.72 18.2 1928.35 58
Imphal East 100.00 5.19 99.92 97.43 70.98 8.35 7.0 548.90 72
Imphal West 100.00 2.12 100.00 9.01 98.68 8.30 15.7 516.60 66
Jiribam 100.00 Null 100.00 76.92 16.28 1.54 Null 2906.98 66
Kakching 100.00 Null 99.98 28.44 73.04 1.26 Null 688.51 67
Kamjong 100.00 Null 99.90 3.60 3.40 Null Null 369.69 61
Kangpokpi 100.00 Null 99.81 14.29 21.72 0.00 Null 166.26 53
Noney 100.00 Null 99.67 21.11 2.34 Null Null 322.06 63
Pherzawl 100.00 Null 98.99 0.00 1.73 10.93 Null 1302.08 48
Senapati 100.00 15.60 99.99 20.00 8.82
0.00 15.4 485.27 54
Tamenglong 100.00 18.50 100.00 8.28 3.34 2.97 16.8 493.10 51
Tengnoupal 100.00 Null 99.84 34.20 8.30 12.22 Null 404.17 59
Thoubal 100.00 7.46 99.99 70.33 86.25 19.35 19.1 206.60 74
Ukhrul 100.00 17.87 99.95 40.32 11.69 Null 17.0 632.41 64
TABLE 1.1: PERFORMANCE OF DISTRICTS ON SDG 1
35Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 1.3 1.2 1.3 1.3 1.3 1.4 1.3 1.3
District
Percentage of
beneficiaries
covered under
NFSA
Head count ratio
as per the Multi-
Dimensional
Poverty Index
Persons offered
employment as
a percentage
of persons who
demanded
employment
under MGNREGA
Percentage
of Self-Help
Groups (SHGs)
provided credit
linkage
Percentage of
women receiving
benefits under PM-
MVY or any other
maternity related
State schemes
against target
Percentage of
affordable houses
completed against
sanctioned (rural
+urban) under
PMAY and related
State schemes
Percentage of
households with
any usual mem-
ber covered by a
health scheme or
health insurance
Hospital beds
empanelled
under PMJAY or
related State
schemes per
10,000 eligible
population
SDG 1
Meghalaya
East Garo Hills 100.00 14.96 99.92 34.75 166.76 38.07 71.9 25.58 68
East Jaintia Hills100.00 43.79 100.00 59.66 73.02 27.59 74.1 16.19 58
East Khasi Hills 100.00 24.10 100.00 56.95 72.50 23.90 47.1 71.66 63
Eastern West Khasi Hills Null Null Null Null Null Null Null Null *
North Garo Hills 100.00 13.26 99.96 40.72 42.26 29.16 60.8 11.67 59
Ri Bhoi 100.00 31.67 99.95 76.46 113.86 34.28 66.8 20.13 67
South Garo Hills 100.00 9.77 100.00 58.16 14.03 12.64 79.5 20.48 59
South West Garo Hills 100.00 18.27 99.98 41.74 95.67 22.97 75.1 12.36 65
South West Khasi Hills 100.00 40.98 99.99 64.26 216.44 37.57 72.3 19.52 64
West Garo Hills 100.00 8.00 99.98 37.89 47.88 30.17 77.9 30.97 63
West Jaintia Hills100.00 52.08 99.99 74.53 236.31 34.47 65.6 26.35 61
West Khasi Hills 100.00 52.48 99.98 69.71 6.17 47.15 60.1 21.79 49
Mizoram
Aizawl 100.00 0.87 100.00 7.74 59.55 95.65 37.5 39.25 64
Champhai 100.00 1.51 99.90 16.52 35.64 79.40 64.9 15.24 62
Hnahthial 100.00 Null 100.00 4.17 0.00 83.73 Null 141.19 60
Khawzawl 100.00 Null 100.00 15.14 16.98 59.66 Null 160.43 62
Kolasib 100.00 5.25 99.98 12.72 22.79 95.18 61.1 17.27 62
Lawngtlai 100.00 21.63 100.00 5.42 11.98 80.02 31.3 23.65 52
Lunglei 100.00 5.15 99.98 4.87 18.21 93.01 46.5 22.91 59
Mamit 100.00 9.29 100.00 12.87 33.74 72.55 61.7 13.65 61
Saitual 100.00 Null 100.00 19.82 38.39 75.29 Null 216.88 72
Serchhip 99.12 3.30 99.99 16.18 46.74 82.91 58.8 21.15 63
Siaha 99.92 6.90 100.00 10.94 49.58 89.51 44.2 28.91 63
Nagaland
Chumoukedima Null Null Null Null Null Null Null Null *
Dimapur 100.00 7.23 99.35 92.54 104.98 19.86 5.7 80.06 67
Kiphire 100.00 28.19 99.30 95.55 100.00 51.23 8.8 41.65 64
Kohima 100.00 6.50 99.65 100.00 124.14 13.38 26.7 82.45 71
Longleng 100.00 26.90 99.91 96.62 95.61 7.66 38.3 28.08 64
Mokokchung 100.00 7.22 99.93 100.00 146.90 87.26 22.3 47.34 78
Mon 100.00 22.95 99.85 85.54 75.43 59.35 39.3 21.59 67
Noklak Null Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null *
Peren 100.00 17.46 98.85 77.20 79.90 12.98 5.4 34.67 56
Phek 100.00 17.28 99.30 96.33 100.80
11.59 24.9 32.07 64
Shamator Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null *
Tuensang 100.00 29.21 99.89 100.00 78.37 62.14 22.0 38.12 66
Wokha 100.00 11.99 100.00 100.00 80.43 16.01 20.6 40.06 66
Zunheboto 100.00 20.31 99.97 91.44 77.95 16.88 18.1 22.90 61
Sikkim
Gangtok 100.00 2.12 99.98 15.09 Null 96.20 29.9 592.12 77
Gyalshing 100.00 2.77 99.99 19.73 Null 98.88 19.9 44.52 65
Mangan 100.00 5.17 99.87 12.59 Null 100.00 24.5 33.14 64
Namchi 100.00 2.90 99.99 29.16 Null 94.85 20.8 66.50 68
Pakyong 100.00 Null 100.00 27.72 Null 95.74 Null 20.79 67
Soreng 100.00 Null 99.99 26.28 Null 99.75 Null 4.36 65
Tripura
Dhalai 100.00 21.89 99.99 63.34 34.72 94.15 44.2 29.89 65
Gomati 100.00 9.06 100.00 71.08 50.68 91.96 29.9 20.65 69
Khowai 100.00 17.27 99.99 53.25 41.58 93.39 44.1 23.12 66
North Tripura 100.00 17.85 99.99 52.93 45.14 97.59 28.7 20.06 64
Sepahijala 100.00 12.27 99.99 55.42 53.25 95.70 31.6 16.35 67
South Tripura 100.00 11.89 99.99 80.52 55.31 90.22 37.3 28.32 72
Unakoti 100.00 24.92 99.99 68.99 50.58 98.00 28.0 20.54 65
West Tripura 100.00 6.00 99.99 58.02 65.24 94.98 28.1 84.79 73
Target 100 12.43 100.00 100.00 100 100.00 100 196.89 100
TABLE 1.1: PERFORMANCE OF DISTRICTS ON SDG 1
The SDGs aim to end all forms of hunger and
malnutrition by 2030, making sure all people
- especially children - have sufficient and nutritious
food all year. This involves promoting sustainable
agriculture, supporting small-scale farmers, and
equal access to land, technology and markets. It
also requires international cooperation to ensure
investment in infrastructure and technology to
improve agricultural productivity. The goal also
focuses at - doubling agricultural productivity,
maintaining genetic diversity of seeds, plants and
farmed animals, and strengthening capacity for
climate change adaptive agriculture.
Targets
2.1 By 2030, end hunger and ensure access by
all people, in particular the poor and people
in vulnerable situations, including infants,
to safe, nutritious and sufficient food all
year round
2.2 By 2030, end all forms of malnutrition,
including achieving, by 2025, the
internationally agreed targets on stunting
and wasting in children under 5 years of
age, and address the nutritional needs of
adolescent girls, pregnant and lactating
women and older persons
2.3 By 2030, double the agricultural productivity
and incomes of small-scale food producers,
in particular women, indigenous peoples,
family farmers, pastoralists and fishers,
including through secure and equal access to
land, other productive resources and inputs,
knowledge, financial services, markets
and opportunities for value addition and
non-farm employment
2.4 By 2030, ensure sustainable food production
systems and implement resilient agricultural
practices that increase productivity and
production, that help maintain ecosystems,
that strengthen capacity for adaptation
to climate change, extreme weather,
drought, flooding and other disasters and
progressively improve land and soil quality
2.5 By 2020, maintain the genetic diversity of
seeds, cultivated plants and farmed and
domesticated animals and their related wild
species, including through soundly managed
and diversified seed and plant banks at
the national, regional and international
levels, and promote access to and fair
and equitable sharing of benefits arising
from the utilization of genetic resources
and associated traditional knowledge, as
internationally agreed
2.a Increase investment, including through
enhanced international cooperation, in rural
infrastructure, agricultural research and
extension services, technology development
and plant and livestock gene banks in order
to enhance agricultural productive capacity
in developing countries, in particular least
developed countries
2.b Correct and prevent trade restrictions and
distortions in world agricultural markets,
including through the parallel elimination of
all forms of agricultural export subsidies and
all export measures with equivalent effect, in
accordance with the mandate of the Doha
Development Round
2.c Adopt measures to ensure the proper
functioning of food commodity markets and
their derivatives and facilitate timely access
to market information, including on food
reserves, in order to help limit extreme food
price volatility
37
CONTEXT & OVERVIEW
SDG 2
ZERO HUNGER
End hunger, achieve food security, improve nutrition and
promote sustainable agriculture
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 2
The score for Goal 2 ranges between 83 and 40 for the
121 districts included in the ranking and computation.
Champhai [MZ], Phek [NL] and Kakching [MN] are the
top performing districts. 83 districts fall in the category
of Front Runners and 37 in the category of Performers,
while 1 district is in the category of Aspirant with scores
less than 50.
FIGURE 2.1: SDG 2 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Champhai MZ 1 83
Phek NL 2 82
Kakching MN 3 80
Lohit AR 4 79
Siang AR 4 79
South Tripura TR 4 79
Serchhip MZ 7 78
Kohima NL 7 78
East Siang AR 9 77
Thoubal MN 9 77
North Garo Hills ML 9 77
Lower Dibang Valley AR 12 76
West Kameng AR 12 76
Gomati TR 12 76
West Tripura TR 12 76
Papum Pare AR 16 75
Upper Siang AR 16 75
Aizawl MZ 16 75
Longleng NL 16 75
North Tripura TR 16 75
West Siang AR 21 74
South West Garo Hills ML 21 74
Peren NL 21 74
Sepahijala TR 21 74
Barpeta AS 25 73
Sivasagar AS 25 73
Imphal East MN 25 73
Lunglei MZ 25 73
Kiphire NL 25 73
Mokokchung NL 25 73
Mon NL 25 73
Wokha NL 25 73
Anjaw AR 33 72
Lower Subansiri AR 33 72
Dibrugarh AS 33 72
Imphal West MN 33 72
Ukhrul MN 33 72
Hnahthial MZ 33 72
Namchi SK 33 72
Longding AR 40 71
Kamrup AS 40 71
Senapati MN 40 71
Kolasib MZ 40 71
Mamit MZ 40 71
Kra Daadi AR 45 70
Goalpara AS 45 70
Majuli AS 45 70
Morigaon AS 45 70
South Salmara-Mankachar AS 45 70
Hojai AS 50 69
Kamrup Metropolitan AS 50 69
East Garo Hills ML 50 69
Mangan SK 50 69
Unakoti TR 50 69
Pakke Kessang AR 55 68
Sonitpur AS 55 68
Bishnupur MN 55 68
Tamenglong MN 55 68
West Garo Hills ML 55 68
Gangtok SK 55 68
Tirap AR 61 67
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
382023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
FIGURE 2.1: SDG 2 INDEX SCORE OF DISTRICTS
District StateRank
Karbi Anglong AS 61 67
Nalbari AS 61 67
Chandel MN 61 67
South Garo Hills ML 61 67
Dimapur NL 61 67
Soreng SK 61 67
Khowai TR 61 67
Changlang AR 69 66
Dibang Valley AR 69 66
Charaideo AS 69 66
Dima Hasao AS 69 66
Golaghat AS 69 66
Churachandpur MN 69 66
Siaha MZ 69 66
Pakyong SK 69 66
Leparada AR 77 65
Darrang AS 77 65
Jorhat AS 77 65
Karimganj AS 77 65
Nagaon AS 77 65
Tuensang NL 77 65
Gyalshing SK 77 65
Bongaigaon AS 84 64
Cachar AS 84 64
Jiribam MN 84 64
East Khasi Hills ML 84 64
Lawngtlai MZ 84 64
Kamle AR 89 63
Namsai AR 89 63
Tawa n g AR 89 63
Kurung Kumey AR 92 62
Shi Yomi AR 92 62
Tinsukia AS 92 62
Kangpokpi MN 92 62
Tengnoupal MN 92 62
Zunheboto NL 92 62
East Kameng AR 98 61
Upper Subansiri AR 98 61
Dhemaji AS 98 61
Dhubri AS 98 61
West Karbi Anglong AS 98 61
West Khasi Hills ML 98 61
Hailakandi AS 104 60
Dhalai TR 104 60
Biswanath AS 106 59
Kamjong MN 106 59
Khawzawl MZ 106 59
Pherzawl MN 109 58
Lower Siang AR 110 57
Lakhimpur AS 110 57
Noney MN 110 57
East Jaintia Hills ML 110 57
South West Khasi Hills ML 110 57
West Jaintia Hills ML 110 57
Udalguri AS 116 56
Kokrajhar AS 117 55
Ri Bhoi ML 117 55
Baksa AS 119 54
Chirang AS 119 54
Saitual MZ 121 40
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
39
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) © 2022 Mapbox © Op enStreetMap
FIGURE 2.2: PERFORMANCE OF DISTRICTS IN SDG 2
2023-24
2021-22
402023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
2.1
Percentage of Fair Price Shops (FPS)
covered under online transaction
system for PDS in the district
100
Global SDG target 2.1 aims to end hunger and ensure access to
safe, nutritious and sufficient food all year round, by all. The Public
Distribution System in India facilitates the supply of food grains
and essential commodities at subsidized price to a large number
of poor people through a network of FPS. Automation of FPS is
critical for having greater transparency in the overall PDS value
chain. To encourage FPS automation, the target has been set to be
the average of the best five scores, rounded to the nearest whole
number.
2.2
Percentage of anganwadi centres
in the district with anthropometric
measurement devices (height, weight
measurement)
100
Global SDG target 2.2 aims to end all forms of malnutrition,
including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age. Availability of
anthropometric measurement devices is important to identify cases
of stunting and wasting in children under 5 years of age.
2.2
Percentage of anganwadis with own
buildings
100
Under the ICDS scheme, anganwadis function as the centre for
health, nutrition and early learning. To carry out their activities
effectively, all anganwadis must necessarily have their own buildings
that meet the guidelines specified by the Ministry of Women and
Child Development.
2.2
Percentage of children under age 5
years who are stunted
23.7
The target has been set to 23.7 percent as per the WHO Global
Nutrition Targets tracking tool
2.2
Percentage of children under age 5
years who are underweight
2.6
The target has been set to 2.6 per cent as this the corresponding
percentage of children under five years who are underweight in
upper middle-income countries as per the 2019 database of the
World Bank.
2.2
Percentage of pregnant women aged
15-49 years who are anaemic (<11.0
g/dl)
25.2
The WHO targets a 50 percent reduction of anaemia in women of
reproductive age by 2025 (Global Nutrition Targets 2025, Policy
Brief Series). Hence, 50 percent reduction from base year (2015-
16) has been set to be the target.
2.2
Percentage of children aged 6-59
months who are anaemic (<11.0 g/dl)
21
The target has been set to 21 per cent as this is the corresponding
prevalence of anaemia in children aged 6-59 months in upper
middle-income countries as per the 2019 database of the World
Bank.
2.3 Average yield of rice (kg/ha) 4114
Global SDG target 2.3 aims to double the agricultural productivity
by 2030. Hence, target is to double the agricultural productivity of
the North Eastern Region from the base year (2015-16).
2.3
Productivity of fruits and vegetables
(kg/ha)
16919.3
Global SDG target 2.3 aims to double the agricultural productivity
by 2030. The target has been set as the average of the 5 best
scores, after removing the outliers.
41
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
42Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 2.1 2.2 2.2 2.2 2.2 2.2 2.2 2.3 2.3
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage
of anganwadi
centres in the
district with
anthropometric
measurement
devices
(height, weight
measurement)
Percentage of
anganwadis
with own
buildings
Percentage of
children under
age 5 years who
are stunted
Percentage of
children under
age 5 years who
are underweight
Percentage of
pregnant wom-
en aged 15-49
years who are
anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who are
anaemic
(<11.0 g/dl)
Average yield of
rice (kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Arunachal Pradesh
Anjaw 100.00 100.00 77.84 23.6 16.0 19.7 57.1 1683.89 3705.05 72
Bichom Null Null Null Null Null Null Null Null Null *
Changlang 98.06 100.00 70.70 26.3 25.0 60.6 65.3 3368.05 6139.40 66
Dibang Valley 100.00 100.00 94.12 16.9 16.0 39.0 88.6 1800.94 3885.71 66
East Kameng 53.81 100.00 53.93 35.7 14.2 13.1 51.7 2024.78 4502.53 61
East Siang 95.70 100.00 86.10 24.6 10.3 32.8 51.5 2783.91 5573.62 77
Kamle 82.61 100.00 57.69 Null Null Null Null 2900.90 3681.61 63
Keyi Panyor Null Null Null Null Null Null Null Null Null *
Kra Daadi 82.61 100.00 62.92 28.8 14.5 2.0 62.0 3005.98 3777.14 70
Kurung Kumey 66.67 100.00 53.85 29.2 13.9 Null 62.4 3000.00 3651.01 62
Leparada 97.44 100.00 54.79 Null Null Null Null 2514.31 4373.24 65
Lohit 100.00 100.00 88.24 24.5 12.9 33.2 52.5 3199.41 5920.86 79
Longding 82.81 100.00 46.88 15.8 13.8 19.1 38.4 2639.53 1932.37 71
Lower Dibang Valley 90.91 100.00 79.89 14.3 9.7 19.6 51.5 2472.24 5121.27 76
Lower Siang 74.36 100.00 47.39 Null Null Null Null 2358.63 4992.58 57
Lower Subansiri 85.19 100.00 54.95 30.7 8.1 22.1 52.4 3098.48 4777.39 72
Namsai 85.19 100.00 61.88 28.7 17.7 52.6 59.2 3418.56 662.69 63
Pakke Kessang 100.00 100.00 80.18 Null Null Null Null 2046.63 4379.12 68
Papum Pare 97.70 100.00 68.77 29.7 15.6 18.6 53.4 3028.31 5366.88 75
Shi Yomi 92.00 100.00 53.96 Null Null Null Null 2501.28 3435.48 62
Siang 74.26 100.00 63.01 21.3 8.8 15.4 24.9 3220.38 5343.79 79
Tawang 100.00 100.00 68.53 30.4 9.0 57.4 89.6 2966.39 5002.20 63
Tirap 91.89 100.00 61.60 38.6 16.0 24.1 48.4 2189.17 4322.86 67
Upper Siang 97.06 100.00 71.79 30.4 12.0 22.4 51.0 2947.19 4673.12 75
Upper Subansiri 74.65 100.00 56.18 36.8 19.2 37.9 60.4 3164.85 2704.78 61
West Kameng 89.33 100.00 100.00 24.2 13.4 18.2 66.6 2775.30 5041.80 76
West Siang 88.44 100.00 69.92 24.5 16.2 16.8 45.6 2529.14 4750.00 74
Assam
Bajali Null Null Null Null Null Null Null Null Null *
Baksa 100.00 100.00 41.25 41.2 34.0 65.3 78.6 2575.83 11695.27 54
Barpeta 100.00 100.00 86.74 29.8 26.2 47.6 63.5 2812.09 13548.74 73
Biswanath 100.00 100.00 58.51 42.7 41.0 45.1
79.8 2549.22 13290.68 59
Bongaigaon 100.00 100.00 96.13 46.2 35.3 51.2 77.2 2845.85 12922.07 64
Cachar 100.00 100.00 46.33 28.7 38.2 44.0 61.8 2094.97 13818.73 64
Charaideo 100.00 100.00 90.87 39.0 34.8 61.6 69.7 2539.76 16601.31 66
Chirang 100.00 100.00 16.50 42.7 39.7 54.1 70.4 2715.01 12335.75 54
Darrang 100.00 100.00 79.52 42.0 33.1 51.6 66.8 2872.11 12639.94 65
Dhemaji 100.00 100.00 67.44 37.2 25.7 61.7 73.1 2176.94 13281.69 61
Dhubri 100.00 100.00 93.44 48.5 37.8 69.7 73.1 3102.67 14978.67 61
Dibrugarh 100.00 100.00 96.51 27.3 32.0 47.2 66.4 2762.68 12054.57 72
Dima Hasao 100.00 100.00 34.26 30.6 21.7 43.3 73.1 2258.64 16296.44 66
Goalpara 100.00 100.00 98.47 38.9 35.4 49.2 60.7 2949.61 13992.90 70
Golaghat 100.00 100.00 83.04 26.3 25.5 76.7 75.1 2764.54 14632.76 66
Hailakandi 100.00 100.00 52.98 42.9 42.4 58.7 59.5 2728.63 15746.56 60
Hojai 100.00 100.00 60.26 39.3 28.4 51.4 56.8 3407.33 14419.93 69
Jorhat 100.00 100.00 76.98 38.7 33.2 56.4 74.1 2911.88 15206.28 65
Kamrup 100.00 100.00 85.44 22.6 19.7 66.5 72.9 2959.47 13682.38 71
Kamrup Metropolitan 100.00 100.00 65.89 25.4 25.0 56.4 80.4 2988.20 14834.21 69
Karbi Anglong 100.00 100.00 40.31 31.6 28.2 42.1 67.5 2577.77 15147.70 67
Karimganj 100.00 100.00 81.77 29.1 52.9 41.9 64.1 2050.85 13836.29 65
Kokrajhar 100.00 100.00 26.44 34.6 35.2 59.5 74.7 2120.06 13083.62 55
Lakhimpur 100.00 100.00 30.76 38.5 34.4 42.3 69.3 1962.78 10865.45 57
Majuli 100.00 100.00 79.26 35.4 22.2 Null 73.0 2523.87 12931.75 70
Morigaon 100.00 100.00 88.54 43.2 30.5 48.0 53.3 2853.50 14410.95 70
Nagaon 100.00 100.00 99.73 38.9 32.4 62.4 68.6 2515.29 13193.33 65
Nalbari 100.00 100.00 59.23 27.5 26.7 53.2 71.0 2681.43 12661.17 67
Sivasagar 100.00 100.00 90.72 26.1 25.9 54.3 67.5 2644.51 15750.14 73
Sonitpur 100.00 100.00 73.67 36.7 21.9 47.3 69.4 2940.93 10301.63 68
South Salmara-Mankachar 100.00 100.00 73.45 38.9 27.9 37.6 69.6 3012.01 13865.11 70
Tamulpur Null Null Null Null Null Null Null Null Null *
Tinsukia 100.00 100.00 91.29 32.8 32.2 71.7 66.4 1805.51 12559.03 62
Udalguri 100.00 100.00 30.73 33.8 32.5 63.9 77.6 2594.00 11806.95 56
West Karbi Anglong 100.00 100.00 39.79 40.9 31.1 38.8 79.0 2523.54 14336.27 61
Manipur
Bishnupur 100.00 100.00 32.92 15.5 11.7 39.0 42.4 1983.48 5260.54 68
Chandel 100.00 100.00 13.47 34.0 14.7 20.3 42.4 1621.35 9914.79 67
Churachandpur 100.00 100.00 27.53 25.1 9.8 51.8 41.1 1208.40 10859.68 66
Imphal East 100.00 100.00 19.55 18.4 14.4 27.4 50.3 2208.89 13080.38 73
Imphal West 100.00 100.00 26.62 15.6 10.2 39.5 41.8 1646.39 12573.50
72
Jiribam 100.00 100.00 10.61 Null Null Null Null 1528.74 19490.64 64
Kakching 100.00 100.00 41.48 Null Null Null Null 4642.79 10839.97 80
Kamjong 100.00 100.00 15.83 Null Null Null Null 1517.41 11494.34 59
Kangpokpi 100.00 100.00 17.89 Null Null Null Null 1772.37 12411.14 62
Noney 100.00 100.00 35.16 Null Null Null Null 798.67 9397.21 57
Pherzawl 100.00 100.00 18.06 Null Null Null Null 1285.84 11664.23 58
Senapati 100.00 100.00 27.80 27.3 12.9 18.3 48.5 1771.54 10814.56 71
Tamenglong 100.00 100.00 31.77 27.1 19.3 31.4 37.0 783.92 11224.13 68
Tengnoupal 100.00 100.00 23.87 Null Null Null Null 1620.33 11441.45 62
Thoubal 100.00 100.00 26.29 31.5 14.9 32.0 39.7 4561.63 11236.48 77
Ukhrul 100.00 100.00 26.57 27.1 16.0 25.7 34.6 1528.23 10433.22 72
TABLE 2.1: PERFORMANCE OF DISTRICTS ON SDG 2
43Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 2.1 2.2 2.2 2.2 2.2 2.2 2.2 2.3 2.3
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage
of anganwadi
centres in the
district with
anthropometric
measurement
devices
(height, weight
measurement)
Percentage of
anganwadis
with own
buildings
Percentage of
children under
age 5 years who
are stunted
Percentage of
children under
age 5 years who
are underweight
Percentage of
pregnant wom-
en aged 15-49
years who are
anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who are
anaemic
(<11.0 g/dl)
Average yield of
rice (kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Meghalaya
East Garo Hills 99.68 100.00 29.61 39.7 26.5 29.1 28.0 1939.82 13378.64 69
East Jaintia Hills100.00 100.00 46.55 49.8 23.6 46.5 47.2 2201.00 5071.60 57
East Khasi Hills 90.20 100.00 52.80 44.6 23.8 43.7 39.0 1947.01 12177.38 64
Eastern West Khasi Hills Null Null Null Null Null Null Null Null Null *
North Garo Hills100.00 100.00 67.56 35.6 15.8 40.8 30.2 2741.71 12229.38 77
Ri Bhoi 25.00 100.00 64.23 42.5 29.6 65.0 45.7 3369.22 12465.73 55
South Garo Hills 76.62 100.00 31.72 29.8 20.8 33.7 33.6 2174.54 9537.71 67
South West Garo Hills100.00 100.00 49.53 32.2 26.4 37.8 35.5 3345.28 10163.92 74
South West Khasi Hills100.00 100.00 70.95 51.4 27.6 63.2 61.3 1870.11 12106.56 57
West Garo Hills 51.68 100.00 64.18 39.5 26.3 26.7 30.2 3018.02 9266.21 68
West Jaintia Hills98.67 100.00 75.23 48.7 28.3 64.6 54.6 1885.88 9414.23 57
West Khasi Hills100.00 100.00 75.49 59.0 31.1 49.6 56.2 1910.90 18165.16 61
Mizoram
Aizawl 99.31 100.00 100.00 25.3 9.6 33.4 44.0 1216.48 5895.38 75
Champhai 100.00 100.00 100.00 27.2 13.1 15.7 38.3 2994.00 5689.78 83
Hnahthial 100.00 Null Null Null Null Null Null 1283.55 35993.36 72
Khawzawl 100.00 Null Null Null Null Null Null 1792.29 8034.36 59
Kolasib 100.00 100.00 100.00 30.4 12.6 43.8 53.8 1865.34 4783.73 71
Lawngtlai 89.93 100.00 100.00 32.7 16.9 46.5 55.3 1775.52 418.94 64
Lunglei 89.19 100.00 100.00 26.5 11.1 27.5 45.7 1521.99 2729.03 73
Mamit 100.00 100.00 100.00 26.4 13.9 29.9 45.5 1279.82 47.22 71
Saitual 100.00 Null Null Null Null Null Null 1417.27 3.11 40
Serchhip 100.00 100.00 100.00 31.8 14.4 43.4 43.2 1667.22 14927.13 78
Siaha 92.31 100.00 100.00 43.8 17.6 30.0 46.4 1504.39 2306.73 66
Nagaland
Chumoukedima Null Null Null Null Null Null Null Null Null *
Dimapur 100.00 100.00 51.62 28.3 29.8 32.9 48.9 3063.15 1274.50 67
Kiphire 100.00 100.00 82.84 36.9 25.0 19.5 55.2 2354.49 10058.10 73
Kohima 100.00 100.00 64.97 28.3 22.1 3.9 38.4 2922.86 8920.65 78
Longleng 100.00 100.00 60.49 34.1 25.7 30.5 40.4 2375.19 14054.25 75
Mokokchung 100.00 100.00 52.00 31.4 22.9 11.5 35.5 2462.85 7945.12 73
Mon 100.00 100.00 63.03 35.5 23.3 27.0 39.4 2286.04 9398.80 73
Noklak Null Null Null Null Null
Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null Null *
Peren 100.00 100.00 61.83 34.9 20.7 26.4 51.0 2825.79 10968.16 74
Phek 100.00 100.00 74.49 28.0 15.6 18.2 44.9 2981.26 11699.58 82
Shamator Null Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null Null *
Tuensang 100.00 100.00 59.56 37.1 34.2 20.0 38.8 2413.69 1805.22 65
Wokha 100.00 100.00 51.68 26.3 28.0 29.8 45.4 2554.75 10163.72 73
Zunheboto 100.00 100.00 60.57 44.0 44.5 40.8 34.9 2412.06 7469.68 62
Sikkim
Gangtok 97.44 100.00 61.24 17.8 13.0 Null 49.8 1817.76 3581.95 68
Gyalshing 97.47 100.00 71.60 25.2 19.3 Null 67.1 1974.68 4089.92 65
Mangan 94.52 100.00 91.05 31.8 15.3 26.9 53.5 1511.38 3314.35 69
Namchi 99.42 100.00 79.52 24.8 7.2 Null 56.5 1968.03 4116.24 72
Pakyong 95.81 100.00 83.02 Null Null Null Null 1872.17 3614.61 66
Soreng 95.63 100.00 85.06 Null Null Null Null 1971.43 3674.09 67
Tripura
Dhalai 100.00 100.00 87.21 45.7 27.6 75.4 81.2 2882.80 14227.35 60
Gomati 100.00 100.00 94.88 22.7 29.0 52.8 70.7 3334.59 15358.73 76
Khowai 100.00 100.00 91.61 47.0 24.7 63.7 73.4 3314.31 16965.56 67
North Tripura 100.00 100.00 88.88 26.2 32.2 55.3 52.5 3011.20 15956.84 75
Sepahijala 100.00 100.00 93.35 34.5 21.0 55.8 72.1 3497.02 15611.76 74
South Tripura 100.00 100.00 94.63 25.5 21.6 57.1 59.6 3455.88 16590.63 79
Unakoti 100.00 100.00 91.78 31.8 32.0 76.7 62.8 3263.63 17362.30 69
West Tripura 100.00 100.00 86.05 30.3 21.2 56.2 54.5 3386.43 14992.47 76
Target 100 100 100 23.7 2.6 25.2 21 4114 16919.32 100
TABLE 2.1: PERFORMANCE OF DISTRICTS ON SDG 2
Good health is essential to sustainable development
and the 2030 Agenda reflects the complexity
and interconnectedness of the two. It takes into
account widening economic and social inequalities,
rapid urbanization, threats to the climate and the
environment, the continuing burden of HIV and
other infectious diseases, and emerging challenges
such as non-communicable diseases. It calls for
a renewed focus on mental health issues as well.
Universal health coverage, including financial risk
protection, access to quality essential health care
services and access to safe, effective, quality, and
affordable medicines are integral to this goal.
Targets
3.1 By 2030, reduce the global maternal mortality
ratio to less than 70 per 100,000 live births
3.2 By 2030, end preventable deaths of newborns
and children under 5 years of age, with all
countries aiming to reduce neonatal mortality
to at least as low as 12 per 1,000 live births and
under-5 mortality to at least as low as 25 per
1,000 live births
3.3 By 2030, end the epidemics of AIDS,
tuberculosis, malaria and neglected tropical
diseases and combat hepatitis, water-borne
diseases and other communicable diseases
3.4 By 2030, reduce by one third premature
mortality from non-communicable diseases
through prevention and treatment and
promote mental health and well-being
3.5 Strengthen the prevention and treatment
of substance abuse, including narcotic drug
abuse and harmful use of alcohol
3.6 By 2020, halve the number of global deaths
and injuries from road traffic accidents
3.7 By 2030, ensure universal access to sexual and
reproductive health-care services, including for
family planning, information and education,
and the integration of reproductive health into
national strategies and programmes
3.8 Achieve universal health coverage, including
financial risk protection, access to quality
essential health-care services and access to
safe, effective, quality and affordable essential
medicines and vaccines for all
3.9 By 2030, substantially reduce the number
of deaths and illnesses from hazardous
chemicals and air, water and soil pollution and
contamination
3.a Strengthen the implementation of the World
Health Organization Framework Convention on
Tobacco Control in all countries, as appropriate
3.b Support the research and development of
vaccines and medicines for the communicable
and non‑communicable diseases that primarily
affect developing countries, provide access to
affordable essential medicines and vaccines,
in accordance with the Doha Declaration on
the TRIPS Agreement and Public Health, which
affirms the right of developing countries to use
to the full the provisions in the Agreement on
Trade-Related Aspects of Intellectual Property
Rights regarding flexibilities to protect public
health, and, in particular, provide access to
medicines for all
3.c Substantially increase health financing and
the recruitment, development, training and
retention of the health workforce in developing
countries, especially in least developed
countries and small island developing States
3.d Strengthen the capacity of all countries, in
particular developing countries, for early
warning, risk reduction and management of
national and global health risks
45
CONTEXT & OVERVIEW
SDG 3
GOOD HEALTH AND WELL-BEING
Ensure healthy lives and promote well-being for all at all
ages
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) The score for Goal 3 ranges between 84 and 39 for the
121 districts included in the ranking and computation.
Upper Siang [AR], East Siang [AR] and West Siang
[AR] are the top performing districts. 48 districts fall in
the category of Front Runners and 67 in the category
of Performers, while 6 districts are in the category of
Aspirants with scores less than 50.
NER District SDG Index: Goal 3
FIGURE 3.1: SDG 3 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Upper Siang AR 1 84
East Siang AR 2 80
West Siang AR 3 77
East Kameng AR 4 76
Champhai MZ 4 76
Hnahthial MZ 4 76
Imphal West MN 7 75
Serchhip MZ 7 75
Kolasib MZ 9 74
West Khasi Hills ML 10 73
Kamrup Metropolitan AS 11 72
Longleng NL 11 72
Lohit AR 13 71
East Garo Hills ML 13 71
South West Garo Hills ML 13 71
Thoubal MN 16 70
Lower Subansiri AR 17 69
Imphal East MN 17 69
Mamit MZ 17 69
Dibang Valley AR 20 68
Tawa n g AR 20 68
West Kameng AR 20 68
Aizawl MZ 20 68
Siaha MZ 20 68
Anjaw AR 25 67
Lower Dibang Valley AR 25 67
Dhemaji AS 25 67
Nalbari AS 25 67
Bishnupur MN 25 67
East Khasi Hills ML 25 67
Ri Bhoi ML 25 67
Kiphire NL 25 67
Leparada AR 33 66
Cachar AS 33 66
Goalpara AS 33 66
Lakhimpur AS 33 66
Lunglei MZ 33 66
Gangtok SK 33 66
Kurung Kumey AR 39 65
Hailakandi AS 39 65
Jorhat AS 39 65
Kamrup AS 39 65
Karimganj AS 39 65
Majuli AS 39 65
Tinsukia AS 39 65
North Garo Hills ML 39 65
South Garo Hills ML 39 65
Saitual MZ 39 65
Upper Subansiri AR 49 64
Barpeta AS 49 64
Darrang AS 49 64
Karbi Anglong AS 49 64
Kokrajhar AS 49 64
East Jaintia Hills ML 49 64
West Garo Hills ML 49 64
Mokokchung NL 49 64
Dhalai TR 49 64
Gomati TR 49 64
Sepahijala TR 49 64
South Tripura TR 49 64
Namsai AR 61 63
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
462023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
FIGURE 3.1: SDG 3 INDEX SCORE OF DISTRICTS
District StateRank
Papum Pare AR 61 63
Tirap AR 61 63
Dhubri AS 61 63
Dibrugarh AS 61 63
Golaghat AS 61 63
Nagaon AS 61 63
Peren NL 61 63
Wokha NL 61 63
Biswanath AS 70 62
Dima Hasao AS 70 62
Sonitpur AS 70 62
Churachandpur MN 70 62
West Jaintia Hills ML 70 62
Phek NL 70 62
Zunheboto NL 70 62
Mangan SK 70 62
West Tripura TR 70 62
Bongaigaon AS 79 61
Chirang AS 79 61
Hojai AS 79 61
Morigaon AS 79 61
Chandel MN 79 61
Gyalshing SK 79 61
Khowai TR 79 61
Changlang AR 86 60
Pakke Kessang AR 86 60
Baksa AS 86 60
Kakching MN 86 60
Senapati MN 86 60
Kohima NL 86 60
Tuensang NL 86 60
Lower Siang AR 93 59
Udalguri AS 93 59
Mon NL 93 59
North Tripura TR 93 59
Siang AR 97 58
Sivasagar AS 97 58
South West Khasi Hills ML 97 58
Unakoti TR 97 58
Charaideo AS 101 57
Noney MN 101 57
Namchi SK 101 57
Khawzawl MZ 104 56
Shi Yomi AR 105 55
West Karbi Anglong AS 105 55
Lawngtlai MZ 105 55
South Salmara-Mankachar AS 108 53
Ukhrul MN 108 53
Longding AR 110 52
Tamenglong MN 110 52
Kra Daadi AR 112 51
Dimapur NL 112 51
Kamle AR 114 50
Tengnoupal MN 114 50
Pherzawl MN 116 49
Pakyong SK 117 48
Jiribam MN 118 47
Kangpokpi MN 119 45
Kamjong MN 120 40
Soreng SK 121 39
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
47
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 3.2: PERFORMANCE OF DISTRICTS IN SDG 3
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
482023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
3.1
Percentage of pregnant women
who completed 4 Antenatal Cares
(ANC) in the district
100
This target corresponds to global SDG target 3.1 that aims to reduce maternal
mortality. The antenatal period presents opportunities for reaching pregnant
women with interventions that may be vital to their health and wellbeing and that
of their infants. The WHO recommends receiving antenatal care at least four times
to increase the likelihood of receiving effective maternal health interventions
during the antenatal period.
3.1
Percentage of births attended by
skilled health personnel
100
This target corresponds to global SDG target 3.1 that aims to reduce maternal
mortality. All women should have access to skilled care during pregnancy and
childbirth to ensure prevention, detection and management of complications.
Assistance by competent health personnel working within an enabling
environment is key to lowering maternal and newborn deaths.
3.2
Percentage of children aged 9-11
months fully immunized
100
This target corresponds to the global SDG target 3.2 which aims to end
preventable deaths of newborns and children under 5 years of age. 100 percent
immunization coverage (BCG, measles, and 3 doses each of polio and DPT) is a
prerequisite to achieve this global target.
3.2 Infant Mortality Rate 11
The target has been set to 11 per cent as this is the corresponding rate of infant
mortality in upper middle-income countries as per the 2019 database of the
World Bank.
3.8
Number of functional new born
facilities (SNCU, NBSU, NBCC) per
10,000 population
3.13
Global SDG target 3.8 aims to achieve universal health coverage, including
financial risk protection, access to quality essential health-care services and
access to safe, effective, quality and affordable essential medicines and vaccines
for all. The target has been set as the average of the 5 best scores.
3.3
Number of new HIV infections per
1,000 uninfected population
0
The target is aligned with the global SDG target 3.3 that aims to end the epidemic
of AIDS by 2030.
3.8
Percentage of TB cases successfully
treated among TB cases notified to
the national health authorities
100
The target is aligned with the global SDG target 3.8 that aims to provide access
to quality essential health-care services and access to safe, effective, quality and
affordable essential medicines and vaccines for all. It is also aligned to global
SDG target 3.3.
3.4
Number of suicide deaths reported
per 1,00,000 population
3.5
Global SDG target 3.4 aims to reduce by one third premature mortality from non-
communicable diseases through prevention and treatment and promote mental
health and well-being, by 2030. Hence, the target has been set to reduce by a
third from the base year (2015) figures.
3.5
Number of de-addiction centres
(public and private) per 10,000
population
5.7
Global SDG target 3.5 aims to strengthen the prevention and treatment of
substance abuse, including narcotic drug abuse and harmful use of alcohol. The
target has been set as the average of the 5 best scores.
3.8
First Referral Units (FRUs) per
10,000 population
3.7
The target is aligned with the global SDG target 3.8 that aims to provide access
to quality essential health-care services and access to safe, effective, quality and
affordable essential medicines and vaccines for all. The target has been set as the
average of the 5 best scores.
3.c
Total physicians, nurses and
midwives per 10,000 population
45
Global SDG target 3.c aims to substantially increase health financing and the
recruitment, development, training and retention of the health workforce. The WHO,
in its report “Monitoring Health in the Sustainable Development Goals: 2017,
World Health Organization, Regional Office for South East Asia”, lays out a target
to have a skilled health professionals density (physicians/nurses/midwives per
10,000 population) of 44.5.
49
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
50Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 3.1 3.1 3.2 3.2 3.8 3.3 3.8 3.4 3.5 3.8 3.c
District
Percentage
of pregnant
women who
completed
4 ANCs in
the district
Percentage
of births
attended
by skilled
health
personnel
Percentage
of children
aged 9-11
months fully
immunized
Infant
Mortality
Rate
Number of
functional new
born facilities
(SNCU, NBSU,
NBCC) per
10,000
population
Number of
new HIV
infections
per 1,000
uninfected
population
Percentage of
TB cases suc-
cessfully treated
among TB cases
notified to the
national health
authorities
Number
of suicide
deaths
reported per
1,00,000
population
Number of
de-addiction
centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs) per
1,00,000
population
Total
physicians,
nurses and
midwives
per 10,000
population
SDG 3
Arunachal Pradesh
Anjaw 41.91 78.33 65.85 0.00 1.89 0.00 Null 4.72 4.72 0.00 28.35 67
Bichom Null Null Null Null Null Null Null Null Null Null Null *
Changlang 43.91 90.87 83.64 0.97 1.01 0.51 120.72 8.77 0.67 0.00 12.55 60
Dibang Valley 3.03 93.75 76.74 0.00 3.75 0.00 102.74 12.49 0.00 0.00 66.22 68
East Kameng 111.39 99.39 93.18 0.00 2.06 0.08 179.52 1.59 0.00 1.59 19.38 76
East Siang 86.86 100.00 98.7212.35 1.95 0.49 88.10 30.62 1.39 2.78 47.88 80
Kamle 23.53 76.12 38.78 0.00 1.80 0.00 Null 9.02 0.00 0.00 21.20 50
Keyi Panyor Null Null Null Null Null Null Null Null Null Null Null *
Kra Daadi 70.55 80.46 31.61 0.00 0.86 0.00 Null 0.00 0.00 0.00 13.70 51
Kurung Kumey 72.36 100.00 90.77 0.00 0.88 0.00 425.00 0.00 0.00 0.00 13.44 65
Leparada 41.76 98.96 89.37 0.00 2.48 0.05 Null 4.96 0.00 0.00 28.78 66
Lohit 76.87 99.15 98.7419.13 1.61 1.05 83.10 20.09 2.01 2.01 21.50 71
Longding 36.76 75.49 87.51 5.25 0.53 0.00 Null 1.77 0.00 0.00 12.89 52
Lower Dibang Valley51.50 99.30 86.99 2.16 1.48 0.52 Null 7.40 0.00 1.85 24.78 67
Lower Siang 32.00 98.99 61.9012.66 2.30 0.14 Null 27.57 0.00 0.00 36.76 59
Lower Subansiri38.08 98.04 32.2710.91 1.89 0.02 102.70 2.36 0.00 2.36 40.14 69
Namsai 80.43 97.92 105.11 7.61 0.83 3.76 96.67 6.25 1.04 1.04 13.76 63
Pakke Kessang 15.00 100.00 36.04 0.00 3.31 0.00 Null 16.53 0.00 0.00 41.33 60
Papum Pare 45.88 99.96 113.06 4.62 1.81 1.57 54.17 31.71 0.57 0.57 41.40 63
Shi Yomi 18.79 84.21 83.0222.22 1.50 0.00 Null 7.51 0.00 0.00 23.29 55
Siang 21.90 78.33 70.44 0.00 2.19 0.00 Null 9.40 0.00 0.00 32.89 58
Tawang 44.85 81.37 72.6015.22 2.20 0.02 115.15 2.00 0.00 2.00 22.60 68
Tirap 64.46 81.02 80.66 0.00 0.90 0.52 89.51 7.23 1.81 0.00 21.86 63
Upper Siang 67.61 99.22 85.5811.17 2.27 0.06 90.24 0.00 2.83 2.83 40.77 84
Upper Subansiri71.85 100.00 39.12 0.001.04 0.29 194.34 10.45 0.00 1.31 24.17 64
West Kameng 68.78 99.08 79.75 2.60 1.53 0.09 118.18 12.75 0.00 1.27 20.14 68
West Siang 74.44 99.74 89.66 8.22 1.52 0.17 113.27 1.90 1.90 1.90 26.47 77
Assam
Bajali Null Null Null Null Null Null Null Null Null Null Null *
Baksa 87.16 99.98 68.6528.66 0.59 0.00 116.07 5.89 0.00 0.11 8.14 60
Barpeta 91.49 99.76 85.11 9.92 0.35 0.03 111.60 6.55 0.18 0.18 8.44 64
Biswanath 95.01 99.96 100.84 9.10 0.59 0.01 Null 21.22 0.00 0.49 10.53 62
Bongaigaon 90.96 99.93 72.78 7.61 0.69 0.09 112.72 25.04 0.14 0.27 7.35 61
Cachar 91.06 99.72 106.97 4.16 0.40 0.02 112.22 4.66 0.63 0.12 7.22 66
Charaideo 92.22 100.00 66.7313.35 0.35 0.01 Null 16.57 0.44 0.22 7.92 57
Chirang 84.41 91.32 78.43 9.06 0.83 0.04 106.93 18.25 0.00 0.21 8.15 61
Darrang 95.08 99.99 77.27 6.70 0.59 0.06 110.34 13.46 0.65 0.32 9.99 64
Dhemaji 90.36 99.96 82.40 7.50 0.64 0.03 111.24 10.06 1.46 0.44 9.11 67
Dhubri 92.52 85.33 95.21 9.72 0.49 0.01 107.10 11.33 0.14 0.14 7.66 63
Dibrugarh 91.57 99.96 81.23 5.85 0.34 0.05 115.61 10.56 0.23 0.15 8.60 63
Dima Hasao 62.32 83.89 68.32 8.39 0.98 0.01 112.74 2.34 0.47 0.47 17.33 62
Goalpara 92.35 99.92 86.12 9.07 0.78 0.07 113.75 8.23 0.20 0.30 8.90 66
Golaghat 93.17 99.94 72.9816.98 0.52 0.06 114.13 6.47 0.28 0.28 8.45 63
Hailakandi 90.10 98.57 99.74 6.65 0.65 0.05 116.07 9.86 0.15 0.15 7.95 65
Hojai 96.07 97.24 96.83 4.87 0.35 0.03 Null 8.70 0.21 0.32 4.08 61
Jorhat 84.22 99.99 93.7311.62 0.48 0.05 117.04 8.00 0.22 0.22 10.68 65
Kamrup 93.51 99.95 87.4110.83 0.49 0.12 119.28 18.19 0.59 0.66 9.68 65
Kamrup Metropolitan132.48 99.78 121.98 4.39 0.26 0.31 121.44 24.48 5.26 0.32 9.72 72
Karbi Anglong 71.85 97.01 93.93 6.61 0.86 0.05 112.20 0.00 0.15 0.00 9.20 64
Karimganj 92.37 97.31 88.91 7.10 0.47 0.05 119.83 3.42 0.49 0.08 6.44 65
Kokrajhar 86.44 99.03 76.5710.81 0.56 0.04 112.38 1.69 0.00 0.23 10.26 64
Lakhimpur 94.91 99.99 84.67 6.68 0.58 0.02 111.52 5.66 1.06 0.10 8.89 66
Majuli 92.96 99.29 108.4817.05 0.78 0.02 Null 4.78 0.00 0.60 14.29 65
Morigaon 82.90 98.50 85.12 9.12 0.61 0.06 111.23 25.28 0.10 0.10 8.18 61
Nagaon 89.44 98.44 80.10 5.24 0.41 0.24 107.67 6.13 0.21 0.21 8.60 63
Nalbari 91.99 100.00 91.23 7.67 0.48 0.06 110.23 1.30 0.13 0.39 12.23 67
Sivasagar
92.73 99.97 65.4214.16 0.35 0.13 113.69 38.13 0.29 0.43 11.65 58
Sonitpur 83.89 98.11 73.46 4.97 0.27 0.03 112.83 0.00 0.46 0.15 5.79 62
South Salmara-Mankachar83.19 75.34 70.60 8.76 0.34 0.00 Null 3.06 0.18 0.00 3.73 53
Tamulpur Null Null Null Null Null Null Null Null Null Null Null *
Tinsukia 95.82 99.45 79.29 6.44 0.48 0.01 120.15 7.61 1.05 0.38 6.21 65
Udalguri 86.28 99.72 65.3222.29 0.57 0.02 112.38 14.43 0.00 0.24 8.39 59
West Karbi Anglong62.27 69.45 87.29 7.25 0.95 0.01 Null 3.05 0.00 0.34 7.89 55
TABLE 3.1: PERFORMANCE OF DISTRICTS ON SDG 3
51Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 3.1 3.1 3.2 3.2 3.8 3.3 3.8 3.4 3.5 3.8 3.c
District
Percentage
of pregnant
women who
completed
4 ANCs in
the district
Percentage
of births
attended
by skilled
health
personnel
Percentage
of children
aged 9-11
months fully
immunized
Infant
Mortality
Rate
Number of
functional new
born facilities
(SNCU, NBSU,
NBCC) per
10,000
population
Number of
new HIV
infections
per 1,000
uninfected
population
Percentage of
TB cases suc-
cessfully treated
among TB cases
notified to the
national health
authorities
Number
of suicide
deaths
reported per
1,00,000
population
Number of
de-addiction
centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs) per
1,00,000
population
Total
physicians,
nurses and
midwives
per 10,000
population
SDG 3
Manipur
Bishnupur 118.63 98.04 94.99 3.03 0.29 0.09 61.54 2.53 2.53 0.42 10.07 67
Chandel 23.42 96.80 83.2316.00 0.48 0.36 80.49 0.00 1.20 1.20 20.70 61
Churachandpur 50.38 95.66 118.6434.97 0.17 0.76 87.69 0.00 1.29 1.72 13.01 62
Imphal East 27.11 99.89 84.25 4.85 0.29 0.33 84.90 0.73 5.09 0.97 23.09 69
Imphal West135.12 99.93 81.62 3.52 0.15 0.47 62.33 1.93 5.60 1.35 26.29 75
Jiribam 3.25 68.75 27.05 0.00 0.46 0.07 95.45 4.56 2.28 0.00 6.16 47
Kakching 43.38 82.84 84.28 0.00 0.27 0.05 79.81 0.69 2.06 0.69 12.48 60
Kamjong 40.55 57.07 43.5020.73 0.21 0.08 11.11 0.00 2.07 0.00 6.01 40
Kangpokpi 22.21 74.87 39.90 2.68 0.26 0.10 70.50 0.52 0.52 0.00 5.88 45
Noney 64.39 66.86 65.14 0.00 0.59 0.02 81.82 0.00 1.97 0.00 11.20 57
Pherzawl 60.92 85.50 20.8915.38 0.24 0.00 Null 0.00 2.42 0.00 6.05 49
Senapati 38.28 88.65 201.65 0.49 0.35 0.16 90.73 0.00 0.70 0.35 8.97 60
Tamenglong 35.39 62.36 94.3929.98 0.45 0.01 68.75 0.00 0.00 1.11 10.03 52
Tengnoupal 34.12 92.67 30.72 0.00 0.00 0.00 67.57 3.30 1.65 0.00 13.53 50
Thoubal 73.92 99.30 94.13 0.00 0.25 0.08 81.87 0.36 3.26 0.36 23.70 70
Ukhrul 37.72 84.09 63.61 0.00 0.22 0.49 70.83 0.00 0.74 0.74 11.42 53
Meghalaya
East Garo Hills71.41 77.97 101.7316.43 0.89 0.05 87.01 2.06 0.00 6.86 19.14 71
East Jaintia Hills43.34 82.16 110.3522.99 0.73 1.70 92.82 4.07 0.00 6.51 14.15 64
East Khasi Hills90.68 81.59 76.5528.81 0.44 0.85 85.04 6.42 0.61 4.60 18.50 67
Eastern West Khasi HillsNull Null Null Null Null Null Null Null Null Null Null *
North Garo Hills84.65 66.74 85.6125.14 0.76 0.01 81.88 2.32 0.00 6.97 10.81 65
Ri Bhoi 83.42 65.13 95.6420.86 0.58 0.31 89.50 7.34 0.77 5.02 10.74 67
South Garo Hills64.25 55.58 104.3220.24 0.91 0.02 88.15 7.03 0.00 5.62 13.77 65
South West Garo Hills92.67 87.75 109.0429.16 0.68 0.02 92.61 9.01 0.00 6.20 12.50 71
South West Khasi Hills60.54 39.09 104.94
33.91 0.50 0.06 81.55 14.12 0.00 17.14 14.52 58
West Garo Hills72.94 68.41 85.1624.31 0.45 0.07 88.11 7.52 0.21 4.08 12.65 64
West Jaintia Hills34.38 74.26 124.6917.55 0.51 1.66 87.00 9.92 0.37 6.25 16.24 62
West Khasi Hills91.22 70.23 106.8119.98 1.37 0.14 92.99 11.12 0.65 5.89 17.73 73
Mizoram
Aizawl 89.72 99.92 135.2617.61 0.33 1.49 85.55 16.87 1.91 0.54 34.78 68
Champhai 77.01 98.28 97.0910.32 2.78 0.77 91.72 5.56 1.39 1.39 22.39 76
Hnahthial 75.98 97.91 99.7016.74 2.81 0.35 Null 28.08 0.00 3.51 29.14 76
Khawzawl 66.88 98.51 77.5818.59 1.36 0.49 Null 32.55 0.00 0.00 22.78 56
Kolasib 69.12 97.07 99.2314.23 0.95 0.18 93.33 9.53 2.38 2.38 19.53 74
Lawngtlai 46.14 73.30 74.2017.31 1.70 0.14 71.43 13.57 0.00 0.85 11.62 55
Lunglei 62.54 82.97 87.9310.42 1.59 0.08 88.81 4.55 0.00 0.76 23.76 66
Mamit 60.11 79.08 85.92 7.85 1.85 0.09 225.58 8.11 0.00 2.32 19.57 69
Saitual 64.15 99.74 92.5212.79 0.99 0.26 Null 15.81 0.00 1.98 19.17 65
Serchhip 61.39 99.76 97.8011.93 0.61 0.18 88.89 6.12 1.53 3.06 27.53 75
Siaha 51.64 87.68 91.1025.29 2.83 0.46 95.20 14.14 0.00 1.77 19.09 68
Nagaland
Chumoukedima Null Null Null Null Null Null Null Null Null Null Null *
Dimapur 36.09 95.86 106.5413.15 0.88 4.72 Null 22.02 1.96 0.98 14.29 51
Kiphire 53.39 89.04 42.63 6.56 1.89 0.47 Null 1.35 2.70 2.70 19.05 67
Kohima 36.06 97.50 74.5513.64 1.47 1.32 Null 5.21 1.89 0.47 18.61 60
Longleng 25.44 95.00 47.42 3.01 1.58 0.32 98.04 0.00 7.92 1.98 20.40 72
Mokokchung 53.86 98.53 64.43 7.83 1.23 0.54 57.82 1.54 3.60 0.51 18.24 64
Mon 17.99 77.15 57.86 1.23 1.92 0.32 83.28 0.00 2.80 0.40 10.83 59
Noklak Null Null Null Null Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null Null Null Null *
Peren 19.74 74.66 48.78 6.17 1.68 0.60 75.40 0.00 4.20 2.10 14.91 63
Phek 23.44 89.31 46.40 4.53 1.41 0.39 96.64 0.61 3.06 0.61 18.48 62
Shamator Null Null Null Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null Null Null Null *
Tuensang 15.44 94.65 47.68 4.02 1.31 1.84 79.52 9.33 4.67 0.93 19.69 60
Wokha 29.25 97.89 50.04 3.91 0.96 0.30 93.65 0.60 3.01 1.20 14.25 63
Zunheboto 25.05 96.89 46.08 1.20 0.71 0.23 92.00 0.00 3.55 0.71 16.70
62
Sikkim
Gangtok 70.10 99.84 73.65 2.51 0.68 0.15 92.72 37.82 2.28 0.00 60.29 66
Gyalshing 85.75 99.49 59.3035.71 2.09 0.07 88.74 53.02 0.00 1.40 28.74 61
Mangan 81.05 96.55 48.0886.21 1.83 0.09 86.08 16.02 0.00 2.29 41.41 62
Namchi 85.38 99.32 63.3218.06 0.75 0.03 82.69 48.35 0.68 0.00 26.22 57
Pakyong Null Null Null0.00 0.00 0.11 86.15 63.93 3.12 1.56 0.78 48
Soreng Null Null Null0.00 0.00 0.03 82.97 46.32 0.00 0.00 0.15 39
Tripura
Dhalai 71.07 94.48 106.59 9.35 0.69 0.57 119.15 16.13 0.00 0.53 16.21 64
Gomati 85.21 99.32 93.14 7.63 0.42 0.33 153.27 15.61 0.00 0.47 15.47 64
Khowai 82.53 98.51 84.68 6.79 0.34 0.44 92.58 19.23 0.00 0.61 12.00 61
North Tripura91.86 97.62 121.60 6.77 0.48 0.28 41.69 11.98 0.00 0.24 10.85 59
Sepahijala 80.69 98.14 111.62 3.17 0.44 0.27 269.23 17.08 0.00 0.42 13.29 64
South Tripura79.21 99.49 92.55 3.92 0.65 0.14 93.96 19.25 0.00 0.45 16.25 64
Unakoti 75.52 93.61 112.9110.65 0.40 0.24 49.69 14.47 0.00 0.36 14.10 58
West Tripura134.55 99.91 83.3521.98 0.39 0.94 111.45 26.03 0.11 0.33 24.52 62
Target 100 100 100 11 3.13 0 100 3.5 5.7 3.70 45 100
TABLE 3.1: PERFORMANCE OF DISTRICTS ON SDG 3
Achieving inclusive and quality education for all
reaffirms the belief that education is one of the
most powerful and proven vehicles for sustainable
development. This goal is aimed at ensuring that
all girls and boys complete primary and secondary
schooling by 2030 and are provided equal access
to affordable vocational training, to eliminate
gender and wealth disparities, and achieve universal
access to a quality higher education. Additionally,
it emphasizes on lifelong learning opportunities,
so as to achieve substantial adult literacy and
numeracy, and on building and upgrading existing
education facilities that are child, disability and
gender-sensitive.
Targets
4.1 By 2030, ensure that all girls and boys
complete free, equitable and quality primary
and secondary education leading to relevant
and effective learning outcomes
4.2 By 2030, ensure that all girls and boys have
access to quality early childhood development,
care and pre‑primary education so that they
are ready for primary education
4.3 By 2030, ensure equal access for all women
and men to affordable and quality technical,
vocational and tertiary education, including
university
4.4 By 2030, substantially increase the number
of youth and adults who have relevant
skills, including technical and vocational
skills, for employment, decent jobs and
entrepreneurship
4.5 By 2030, eliminate gender disparities in
education and ensure equal access to all levels
of education and vocational training for the
vulnerable, including persons with disabilities,
indigenous peoples and children in vulnerable
situations
4.6 By 2030, ensure that all youth and a substantial
proportion of adults, both men and women,
achieve literacy and numeracy
4.7 By 2030, ensure that all learners acquire the
knowledge and skills needed to promote
sustainable development, including, among
others, through education for sustainable
development and sustainable lifestyles, human
rights, gender equality, promotion of a culture
of peace and non-violence, global citizenship
and appreciation of cultural diversity and
of culture’s contribution to sustainable
development
4.a Build and upgrade education facilities that
are child, disability and gender sensitive
and provide safe, non-violent, inclusive and
effective learning environments for all
4.b By 2020, substantially expand globally the
number of scholarships available to developing
countries, in particular, least developed
countries, small island developing States and
African countries, for enrolment in higher
education, including vocational training and
information and communications technology,
technical, engineering and scientific
programmes, in developed countries and other
developing countries
4.c By 2030, substantially increase the supply
of qualified teachers, including through
international cooperation for teacher
training in developing countries, especially
least developed countries and small island
developing States
53
CONTEXT & OVERVIEW
SDG 4
QUALITY EDUCATION
Ensure inclusive and equitable quality education and
promote lifelong learning opportunities for all.
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 4
The score for Goal 4 ranges between 88 and 38 for the
121 districts included in the ranking and computation.
West Tripura [TR], Dimapur [NL] and Gangtok [SK]
are the top performing districts. 80 districts fall in the
category of Front Runners and 30 in the category of Performers, while 11 districts are in the category of
Aspirants with scores less than 50.
FIGURE 4.1: SDG 4 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
West Tripura TR 1 88
Dimapur NL 2 86
Gangtok SK 2 86
Soreng SK 4 85
East Siang AR 5 83
Kohima NL 5 83
Pakyong SK 5 83
Imphal West MN 8 82
Aizawl MZ 8 82
Gyalshing SK 8 82
Namchi SK 8 82
Tawa n g AR 12 81
Kamrup Metropolitan AS 12 81
Mokokchung NL 14 79
Mangan SK 14 79
Dibang Valley AR 16 78
Sivasagar AS 16 78
Khowai TR 16 78
South Tripura TR 16 78
West Siang AR 20 77
Saitual MZ 20 77
Gomati TR 20 77
Leparada AR 23 75
Lower Dibang Valley AR 23 75
Kolasib MZ 23 75
Phek NL 23 75
Sepahijala TR 23 75
Unakoti TR 23 75
Charaideo AS 29 74
Darrang AS 29 74
Dhemaji AS 29 74
Dibrugarh AS 29 74
Jorhat AS 29 74
Dima Hasao AS 34 73
Kamrup AS 34 73
Champhai MZ 34 73
North Tripura TR 34 73
Morigaon AS 38 72
Thoubal MN 38 72
Siaha MZ 38 72
Lohit AR 41 71
Papum Pare AR 41 71
Golaghat AS 41 71
Nalbari AS 41 71
Senapati MN 41 71
Longleng NL 41 71
West Kameng AR 47 70
Baksa AS 47 70
Lakhimpur AS 47 70
Tinsukia AS 47 70
Udalguri AS 47 70
Imphal East MN 47 70
Hnahthial MZ 47 70
Tuensang NL 47 70
Lower Subansiri AR 55 69
Upper Subansiri AR 55 69
Zunheboto NL 55 69
Kurung Kumey AR 58 68
Siang AR 58 68
Sonitpur AS 58 68
Changlang AR 61 67
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
542023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0 2010 4030 50 60 908070 100
FIGURE 4.1: SDG 4 INDEX SCORE OF DISTRICTS
District StateRank
Lower Siang AR 61 67
Biswanath AS 61 67
Cachar AS 61 67
Goalpara AS 61 67
Kokrajhar AS 61 67
Khawzawl MZ 61 67
Wokha NL 61 67
Dhalai TR 61 67
Chirang AS 70 66
Hojai AS 70 66
Karbi Anglong AS 70 66
Bishnupur MN 70 66
Kamjong MN 70 66
East Kameng AR 75 65
Kamle AR 75 65
Tirap AR 75 65
Barpeta AS 75 65
Nagaon AS 75 65
Serchhip MZ 75 65
Kra Daadi AR 81 64
Longding AR 81 64
Upper Siang AR 81 64
Karimganj AS 81 64
Majuli AS 81 64
Lunglei MZ 81 64
Mamit MZ 81 64
Namsai AR 88 63
Pakke Kessang AR 88 63
Bongaigaon AS 88 63
Dhubri AS 88 63
Hailakandi AS 88 63
West Karbi Anglong AS 88 63
Chandel MN 88 63
Kiphire NL 88 63
Peren NL 88 63
Kakching MN 97 62
Ukhrul MN 97 62
East Khasi Hills ML 97 62
Mon NL 97 62
Shi Yomi AR 101 61
South Salmara-Mankachar AS 101 61
Churachandpur MN 101 61
Tamenglong MN 101 61
Jiribam MN 105 60
Kangpokpi MN 106 57
Tengnoupal MN 106 57
East Garo Hills ML 108 51
Ri Bhoi ML 108 51
Anjaw AR 110 50
West Jaintia Hills ML 111 47
East Jaintia Hills ML 112 46
Lawngtlai MZ 112 46
Pherzawl MN 114 45
South West Garo Hills ML 115 43
South West Khasi Hills ML 115 43
West Garo Hills ML 115 43
Noney MN 118 42
South Garo Hills ML 119 41
North Garo Hills ML 120 38
West Khasi Hills ML 120 38
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
55
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 4.2: PERFORMANCE OF DISTRICTS IN SDG 4
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
562023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
4.1
Average annual dropout rate at
secondary level (Class 9-10)
3.21
This target corresponds to the global SDG target 4.1 which aims to
ensure that all girls and boys complete free, equitable and quality
primary and secondary education. The National Education Policy,
2020 also aims to curtail drop-out rates with a goal to achieve 100
per cent Gross Enrolment Ratio in preschool to secondary level by
2030. Average of the 5 best scores has been set as the target.
4.5
Ratio of female to male enrolment at
secondary level (Class 9-10)
1
This target is aligned with the global SDG target 4.5 which aims to
eliminate gender disparities in education.
4.1
Percentage of students in grade
VIII achieving at least a minimum
proficiency level in terms of nationally
defined learning outcomes to be
attained at the end of the grade
100
This target corresponds to the global SDG target 4.1 which aims to
ensure that all girls and boys complete free, equitable and quality
primary and secondary education with relevant and effective learning
outcomes.
4.a
Percentage of schools with computers
available
100
The National Education Policy 2020 aims to provide effective and
sufficient infrastructure so that all students have access to safe and
engaging school education at all levels from pre-primary school
to Grade 12. It aims to take special care to ensure that no school
remains deficient on infrastructure support.
4.a
Percentage of schools with access to
electricity
100
The National Education Policy 2020 aims to provide effective and
sufficient infrastructure so that all students have access to safe and
engaging school education at all levels from pre-primary school
to Grade 12. It aims to take special care to ensure that no school
remains deficient on infrastructure support.
4.c
Percentage of trained teachers at
secondary level (Class 9-10)
100
This target is aligned with global SDG target 4.c which aims to
substantially increase the supply of qualified teachers.
4.c
Pupil Teacher Ratio at secondary level
(Class 9-10)
30
The National Education Policy 2020 proposes to ensure a pupil-tea-
cher ratio (PTR) of under 30:1 at each level of school education.
57
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
58Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 4.1 4.5 4.1 4.a 4.a 4.c 4.c
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of female to
male enrolment
at secondary level
(Class 9-10)
Percentage of students in grade 8
achieving at least a minimum pro-
ficiency level in terms of nationally
defined learning outcomes to be
attained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary level
(Class 9-10)
Pupil Teacher Ratio
at secondary level
(Class 9-10)
SDG 4
Arunachal Pradesh
Anjaw 35.62 0.85 69.5 16.22 91.89 91.67 7.70 50
Bichom Null Null Null Null Null Null Null *
Changlang 27.33 1.09 60 35.84 88.55 89.11 13.72 67
Dibang Valley 17.14 1.18 81.5 34.78 86.96 100.00 3.24 78
East Kameng 20.93 1.01 66.5 33.53 45.29 95.80 9.04 65
East Siang 10.22 1.01 83.5 51.85 97.53 93.37 7.97 83
Kamle 27.49 1.36 85 22.78 39.24 97.96 9.07 65
Keyi Panyor Null Null Null Null Null Null Null *
Kra Daadi 20.75 1.29 74.5 18.80 48.87 91.44 7.24 64
Kurung Kumey 34.99 1.03 69 36.36 88.89 94.81 4.74 68
Leparada 11.81 1.04 73 42.86 63.49 97.32 5.77 75
Lohit 17.25 1.20 68 49.06 69.81 88.06 11.58 71
Longding 14.37 1.02 57.5 36.79 42.45 90.39 12.98 64
Lower Dibang Valley 20.65 0.96 81 67.00 79.00 94.26 8.04 75
Lower Siang 20.62 0.98 70 50.00 59.46 89.96 5.49 67
Lower Subansiri 16.79 0.91 82 56.52 87.68 87.17 6.26 69
Namsai 21.08 0.95 75.5 28.44 69.19 88.14 10.47 63
Pakke Kessang 27.52 1.84 70 20.75 43.40 100.00 10.61 63
Papum Pare 29.31 1.08 80 51.68 63.03 94.73 8.38 71
Shi Yomi 23.16 1.50 64.5 28.21 33.33 95.45 12.17 61
Siang 16.85 1.05 80 25.00 50.93 91.86 5.22 68
Tawang 15.26 1.76 80 71.19 79.66 92.58 10.37 81
Tirap 20.39 0.96 72.5 40.28 61.11 92.49 10.37 65
Upper Siang 19.41 0.89 77 37.80 76.38 95.45 7.58 64
Upper Subansiri 8.09 1.08 70.5 41.60 29.20 94.62 13.74 69
West Kameng 26.02 1.11 71.5 52.92 67.92 92.65 9.94 70
West Siang 18.92 1.06 79 38.78 97.28 92.84 5.94 77
Assam
Bajali Null Null Null Null Null Null Null *
Baksa 25.39 1.06 78.5 84.84 88.35 62.12 7.82 70
Barpeta 29.42 1.30 79 58.71 83.89 65.32 12.12 65
Biswanath 31.45 1.18 69 59.26 88.21 78.59 14.10 67
Bongaigaon 31.96 1.24 65 65.36 88.19 65.61 14.67 63
Cachar 27.06 1.13 64.5 67.19 90.20 69.97 18.03 67
Charaideo 23.29 1.19 79 95.20 98.44 61.98 9.22 74
Chirang 27.24 1.16 64 61.43 83.87 73.70 13.07 66
Darrang 18.87 1.26 70 80.66 90.68 73.12 10.63 74
Dhemaji 11.24 1.06 76 59.05 90.83 72.29 10.00 74
Dhubri 24.55 1.29 72.5 49.60 68.92 69.59 18.15 63
Dibrugarh 19.43 1.08 69.5 75.74 97.23 74.57 10.34 74
Dima Hasao 14.94 1.03 77 55.37 89.37 72.48 8.30
73
Goalpara 29.02 1.40 67.5 64.17 89.13 72.86 15.91 67
Golaghat 23.57 1.09 67.5 77.33 91.25 71.00 9.45 71
Hailakandi 22.71 1.25 69 49.95 69.99 68.96 15.08 63
Hojai 28.25 1.48 62 79.34 91.07 63.53 15.17 66
Jorhat 22.65 1.04 80.5 63.69 95.68 76.05 7.64 74
Kamrup 34.85 1.13 79.5 83.31 92.70 79.47 10.02 73
Kamrup Metropolitan 13.82 1.02 85 70.85 96.53 80.26 8.24 81
Karbi Anglong 25.78 1.07 63.5 76.02 86.41 65.99 10.77 66
Karimganj 26.72 1.43 60.5 64.43 82.74 69.57 17.16 64
Kokrajhar 20.28 1.08 71.5 67.36 68.32 69.28 13.89 67
Lakhimpur 21.39 1.10 73.5 58.54 88.49 71.99 7.71 70
Majuli 16.59 0.90 79.5 69.86 89.64 67.88 5.97 64
Morigaon 29.39 1.39 73.5 79.88 90.22 76.33 14.32 72
Nagaon 30.05 1.53 68.5 64.25 88.18 69.36 10.16 65
Nalbari 18.80 1.10 84.5 53.67 87.99 67.84 7.91 71
Sivasagar 20.02 1.03 86 94.63 97.73 65.19 6.22 78
Sonitpur 31.51 1.26 69 73.63 85.58 75.99 13.50 68
South Salmara-Mankachar 27.24 1.55 73.5 55.28 73.93 62.01 14.03 61
Tamulpur Null Null Null Null Null Null Null *
Tinsukia 30.68 1.13 69 73.30 94.88 75.48 13.25 70
Udalguri 16.89 1.17 71 67.28 90.51 63.97 11.85 70
West Karbi Anglong 33.80 1.13 62 58.68 88.08 72.07 12.30 63
TABLE 4.1: PERFORMANCE OF DISTRICTS ON SDG 4
59Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 4.1 4.5 4.1 4.a 4.a 4.c 4.c
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of female to
male enrolment
at secondary level
(Class 9-10)
Percentage of students in grade 8
achieving at least a minimum pro-
ficiency level in terms of nationally
defined learning outcomes to be
attained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary level
(Class 9-10)
Pupil Teacher Ratio
at secondary level
(Class 9-10)
SDG 4
Manipur
Bishnupur 20.01 0.96 74.5 40.92 75.25 83.79 10.80 66
Chandel 25.92 1.09 80.5 14.35 93.48 69.64 9.12 63
Churachandpur 33.43 1.02 84 30.37 67.56 76.38 10.94 61
Imphal East 18.17 0.98 82 43.95 77.34 83.27 7.22 70
Imphal West 0.00 1.00 85.5 55.56 86.48 83.51 7.73 82
Jiribam 21.78 1.19 52.5 29.63 100.00 67.39 14.34 60
Kakching 30.47 0.94 80 50.60 76.79 80.04 9.39 62
Kamjong 1.92 1.08 78 9.94 27.95 93.18 10.82 66
Kangpokpi 24.64 0.97 80.5 20.75 56.98 74.66 9.81 57
Noney 32.22 0.91 71 18.57 36.43 70.23 11.70 42
Pherzawl 41.93 0.95 76 17.69 23.08 81.88 5.62 45
Senapati 4.92 0.98 81 26.70 73.86 81.92 9.56 71
Tamenglong 16.88 1.09 70.5 16.61 36.90 89.55 9.83 61
Tengnoupal 29.75 1.02 72 21.71 69.74 69.42 9.18 57
Thoubal 8.18 0.96 74.5 49.11 77.22 86.26 11.21 72
Ukhrul 22.51 1.07 78 42.73 51.98 73.71 9.55 62
Meghalaya
East Garo Hills 14.57 1.15 43.5 24.44 23.04 76.86 17.05 51
East Jaintia Hills 38.61 1.46 59.5 16.43 30.26 76.36 11.33 46
East Khasi Hills 11.16 1.26 72 34.26 53.69 68.58 9.33 62
Eastern West Khasi Hills Null Null Null Null Null Null Null *
North Garo Hills 44.01 1.26 43 14.43 21.53 75.68 13.42 38
Ri Bhoi 16.93 1.39 61.5 20.24 34.38 65.39 10.82 51
South Garo Hills 30.70 1.22 46 9.80 13.76 76.11 8.82 41
South West Garo Hills 29.25 1.13 50 12.71 14.38 73.67 10.01 43
South West Khasi Hills 26.30 1.29 53 10.43 21.59 66.50 7.46 43
West Garo Hills 25.36 1.20 53 15.23 24.08 61.70 9.77 43
West Jaintia Hills 20.56 1.50 63.5 17.81 28.02 60.96 11.88 47
West Khasi Hills 32.13 1.30 38 10.32 17.02 69.97 11.97 38
Mizoram
Aizawl 0.00 1.11 78.5 67.34 99.21 78.36 10.64 82
Champhai 20.26 1.13 62.5 79.03 98.13 74.81 10.27 73
Hnahthial 32.50 1.21 Null 46.38 93.48 83.20 8.43 70
Khawzawl 24.73 1.14 Null 41.35 95.49 67.36 8.53 67
Kolasib 23.34 1.15 66.5 45.04 98.58 95.28 9.22 75
Lawngtlai 29.45 0.92 57 16.44 56.40 78.44 10.76 46
Lunglei 24.57 1.02 63.5 40.45 78.47 78.50 6.51 64
Mamit 39.96 1.06 68 40.16 79.53 92.59 7.07 64
Saitual 29.85 1.10 Null 63.05 99.51 87.21 7.15 77
Serchhip 23.13 0.92 69 43.04 96.96 87.68 8.12 65
Siaha 0.00 0.98 63 27.99 95.90 82.08 10.18 72
Nagaland
Chumoukedima Null Null Null Null Null
Null Null *
Dimapur 0.37 1.05 80 94.83 96.49 74.98 8.78 86
Kiphire 27.88 1.15 66.5 72.18 72.93 65.61 10.99 63
Kohima 0.00 1.04 80 86.91 89.09 74.86 7.05 83
Longleng 14.63 1.22 71.5 94.50 44.04 73.77 7.10 71
Mokokchung 14.22 0.96 82.5 92.19 94.14 79.33 5.35 79
Mon 26.68 1.16 66.5 82.84 69.97 57.36 9.91 62
Noklak Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null *
Peren 15.99 0.92 75 69.36 75.72 69.06 8.34 63
Phek 25.52 1.10 78 88.46 91.88 74.24 5.45 75
Shamator Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null *
Tuensang 21.88 1.21 64.5 87.24 68.31 77.50 9.07 70
Wokha 33.56 1.07 77 72.97 57.84 82.35 6.05 67
Zunheboto 26.74 1.08 77 67.28 81.99 71.74 5.93 69
Sikkim
Gangtok 14.40 1.03 79 91.77 100.00 88.44 7.22 86
Gyalshing 19.66 1.01 69 94.30 96.37 88.03 4.58 82
Mangan 22.41 1.05 76 80.00 97.27 85.49 5.33 79
Namchi 18.83 1.03 71 91.44 99.17 87.03 5.54 82
Pakyong 24.07 0.98 Null 93.72 98.95 89.63 4.72 83
Soreng 22.86 1.02 Null 96.13 100.00 84.34 3.69 85
Tripura
Dhalai 11.89 1.05 62 28.02 57.29 91.82 11.77 67
Gomati 11.98 0.99 76 42.67 94.95 90.16 13.86 77
Khowai 14.12 1.01 76 53.89 96.61 85.46 9.67 78
North Tripura 13.86 1.14 72.5 44.65 68.82 89.66 10.78 73
Sepahijala 13.21 1.00 77.5 50.31 71.23 88.36 9.03 75
South Tripura 11.60 1.00 84.5 40.75 82.84 91.34 12.60 78
Unakoti 13.33 1.10 70.5 55.17 81.96 86.66 14.94 75
West Tripura 3.52 1.00 81.5 86.69 91.03 88.64 10.30 88
Target 3.21 1 100 100 100 100 30 100
TABLE 4.1: PERFORMANCE OF DISTRICTS ON SDG 4
Ending all discrimination against women and
girls is a basic human right and is a prerequisite
for sustainable development. Goal 5 calls
for ending all forms of violence, trafficking
and sexual exploitation of women and girls.
Recognising and valuing unpaid care and
domestic work is a key component of this goal,
with emphasis on the importance of full and
effective participation and equal opportunities
for leadership at all levels of decision-making in
political, economic and public life for women.
Targets
5.1 End all forms of discrimination against all
women and girls everywhere
5.2 Eliminate all forms of violence against all
women and girls in the public and private
spheres, including trafficking and sexual
and other types of exploitation
5.3 Eliminate all harmful practices, such as
child, early and forced marriage and
female genital mutilation
5.4 Recognize and value unpaid care and
domestic work through the provision of
public services, infrastructure and social
protection policies and the promotion of
shared responsibility within the household
and the family as nationally appropriate
5.5 Ensure women’s full and effective
participation and equal opportunities for
leadership at all levels of decision-making
in political, economic and public life
5.6 Ensure universal access to sexual and
reproductive health and reproductive
rights as agreed in accordance with the
Programme of Action of the International
Conference on Population and
Development and the Beijing Platform
for Action and the outcome documents
of their review conferences
5.a Undertake reforms to give women equal
rights to economic resources, as well
as access to ownership and control
over land and other forms of property,
financial services, inheritance and
natural resources, in accordance with
national laws
5.b Enhance the use of enabling
technology,
in particular information
and
communications technology, to
promote the empowerment of women
5.c Adopt and strengthen sound policies and
enforceable legislation for the promotion
of gender equality and the empowerment
of all women and girls at all levels
61
CONTEXT & OVERVIEW
SDG 5
GENDER EQUALITY
Achieve gender equality and empower all women and girls
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) The score for Goal 5 ranges between 98 and 45 for the
121 districts included in the ranking and computation.
Saitual [MZ], Wokha [NL] and Longleng [NL] are the
top performing districts. 112 districts fall in the category
of Front Runners and 8 in the category of Performers,
while 1 district is in the category of Aspirant with scores
less than 50.
NER District SDG Index: Goal 5
0 2010 4030 50 60 908070 100
FIGURE 5.1: SDG 5 INDEX SCORE OF DISTRICTS
District StateRank
Saitual MZ 1 98
Wokha NL 1 98
Longleng NL 3 96
Mokokchung NL 3 96
Zunheboto NL 5 95
Mon NL 6 94
West Tripura TR 7 91
Tawa n g AR 8 90
Karbi Anglong AS 8 90
Tuensang NL 8 90
Champhai MZ 11 88
Khowai TR 11 88
Kurung Kumey AR 13 87
Biswanath AS 13 87
Golaghat AS 13 87
Dhalai TR 13 87
West Karbi Anglong AS 17 86
Hnahthial MZ 17 86
Kolasib MZ 17 86
Kohima NL 17 86
Baksa AS 21 85
Charaideo AS 21 85
Dhemaji AS 21 85
Dima Hasao AS 21 85
Sivasagar AS 21 85
Lunglei MZ 21 85
North Tripura TR 21 85
Dibrugarh AS 28 84
Karimganj AS 28 84
Sepahijala TR 28 84
Chirang AS 31 83
Lakhimpur AS 31 83
Peren NL 31 83
Barpeta AS 34 82
Udalguri AS 34 82
Jiribam MN 34 82
Phek NL 34 82
Gyalshing SK 34 82
Gomati TR 34 82
Kokrajhar AS 40 81
Nagaon AS 40 81
South Salmara-Mankachar AS 40 81
Tinsukia AS 40 81
South Tripura TR 40 81
Unakoti TR 40 81
Dhubri AS 46 80
Hailakandi AS 46 80
Morigaon AS 46 80
Noney MN 46 80
Khawzawl MZ 46 80
Serchhip MZ 46 80
Dimapur NL 46 80
Dibang Valley AR 53 79
Shi Yomi AR 53 79
Bongaigaon AS 53 79
Jorhat AS 53 79
Kamle AR 57 78
Lower Subansiri AR 57 78
Namsai AR 57 78
Tengnoupal MN 57 78
Aizawl MZ 57 78
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
622023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 5.1: SDG 5 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Goalpara AS 62 77
Sonitpur AS 62 77
South West Garo Hills ML 62 77
East Kameng AR 65 76
Majuli AS 65 76
Nalbari AS 65 76
Kamjong MN 65 76
Kiphire NL 65 76
Siang AR 70 75
Upper Subansiri AR 70 75
Cachar AS 70 75
Hojai AS 70 75
Imphal East MN 70 75
Thoubal MN 70 75
Lawngtlai MZ 70 75
Changlang AR 77 74
Longding AR 77 74
Tirap AR 77 74
West Kameng AR 77 74
Tamenglong MN 77 74
Namchi SK 77 74
Lower Dibang Valley AR 83 73
Upper Siang AR 83 73
Kamrup Metropolitan AS 83 73
West Jaintia Hills ML 83 73
Mamit MZ 83 73
Chandel MN 88 72
East Garo Hills ML 88 72
Ri Bhoi ML 88 72
Soreng SK 88 72
Lohit AR 92 71
Siaha MZ 92 71
East Siang AR 94 70
Lower Siang AR 94 70
Darrang AS 94 70
Ukhrul MN 94 70
West Garo Hills ML 94 70
Gangtok SK 94 70
South West Khasi Hills ML 100 69
Leparada AR 101 68
Mangan SK 101 68
Churachandpur MN 103 67
Kakching MN 103 67
East Khasi Hills ML 103 67
West Khasi Hills ML 103 67
Pakyong SK 103 67
Anjaw AR 108 66
Kamrup AS 108 66
Senapati MN 108 66
South Garo Hills ML 108 66
West Siang AR 112 65
Pakke Kessang AR 113 64
Imphal West MN 114 63
Kangpokpi MN 114 63
Bishnupur MN 116 59
North Garo Hills ML 116 59
Papum Pare AR 118 58
East Jaintia Hills ML 119 57
Kra Daadi AR 120 55
Pherzawl MN 121 45
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
63
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 5.2: PERFORMANCE OF DISTRICTS IN SDG 5
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
642023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
5.2
Crimes against women per 10,000
female population
0
This target is aligned with the global SDG target 5.2 that aims to
eliminate all forms of violence against women and girls in the public
and private spheres.
5.1 Sex ratio at birth 950
The 2019 UNFPA report on ‘‘Sex Ratio at Birth in India: Recent
trends and patterns’’ observes that in the absence of sex selection
the Sex Ratio at Birth (SRB) is around 105 male births per 100
female births or around 950 female births per 1,000 male births.
5.2
Percentage of sexual crimes against
women to total crimes against women
0
This target is aligned with the global SDG target 5.2 that aims to
eliminate all forms of violence against women and girls in the public
and private spheres, including trafficking and sexual and other types
of exploitation.
5.6
Unmet need for family planning for
currently married women aged 15-49
years
0
This target corresponds to the global SDG target 5.6 that aims
ensure universal access to sexual and reproductive health and
reproductive rights.
5.a
Exclusive women Self Help Groups
(SHGs) in bank linked SHGs
99.4
Global SDG target 5.a aims to undertake reforms to give women
equal rights to economic resources, as well as access to financial
services. Average of the 5 best scores has been set as the target.
65
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
66Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 5.2 5.1 5.2 5.6 5.a
District
Crimes against women per
10,000 female population
Sex ratio at birth
Percentage of sexual crimes
against women to total crimes
against women
Unmet need for family
planning for currently married
women aged 15-49 years
Exclusive women SHGs in
bank linked SHGs
SDG 5
Arunachal Pradesh
Anjaw 4.14 818 50.00 6.8 47.4 66
Bichom Null Null Null Null Null *
Changlang 2.24 962 68.75 6.7 45.3 74
Dibang Valley 0.00 778 0.00 4.6 61.9 79
East Kameng 4.37 1189 100.00 9.7 91.4 76
East Siang 6.74 931 80.95 17.6 94.2 70
Kamle 0.90 1161 100.00 Null 78.6 78
Keyi Panyor Null Null Null Null Null *
Kra Daadi 0.42 636 100.00 16.5 87.7 55
Kurung Kumey 0.00 971 0.00 16.4 86.3 87
Leparada 8.18 920 80.00 Null 77.1 68
Lohit 5.98 992 64.29 14.6 70.8 71
Longding 1.42 867 50.00 7.3 55.6 74
Lower Dibang Valley 4.23 901 90.91 4.9 74.5 73
Lower Siang 5.62 923 66.67 Null 58.4 70
Lower Subansiri 3.33 966 71.43 8.5 Null 78
Namsai 1.52 1002 80.00 8.7 71.4 78
Pakke Kessang 6.51 833 100.00 Null 89.7 64
Papum Pare 17.74 980 34.67 20.3 72.8 58
Shi Yomi 3.08 1192 100.00 Null 94.2 79
Siang 1.96 871 100.00 5.0 86.0 75
Tawang 1.44 1029 0.00 14.6 99.3 90
Tirap 0.38 934 100.00 10.6 66.4 74
Upper Siang 4.21 1056 85.71 11.9 77.6 73
Upper Subansiri 2.62 895 33.33 17.3 80.2 75
West Kameng 2.28 910 50.00 17.0 78.6 74
West Siang 9.87 914 72.00 15.5 83.4 65
Assam
Bajali Null Null Null Null Null *
Baksa 2.65 929 24.19 12.5 100.0 85
Barpeta 7.15 965 23.35 12.3 100.0 82
Biswanath 6.34 961 19.90 5.3 100.0 87
Bongaigaon 7.77 943 19.86 16.1 99.9 79
Cachar 11.92 969 20.02 15.6 100.0 75
Charaideo 6.78 949 22.37 8.3 100.0 85
Chirang 6.83 962 24.07 9.8 99.7 83
Darrang 16.53 953 21.63 14.8 100.0 70
Dhemaji 5.97 966 32.50 7.1 99.8 85
Dhubri 9.04 971 23.00 11.5 100.0 80
Dibrugarh 6.08 918 16.20 8.7 100.0 84
Dima Hasao 2.90 924 33.33 9.7 100.0 85
Goalpara 13.60 941 19.47 7.4 100.0 77
Golaghat 3.82 939 13.00 10.9 100.0 87
Hailakandi 9.40 944 33.11 8.6 100.0 80
Hojai 13.13 959 16.92 13.2 99.9 75
Jorhat 7.54 914 34.50 10.4 100.0 79
Kamrup 16.47 967 38.13 17.6 100.0 66
Kamrup Metropolitan 16.15 935 24.41 8.8 100.0 73
Karbi Anglong 1.80 976 20.69 9.3 100.0 90
Karimganj 7.90 953 17.02 8.6 99.5 84
Kokrajhar 7.99 961 31.12 10.0 99.9 81
Lakhimpur 7.79 950 18.55 9.8 100.0 83
Majuli 8.20 890 28.36 11.6 100.0 76
Morigaon 11.64 961 21.72 6.5 99.9 80
Nagaon 8.39 969 20.26 12.3 100.0 81
Nalbari
9.69 923 30.49 13.2 100.0 76
Sivasagar 6.69 980 18.14 8.3 99.3 85
Sonitpur 12.71 905 17.61 5.8 100.0 77
South Salmara-Mankachar 10.40 953 17.25 8.0 99.6 81
Tamulpur Null Null Null Null Null *
Tinsukia 6.98 941 28.98 11.0 100.0 81
Udalguri 6.27 956 17.12 14.6 100.0 82
West Karbi Anglong 2.77 901 25.00 7.1 99.4 86
TABLE 5.1: PERFORMANCE OF DISTRICTS ON SDG 5
67Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 5.2 5.1 5.2 5.6 5.a
District
Crimes against women per
10,000 female population
Sex ratio at birth
Percentage of sexual crimes
against women to total crimes
against women
Unmet need for family
planning for currently married
women aged 15-49 years
Exclusive women SHGs in
bank linked SHGs
SDG 5
Manipur
Bishnupur 1.69 808 65.00 20.0 51.0 59
Chandel 0.25 931 0.00 11.0 1.3 72
Churachandpur 0.87 949 80.00 8.7 16.1 67
Imphal East 2.11 908 75.00 16.7 97.4 75
Imphal West 3.27 930 55.81 12.5 9.0 63
Jiribam 1.41 1196 66.67 Null 76.9 82
Kakching 2.33 1096 82.35 Null 28.4 67
Kamjong 0.00 1193 0.00 Null 3.6 76
Kangpokpi 0.11 976 100.00 Null 14.3 63
Noney 0.00 988 0.00 Null 21.1 80
Pherzawl 0.98 781 100.00 Null 0.0 45
Senapati 0.15 934 100.00 8.5 20.0 66
Tamenglong 0.23 914 0.00 8.4 8.3 74
Tengnoupal 1.69 962 20.00 Null 34.2 78
Thoubal 2.82 881 69.23 6.0 70.3 75
Ukhrul 0.76 1005 80.00 12.7 40.3 70
Meghalaya
East Garo Hills 4.35 890 36.84 21.0 87.8 72
East Jaintia Hills 6.97 1050 146.67 26.0 92.2 57
East Khasi Hills 4.84 937 37.18 33.0 89.1 67
Eastern West Khasi Hills Null Null Null Null Null *
North Garo Hills 2.81 998 166.67 25.2 88.8 59
Ri Bhoi 5.15 954 32.14 27.0 87.3 72
South Garo Hills 3.47 926 92.31 25.3 87.6 66
South West Garo Hills 1.17 955 25.00 30.4 99.7 77
South West Khasi Hills 3.06 980 75.00 26.2 85.5 69
West Garo Hills 6.27 916 41.76 19.7 79.6 70
West Jaintia Hills 3.86 974 27.78 29.3 92.4 73
West Khasi Hills 7.47 956 68.42 25.8 93.9 67
Mizoram
Aizawl 3.25 967 35.48 24.0 99.8 78
Champhai 2.51 972 21.05 11.2 100.0 88
Hnahthial 2.10 889 37.50 Null 97.1 86
Khawzawl 6.05 906 50.00 Null 100.0 80
Kolasib 2.68 1040 12.50 15.6 99.8 86
Lawngtlai 2.86 967 90.91 17.3 100.0 75
Lunglei 1.73 970 33.33 15.4 100.0 85
Mamit 2.89 923 100.00 17.0 99.9 73
Saitual 1.60 1037 0.00 Null 100.0 98
Serchhip 3.72 1096 50.00 15.9 100.0 80
Siaha 2.14 838 50.00 22.5 99.9 71
Nagaland
Chumoukedima Null Null Null Null Null *
Dimapur 0.72 902 54.55 14.3 92.5 80
Kiphire 0.28 887 66.67 17.3 95.5 76
Kohima 0.97 915 40.00 9.1 100.0 86
Longleng 0.85 971 0.00 4.3 96.6 96
Mokokchung 0.32 973 0.00 6.4 100.0 96
Mon 0.51 967 0.00 3.7 85.5 94
Noklak Null Null Null Null Null *
Niuland Null Null Null Null Null *
Peren 0.70 976 66.67 6.2 77.2 83
Phek 0.38 841 50.00 6.5 96.3 82
Shamator Null Null Null Null Null *
Tseminyu Null Null Null Null Null *
Tuensang 0.51 930 0.00 12.9 100.0 90
Wokha 0.12 996 0.00 3.2 100.0
98
Zunheboto 0.43 930 0.00 2.8 91.4 95
Sikkim
Gangtok 6.92 964 94.74 17.7 100.0 70
Gyalshing 5.51 1018 75.00 4.3 100.0 82
Mangan 6.32 871 100.00 12.8 100.0 68
Namchi 5.98 852 78.57 5.2 100.0 74
Pakyong 7.11 Null 100.00 Null 100.0 67
Soreng 4.42 Null 100.00 Null 100.0 72
Tripura
Dhalai 3.59 925 40.91 4.0 100.0 87
Gomati 5.90 977 33.87 12.1 100.0 82
Khowai 2.37 943 50.00 4.1 100.0 88
North Tripura 5.42 1001 46.85 6.1 100.0 85
Sepahijala 3.25 1013 23.68 15.3 100.0 84
South Tripura 3.75 948 36.59 17.3 100.0 81
Unakoti 7.85 954 38.32 9.7 100.0 81
West Tripura 3.25 987 33.33 2.5 100.0 91
Target 0 950 0 0 99.4 100
TABLE 5.1: PERFORMANCE OF DISTRICTS ON SDG 5
Goal 6 calls for access to safe and affordable
drinking water, sanitation facilities, and hygiene
for all by 2030. Water resources are also critical
for agriculture and industrial use, and therefore
protecting and restoring water-related ecosystems
is essential. The goal is aimed at -improving
water quality by reducing pollution, substantially
increasing water-use efficiency across all sectors,
and strengthening the participation of local
communities in improving water and sanitation
management.
Targets
6.1 By 2030, achieve universal and equitable
access to safe and affordable drinking
water for all
6.2 By 2030, achieve access to adequate and
equitable sanitation and hygiene for all
and end open defecation, paying special
attention to the needs of women and girls
and those in vulnerable situations
6.3 By 2030, improve water quality by reducing
pollution, eliminating dumping and
minimizing release of hazardous chemicals
and materials, halving the proportion of
untreated wastewater and substantially
increasing recycling and safe reuse globally
6.4 By 2030, substantially increase water-use
efficiency across all sectors and ensure
sustainable withdrawals and supply of
freshwater to address water scarcity and
substantially reduce the number of people
suffering from water scarcity
6.5 By 2030, implement integrated water
resources management at all levels, including
through transboundary cooperation as
appropriate
6.6 By 2020, protect and restore water-related
ecosystems, including mountains, forests,
wetlands, rivers, aquifers and lakes
6.a By 2030, expand international cooperation
and capacity-building support to developing
countries in water- and sanitation-related
activities and programmes, including water
harvesting, desalination, water efficiency,
wastewater treatment, recycling and reuse
technologies
6.b Support and strengthen the participation of
local communities in improving water and
sanitation management
69
CONTEXT & OVERVIEW
SDG 6
CLEAN WATER AND SANITATION
Ensure availability and sustainable management of water
and sanitation for all
METHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 6
The score for Goal 6 ranges between 94 and 52 for the
121 districts included in the ranking and computation.
Saitual [MZ] and Serchhip [MZ] are the top performing
districts. 114 districts fall in the category of Front
Runners and 7 in the category of Performers, while
no district is in the category of Aspirants with scores
less than 50.
0 2010 4030 50 60 908070 100
FIGURE 6.1: SDG 6 INDEX SCORE OF DISTRICTS
District StateRank
Saitual MZ 1 94
Serchhip MZ 1 94
Leparada AR 3 92
Lohit AR 3 92
Lower Dibang Valley AR 3 92
Champhai MZ 3 92
Soreng SK 3 92
Shi Yomi AR 8 91
Aizawl MZ 8 91
Mamit MZ 8 91
Pakyong SK 8 91
Anjaw AR 12 90
Dibang Valley AR 12 90
Lower Subansiri AR 12 90
Khawzawl MZ 12 90
Kolasib MZ 12 90
Lunglei MZ 12 90
Siaha MZ 12 90
Mokokchung NL 12 90
Gyalshing SK 12 90
Kra Daadi AR 21 89
West Siang AR 21 89
Hnahthial MZ 21 89
Longleng NL 21 89
Gangtok SK 21 89
Mangan SK 21 89
Upper Siang AR 27 88
West Kameng AR 27 88
Mon NL 27 88
Peren NL 27 88
Wokha NL 27 88
Namchi SK 27 88
Changlang AR 33 87
Tawa n g AR 33 87
Kakching MN 33 87
Lawngtlai MZ 33 87
Lower Siang AR 37 86
Tirap AR 37 86
Sivasagar AS 37 86
Churachandpur MN 37 86
Dimapur NL 37 86
Kohima NL 37 86
East Siang AR 43 85
Pakke Kessang AR 43 85
Tamenglong MN 43 85
Namsai AR 46 84
Dima Hasao AS 46 84
Kiphire NL 46 84
Longding AR 49 83
Upper Subansiri AR 49 83
Chandel MN 49 83
Senapati MN 49 83
Papum Pare AR 53 82
Tengnoupal MN 53 82
Phek NL 53 82
Kamle AR 56 81
Kurung Kumey AR 56 81
Dibrugarh AS 56 81
South Garo Hills ML 56 81
Tuensang NL 56 81
Siang AR 61 80
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
702023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 6.1: SDG 6 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Kamrup Metropolitan AS 61 80
Kangpokpi MN 61 80
Noney MN 61 80
East Kameng AR 65 79
Baksa AS 65 79
Kamjong MN 65 79
West Khasi Hills ML 65 79
Golaghat AS 69 78
Jorhat AS 69 78
Lakhimpur AS 69 78
Majuli AS 69 78
South West Khasi Hills ML 69 78
Cachar AS 74 77
East Garo Hills ML 74 77
East Khasi Hills ML 74 77
Charaideo AS 77 76
Goalpara AS 77 76
Karbi Anglong AS 77 76
Udalguri AS 77 76
Chirang AS 81 75
Karimganj AS 81 75
Kokrajhar AS 81 75
North Garo Hills ML 81 75
Ri Bhoi ML 81 75
Zunheboto NL 81 75
Dhemaji AS 87 74
Hojai AS 87 74
Imphal East MN 87 74
Thoubal MN 87 74
Nalbari AS 91 73
Sonitpur AS 91 73
South Salmara-Mankachar AS 91 73
Tinsukia AS 91 73
Imphal West MN 95 72
Jiribam MN 95 72
Pherzawl MN 95 72
Ukhrul MN 95 72
West Jaintia Hills ML 95 72
Bongaigaon AS 100 71
Hailakandi AS 100 71
West Karbi Anglong AS 100 71
West Garo Hills ML 100 71
Barpeta AS 104 70
Bishnupur MN 104 70
Biswanath AS 106 69
East Jaintia Hills ML 106 69
Kamrup AS 108 68
Sepahijala TR 109 67
Dhubri AS 110 66
Nagaon AS 110 66
West Tripura TR 110 66
Morigaon AS 113 65
Gomati TR 113 65
North Tripura TR 115 64
Khowai TR 116 63
Unakoti TR 117 59
South West Garo Hills ML 118 58
Dhalai TR 119 57
South Tripura TR 119 57
Darrang AS 121 52
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
71
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 6.2: PERFORMANCE OF DISTRICTS IN SDG 6
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
722023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
6.1
Percentage of rural population using
an improved drinking water source
100
Global SDG target 6.1 aims to achieve universal and equitable
access to safe and affordable drinking water for all by 2030.
6.1
Percentage of rural population getting
safe and adequate drinking water
within premises through Piped Water
Supply (PWS)
100
The Jal Jeevan Mission aims to provide piped water supply to the
entire rural population by 2024.
6.2
Percentage of population living in
households that use an improved
sanitation facility
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030.
6.2
Percentage of individual household
toilets constructed against target
(SBM(G))
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030. This is also in line with the objectives of the Government
of India’s Swachh Bharat Mission (Gramin).
6.2
Percentage of schools with functional
toilet facility for girls
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030.
6.2
Percentage of GPs/villages verified as
ODF (SBM(G)) in the district
100
Global SDG target 6.2 aims to achieve access to adequate and
equitable sanitation and hygiene for all and end open defecation
by 2030. This is also in line with the objectives of the Government
of India’s Swachh Bharat Mission (Gramin).
6.4 Stage of groundwater extraction (%)0.06
Global SDG target 6.4 that aims to substantially increase water-use
efficiency across all sectors and ensure sustainable withdrawals to
address water scarcity. Average of the 5 best scores has been set
as the target.
73
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
74Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 6.1 6.1 6.2 6.2 6.2 6.2 6.4
District
Percentage of rural
population using an
improved drinking
water source
Percentage of rural
population getting
safe and adequate
drinking water within
premises through
Piped Water Supply
(PWS)
Percentage of
population living
in households that
use an improved
sanitation facility
Toilets constructed
against
target - SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of GPs/
Villages verified as
ODF in the district
Stage of
groundwater
extraction (%)
SDG 6
Arunachal Pradesh
Anjaw 100.00 89.84 86.8 100.00 90.54 100.00 Null 90
Bichom Null Null Null Null Null Null Null *
Changlang 100.00 89.97 82.3 100.00 76.81 100.00 0.66 87
Dibang Valley 100.00 91.77 95.0 100.00 73.91 100.00 Null 90
East Kameng 100.00 95.34 75.6 100.00 46.15 100.00 2.63 79
East Siang 100.00 90.87 83.9 100.00 62.35 100.00 0.88 85
Kamle 100.00 92.00 Null 100.00 45.57 100.00 Null 81
Keyi Panyor Null Null Null Null Null Null Null *
Kra Daadi 100.00 92.83 89.3 100.00 78.95 100.00 Null 89
Kurung Kumey 100.00 92.76 78.3 100.00 61.62 100.00 Null 81
Leparada 100.00 92.92 Null 100.00 79.37 100.00 Null 92
Lohit 100.00 92.13 83.7 100.00 95.28 100.00 0.73 92
Longding 100.00 92.58 83.5 100.00 61.32 100.00 Null 83
Lower Dibang Valley 100.00 91.15 89.9 100.00 88.00 100.00 0.33 92
Lower Siang 100.00 94.02 Null 100.00 58.11 100.00 Null 86
Lower Subansiri 100.00 92.89 82.8 100.00 87.59 100.00 2.33 90
Namsai 100.00 90.67 75.1 100.00 81.99 100.00 Null 84
Pakke Kessang 100.00 92.14 Null 100.00 58.49 100.00 Null 85
Papum Pare 100.00 93.11 75.7 100.00 59.66 100.00 1.28 82
Shi Yomi 100.00 93.20 Null 100.00 76.92 100.00 Null 91
Siang 100.00 93.47 91.2 100.00 37.96 100.00 Null 80
Tawang 100.00 89.05 81.7 100.00 85.34 100.00 Null 87
Tirap 100.00 90.24 86.7 100.00 64.34 100.00 1.75 86
Upper Siang 100.00 95.74 91.8 100.00 68.25 100.00 Null 88
Upper Subansiri 100.00 94.20 80.9 100.00 56.00 100.00 0.61 83
West Kameng 100.00 89.75 88.9 100.00 69.58 100.00 0.11 88
West Siang 100.00 93.78 87.7 100.00 72.79 100.00 1.03 89
Assam
Bajali Null Null Null Null Null Null Null *
Baksa 100.00 73.93 68.9 93.83 86.65 100.00 3.49 79
Barpeta 99.43 76.14 63.7 95.63 90.09 100.00 29.68 70
Biswanath 87.66 63.64 76.6 93.64 85.53 100.00 Null 69
Bongaigaon 95.91 71.02 72.5 93.30 90.58 100.00 25.76 71
Cachar 100.00 74.24 57.6 95.55 91.82 100.00 3.29 77
Charaideo 94.98 63.12 75.9 93.05 97.96 100.00 Null 76
Chirang 97.10 51.81 77.1 96.24 83.21 100.00 2.75 75
Darrang 72.72 72.47 67.9 93.66 90.25 100.00 42.71 52
Dhemaji 89.35 65.46 70.8 94.38 93.05 100.00 4.05 74
Dhubri 99.66 66.26 61.8 94.77 84.51 100.00 29.72 66
Dibrugarh 99.17 70.06 75.3 95.19 95.94 100.00 7.63 81
Dima Hasao 100.00 74.03 83.8 94.82
81.11 100.00 1.01 84
Goalpara 100.00 70.70 75.3 95.17 91.39 100.00 20.82 76
Golaghat 95.05 69.29 73.1 94.73 93.65 100.00 5.42 78
Hailakandi 100.00 64.27 60.0 96.41 67.68 100.00 3.62 71
Hojai 99.85 65.62 63.1 94.08 93.29 100.00 Null 74
Jorhat 96.71 57.69 80.4 94.94 96.48 100.00 9.35 78
Kamrup 99.02 61.26 68.7 94.25 96.29 100.00 33.91 68
Kamrup Metropolitan 100.00 77.17 65.2 95.65 96.32 100.00 Null 80
Karbi Anglong 99.01 57.89 75.2 92.45 84.14 100.00 2.48 76
Karimganj 100.00 68.10 61.5 96.17 81.21 100.00 2.94 75
Kokrajhar 97.13 71.18 72.2 95.64 75.64 100.00 5.63 75
Lakhimpur 99.87 72.86 74.2 94.15 87.23 100.00 10.26 78
Majuli 100.00 81.12 65.6 93.68 88.03 100.00 Null 78
Morigaon 99.77 49.88 62.3 94.68 87.36 100.00 25.21 65
Nagaon 96.41 64.78 66.1 93.83 89.19 100.00 28.86 66
Nalbari 99.98 72.35 68.1 94.31 92.76 100.00 24.11 73
Sivasagar 99.12 80.86 82.3 94.53 94.89 100.00 4.19 86
Sonitpur 92.74 67.67 72.2 94.61 87.78 100.00 10.44 73
South Salmara-Mankachar 100.00 74.14 59.0 94.68 82.18 100.00 Null 73
Tamulpur Null Null Null Null Null Null Null *
Tinsukia 87.94 72.77 66.7 94.39 95.97 100.00 6.67 73
Udalguri 96.86 63.82 73.8 94.72 90.76 100.00 8.90 76
West Karbi Anglong 100.00 46.18 76.7 92.49 82.07 100.00 Null 71
TABLE 6.1: PERFORMANCE OF DISTRICTS ON SDG 6
75Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
SDG Target 6.1 6.1 6.2 6.2 6.2 6.2 6.4
District
Percentage of rural
population using an
improved drinking
water source
Percentage of rural
population getting
safe and adequate
drinking water within
premises through
Piped Water Supply
(PWS)
Percentage of
population living
in households that
use an improved
sanitation facility
Toilets constructed
against
target - SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of GPs/
Villages verified as
ODF in the district
Stage of
groundwater
extraction (%)
SDG 6
Manipur
Bishnupur 100.00 69.86 52.6 100.00 68.65 100.00 5.67 70
Chandel 100.00 67.67 85.2 100.00 88.26 100.00 Null 83
Churachandpur 100.00 79.05 81.2 100.00 94.01 100.00 6.18 86
Imphal East 100.00 77.20 59.5 100.00 71.76 100.00 7.98 74
Imphal West 100.00 68.46 58.7 100.00 80.11 100.00 10.97 72
Jiribam 100.00 39.89 Null 100.00 74.53 100.00 Null 72
Kakching 100.00 77.81 Null 100.00 81.55 100.00 Null 87
Kamjong 100.00 67.20 Null 100.00 65.84 100.00 Null 79
Kangpokpi 100.00 80.58 Null 100.00 53.40 100.00 Null 80
Noney 100.00 66.52 Null 100.00 69.29 100.00 Null 80
Pherzawl 100.00 48.09 Null 100.00 64.62 100.00 Null 72
Senapati 100.00 70.87 84.4 100.00 87.22 100.00 Null 83
Tamenglong 100.00 73.58 77.9 100.00 99.63 100.00 Null 85
Tengnoupal 100.00 86.66 Null 100.00 53.95 100.00 Null 82
Thoubal 100.00 76.14 61.3 100.00 72.49 100.00 9.84 74
Ukhrul 100.00 71.70 81.4 100.00 44.93 100.00 Null 72
Meghalaya
East Garo Hills 100.00 81.52 83.9 71.84 69.83 100.00 6.93 77
East Jaintia Hills 100.00 52.07 83.6 76.33 57.20 100.00 2.28 69
East Khasi Hills 100.00 63.84 80.9 84.58 78.91 100.00 2.58 77
Eastern West Khasi Hills Null Null Null NUll Null Null Null *
North Garo Hills 100.00 74.81 84.9 66.47 68.27 100.00 3.59 75
Ri Bhoi 100.00 78.08 85.3 59.72 72.85 100.00 6.17 75
South Garo Hills 100.00 80.10 88.4 76.96 71.25 100.00 1.59 81
South West Garo Hills 100.00 76.94 71.4 37.57 51.73 100.00 17.65 58
South West Khasi Hills 100.00 71.35 89.6 57.66 85.02 100.00 1.71 78
West Garo Hills 100.00 65.99 86.3 64.58 58.89 100.00 4.15 71
West Jaintia Hills 100.00 64.89 75.1 83.20 64.95 100.00 4.45 72
West Khasi Hills 100.00 74.30 87.8 74.48 72.06 100.00 1.74 79
Mizoram
Aizawl 100.00 89.99 96.1 100.00 94.69 100.00 14.06 91
Champhai 100.00 91.79 98.3 100.00 80.52 100.00 3.03 92
Hnahthial 100.00 87.62 Null 100.00 75.36 100.00 Null 89
Khawzawl 100.00 92.09 Null 100.00 76.69 100.00 Null 90
Kolasib 100.00 91.72 96.8 100.00 66.31 100.00 1.30 90
Lawngtlai 100.00 89.62 90.3 100.00 67.99 100.00 3.62 87
Lunglei 100.00 90.43 95.6 100.00 74.65 100.00 4.10 90
Mamit 100.00 91.40 92.7 100.00 78.68 100.00 2.06 91
Saitual 100.00 90.25 Null 100.00 89.16 100.00 Null 94
Serchhip 100.00 92.13 98.2 100.00 92.61 100.00 6.19 94
Siaha 100.00 91.83 91.5 100.00 84.70 100.00 5.78 90
Nagaland
Chumoukedima Null Null
Null Null Null Null Null *
Dimapur 100.00 77.50 81.1 100.00 92.80 100.00 3.98 86
Kiphire 100.00 89.36 83.1 100.00 72.18 100.00 6.43 84
Kohima 100.00 79.41 87.4 100.00 93.09 100.00 10.51 86
Longleng 100.00 83.20 86.6 100.00 88.99 100.00 1.33 89
Mokokchung 100.00 74.69 96.7 100.00 89.06 100.00 0.62 90
Mon 100.00 79.01 86.4 100.00 92.08 100.00 5.11 88
Noklak Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null *
Peren 100.00 79.97 89.4 100.00 83.24 100.00 0.90 88
Phek 100.00 81.37 90.1 100.00 58.12 100.00 6.43 82
Shamator Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null *
Tuensang 100.00 76.64 92.0 100.00 65.02 100.00 10.09 81
Wokha 100.00 82.34 88.5 100.00 79.46 100.00 1.38 88
Zunheboto 100.00 80.76 88.9 100.00 32.35 100.00 8.06 75
Sikkim
Gangtok 100.00 85.99 85.0 100.00 99.55 100.00 9.29 89
Gyalshing 100.00 81.17 88.9 100.00 97.83 100.00 4.63 90
Mangan 100.00 79.82 83.8 100.00 98.95 100.00 2.58 89
Namchi 100.00 77.34 91.7 100.00 96.77 100.00 9.78 88
Pakyong 100.00 74.23 Null 100.00 96.67 100.00 3.60 91
Soreng 100.00 77.50 Null 100.00 100.00 100.00 5.41 92
Tripura
Dhalai 97.87 63.68 67.6 25.51 64.58 100.00 6.73 57
Gomati 96.78 69.37 77.4 36.92 71.66 100.00 5.42 65
Khowai 97.99 65.82 67.8 42.30 78.04 100.00 8.67 63
North Tripura 100.00 72.60 74.1 33.58 78.48 100.00 13.26 64
Sepahijala 99.52 67.59 75.4 54.85 74.54 100.00 11.91 67
South Tripura 95.14 67.01 68.6 26.75 64.33 100.00 6.45 57
Unakoti 94.52 76.06 61.8 30.10 78.51 100.00 8.37 59
West Tripura 99.11 80.15 80.2 23.94 90.26 100.00 20.20 66
Target 100 100 100 100 100 100 0.06 100
TABLE 6.1: PERFORMANCE OF DISTRICTS ON SDG 6
Energy security is a prerequisite for socio-
economic development. Access to energy
enables people to augment their income and
productivity, enhance access to healthcare, water
and education, and improve their overall well-
being. Goal 7 is aimed at ensuring universal access
to affordable, reliable and efficient energy services
by 2030. Expanding infrastructure and upgrading
technology to provide clean and efficient energy
is critical to this endeavour.
Targets
7.1 By 2030, ensure universal access to affordable,
reliable and modern energy services
7.2 By 2030, increase substantially the share of
renewable energy in the global energy mix
7.3 By 2030, double the global rate of improvement
in energy efficiency
7.a By 2030, enhance international cooperation
to facilitate access to clean energy research
and technology, including renewable
energy, energy efficiency and advanced and
cleaner fossil-fuel technology, and promote
investment in energy infrastructure and
clean energy technology
7.b By 2030, expand infrastructure and upgrade
technology for supplying modern and
sustainable energy services for all in developing
countries, in particular least developed
countries, small island developing States and
landlocked developing countries, in accordance
with their respective programmes of support
SDG 7
AFFORDABLE AND CLEAN ENERGY
Ensure access to affordable, reliable, sustainable
and modern energy for all
77
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 7.1: SDG 7 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Leparada AR 1 100
Lower Siang AR 1 100
Jiribam MN 1 100
Kakching MN 1 100
Kamjong MN 1 100
Kangpokpi MN 1 100
Noney MN 1 100
Pherzawl MN 1 100
Tengnoupal MN 1 100
Hnahthial MZ 1 100
Khawzawl MZ 1 100
Saitual MZ 1 100
Pakyong SK 1 100
Soreng SK 1 100
Aizawl MZ 15
95
West Kameng AR 16
94
Imphal West MN 16 94
Tawa n g AR 18 93
Kolasib MZ 18 93
Gangtok SK 18 93
Kamrup Metropolitan AS 21 91
Siaha MZ 21 91
Dimapur NL 21 91
Serchhip MZ 24 90
Papum Pare AR 25 89
Imphal East MN 25 89
Champhai MZ 25 89
Thoubal MN 28 86
Bishnupur MN 29 84
Gyalshing SK 30 83
Namchi SK 31 82
Mangan SK 32 81
West Tripura TR 32 81
Lunglei MZ 34 80
Churachandpur MN 35 79
Kohima NL 35 79
Kamrup AS 37 76
East Siang AR 38 74
Chandel MN 38 74
Tirap AR 40 73
Bongaigaon AS 40 73
Hojai AS 40 73
Nalbari AS 40 73
Senapati MN 40 73
Dibang Valley AR 45 72
Mamit MZ 45 72
West Siang AR 47 71
East Khasi Hills ML 47 71
Mokokchung NL 47 71
Gomati TR 47 71
Dibrugarh AS 51 70
Dima Hasao AS 51 70
Jorhat AS 51 70
Sivasagar AS 51 70
Sonitpur AS 51 70
West Garo Hills ML 51 70
Kurung Kumey AR 57 69
Chirang AS 57 69
Kokrajhar AS 57 69
Cachar AS 60 68
Tinsukia AS 60 68
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
NER District SDG Index: Goal 7
The score for Goal 7 ranges between 100 and 5 for the
121 districts included in the ranking and computation.
14 districts Leparada [AR], Lower Siang [AR], Jiribam
[MN], Kakching [MN], Kamjong [MN], Kangpokpi
[MN], Noney [MN], Tengnoupal [MN], Pherzawl [MN],
Hnahthial [MZ], Khawzawl [MZ], Saitual [MZ], Pakyong
[SK], Soreng [SK] have scored a 100 in this Goal and
fall in the category of Achievers. 58 districts fall in the
category of Front Runners and 41 in the category of
Performers, while 8 districts are in the category of
Aspirants with scores less than 50.
782023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 7.1: SDG 7 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Wokha NL 60 68
Khowai TR 60 68
North Tripura TR 60 68
Dhubri AS 65 67
Karimganj AS 65 67
Barpeta AS 67 66
Morigaon AS 67 66
Nagaon AS 67 66
Sepahijala TR 67 66
Baksa AS 71 65
Goalpara AS 71 65
Biswanath AS 73 64
Hailakandi AS 73 64
Udalguri AS 73 64
Dhalai TR 73 64
Upper Subansiri AR 77 63
Golaghat AS 77 63
Lakhimpur AS 77 63
South West Garo Hills ML 77 63
Karbi Anglong AS 81 62
Tamenglong MN 81 62
Peren NL 81 62
Namsai AR 84 61
South Salmara-Mankachar AS 84 61
South Tripura TR 84 61
Unakoti TR 84 61
Changlang AR 88 60
Charaideo AS 88 60
East Garo Hills ML 90 59
Phek NL 90 59
Longding AR 92 58
Upper Siang AR 92 58
Ukhrul MN 92 58
Darrang AS 95 57
East Jaintia Hills ML 95 57
North Garo Hills ML 95 57
East Kameng AR 98 56
Lower Dibang Valley AR 98 56
Dhemaji AS 98 56
Majuli AS 98 56
Tuensang NL 98 56
Zunheboto NL 103 55
West Karbi Anglong AS 104 54
Kiphire NL 104 54
Anjaw AR 106 53
Ri Bhoi ML 106 53
Lawngtlai MZ 106 53
Kra Daadi AR 109 52
Siang AR 109 52
West Jaintia Hills ML 109 52
Longleng NL 109 52
Mon NL 109 52
South Garo Hills ML 114 49
South West Khasi Hills ML 115 47
West Khasi Hills ML 115 47
Lower Subansiri AR 117 46
Pakke Kessang AR 118 41
Lohit AR 119 30
Shi Yomi AR 120 11
Kamle AR 121 5
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
79
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 7.2: PERFORMANCE OF DISTRICTS IN SDG 7
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
802023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
7.1 Percentage of villages/GPs electrified100
This target corresponds to global SDG target 7.1 that aims to ensure
universal access to affordable, reliable and modern energy services.
7.1
Percentage of households using clean
fuel for cooking
100
This target corresponds to global SDG target 7.1 that aims to ensure
universal access to affordable, reliable and modern energy services.
81
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
82Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 7.1: PERFORMANCE OF DISTRICTS ON SDG 7
SDG Target 7.1 7.1
District Percentage of villages/GPs electrified
Percentage of households
using clean fuel for cooking
SDG 7
Arunachal Pradesh
Anjaw 93.77 29.0 53
Bichom Null Null *
Changlang 96.69 34.1 60
Dibang Valley 100.00 49.3 72
East Kameng 87.32 49.5 56
East Siang 177.38 52.4 74
Kamle 62.34 Null 5
Keyi Panyor Null Null *
Kra Daadi 71.51 78.3 52
Kurung Kumey 94.18 57.3 69
Leparada 105.56 Null 100
Lohit 60.16 63.9 30
Longding 100.00 22.4 58
Lower Dibang Valley 83.44 57.4 56
Lower Siang 108.08 Null 100
Lower Subansiri 74.14 60.8 46
Namsai 127.68 28.7 61
Pakke Kessang 76.54 Null 41
Papum Pare 99.18 81.3 89
Shi Yomi 64.66 Null 11
Siang 93.62 27.6 52
Tawang 99.57 88.1 93
Tirap 166.67 50.4 73
Upper Siang 94.64 36.3 58
Upper Subansiri 112.40 32.8 63
West Kameng 106.92 88.9 94
West Siang 95.24 57.1 71
Assam
Bajali Null Null *
Baksa 100.00 35.2 65
Barpeta 99.66 38.7 66
Biswanath 99.47 35.0 64
Bongaigaon 100.00 49.8 73
Cachar 99.62 43.0 68
Charaideo 99.43 27.3 60
Chirang 99.80 44.5 69
Darrang 96.43 30.1 57
Dhemaji 98.86 21.6 56
Dhubri 99.54 40.7 67
Dibrugarh 99.85 44.7 70
Dima Hasao 98.99 48.2 70
Goalpara 99.64 36.3 65
Golaghat 99.91 33.1 63
Hailakandi 99.40 35.2 64
Hojai 99.29 52.0 73
Jorhat 98.43 48.3 70
Kamrup 99.72 57.4 76
Kamrup Metropolitan 99.07 85.1 91
Karbi Anglong 98.80 33.4 62
Karimganj 99.79 39.6 67
Kokrajhar 99.91 43.3 69
Lakhimpur 98.48 36.1 63
Majuli 100.00 19.3 56
Morigaon 99.84 37.6 66
Nagaon 99.41 38.6 66
Nalbari 100.00 51.1 73
Sivasagar 99.62 45.5 70
Sonitpur 99.38 45.8 70
South Salmara-Mankachar 99.77 28.5 61
Tamulpur Null Null *
Tinsukia 100.00 40.9 68
Udalguri 100.00 34.0 64
West Karbi Anglong 98.89 17.7 54
Manipur
Bishnupur 100.00 71.3 84
Chandel 100.00 52.0 74
Churachandpur 100.00 62.3 79
Imphal East 100.00 79.0 89
Imphal West 100.00 88.6 94
83Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 7.1: PERFORMANCE OF DISTRICTS ON SDG 7
SDG Target 7.1 7.1
District Percentage of villages/GPs electrified
Percentage of households
using clean fuel for cooking
SDG 7
Manipur
Jiribam 100.00 Null 100
Kakching 100.00 Null 100
Kamjong 100.00 Null 100
Kangpokpi 100.00 Null 100
Noney 100.00 Null 100
Pherzawl 100.00 Null 100
Senapati 100.00 50.0 73
Tamenglong 100.00 30.5 62
Tengnoupal 100.00 Null 100
Thoubal 100.00 74.7 86
Ukhrul 100.00 22.9 58
Meghalaya
East Garo Hills 98.05 29.1 59
East Jaintia Hills 97.93 26.5 57
East Khasi Hills 99.61 47.4 71
Eastern West Khasi Hills Null Null *
North Garo Hills 98.60 24.4 57
Ri Bhoi 97.29 21.0 53
South Garo Hills 93.60 22.3 49
South West Garo Hills 99.45 33.9 63
South West Khasi Hills 96.19 11.6 47
West Garo Hills 98.54 47.6 70
West Jaintia Hills 96.12 20.7 52
West Khasi Hills 97.44 8.6 47
Mizoram
Aizawl 98.39 95.4 95
Champhai 100.00 79.4 89
Hnahthial 100.00 Null 100
Khawzawl 100.00 Null 100
Kolasib 100.00 87.5 93
Lawngtlai 81.76 56.3 53
Lunglei 92.68 79.9 80
Mamit 89.66 73.3 72
Saitual 100.00 Null 100
Serchhip 100.00 81.8 90
Siaha 100.00 83.7 91
Nagaland
Chumoukedima Null Null *
Dimapur 100.00 84.2 91
Kiphire 100.00 16.4 54
Kohima 100.00 61.7 79
Longleng 100.00 11.8 52
Mokokchung 100.00 46.2 71
Mon 100.00 13.0 52
Noklak Null Null *
Niuland Null Null *
Peren 100.00 31.4 62
Phek 100.00 24.2 59
Shamator Null Null *
Tseminyu Null Null *
Tuensang 100.00 19.7 56
Wokha 100.00 41.2 68
Zunheboto 100.00 18.6 55
Sikkim
Gangtok 100.00 87.6 93
Gyalshing 100.00 69.8 83
Mangan 100.00 65.9 81
Namchi 100.00 66.5 82
Pakyong 100.00 Null 100
Soreng 100.00 Null 100
Tripura
Dhalai 100.00 34.0 64
Gomati 100.00 47.7 71
Khowai 100.00 41.5 68
North Tripura 100.00 41.6 68
Sepahijala 100.00 37.1 66
South Tripura 100.00 29.4 61
Unakoti 100.00 29.2 61
West Tripura 100.00 65.2 81
Target 100 100 100
Goal 8 promotes sustained economic growth, higher
levels of productivity and technological innovation.
Encouraging entrepreneurship and job creation
are crucial to this, as are effective measures to
eradicate forced labour, modern slavery and human
trafficking. It also seeks to protect labour rights and
promote policies which support decent job creation
and safe and secure working environments. With
these targets in mind, the goal is to achieve full and
productive employment, and decent work, for all
women and men by 2030.
Targets
8.1 Sustain per capita economic growth in
accordance with national circumstances and,
in particular, at least 7 percent gross domestic
product growth per annum in the least
developed countries
8.2 Achieve higher levels of economic productivity
through diversification, technological
upgrading and innovation, including through
a focus on high-value added and labour-
intensive sectors
8.3 Promote development-oriented policies that
support productive activities, decent job
creation, entrepreneurship, creativity and
innovation, and encourage the formalization
and growth of micro-, small- and medium-
sized enterprises, including through access to
financial services
8.4 Improve progressively, through 2030, global
resource efficiency in consumption and
production and endeavour to decouple
economic growth from environmental
degradation, in accordance with the 10‑ Year
Framework of Programmes on Sustainable
Consumption and Production, with developed
countries taking the lead
8.5 By 2030, achieve full and productive
employment and decent work for all women
and men, including for young people and
persons with disabilities, and equal pay for
work of equal value
8.6 By 2020, substantially reduce the proportion of
youth not in employment, education or training
8.7 Take immediate and effective measures
to eradicate forced labour, end modern
slavery and human trafficking and secure the
prohibition and elimination of the worst forms
of child labour, including recruitment and use
of child soldiers, and by 2025 end child labour
in all its forms
8.8 Protect labour rights and promote safe and
secure working environments for all workers,
including migrant workers, in particular women
migrants, and those in precarious employment
8.9 By 2030, devise and implement policies to
promote sustainable tourism that creates jobs
and promotes local culture and products
8.10 Strengthen the capacity of domestic financial
institutions to encourage and expand access to
banking, insurance and financial services for all
8.a Increase Aid for Trade support for developing
countries, in particular least developed
countries, including through the Enhanced
Integrated Framework for Trade related
Technical Assistance to Least Developed
Countries
8.b By 2020, develop and operationalize a global
strategy for youth employment and implement
the Global Jobs Pact of the International
Labour Organization
SDG 8
DECENT WORK AND
ECONOMIC GROWTH
Promote sustained, inclusive and sustainable economic growth,
full and productive employment and decent work for all
85
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
FIGURE 8.1: SDG 8 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Lower Siang AR 1 100
Lower Subansiri AR 2 99
Kamrup Metropolitan AS 2 99
Gangtok SK 4 98
Dimapur NL 5 97
Kohima NL 6 96
Papum Pare AR 7 95
Anjaw AR 8 92
East Siang AR 8 92
Imphal West MN 8 92
West Tripura TR 8 92
Sivasagar AS 12 91
West Kameng AR 13 90
Jorhat AS 13 90
Pakyong SK 13 90
Bongaigaon AS 16 89
Imphal East MN 16 89
Namchi SK 16 89
North Tripura TR 16 89
Lower Dibang Valley AR 20 88
Dibrugarh AS 20 88
Golaghat AS 20 88
Dima Hasao AS 23 87
Nalbari AS 23 87
Thoubal MN 23 87
Gomati TR 23 87
Lohit AR 27 86
Dhubri AS 27 86
Goalpara AS 27 86
Hailakandi AS 27 86
Lakhimpur AS 27 86
Tinsukia AS 27 86
Bishnupur MN 27 86
Dhalai TR 27 86
Sepahijala TR 27 86
South Tripura TR 27 86
Barpeta AS 37 85
Cachar AS 37 85
Chirang AS 37 85
Dhemaji AS 37 85
Karimganj AS 37 85
Kurung Kumey AR 42 84
Darrang AS 42 84
Karbi Anglong AS 42 84
Nagaon AS 42 84
Aizawl MZ 42 84
Mangan SK 42 84
Khowai TR 42 84
Majuli AS 49 83
Ukhrul MN 49 83
Lawngtlai MZ 49 83
Siaha MZ 49 83
Unakoti TR 49 83
Shi Yomi AR 54 82
Upper Siang AR 54 82
Charaideo AS 54 82
Kokrajhar AS 54 82
Sonitpur AS 54 82
East Khasi Hills ML 54 82
Kolasib MZ 54 82
East Kameng AR 61 81
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
NER District SDG Index: Goal 8
The score for Goal 8 ranges between 100 and 52 for the
121 districts included in the ranking and computation.
Lower Siang [AR] is the Achiever district. 111 districts
fall in the category of Front Runners and 9 in the
category of Performers, with no district in the category
of Aspirants with scores less than 50.
862023-24NER DISTRICT SDG INDEX
0 2010 4030 50 60 908070 100
FIGURE 8.1: SDG 8 INDEX SCORE OF DISTRICTS
District StateRank
West Siang AR 61 81
Champhai MZ 61 81
Lunglei MZ 61 81
Mamit MZ 61 81
Changlang AR 66 80
Leparada AR 66 80
Tawa n g AR 68 79
Kamle AR 69 78
Namsai AR 69 78
Tirap AR 69 78
Mokokchung NL 69 78
Morigaon AS 73 77
Kakching MN 73 77
Senapati MN 73 77
West Khasi Hills ML 73 77
Mon NL 73 77
Gyalshing SK 73 77
Siang AR 79 75
Upper Subansiri AR 79 75
Hojai AS 79 75
Udalguri AS 79 75
Chandel MN 79 75
Khawzawl MZ 79 75
Kiphire NL 79 75
Longleng NL 79 75
Peren NL 79 75
Longding AR 88 74
Jiribam MN 88 74
Wokha NL 88 74
Baksa AS 91 73
Kamrup AS 91 73
Tengnoupal MN 91 73
East Jaintia Hills ML 91 73
Biswanath AS 95 72
West Karbi Anglong AS 95 72
Ri Bhoi ML 95 72
Zunheboto NL 95 72
South Salmara-Mankachar AS 99 71
Tamenglong MN 99 71
South West Garo Hills ML 99 71
Phek NL 99 71
Churachandpur MN 103 70
Serchhip MZ 103 70
Tuensang NL 103 70
Dibang Valley AR 106 68
South Garo Hills ML 107 67
Saitual MZ 108 66
Soreng SK 108 66
Kangpokpi MN 110 65
Noney MN 110 65
West Garo Hills ML 110 65
Hnahthial MZ 113 63
Kra Daadi AR 114 62
Pakke Kessang AR 114 62
East Garo Hills ML 114 62
Kamjong MN 117 61
North Garo Hills ML 117 61
South West Khasi Hills ML 117 61
West Jaintia Hills ML 120 60
Pherzawl MN 121 52
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
87
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 8.2: PERFORMANCE OF DISTRICTS IN SDG 8
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
882023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
8.3
Percentage of loans disbursed to
MSMEs against sanctioned
100
This target corresponds to Global SDG target 8.3 that aims to
promote development oriented policies that support productive
activities, decent job creation, entrepreneurship, creativity and
innovation, and encourage the formalization and growth of micro,
small-and medium-sized enterprises, including through access to
financial services.
8.7
Number of victims of human
trafficking per 10,000 population
0
Global SDG target 8.7 aims to take immediate and effective
measures to eradicate forced labour, and end modern slavery and
human trafficking.
8.10
Percentage of households covered
with a bank account under Pradhan
Mantri Jan Dhan Yojana (PMJDY)
against target
100
The Pradhan Mantri Jan Dhan Yojana aims to provide at least one
basic savings banking account to every household.
8.10
Number of bank branches including
Business Correspondents (BCs) in
Urban, Semi-urban and Rural areas
per 10,000 population
8.58
Global SDG target 8.10 aims to strengthen the capacity of
domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all. Average of the 5
best scores has been set as the target.
8.10
Automated Teller Machines (ATMs)
per 10,000 population
5.65
Global SDG target 8.10 aims to strengthen the capacity of
domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all. Average of the 5
best scores has been set as the target.
8.10
Percentage of women account
holders in Pradhan Mantri Jan Dhan
Yojana (PMJDY)
50
This target corresponds to the global SDG target 5.a that aims
to undertake reforms to give women equal rights to economic
resource and access to financial services, and to the global SDG
target 8.10 that aims to expand access to banking, insurance and
financial services for all.
89
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
90Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 8.1: PERFORMANCE OF DISTRICTS ON SDG 8
SDG Target 8.3 8.7 8.10 8.10 8.10 8.10
District
Percentage of loans
disbursed to MSMEs
against sanctioned
Number of victims of
human trafficking per
10,000 population
Percentage of households
covered with a bank account
under PMJDY against target
Number of bank branches including Business
Correspondents (BCs) in Urban, Semi-urban
and Rural areas per 10,000 population
Automated Teller
Machines (ATMs) per
10,000 population
Percentage of
women account
holders in PMJDY
SDG 8
Arunachal Pradesh
Anjaw 100.00 0.00 100.00 5.20 Null 55.08 92
Bichom Null Null Null Null Null Null *
Changlang 100.00 0.00 100.00 5.94 0.94 54.80 80
Dibang Valley 100.00 0.00 100.00 3.75 Null 41.43 68
East Kameng 100.00 0.00 100.00 6.19 0.95 54.66 81
East Siang 100.00 0.00 100.00 18.10 3.06 52.32 92
Kamle 100.00 0.00 Null 1.35 Null 58.95 78
Keyi Panyor Null Null Null Null Null Null *
Kra Daadi 100.00 0.00 Null 0.43 0.64 62.20 62
Kurung Kumey 100.00 0.00 100.00 1.98 Null 58.67 84
Leparada 100.00 0.00 Null 7.44 0.99 53.87 80
Lohit 100.00 0.00 100.00 6.43 2.61 60.20 86
Longding 100.00 0.00 100.00 3.88 0.35 62.75 74
Lower Dibang Valley 100.00 0.00 100.00 14.61 1.66 53.80 88
Lower Siang 100.00 0.00 Null 21.60 Null 53.19 100
Lower Subansiri 100.00 0.00 100.00 11.10 5.19 54.79 99
Namsai 100.00 0.00 Null 6.46 0.94 52.05 78
Pakke Kessang 100.00 0.00 Null 1.65 0.83 48.25 62
Papum Pare 100.00 0.11 100.00 47.06 7.82 56.26 95
Shi Yomi 100.00 0.00 Null 8.26 0.75 53.55 82
Siang 100.00 0.00 Null 4.07 Null 46.21 75
Tawang 100.00 0.20 100.00 7.20 2.20 51.61 79
Tirap 100.00 0.00 100.00 5.06 0.72 57.37 78
Upper Siang 100.00 0.00 100.00 5.66 1.70 54.93 82
Upper Subansiri 100.00 0.00 100.00 3.13 1.18 55.32 75
West Kameng 100.00 0.00 100.00 7.14 3.44 53.87 90
West Siang 100.00 0.19 100.00 9.14 2.67 48.74 81
Assam
Bajali Null Null Null Null Null Null *
Baksa 100.00 0.08 100.00 4.73 0.47 61.56 73
Barpeta 100.00 0.02 100.00 13.21 1.03 56.16 85
Biswanath 100.00 0.21 Null 8.75 0.80 59.96 72
Bongaigaon 100.00 0.00 100.00 11.53 2.11 58.78 89
Cachar 100.00 0.00 99.62 14.27 1.45 56.28 85
Charaideo 100.00 0.00 Null 8.50 0.85 63.13 82
Chirang 100.00 0.00 100.00 8.13 0.87 61.51 85
Darrang 100.00 0.05 100.00 16.68 1.11 57.10 84
Dhemaji 100.00 0.04 100.00 17.50 1.33 57.53 85
Dhubri 100.00 0.01 100.00 17.79 1.09 57.39 86
Dibrugarh 100.00 0.07 100.00 12.18 2.47 61.18 88
Dima Hasao 100.00 0.00 100.00 7.89 1.63 55.12 87
Goalpara 100.00 0.01 100.00 16.25 1.06 58.76 86
Golaghat 100.00 0.01 100.00 11.44 1.86 59.21 88
Hailakandi 100.00 0.02 100.00 11.24 1.15 56.45 86
Hojai 100.00 0.05 Null 6.39 0.87 58.44 75
Jorhat 100.00 0.01 99.89 14.10 2.76 60.81 90
Kamrup 100.00 0.41 100.00 12.81 2.31 58.03 73
Kamrup Metropolitan 100.00 0.02
100.00 115.85 6.64 56.13 99
Karbi Anglong 100.00 0.03 100.00 8.41 0.91 59.54 84
Karimganj 100.00 0.00 100.00 8.02 1.06 55.50 85
Kokrajhar 100.00 0.09 100.00 11.95 1.01 57.66 82
Lakhimpur 100.00 0.05 100.00 12.18 1.54 57.74 86
Majuli 100.00 0.00 Null 13.21 1.02 61.40 83
Morigaon 100.00 0.10 99.43 13.42 0.74 58.00 77
Nagaon 100.00 0.08 100.00 27.65 1.40 57.08 84
Nalbari 100.00 0.01 100.00 13.66 1.46 59.24 87
Sivasagar 100.00 0.03 99.97 17.20 3.06 59.51 91
Sonitpur 100.00 0.13 100.00 16.33 1.58 60.27 82
South Salmara-Mankachar 100.00 0.20 Null 13.91 0.20 62.13 71
Tamulpur Null Null Null Null Null Null *
Tinsukia 100.00 0.02 100.00 11.40 1.36 61.71 86
Udalguri 100.00 0.25 100.00 11.06 0.71 59.11 75
West Karbi Anglong 100.00 0.00 Null 5.04 0.27 57.49 72
Manipur
Bishnupur 100.00 0.00 100.00 17.35 1.14 60.47 86
Chandel 100.00 0.00 100.00 3.95 0.36 54.98 75
Churachandpur 100.00 0.00 97.43 15.98 1.33 54.18 70
Imphal East 100.00 0.00 100.00 13.49 1.89 60.08 89
Imphal West 100.00 0.00 100.00 69.92 3.07 60.54 92
91Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 8.1: PERFORMANCE OF DISTRICTS ON SDG 8
SDG Target 8.3 8.7 8.10 8.10 8.10 8.10
District
Percentage of loans
disbursed to MSMEs
against sanctioned
Number of victims of
human trafficking per
10,000 population
Percentage of households
covered with a bank account
under PMJDY against target
Number of bank branches including Business
Correspondents (BCs) in Urban, Semi-urban
and Rural areas per 10,000 population
Automated Teller
Machines (ATMs) per
10,000 population
Percentage of
women account
holders in PMJDY
SDG 8
Jiribam 100.00 0.00 Null 6.16 0.23 56.91 74
Kakching 100.00 0.00 Null 6.65 0.69 57.11 77
Kamjong 100.00 0.00 Null 1.24 0.21 49.52 61
Kangpokpi 100.00 0.00 Null 2.01 0.41 53.75 65
Noney 100.00 0.00 Null 4.52 0.20 47.51 65
Pherzawl 0.00 0.00 Null 1.21 Null 55.56 52
Senapati 100.00 0.00 100.00 4.17 0.84 52.41 77
Tamenglong 100.00 0.00 100.00 4.46 0.11 47.79 71
Tengnoupal 100.00 0.00 Null 4.62 0.83 54.80 73
Thoubal 100.00 0.00 100.00 25.62 1.34 58.50 87
Ukhrul 100.00 0.00 100.00 11.79 0.29 49.61 83
Meghalaya
East Garo Hills 10.64 0.00 100.00 4.60 0.55 58.29 62
East Jaintia Hills 22.73 0.00 100.00 12.53 0.81 61.71 73
East Khasi Hills 33.45 0.00 100.00 11.03 3.40 58.38 82
Eastern West Khasi Hills Null Null Null Null Null Null *
North Garo Hills 13.21 0.06 100.00 5.40 0.29 56.45 61
Ri Bhoi 21.88 0.00 100.00 7.22 1.55 60.53 72
South Garo Hills 36.67 0.00 100.00 5.06 0.42 54.62 67
South West Garo Hills 38.78 0.06 100.00 8.67 0.28 53.10 71
South West Khasi Hills 10.00 0.00 100.00 3.93 0.91 64.47 61
West Garo Hills 16.42 0.17 100.00 13.25 1.14 57.27 65
West Jaintia Hills 16.04 0.00 Null 5.62 1.25 65.79 60
West Khasi Hills 50.00 0.00 100.00 9.09 0.65 54.79 77
Mizoram
Aizawl 100.00 0.00 99.80 5.23 3.18 51.54 84
Champhai 100.00 0.00 100.00 6.26 0.97 52.29 81
Hnahthial 100.00 0.00 Null 4.21 0.35 46.83 63
Khawzawl 100.00 0.00 Null 6.24 0.27 55.97 75
Kolasib 100.00 0.00 100.00 6.31 1.07 57.00 82
Lawngtlai 100.00 0.00 100.00 7.80 0.51 51.43 83
Lunglei 100.00 0.00 100.00 6.15 1.14 50.08 81
Mamit 100.00 0.00 100.00 6.72 0.69 56.36 81
Saitual 100.00 0.00 Null 2.37 0.40 55.37 66
Serchhip 100.00 0.31 100.00 7.34 0.76 54.46 70
Siaha 100.00 0.00 100.00 7.07 0.88 53.40 83
Nagaland
Chumoukedima Null Null Null Null Null Null *
Dimapur 100.00 0.00 99.60 15.47 6.75 54.13 97
Kiphire 100.00 0.00 100.00 4.19 0.27 55.43 75
Kohima 100.00 0.00 100.00 12.93 4.17 59.93 96
Longleng 100.00 0.00 100.00 4.36 0.20 53.93 75
Mokokchung 100.00 0.00 100.00 3.55 1.80 55.21 78
Mon 100.00 0.00 100.00 4.91 0.36 51.80 77
Noklak Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null *
Peren 100.00 0.00 100.00 3.78 0.53 56.32 75
Phek 100.00 0.00 100.00 2.26 0.37 57.74 71
Shamator Null Null Null Null Null Null *
Tseminyu Null
Null Null Null Null Null *
Tuensang 100.00 0.00 100.00 1.77 0.47 52.12 70
Wokha 100.00 0.00 100.00 3.61 0.54 62.92 74
Zunheboto 100.00 0.00 100.00 2.20 0.64 58.01 72
Sikkim
Gangtok 90.09 0.00 100.00 14.31 6.20 51.00 98
Gyalshing 73.51 0.00 100.00 4.88 2.09 58.56 77
Mangan 81.98 0.00 100.00 6.63 3.20 49.40 84
Namchi 91.24 0.00 100.00 7.76 3.00 53.76 89
Pakyong 85.19 0.00 Null 7.33 4.68 53.00 90
Soreng 73.99 0.00 Null 3.71 1.08 54.45 66
Tripura
Dhalai 97.75 0.00 100.00 8.83 1.22 55.32 86
Gomati 97.33 0.00 100.00 10.44 1.63 54.52 87
Khowai 95.06 0.00 100.00 8.49 0.70 55.43 84
North Tripura 98.72 0.02 100.00 13.63 2.23 54.17 89
Sepahijala 98.19 0.00 100.00 9.00 1.04 56.48 86
South Tripura 98.72 0.00 100.00 8.13 1.23 56.05 86
Unakoti 98.34 0.00 100.00 7.59 0.80 58.35 83
West Tripura 97.36 0.00 100.00 8.45 3.37 56.79 92
Target 100 0 100 8.58 5.65 50 100
This goal promotes investment in innovation; and
reliable and resilient infrastructure which are crucial
drivers of economic growth and development.
It further aims at promoting increased resource
use efficiency and greater adoption of clean and
environmentally sound technologies and industrial
processes. It recognizes the importance of promoting
sustainable industries and investing in scientific
research and innovation, which are all important
ways to facilitate sustainable development.
Targets
9.1 Develop quality, reliable, sustainable and
resilient infrastructure, including regional
and transborder infrastructure, to support
economic development and human well-
being, with a focus on affordable and equitable
access for all
9.2 Promote inclusive and sustainable
industrialization and, by 2030, significantly
raise industry’s share of employment and
gross domestic product, in line with national
circumstances, and double its share in least
developed countries
9.3 Increase the access of small-scale industrial and
other enterprises, in particular in developing
countries, to financial services, including
affordable credit, and their integration into
value chains and markets
9.4 By 2030, upgrade infrastructure and retrofit
industries to make them sustainable, with
increased resource-use efficiency and greater
adoption of clean and environmentally sound
technologies and industrial processes, with
all countries taking action in accordance with
their respective capabilities
9.5 Enhance scientific research, upgrade the
technological capabilities of industrial sectors
in all countries, in particular developing
countries, including, by 2030, encouraging
innovation and substantially increasing the
number of research and development workers
per 1 million people and public and private
research and development spending
9.a Facilitate sustainable and resilient infrastructure
development in developing countries through
enhanced financial, technological and technical
support to African countries, least developed
countries, landlocked developing countries
and small island developing States
9.b Support domestic technology development,
research and innovation in developing
countries, including by ensuring a conducive
policy environment for, inter alia, industrial
diversification and value addition to
commodities
9.c Significantly increase access to information
and communications technology and strive to
provide universal and affordable access to the
Internet in least developed countries by 2020
SDG 9
INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Build resilient infrastructure, promote inclusive and
sustainable industrialisation and foster innovation
93
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 9.1: SDG 9 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 9
0 2010 4030 50 60 908070 100
District StateRank
Hnahthial MZ 1 100
Champhai MZ 2 98
Sepahijala TR 2 98
West Tripura TR 2 98
Nagaon AS 5 97
Unakoti TR 5 97
Biswanath AS 7 96
Dibrugarh AS 7 96
Morigaon AS 7 96
Nalbari AS 7 96
Sonitpur AS 7 96
South West Garo Hills ML 7 96
West Garo Hills ML 7 96
Aizawl MZ 7 96
Cachar AS 15 95
Dhubri AS 15 95
Karimganj AS 15 95
Barpeta AS 18 94
Bongaigaon AS 18 94
Darrang AS 18 94
Hailakandi AS 18 94
Kamrup AS 18 94
Kamrup Metropolitan AS 18 94
Sivasagar AS 18 94
Khowai TR 18 94
North Tripura TR 18 94
South Tripura TR 18 94
Baksa AS 28 93
Dhemaji AS 28 93
Goalpara AS 28 93
Hojai AS 28 93
Lakhimpur AS 28 93
Tinsukia AS 28 93
Udalguri AS 28 93
West Jaintia Hills ML 28 93
Gomati TR 28 93
Charaideo AS 37 92
Chirang AS 37 92
Majuli AS 37 92
Dhalai TR 37 92
Jorhat AS 41 91
East Khasi Hills ML 41 91
North Garo Hills ML 41 91
Ri Bhoi ML 41 91
Golaghat AS 45 90
Kolasib MZ 45 90
South Salmara-Mankachar AS 47 89
East Garo Hills ML 47 89
East Jaintia Hills ML 49 88
South West Khasi Hills ML 50 87
Kokrajhar AS 51 86
Dimapur NL 51 86
Karbi Anglong AS 53 84
Imphal East MN 54 83
Kohima NL 54 83
South Garo Hills ML 56 82
Longleng NL 56 82
Papum Pare AR 58 81
Bishnupur MN 58 81
Imphal West MN 58 81
Tawa n g AR 61 80
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 9 ranges between 100 and 11 for the
121 districts included in the ranking and computation.
Hnahthial [MZ], Champhai [MZ], Sepahijala [TR] and
West Tripura [TR] are the top performing districts. 1
district falls in the category of Achiever, 92 districts fall
in the category of Front Runners and 11 in the category
of Performers, while 17 districts are in the category of
Aspirants with scores less than 50.
942023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 9.1: SDG 9 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
West Karbi Anglong AS 61 80
Kakching MN 63 79
West Khasi Hills ML 63 79
Dima Hasao AS 65 78
Changlang AR 66
Mokokchung NL 66
Pherzawl MN 68 74
Saitual MZ 68 74
Thoubal MN 70 73
Lunglei MZ 70 73
Phek NL 70 73
East Kameng AR 73 72
Namsai AR 73 72
Lawngtlai MZ 73 72
Serchhip MZ 73 72
Lohit AR 77 71
Chandel MN 77 71
Tengnoupal MN 77 71
Mangan SK 77 71
East Siang AR 81 70
Mamit MZ 81 70
Mon NL 81 70
Gangtok SK 81 70
Pakyong SK 81 70
Pakke Kessang AR 86 68
Namchi SK 86 68
Peren NL 88 67
Soreng SK 88 67
Kangpokpi MN 90 66
Ukhrul MN 90 66
Khawzawl MZ 90 66
Senapati MN 93 65
Kurung Kumey AR 94 64
Churachandpur MN 94 64
Siaha MZ 94 64
Wokha NL 94 64
Gyalshing SK 94 64
Jiribam MN 99 55
Kamjong MN 99 55
Lower Dibang Valley 101 53
Kiphire NL 101 53
Lower Subansiri AR 103 52
Tamenglong MN 104 51
West Kameng AR 105 49
Tuensang NL 105 49
West Siang AR 107 47
Upper Subansiri AR 108 46
Zunheboto NL 109 45
Dibang Valley AR 110 39
Noney MN 110 39
Kra Daadi AR 112 28
Lower Siang AR 113 27
Tirap AR 113 27
Anjaw AR 115 25
Kamle AR 116 22
Shi Yomi AR 116 22
Longding AR 118 21
Upper Siang AR 119 18
Leparada AR 120 15
Siang AR 121 11
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
77
77
95
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 9.2: PERFORMANCE OF DISTRICTS IN SDG 9
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
962023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
9.1
Percentage of targeted habitations
connected by all-weather roads under
Pradhan Mantri Gram Sadak Yojana
(PMGSY) and other schemes
100
Global SDG Target 9.1 aims to develop quality, reliable, sustainable
and resilient infrastructure to support economic development and
equitable access for all. It is aimed that all targeted unconnected
habitations under PMGSY and related state schemes are connected.
9.1
Surfaced road as a percentage of
total road length
100
Global SDG Target 9.1 aims to develop quality, reliable, sustainable
and resilient infrastructure to support economic development and
equitable access for all.
9.c
Percentage of GPs/villages with
internet connection (broadband or
cellular)
100
This target aligns with global SDG target 9.c which aims to
significantly increase access to information and communications
technology “Digital India Initiative” of the Government of India also
aims to boost universal coverage of internet connectivity.
9.c
Percentage of villages covered by a
mobile network
100
This target aligns with global SDG target 9.c which aims to
significantly increase access to information and communications
technology. One of the pillars of the “Digital India Initiative” is
universal access to mobile connectivity.
97
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
98Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 9.1: PERFORMANCE OF DISTRICTS ON SDG 9
SDG Target 9.1 9.1 9.c 9.c
District
Percentage of habitations with
access to all weather roads under
PMGSY and other State schemes
Surfaced road as a percentage of
total road length
Percentage of GPs/villages with
internet connection (broadband or
cellular)
Percentage of villages covered by a
mobile network.
SDG 9
Arunachal Pradesh
Anjaw 13.95 56.99 15.74 24.26 25
Bichom Null Null Null Null *
Changlang 89.39 66.99 66.57 88.40 77
Dibang Valley 47.62 53.34 26.76 36.62 39
East Kameng 98.00 26.20 69.57 109.06 72
East Siang 8.47 78.55 138.10 158.33 70
Kamle 64.18 28.53 1.30 3.03 22
Keyi Panyor Null Null Null Null *
Kra Daadi 90.00 26.99 0.28 0.56 28
Kurung Kumey 80.22 28.12 67.72 87.04 64
Leparada 29.63 36.19 1.39 1.39 15
Lohit 14.71 77.25 201.63 228.46 71
Longding 70.83 23.00 0.00 0.00 21
Lower Dibang Valley 40.00 40.15 67.52 75.16 53
Lower Siang 82.14 32.13 0.00 1.01 27
Lower Subansiri 33.54 30.10 54.31 115.09 52
Namsai 42.24 62.91 91.53 110.73 72
Pakke Kessang 50.00 31.35 345.68 466.67 68
Papum Pare 138.78 48.86 80.82 99.38 81
Shi Yomi 58.97 28.66 5.17 5.17 22
Siang 26.97 20.74 3.19 3.19 11
Tawang 65.52 58.57 134.47 194.04 80
Tirap 65.22 51.12 0.00 0.00 27
Upper Siang 50.75 32.16 0.00 0.00 18
Upper Subansiri 91.78 20.76 34.30 43.39 46
West Kameng 46.00 53.55 39.23 63.85 49
West Siang 44.09 43.34 44.90 63.27 47
Assam
Bajali Null Null Null Null *
Baksa 98.94 75.80 100.00 100.00 93
Barpeta 99.57 77.18 100.00 100.00 94
Biswanath 99.49 86.03 99.47 99.57 96
Bongaigaon 100.19 77.63 99.11 99.64 94
Cachar 98.70 87.09 97.15 98.10 95
Charaideo 100.26 71.49 100.00 100.00 92
Chirang 99.21 69.94 100.00 100.00 92
Darrang 99.69 77.61 99.82 100.00 94
Dhemaji 99.91 77.11 99.01 99.16 93
Dhubri 97.77 84.01 99.79 100.00 95
Dibrugarh 99.74 87.47 99.41 99.56 96
Dima Hasao 96.41 57.00 81.83 82.66 78
Goalpara 98.57 77.12 99.29 99.52 93
Golaghat 100.00 71.72 96.12 96.38 90
Hailakandi 97.75 82.17 97.89 99.40 94
Hojai 99.13 76.67 99.26 99.26 93
Jorhat 99.12 67.76 99.18 99.67 91
Kamrup 99.55 82.77 98.25 98.44 94
Kamrup Metropolitan 99.57 78.59 100.00 100.00 94
Karbi Anglong 97.85 55.93 93.12 94.64 84
Karimganj 98.44 81.85 99.89 100.00 95
Kokrajhar 100.00 50.93 99.34 99.44 86
Lakhimpur 98.83 77.17 99.91 100.00 93
Majuli 99.56 81.04 94.76 96.37 92
Morigaon 99.87 86.20 99.68 100.00 96
Nagaon 99.83 90.35 99.51 99.51 97
Nalbari 100.00 84.49 99.56 99.56 96
Sivasagar 98.95 83.31 98.03 98.03 94
Sonitpur 99.82 87.53 98.72 99.14 96
South Salmara-Mankachar 93.17 67.92 100.00 100.00 89
Tamulpur Null Null Null Null *
Tinsukia 99.59 75.68 98.81 98.89 93
Udalguri 100.16 76.64 99.63 99.63 93
West Karbi Anglong 95.22 48.95 89.93 90.66 80
Manipur
Bishnupur 100.00 73.68 54.17 100.00 81
Chandel 98.21
32.44 89.14 70.41 71
Churachandpur 86.42 39.86 58.68 76.04 64
Imphal East 100.00 99.48 35.46 96.45 83
Imphal West 100.00 91.14 34.58 100.00 81
99Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 9.1: PERFORMANCE OF DISTRICTS ON SDG 9
SDG Target 9.1 9.1 9.c 9.c
District
Percentage of habitations with
access to all weather roads under
PMGSY and other State schemes
Surfaced road as a percentage of
total road length
Percentage of GPs/villages with
internet connection (broadband or
cellular)
Percentage of villages covered by a
mobile network.
SDG 9
Jiribam 100.00 33.37 0.00 92.00 55
Kakching 100.00 65.37 59.26 96.30 79
Kamjong 82.05 34.69 45.53 66.67 55
Kangpokpi 98.36 36.50 50.47 85.74 66
Noney 86.96 19.15 20.55 36.99 39
Pherzawl 95.24 17.50 95.45 93.94 74
Senapati 95.92 59.34 12.50 96.32 65
Tamenglong 94.92 8.35 38.61 69.31 51
Tengnoupal 100.00 58.60 62.58 67.48 71
Thoubal 100.00 48.12 46.67 101.67 73
Ukhrul 100.00 32.68 47.78 87.78 66
Meghalaya
East Garo Hills 94.74 95.61 82.07 82.97 89
East Jaintia Hills 100.00 88.22 82.38 83.33 88
East Khasi Hills 97.01 92.72 87.48 88.83 91
Eastern West Khasi Hills Null Null Null Null *
North Garo Hills 93.10 88.10 92.30 92.46 91
Ri Bhoi 98.15 90.87 85.98 88.11 91
South Garo Hills 82.61 79.62 82.84 84.14 82
South West Garo Hills 95.83 93.73 97.19 97.94 96
South West Khasi Hills 93.10 86.64 83.92 86.55 87
West Garo Hills 98.13 93.96 96.49 96.58 96
West Jaintia Hills 91.67 91.04 93.94 94.85 93
West Khasi Hills 94.74 82.23 70.35 72.28 79
Mizoram
Aizawl 100.00 89.49 97.10 97.10 96
Champhai 100.00 96.56 98.39 98.39 98
Hnahthial 100.00 100.00 100.00 100.00 100
Khawzawl 7.69 73.49 94.74 94.74 66
Kolasib 100.00 65.00 100.00 100.00 90
Lawngtlai 31.11 76.68 92.35 92.35 72
Lunglei 29.41 93.48 87.61 87.61 73
Mamit 10.53 91.83 91.11 91.11 70
Saitual 15.38 92.46 96.30 96.30 74
Serchhip 5.56 91.10 98.92 98.92 72
Siaha 17.86 83.63 79.55 79.55 64
Nagaland
Chumoukedima Null Null Null Null *
Dimapur 100.00 51.16 98.59 100.00 86
Kiphire 44.23 38.61 59.05 77.14 53
Kohima 84.75 65.88 87.63 95.88 83
Longleng 92.73 47.66 93.48 100.00 82
Mokokchung 90.32 29.02 96.51 97.67 77
Mon 76.60 53.31 73.77 81.97 70
Noklak Null Null Null Null *
Niuland Null Null Null Null *
Peren 63.95 60.34 66.67 81.61 67
Phek 65.22 41.51 95.96 97.98 73
Shamator Null Null Null Null *
Tseminyu Null Null Null Null *
Tuensang 32.84 25.44 74.59 74.59 49
Wokha 69.63 32.18 75.19 85.71 64
Zunheboto 27.75 24.38 64.12 74.12 45
Sikkim
Gangtok 19.70 68.96 100.00 100.00 70
Gyalshing 15.58 48.81 100.00 100.00 64
Mangan 17.47 72.60 100.00 100.00 71
Namchi 13.40 67.11 100.00 100.00 68
Pakyong 13.77 72.95 100.00 100.00 70
Soreng 15.48 59.73 100.00 100.00 67
Tripura
Dhalai 97.46 93.55 86.09 91.39 92
Gomati 100.00 94.06 88.44 89.02 93
Khowai 100.00 89.11 87.10 99.19 94
North Tripura 96.83 90.66 93.02 97.67 94
Sepahijala 100.00 95.58 98.22 100.00 98
South Tripura 100.00 90.91 86.98 97.04 94
Unakoti 99.68 91.63 97.80 100.00 97
West Tripura 100.00 93.30 98.82 100.00 98
Target 100 100 100 100 100
The Goal calls for progressively reducing not only
income inequalities but also inequalities-of-outcome
by ensuring access to equal opportunities and
promoting social, economic and political inclusion of
all, irrespective of age, sex, disability, race, ethnicity,
origin, religion or economic or any other status
relevant within a society. It also aims at enhancing
representation and voice for developing countries
in decision making in international economic and
financial institutions.
Targets
10.1 By 2030, progressively achieve and sustain
income growth of the bottom 40 percent
of the population at a rate higher than the
national average
10.2 By 2030, empower and promote the social,
economic and political inclusion of all,
irrespective of age, sex, disability, race,
ethnicity, origin, religion or economic or
other status
10.3 Ensure equal opportunity and reduce
inequalities of outcome, including by
eliminating discriminatory laws, policies
and practices and promoting appropriate
legislation, policies and action in this regard
10.4 Adopt policies, especially fiscal, wage and
social protection policies, and progressively
achieve greater equality
10.5 Improve the regulation and monitoring of
global financial markets and institutions
and strengthen the implementation of such
regulations
10.6 Ensure enhanced representation and voice
for developing countries in decision-making
in global international economic and financial
institutions in order to deliver more effective,
credible, accountable and legitimate
institutions
10.7 Facilitate orderly, safe, regular and responsible
migration and mobility of people, including
through the implementation of planned and
well-managed migration policies
10.a Implement the principle of special and
differential treatment for developing countries,
in particular least developed countries, in
accordance with World Trade Organization
agreements
10.b Encourage official development assistance
and financial flows, including foreign direct
investment, to States where the need is
greatest, in particular least developed
countries, African countries, small island
developing States and landlocked developing
countries, in accordance with their national
plans and programmes
10.c By 2030, reduce to less than 3 percent the
transaction costs of migrant remittances and
eliminate remittance corridors with costs
higher than 5 percent
SDG 10
REDUCED INEQUALITIES
Reduce inequality within and among countries
101
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 10.1: SDG 10 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 10
0 2010 4030 50 60 908070 100
District StateRank
South West Khasi Hills ML 1 86
Pakke Kessang AR 2 84
Dibang Valley AR 3 82
East Kameng AR 3 82
Kra Daadi AR 5 81
East Jaintia Hills ML 5 81
Pakyong SK 7 79
Unakoti TR 7 79
Mon NL 9 78
Kurung Kumey AR 10 77
Jiribam MN 10 77
East Garo Hills ML 10 77
Peren NL 10 77
South West Garo Hills ML 14 76
North Tripura TR 14 76
Kamle AR 16 75
East Khasi Hills ML 16 75
Papum Pare AR 18 74
Upper Subansiri AR 18 74
West Jaintia Hills ML 18 74
Dhalai TR 18 74
Lower Dibang Valley AR 22 72
Gomati TR 22 72
Bishnupur MN 24 71
West Garo Hills ML 24 71
Sepahijala TR 24 71
Majuli AS 27 70
Nagaon AS 27 70
Mangan SK 29 69
Khowai TR 29 69
Biswanath AS 31 68
Nalbari AS 31 68
Jorhat AS 33 67
Karimganj AS 33 67
Mokokchung NL 33 67
West Tripura TR 33 67
Leparada AR 37 66
Tawa n g AR 37 66
Darrang AS 39 65
Hojai AS 39 65
Kakching MN 39 65
Ri Bhoi ML 39 65
South Tripura TR 39 65
Lohit AR 44 64
Upper Siang AR 44 64
Dibrugarh AS 44 64
Namsai AR 47 63
Hailakandi AS 47 63
West Khasi Hills ML 47 63
Champhai MZ 47 63
Anjaw AR 51 62
Morigaon AS 51 62
Sivasagar AS 51 62
North Garo Hills ML 51 62
Namchi SK 51 62
Bongaigaon AS 56 61
Dima Hasao AS 56 61
Lunglei MZ 56 61
Saitual MZ 56 61
Charaideo AS 60 60
Lakhimpur AS 60 60
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 10 ranges between 86 and 0 for the
121 districts included in the ranking and computation.
South West Khasi Hills [ML], Pakke Kessang [AR] and
Dibang Valley [AR] are the top performing districts.
43 districts fall in the category of Front Runners and 45 in the category of Performers, while 33 districts are
in the category of Aspirants with scores less than 50.
1022023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 10.1: SDG 10 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Sonitpur AS 60 60
Tinsukia AS 60 60
Cachar AS 64 59
Golaghat AS 64 59
Mamit MZ 66 58
Gyalshing SK 66 58
Goalpara AS 68 57
Kamrup AS 68 57
Imphal East MN 68 57
South Garo Hills ML 68 57
Dhubri AS 72 56
Imphal West MN 72 56
Aizawl MZ 72 56
Siaha MZ 72 56
Soreng SK 72 56
South Salmara-Mankachar AS 77 55
Lawngtlai MZ 77 55
Wokha NL 77 55
Barpeta AS 80 54
Hnahthial MZ 80 54
Khawzawl MZ 80 54
Kolasib MZ 80 54
Gangtok SK 80 54
Kamrup Metropolitan AS 85 53
Kohima NL 86 52
Baksa AS 87 51
West Kameng AR 88 50
Siang AR 89 49
Dhemaji AS 89 49
Thoubal MN 89 49
Chirang AS 92 46
Serchhip MZ 92 46
Dimapur NL 92 46
Karbi Anglong AS 95 45
Lower Subansiri AR 96 44
West Siang AR 96 44
Kokrajhar AS 96 44
Shi Yomi AR 99 43
Phek NL 99 43
Kamjong MN 101 42
Ukhrul MN 101 42
Senapati MN 103 40
Udalguri AS 104 39
West Karbi Anglong AS 104 39
Tengnoupal MN 106 38
Longleng NL 106 38
Chandel MN 108 37
Churachandpur MN 109 36
Changlang AR 110 35
Tamenglong MN 111 34
East Siang AR 112 33
Lower Siang AR 112 33
Longding AR 114 30
Noney MN 115 29
Kiphire NL 115 29
Tuensang NL 117 26
Tirap AR 118 25
Kangpokpi MN 119 16
Zunheboto NL 120 13
Pherzawl MN 121
0
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
103
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 10.2: PERFORMANCE OF DISTRICTS IN SDG 10
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1042023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
10.2
Percentage of women representatives
in PRIs, ULBs, District Autonomous
Councils, VCs, VECs
56.18
This target corresponds to the global SDG target 10.2 that aims to
empower and promote the social, economic and political inclusion
of all, irrespective of age, sex, disability, race, ethnicity, origin,
religion or economic or other status. Average of the 5 best scores
has been set as the target.
10.3
Women offered employment as a
percentage of total employment
demanded by women under
MGNREGA
100
This target corresponds to the global SDG target 10.3 that aims
to ensure equal opportunity and reduce inequalities of outcome,
including by eliminating discriminatory laws, policies and practices
and promoting appropriate legislation, policies and action in this
regard. Average of the 5 best scores has been set as the target.
10.3
Persons with Disability (PwDs) offered
employment as a percentage of total
employment demanded by PwDs
under MGNREGA
78.27
This target corresponds to the global SDG target 10.3 that aims
to ensure equal opportunity and reduce inequalities of outcome,
including by eliminating discriminatory laws, policies and practices
and promoting appropriate legislation, policies and action in this
regard. Average of the 5 best scores has been set as the target.
105
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
106Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 10.1: PERFORMANCE OF DISTRICTS ON SDG 10
SDG Target 10.2 10.3 10.3
District
Percentage of women representatives in PRIs, ULBs,
District Autonomous Councils, VCs, VECs
Women provided employment as a percentage
of total employment demanded by women under
MGNREGA
Persons with Disability (PWDs) provided
employment as a percentage of total employment
demanded by PWDs under MGNREGA
SDG 10
Arunachal Pradesh
Anjaw 44.87 70.16 33.33 62
Bichom Null Null Null *
Changlang 44.35 28.52 11.67 35
Dibang Valley 43.66 74.28 100.00 82
East Kameng 51.00 63.63 93.67 82
East Siang 41.52 39.02 0.00 33
Kamle 44.35 65.41 70.59 75
Keyi Panyor Null Null Null *
Kra Daadi 48.44 64.63 84.62 81
Kurung Kumey 52.08 49.78 78.26 77
Leparada 45.93 33.16 80.00 66
Lohit 59.01 42.66 50.00 64
Longding 36.40 40.61 0.00 30
Lower Dibang Valley 47.66 44.69 100.00 72
Lower Siang 42.00 30.69 8.33 33
Lower Subansiri 52.14 44.64 6.97 44
Namsai 47.04 30.95 70.66 63
Pakke Kessang 45.54 77.22 100.00 84
Papum Pare 44.10 54.38 77.78 74
Shi Yomi 51.52 28.16 20.00 43
Siang 50.00 32.89 33.33 49
Tawang 51.60 45.97 57.89 66
Tirap 37.07 25.96 0.00 25
Upper Siang 39.08 38.18 91.48 64
Upper Subansiri 50.91 45.84 99.61 74
West Kameng 51.83 42.63 23.81 50
West Siang 40.61 31.07 36.00 44
Assam
Bajali Null Null Null *
Baksa Null 75.61 25.61 51
Barpeta 51.20 55.21 21.47 54
Biswanath 51.46 73.15 34.84 68
Bongaigaon 53.54 63.54 25.28 61
Cachar 53.81 71.47 14.24 59
Charaideo 49.89 67.60 24.35 60
Chirang Null 67.45 26.03 46
Darrang 51.37 70.39 32.58 65
Dhemaji 52.10 45.75 17.36 49
Dhubri 45.46 65.94 24.04 56
Dibrugarh 55.40 65.37 29.67 64
Dima Hasao Null 36.69 100.00 61
Goalpara 57.69 60.72 16.39 57
Golaghat 54.07 62.62 22.04 59
Hailakandi 55.36 57.48 34.82 63
Hojai 55.64 73.34 21.97 65
Jorhat 54.32 69.39 33.46 67
Kamrup 53.27 66.23 13.79 57
Kamrup Metropolitan 57.36 64.51 3.45 53
Karbi Anglong Null 67.59 24.29 45
Karimganj 54.40 77.92 25.50 67
Kokrajhar Null 61.92 28.25 44
Lakhimpur 53.59 64.88 22.16 60
Majuli 53.69 55.73 54.72 70
Morigaon 57.12 68.71 20.39 62
Nagaon 55.28 75.90 33.25 70
Nalbari 50.06 78.49 33.14 68
Sivasagar 47.15 67.72 33.96 62
Sonitpur 56.63 64.56 18.58 60
South Salmara-Mankachar 25.65 82.72 31.56 55
Tamulpur Null Null Null *
Tinsukia 54.81 70.33 15.82 60
Udalguri Null 62.71 19.29 39
West Karbi Anglong Null 67.94 13.64 39
Manipur
Bishnupur 56.63 40.97 66.79 71
Chandel 0.00 33.49 73.39 37
Churachandpur 0.00 31.57 72.73 36
Imphal East 19.05 59.15 69.09 57
Imphal West 48.98 35.59 48.63 56
107Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 10.1: PERFORMANCE OF DISTRICTS ON SDG 10
SDG Target 10.2 10.3 10.3
District
Percentage of women representatives in PRIs, ULBs,
District Autonomous Councils, VCs, VECs
Women provided employment as a percentage
of total employment demanded by women under
MGNREGA
Persons with Disability (PWDs) provided
employment as a percentage of total employment
demanded by PWDs under MGNREGA
SDG 10
Jiribam 60.00 43.91 85.00 77
Kakching 53.33 45.87 53.70 65
Kamjong 0.00 39.88 87.30 42
Kangpokpi 0.00 30.15 27.47 16
Noney 0.00 50.07 38.46 29
Pherzawl 0.00 19.82 0.00 0
Senapati 0.00 37.11 77.78 40
Tamenglong 0.00 21.24 83.33 34
Tengnoupal 0.00 31.11 82.14 38
Thoubal 36.51 38.96 46.36 49
Ukhrul 0.00 40.61 87.50 42
Meghalaya
East Garo Hills 41.96 65.03 100.00 77
East Jaintia Hills 45.26 70.15 78.47 81
East Khasi Hills 49.72 67.14 59.74 75
Eastern West Khasi Hills Null Null Null *
North Garo Hills 46.63 50.22 51.85 62
Ri Bhoi 46.05 61.13 47.25 65
South Garo Hills 49.71 43.72 40.64 57
South West Garo Hills 46.20 55.35 88.48 76
South West Khasi Hills 52.28 72.05 88.82 86
West Garo Hills 49.81 44.53 72.37 71
West Jaintia Hills 47.80 64.69 63.49 74
West Khasi Hills 43.49 58.61 48.66 63
Mizoram
Aizawl 27.03 36.55 84.21 56
Champhai 26.60 52.60 96.15 63
Hnahthial 25.76 33.48 100.00 54
Khawzawl 26.92 42.91 66.67 54
Kolasib 25.54 45.40 66.67 54
Lawngtlai 18.09 46.68 100.00 55
Lunglei 27.55 48.07 100.00 61
Mamit 24.37 44.10 100.00 58
Saitual 24.47 52.17 100.00 61
Serchhip 25.83 40.33 51.43 46
Siaha 21.02 45.27 97.14 56
Nagaland
Chumoukedima Null Null Null *
Dimapur Null 45.11 46.86 46
Kiphire 23.02 53.50 4.30 29
Kohima Null 63.75 38.10 52
Longleng Null 39.00 40.00 38
Mokokchung 40.51 44.01 93.33 67
Mon Null 64.92 92.59 78
Noklak Null Null Null *
Niuland Null Null Null *
Peren Null 78.78 62.50 77
Phek Null 46.32 41.24 43
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang Null 49.12 11.81 26
Wokha Null 74.14 33.33 55
Zunheboto Null 34.30 6.90 13
Sikkim
Gangtok 46.10 58.72 23.91 54
Gyalshing 51.76 54.56 30.67 58
Mangan 48.12 47.43 68.18 69
Namchi 48.40 49.79 48.94 62
Pakyong 55.03 61.41 68.42 79
Soreng 51.50 47.40 31.82 56
Tripura
Dhalai 44.72 54.08 77.30 74
Gomati 44.67 59.75 66.74 72
Khowai 44.95 49.08 70.07 69
North Tripura 45.30 65.61 70.69 76
Sepahijala 45.12 59.38 64.49 71
South Tripura 44.99 54.24 56.99 65
Unakoti 45.41 69.01 74.23 79
West Tripura 45.57 52.75 61.66 67
Target 56.18 100 78.27 100
Goal 11 promotes inclusive and sustainable
urbanisation. Making cities sustainable means
creating career and business opportunities, safe
and affordable housing, and building resilient
societies and economies. It involves investment
in public transport, creating green public spaces,
and improving urban planning and management in
participatory and inclusive ways.
Targets
11.1 By 2030, ensure access for all to adequate,
safe and affordable housing and basic services
and upgrade slums
11.2 By 2030, provide access to safe, affordable,
accessible and sustainable transport systems
for all, improving road safety, notably by
expanding public transport, with special
attention to the needs of those in vulnerable
situations, women, children, persons with
disabilities and older persons
11.3 By 2030, enhance inclusive and sustainable
urbanisation and capacity for participatory,
integrated and sustainable human settlement
planning and management in all countries
11.4 Strengthen efforts to protect and safeguard
the world’s cultural and natural heritage
11.5 By 2030, significantly reduce the number of
deaths and the number of people affected and
substantially decrease the direct economic
losses relative to global gross domestic
product caused by disasters, including water-
related disasters, with a focus on protecting
the poor and people in vulnerable situations
11.6 By 2030, reduce the adverse per capita
environmental impact of cities, including by
paying special attention to air quality and
municipal and other waste management
11.7 By 2030, provide universal access to safe,
inclusive and accessible, green and public
spaces, in particular for women and children,
older persons and persons with disabilities
11.a Support positive economic, social and
environmental links between urban, peri-
urban and rural areas by strengthening
national and regional development planning
11.b By 2020, substantially increase the number
of cities and human settlements adopting
and implementing integrated policies and
plans towards inclusion, resource efficiency,
mitigation and adaptation to climate change,
resilience to disasters, and develop and
implement, in line with the Sendai Framework
for Disaster Risk Reduction 2015-2030, holistic
disaster risk management at all levels
11.c Support least developed countries, including
through financial and technical assistance, in
building sustainable and resilient buildings
utilising local materials.
SDG 11
SUSTAINABLE CITIES
AND COMMUNITIES
Make cities and human settlements inclusive,
safe, resilient and sustainable
109
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 11.1: SDG 11 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 11
0 2010 4030 50 60 908070 100
District StateRank
Gomati TR 1 100
North Tripura TR 1 100
Unakoti TR 1 100
Sepahijala TR 4 99
West Tripura TR 4 99
Khowai TR 6 98
Jiribam MN 7 97
Dhalai TR 7 97
South Tripura TR 9 95
Hailakandi AS 10 91
Imphal West MN 11 89
Morigaon AS 12 88
Zunheboto NL 12 88
Jorhat AS 14 87
Kakching MN 14 87
East Khasi Hills ML 14 87
Kohima NL 14 87
Namchi SK 14 87
Kokrajhar AS 19 86
Sivasagar AS 19 86
Imphal East MN 19 86
Wokha NL 19 86
Gangtok SK 19 86
Pakyong SK 19 86
East Siang AR 25 85
Mokokchung NL 25 85
Mon NL 25 85
Dhubri AS 28 84
Tinsukia AS 28 84
West Karbi Anglong AS 28 84
Thoubal MN 28 84
Kiphire NL 28 84
Phek NL 28 84
Barpeta AS 34 83
Dimapur NL 34 83
Cachar AS 36 82
Chirang AS 36 82
Hojai AS 36 82
Karimganj AS 36 82
Gyalshing SK 36 82
Darrang AS 41 81
Dibrugarh AS 41 81
Dima Hasao AS 41 81
Karbi Anglong AS 41 81
Nalbari AS 41 81
Sonitpur AS 41 81
Bishnupur MN 41 81
Longleng NL 41 81
Goalpara AS 49 80
Lakhimpur AS 49 80
Peren NL 49 80
Kamrup AS 52 79
Tuensang NL 52 79
Bongaigaon AS 54 77
Golaghat AS 54 77
Udalguri AS 54 77
Kamrup Metropolitan AS 57 76
Dhemaji AS 58 75
Nagaon AS 58 75
Biswanath AS 60 74
Aizawl MZ 61 73
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 11 ranges between 100 and 42 and
are computed for the 79 districts which have urban
local bodies. Gomati, North Tripura and Unakoti, all
of them in Tripura are the top performing districts.
These three districts fall in the category of Achiever,
66 districts fall in the category of Front Runners and 9
in the category of Performers, while 1 district is in the
category of Aspirant with scores less than 50.
1102023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 11.1: SDG 11 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Mamit MZ 62 72
Mangan SK 62 72
Hnahthial MZ 64 71
Papum Pare AR 65 70
Charaideo AS 66 68
Khawzawl MZ 66 68
Serchhip MZ 68 66
Champhai MZ 69 65
Lunglei MZ 70 64
Lawngtlai MZ 71 63
Kolasib MZ 72 62
Saitual MZ 72 62
Siaha MZ 74 61
West Jaintia Hills ML 75 60
West Garo Hills ML 76 58
East Garo Hills ML 77 57
South Garo Hills ML 78 53
North Garo Hills ML 79 42
Anjaw AR N /A
Bichom AR N /A
Changlang AR N /A
Dibang Valley AR N /A
East Kameng AR N /A
Kamle AR N /A
Keyi Panyor AR N /A
Kra Daadi AR N /A
Kurung Kumey AR N /A
Leparada AR N /A
Lohit AR N /A
Longding AR N /A
Lower Dibang Valley AR N /A
Lower Siang AR N /A
Lower Subansiri AR N /A
Namsai AR N /A
Pakke Kessang AR N /A
Shi Yomi AR N /A
Siang AR N /A
Tawa n g AR N /A
Tirap AR N /A
Upper Siang AR N /A
Upper Subansiri AR N /A
West Kameng AR N /A
West Siang AR N /A
Bajali AS N /A
Baksa AS N /A
Majuli AS N /A
South Salmara-Mankachar AS N /A
Tamulpur AS N /A
Chandel MN N /A
Churachandpur MN N /A
Kamjong MN N /A
Kangpokpi MN N /A
Noney MN N /A
Pherzawl MN N /A
Senapati MN N /A
Tamenglong MN N /A
Tengnoupal MN N /A
Ukhrul MN N /A
East Jaintia Hills ML N /A
Eastern West Khasi Hills ML N /A
Ri Bhoi ML N /A
South West Garo Hills ML N /A
South West Khasi Hills ML N /A
West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Soreng SK N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
111
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 11.2: PERFORMANCE OF DISTRICTS IN SDG 11
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A)
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
Note: Only districts with an Urban Local Body/Administration were considered for computing scores in SDG 11 for
the year 2023-24.
1122023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
11.1
Houses completed under Pradhan
Mantri Awas Yojana (PMAY) and/or
other schemes as a percentage of net
demand assessment (Urban)
100
This target corresponds to the global SDG target 11.1 that aims to
ensure universal access to adequate, safe and affordable housing
and basic services, and upgrade slums, by 2030.
11.2
Deaths due to road accidents per
1,00,000 population
5.8
This target corresponds to the global SDG target 11.2 that focuses
on improving road safety, and also the global SDG target 3.6 which
aims to halve the number of global deaths and injuries from road
traffic accidents. (Base year 2015)
11.6
Percentage of wards with waste
collection
100
Global SDG target 11.6 aims to reduce the adverse per capita en-
vironmental impact of cities, including by paying special attention
to air quality and municipal and other waste management.
11.1
Percentage of individual household
toilets constructed against target
(SBM(U))
100
Swachh Bharat Mission aims to provide universal sanitation
coverage in urban areas through construction of IHHL units and
community toilets. It aims for completion of construction of toilets
targeted and sanctioned.
11.6
Percentage of Municipal Solid Waste
(MSW) treated out of total MSW
generated
100
This target corresponds to the global SDG target 11.6 that aims
to reduce the adverse per capita environmental impact of cities
by 2030, by focusing on municipal and other waste management.
MSW processing is also critical to the success of the SBM (U).
113
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
114Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 11.1: PERFORMANCE OF DISTRICTS ON SDG 11
SDG Target 11.1 11.2 11.6 11.1 11.6
District
Houses completed under
Pradhan Mantri Awas Yojana
(PMAY) and/or other schemes
as a percentage of net
demand assessment (Urban)
Deaths due to road accidents
per 1,00,000 population
Percentage of wards with
waste collection
Percentage of individual
household toilets constructed
against target (SBM(U))
Percentage of Municipal Solid
Waste (MSW) treated out of
total MSW generated (TPD)
SDG 11
Arunachal Pradesh
Anjaw Null Null Null Null Null *
Bichom Null Null Null Null Null *
Changlang Null Null Null Null Null *
Dibang Valley Null Null Null Null Null *
East Kameng Null Null Null Null Null *
East Siang 100.00 20.88 100.00 163.11 50.00 85
Kamle Null Null Null Null Null *
Keyi Panyor Null Null Null Null Null *
Kra Daadi Null Null Null Null Null *
Kurung Kumey Null Null Null Null Null *
Leparada Null Null Null Null Null *
Lohit Null Null Null Null Null *
Longding Null Null Null Null Null *
Lower Dibang Valley Null Null Null Null Null *
Lower Siang Null Null Null Null Null *
Lower Subansiri Null Null Null Null Null *
Namsai Null Null Null Null Null *
Pakke Kessang Null Null Null Null Null *
Papum Pare 86.77 7.93 100.00 52.97 16.38 70
Shi Yomi Null Null Null Null Null *
Siang Null Null Null Null Null *
Tawang Null Null Null Null Null *
Tirap Null Null Null Null Null *
Upper Siang Null Null Null Null Null *
Upper Subansiri Null Null Null Null Null *
West Kameng Null Null Null Null Null *
West Siang Null Null Null Null Null *
Assam
Bajali Null Null Null Null Null *
Baksa Null Null Null Null Null *
Barpeta 74.95 7.79 100.00 100.00 43.40 83
Biswanath 43.82 11.92 100.00 100.00 35.00 74
Bongaigaon 55.82 11.91 100.00 100.00 37.02 77
Cachar 49.56 7.83 100.00 100.00 62.10 82
Charaideo 23.26 5.23 100.00 100.00 16.00 68
Chirang 68.71 10.58 100.00 100.00 49.12 82
Darrang 54.84 6.57 100.00 100.00 50.11 81
Dhemaji 54.16 15.74 100.00 100.00 36.76 75
Dhubri 71.95 6.67 98.25 100.00 53.45 84
Dibrugarh 38.57 8.14 100.00 100.00 69.00 81
Dima Hasao 42.99 7.94 100.00 100.00 63.95 81
Goalpara 60.87 11.51 100.00 100.00 46.25 80
Golaghat 38.06 11.44 100.00 100.00 56.29 77
Hailakandi 85.95 3.19 100.00 100.00 66.67 91
Hojai 59.62 7.52 100.00 100.00 54.44 82
Jorhat 54.56 5.84 100.00 100.00 80.17 87
Kamrup 66.35 13.05 100.00 100.00 38.83 79
Kamrup Metropolitan 87.69 20.18 100.00 100.00 13.91 76
Karbi Anglong 45.81 8.93 100.00 100.00 62.60 81
Karimganj 48.01 5.37 100.00 100.00 61.98 82
Kokrajhar 67.08 9.02 100.00 100.00 70.02 86
Lakhimpur 54.09 12.47 100.00 100.00 58.10 80
Majuli Null Null Null Null Null *
Morigaon 72.50 6.79 100.00 100.00 70.36 88
Nagaon 53.18 12.05
76.71 100.00 63.70 75
Nalbari 60.00 14.51 100.00 100.00 56.07 81
Sivasagar 66.51 9.39 100.00 100.00 71.40 86
Sonitpur 42.11 12.20 130.00 100.00 72.90 81
South Salmara-Mankachar Null Null Null Null Null *
Tamulpur Null Null Null Null Null *
Tinsukia 63.69 6.78 100.00 100.00 57.73 84
Udalguri 48.08 8.90 100.00 100.00 42.76 77
West Karbi Anglong 45.86 3.39 100.00 100.00 71.83 84
Manipur
Bishnupur 79.95 11.79 100.00 100.00 34.66 81
Chandel Null Null Null Null Null *
Churachandpur Null Null Null Null Null *
Imphal East 95.09 2.91 100.00 100.00 34.46 86
115Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 11.1: PERFORMANCE OF DISTRICTS ON SDG 11
SDG Target 11.1 11.2 11.6 11.1 11.6
District
Houses completed under
Pradhan Mantri Awas Yojana
(PMAY) and/or other schemes
as a percentage of net
demand assessment (Urban)
Deaths due to road accidents
per 1,00,000 population
Percentage of wards with
waste collection
Percentage of individual
household toilets constructed
against target (SBM(U))
Percentage of Municipal Solid
Waste (MSW) treated out of
total MSW generated (TPD)
SDG 11
Imphal West 91.28 3.09 100.00 100.00 56.09 89
Jiribam 89.77 9.12 100.00 100.00 100.00 97
Kakching 91.73 9.60 100.00 100.00 50.63 87
Kamjong Null Null Null Null Null *
Kangpokpi Null Null Null Null Null *
Noney Null Null Null Null Null *
Pherzawl Null Null Null Null Null *
Senapati Null Null Null Null Null *
Tamenglong Null Null Null Null Null *
Tengnoupal Null Null Null Null Null *
Thoubal 95.57 6.88 100.00 100.00 25.99 84
Ukhrul Null Null Null Null Null *
Meghalaya
East Garo Hills 85.71 3.43 100.00 7.77 0.00 57
East Jaintia Hills Null Null Null Null Null *
East Khasi Hills 64.97 7.39 100.00 100.00 74.47 87
Eastern West Khasi Hills Null Null Null Null Null *
North Garo Hills 85.78 6.97 30.77 8.68 25.00 42
Ri Bhoi Null Null Null Null Null *
South Garo Hills 45.57 1.41 100.00 24.19 0.00 53
South West Garo Hills Null Null Null Null Null *
South West Khasi Hills Null Null Null Null Null *
West Garo Hills 74.15 8.59 100.00 15.51 10.96 58
West Jaintia Hills 84.02 7.35 100.00 13.37 10.00 60
West Khasi Hills Null Null Null Null Null *
Mizoram
Aizawl 13.49 14.15 100.00 100.00 63.58 73
Champhai 25.37 12.51 100.00 100.00 8.98 65
Hnahthial 0.00 3.51 100.00 100.00 54.13 71
Khawzawl 21.81 8.14 100.00 100.00 22.62 68
Kolasib 17.60 17.87 100.00 100.00 9.10 62
Lawngtlai 6.55 11.03 100.00 100.00 15.70 63
Lunglei 18.43 9.87 100.00 100.00 5.54 64
Mamit 41.22 6.95 100.00 100.00 20.00 72
Saitual 23.81 27.67 100.00 100.00 18.60 62
Serchhip 20.10 6.12 100.00 100.00 12.14 66
Siaha 7.38 15.91 100.00 100.00 13.21 61
Nagaland
Chumoukedima Null Null Null Null Null *
Dimapur 79.44 16.64 100.00 100.00 54.43 83
Kiphire 97.69 0.00 79.31 100.00 54.34 84
Kohima 79.79 1.89 100.00 100.00 54.55 87
Longleng 77.24 0.00 80.00 100.00 54.29 81
Mokokchung 70.56 4.11 100.00 100.00 54.55 85
Mon 87.80 1.60 87.23 100.00 54.41 85
Noklak Null Null Null Null Null *
Niuland Null Null Null Null Null *
Peren 70.63 0.00 81.48 100.00 53.97 80
Phek 64.55 3.67 100.00 100.00 54.47 84
Shamator Null Null Null Null Null *
Tseminyu Null Null Null Null Null *
Tuensang 75.52 0.00 75.00 100.00 54.41 79
Wokha 74.20 1.80 100.00 100.00 54.39 86
Zunheboto 85.59 0.71 100.00 100.00 54.40 88
Sikkim
Gangtok 84.83 8.20 100.00 100.00 49.08 86
Gyalshing 56.96 1.40 100.00 100.00 54.55 82
Mangan
94.44 70.92 100.00 100.00 64.47 72
Namchi 79.86 9.53 100.00 100.00 62.86 87
Pakyong 97.56 26.51 100.00 100.00 65.85 86
Soreng Null Null Null Null Null *
Tripura
Dhalai 100.00 4.76 100.00 86.44 100.00 97
Gomati 100.00 6.29 100.00 134.59 100.00 100
Khowai 100.00 6.11 100.00 91.55 100.00 98
North Tripura 100.00 5.75 100.00 100.00 100.00 100
Sepahijala 100.00 6.25 100.00 95.64 100.00 99
South Tripura 100.00 6.94 100.00 78.56 100.00 95
Unakoti 100.00 5.06 100.00 122.69 100.00 100
West Tripura 100.00 8.39 100.00 123.17 100.00 99
Target 100 5.8 100 100 100 100
The Goal emphasises on “doing more with less” thus
promoting resource efficiency, green economies
and sustainable infrastructure. It also focusses on
reducing degradation and pollution and minimising
waste. The efficient management of our shared
natural resources and the way we dispose of toxic
waste and pollutants are important targets to
achieve this Goal. It calls for awareness generation
and dissemination on sustainable development,
lifestyles and practices.
Targets
12.1 Implement the 10‑ Year Framework of
Programmes on Sustainable Consumption
and Production Patterns, all countries taking
action, with developed countries taking the
lead, taking into account the development and
capabilities of developing countries
12.2 By 2030, achieve the sustainable management
and efficient use of natural resources
12.3 By 2030, halve per capita global food waste at
the retail and consumer levels and reduce food
losses along production and supply chains,
including post-harvest losses
12.4 By 2020, achieve the environmentally sound
management of chemicals and all wastes
throughout their life cycle, in accordance
with agreed international frameworks, and
significantly reduce their release to air, water
and soil in order to minimize their adverse
impacts on human health and the environment
12.5 By 2030, substantially reduce waste generation
through prevention, reduction, recycling
and reuse
12.6 Encourage companies, especially large and
transnational companies, to adopt sustainable
practices and to integrate sustainability
information into their reporting cycle
12.7 Promote public procurement practices that
are sustainable, in accordance with national
policies and priorities
12.8 By 2030, ensure that people everywhere
have the relevant information and awareness
for sustainable development and lifestyles in
harmony with nature
12.a Support developing countries to strengthen
their scientific and technological capacity to
move towards more sustainable patterns of
consumption and production
12.b Develop and implement tools to monitor
sustainable development impacts for
sustainable tourism that creates jobs and
promotes local culture and products
12.c Rationalize inefficient fossil-fuel subsidies
that encourage wasteful consumption by
removing market distortions, in accordance
with national circumstances, including by
restructuring taxation and phasing out those
harmful subsidies, where they exist, to reflect
their environmental impacts, taking fully into
account the specific needs and conditions
of developing countries and minimizing the
possible adverse impacts on their development
in a manner that protects the poor and the
affected communities
SDG 12
RESPONSIBLE CONSUMPTION
AND PRODUCTION
Ensure sustainable consumption and
production patterns
117
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 12.1: SDG 12 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 12
0 2010 4030 50 60 908070 100
District StateRank
South Tripura TR 1 98
Unakoti TR 1 98
Shi Yomi AR 3 96
Gomati TR 3 96
Kohima NL 5 94
South West Garo Hills ML 6 92
Phek NL 6 92
West Khasi Hills ML 8 90
Serchhip MZ 8 90
Sepahijala TR 10 88
Dimapur NL 11 87
Khowai TR 11 87
West Tripura TR 11 87
North Tripura TR 14 86
Champhai MZ 15 85
Mokokchung NL 15 85
Dhalai TR 15 85
Kolasib MZ 18 84
West Jaintia Hills ML 19 79
Zunheboto NL 19 79
West Garo Hills ML 21 78
Saitual MZ 21 78
Peren NL 23 77
Hnahthial MZ 24 76
Mangan SK 24 76
Ri Bhoi ML 26 75
Pakyong SK 26 75
South Garo Hills ML 28 74
Aizawl MZ 28 74
Namchi SK 28 74
Soreng SK 28 74
North Garo Hills ML 32 73
Khawzawl MZ 32 73
West Siang AR 34 72
Wokha NL 34 72
Lower Dibang Valley AR 36 70
East Khasi Hills ML 36 70
Tuensang NL 36 70
Gangtok SK 36 70
Gyalshing SK 36 70
East Siang AR 41 69
Kurung Kumey AR 41 69
Changlang AR 43 68
Kamle AR 43 68
Kra Daadi AR 43 68
Hailakandi AS 43 68
Karbi Anglong AS 47 67
West Karbi Anglong AS 48 66
Longleng NL 48 66
Lohit AR 50 65
Goalpara AS 50 65
Kiphire NL 52 63
Dima Hasao AS 53 62
Bishnupur MN 53 62
Kakching MN 53 62
Lawngtlai MZ 53 62
Darrang AS 57 61
Nagaon AS 57 61
Imphal East MN 57 61
Jiribam MN 57 61
Thoubal MN 57 61
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 12 ranges between 98 and 7 for the
121 districts included in the ranking and computation.
South Tripura [TR], Unakoti [TR] and Shi Yomi [AR]
are the top performing districts. 51 districts fall in the
category of Front Runners and 52 in the category of
Performers, while 18 districts are in the category of
Aspirants with scores less than 50.
1182023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 12.1: SDG 12 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Mon NL 57 61
Lower Siang AR 63 60
Bongaigaon AS 63 60
Ukhrul MN 63 60
Siaha MZ 63 60
Namsai AR 67 59
Siang AR 67 59
Barpeta AS 67 59
East Garo Hills ML 67 59
Tirap AR 71 58
Imphal West MN 71 58
Biswanath AS 73 57
Dhubri AS 73 57
Tawa n g AR 75 56
Kokrajhar AS 75 56
Morigaon AS 75 56
Sonitpur AS 75 56
Udalguri AS 75 56
Lunglei MZ 75 56
Longding AR 81 55
Upper Siang AR 82 54
Dhemaji AS 82 54
Golaghat AS 82 54
Hojai AS 82 54
Anjaw AR 86 53
Kamrup AS 86 53
Lower Subansiri AR 88 52
Charaideo AS 88 52
Chirang AS 88 52
Jorhat AS 88 52
Lakhimpur AS 88 52
Nalbari AS 88 52
Tinsukia AS 88 52
Mamit MZ 88 52
East Kameng AR 96 51
Leparada AR 96 51
Cachar AS 96 51
Dibrugarh AS 96 51
Kamrup Metropolitan AS 96 51
Sivasagar AS 96 51
Karimganj AS 102 50
Senapati MN 102 50
Upper Subansiri AR 104 49
West Kameng AR 105 47
Pakke Kessang AR 106 46
Papum Pare AR 106 46
Pherzawl MN 106 46
Dibang Valley AR 109 44
Kangpokpi MN 109 44
East Jaintia Hills ML 111 42
South West Khasi Hills ML 111 42
Tengnoupal MN 113 41
Chandel MN 114 40
Churachandpur MN 114 40
Noney MN 116 36
Kamjong MN 117 34
Tamenglong MN 118 29
Majuli AS 119 27
South Salmara-Mankachar AS 120 8
Baksa AS 121 7
Bichom AR N /A
Keyi Panyor AR N /A
Bajali AS N /A
Tamulpur AS N /A
Eastern West Khasi Hills ML N /A
Chumoukedima NL N /A
Noklak NL N /A
Niuland NL N /A
Shamator NL N /A
Tseminyu NL N /A
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
119
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 12.2: PERFORMANCE OF DISTRICTS IN SDG 12
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1202023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
12.3
Area under jhum cultivation as
a percentage of total area under
agriculture
0
Global SDG target 12.2 aims to achieve the sustainable manage-
ment and efficient use of natural resources by 2030. Average
of the 5 best scores, rounded to the nearest whole number, has
been set as the target.
12.3
Percentage of area under micro/
minor irrigation in the district
62.32
Global SDG target 12.2 aims to achieve the sustainable manage-
ment and efficient use of natural resources by 2030. Average of
the 5 best scores, after removing the outliers, has been set as
the target.
12.5
Plastic waste generated per 10,000
population (Tonnes/Annum)
0.04
This target corresponds to the global SDG target 12.5 that aims
to substantially reduce waste generation through prevention,
reduction, recycling and reuse. Average of the 5 best scores has
been set as the target.
121
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
122Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 12.1: PERFORMANCE OF DISTRICTS ON SDG 12
SDG Target 12.3 12.3 12.5
District
Area under jhum cultivation as a
percentage of total area under agriculture
Percentage of area under micro/minor
irrigation in the district
Plastic waste generated
per 10,000 population (Tonnes/Annum)
SDG 12
Arunachal Pradesh
Anjaw 37.71 19.37 168.99 53
Bichom Null Null Null *
Changlang 22.98 30.29 110.56 68
Dibang Valley 39.17 3.90 164.17 44
East Kameng 49.84 19.10 121.73 51
East Siang 6.46 30.01 192.05 69
Kamle 23.67 24.87 44.45 68
Keyi Panyor Null Null Null *
Kra Daadi 15.02 26.86 117.23 68
Kurung Kumey 13.42 25.86 101.36 69
Leparada 32.31 34.15 362.25 51
Lohit 7.35 14.33 102.66 65
Longding 36.75 10.65 67.67 55
Lower Dibang Valley 14.38 26.38 97.86 70
Lower Siang 22.48 27.77 Null 60
Lower Subansiri 24.26 22.72 293.02 52
Namsai 29.72 15.95 87.87 59
Pakke Kessang 35.64 20.04 Null 46
Papum Pare 18.32 36.27 559.57 46
Shi Yomi 7.65 63.07 Null 96
Siang 31.09 29.03 186.39 59
Tawang 8.89 8.78 207.33 56
Tirap 26.09 18.66 145.10 58
Upper Siang 28.05 23.90 253.19 54
Upper Subansiri 28.78 22.79 320.39 49
West Kameng 34.00 3.97 145.16 47
West Siang 26.17 49.45 182.08 72
Assam
Bajali Null Null Null *
Baksa Null 4.30 Null 7
Barpeta Null 11.59 0.61 59
Biswanath Null 8.71 1.35 57
Bongaigaon Null 11.92 0.35 60
Cachar Null 0.81 1.35 51
Charaideo Null 2.91 0.78 52
Chirang Null 2.79 1.31 52
Darrang Null 13.67 0.90 61
Dhemaji Null 4.44 0.37 54
Dhubri Null 9.25 0.53 57
Dibrugarh Null 1.92 1.07 51
Dima Hasao 12.55 0.00 0.64 62
Goalpara Null 19.25 0.90 65
Golaghat Null 5.34 0.32 54
Hailakandi 0.31 2.31 0.16 68
Hojai Null 5.38 0.14 54
Jorhat Null 2.60 1.00 52
Kamrup Null 4.22 0.34 53
Kamrup Metropolitan Null 1.13 1.58 51
Karbi Anglong 2.66 2.17 0.21 67
Karimganj Null 0.64 0.22 50
Kokrajhar Null 7.94 0.97 56
Lakhimpur Null 3.01 0.18 52
Majuli Null 16.72 Null 27
Morigaon Null 8.04 0.65 56
Nagaon Null 14.08 0.20 61
Nalbari Null 3.17 1.47 52
Sivasagar Null 1.47 0.09 51
Sonitpur Null 7.60 0.48 56
South Salmara-Mankachar Null 4.70 Null 8
Tamulpur Null Null Null *
Tinsukia Null 2.36 0.26 52
Udalguri Null 7.65 1.62 56
West Karbi Anglong 6.19 2.82 0.15 66
Manipur
Bishnupur 0.00 5.05 124.43 62
Chandel 59.99 3.81 102.53 40
Churachandpur 61.68 5.01 101.19 40
Imphal East 0.00 7.28 163.31 61
Imphal West 0.00 4.33 192.15 58
123Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 12.1: PERFORMANCE OF DISTRICTS ON SDG 12
SDG Target 12.3 12.3 12.5
District
Area under jhum cultivation as a
percentage of total area under agriculture
Percentage of area under micro/minor
irrigation in the district
Plastic waste generated
per 10,000 population (Tonnes/Annum)
SDG 12
Jiribam 0.00 1.93 111.55 61
Kakching 0.00 3.41 114.99 62
Kamjong 80.07 4.83 95.32 34
Kangpokpi 52.59 6.69 100.75 44
Noney 75.75 3.22 72.72 36
Pherzawl 40.90 1.11 98.50 46
Senapati 45.60 11.93 100.77 50
Tamenglong 88.77 4.68 116.74 29
Tengnoupal 58.77 3.80 98.36 41
Thoubal 0.00 3.00 128.40 61
Ukhrul 21.37 14.63 102.77 60
Meghalaya
East Garo Hills 32.77 11.75 21.34 59
East Jaintia Hills 22.48 5.59 Null 42
East Khasi Hills 1.53 9.94 26.68 70
Eastern West Khasi Hills Null Null Null *
North Garo Hills 12.34 21.03 0.00 73
Ri Bhoi 10.67 22.57 0.00 75
South Garo Hills 16.31 25.04 0.00 74
South West Garo Hills 1.33 52.86 Null 92
South West Khasi Hills 18.89 3.37 Null 42
West Garo Hills 6.93 27.95 19.75 78
West Jaintia Hills 0.52 23.77 1.52 79
West Khasi Hills 26.04 82.37 0.00 90
Mizoram
Aizawl 41.17 43.68 8.46 74
Champhai 39.26 62.87 4.99 85
Hnahthial 57.88 59.14 2.52 76
Khawzawl 38.99 40.51 4.26 73
Kolasib 18.91 45.57 5.58 84
Lawngtlai 29.79 11.84 1.77 62
Lunglei 50.53 16.83 4.67 56
Mamit 53.42 9.44 2.29 52
Saitual 58.14 72.90 3.88 78
Serchhip 25.18 73.94 4.90 90
Siaha 39.90 15.62 4.44 60
Nagaland
Chumoukedima Null Null Null *
Dimapur 2.74 65.18 199.30 87
Kiphire 42.03 21.95 1.01 63
Kohima 14.69 68.06 0.02 94
Longleng 41.74 27.54 0.01 66
Mokokchung 39.83 65.93 0.26 85
Mon 42.78 19.23 0.20 61
Noklak Null Null Null *
Niuland Null Null Null *
Peren 15.12 44.00 Null 77
Phek 14.66 58.71 1.94 92
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang 34.26 30.49 0.05 70
Wokha 34.54 34.97 0.19 72
Zunheboto 43.48 53.97 0.04 79
Sikkim
Gangtok 0.00 7.05 1.77 70
Gyalshing 0.00 6.45 0.20 70
Mangan 0.00 18.01 1.14 76
Namchi 0.00 13.35 0.77 74
Pakyong 0.00 16.55 4.37 75
Soreng 0.00 12.87 0.00 74
Tripura
Dhalai 13.87 44.52 0.30 85
Gomati 3.85 58.14 0.18 96
Khowai 4.05 41.64 0.26 87
North Tripura 10.06 42.57 0.26 86
Sepahijala 0.61 40.82 0.23 88
South Tripura 1.80 59.67 0.44 98
Unakoti 5.63 63.68 0.45 98
West Tripura 2.00 39.06 1.17 87
Target 0 62.32 0.04 100
2023-24
The Goal is aimed at integrating climate change
measures, disaster risk measures and sustainable
natural resource management into national
development strategies. To minimise the human
impact of geophysical disasters, the Goal calls for
strengthening resilience and adaptive capacity,
including human and institutional capacity on
mitigation, adaptation, and early warning. Efforts at
the national level - for adopting green technologies,
promoting the use of clean and modern source
of energy, advocating for behavioural change
for sustainable use of resources, have to be
complemented by international cooperation on
climate change since the causes and effects of
climate change transcend national boundaries.
Targets
13.1 Strengthen resilience and adaptive capacity to
climate-related hazards and natural disasters
in all countries
13.2 Integrate climate change measures into
national policies, strategies and planning
13.3 Improve education, awareness-raising and
human and institutional capacity on climate
change mitigation, adaptation, impact
reduction and early warning
13.a Implement the commitment undertaken by
developed-country parties to the United
Nations Framework Convention on Climate
Change to a goal of mobilising jointly USD
100 billion annually by 2020 from all sources
to address the needs of developing countries
in the context of meaningful mitigation actions
and transparency on implementation and fully
operationalise the Green Climate Fund through
its capitalisation as soon as possible
13.b Promote mechanisms for raising capacity for
effective climate change-related planning and
management in least developed countries
and small island developing States, including
focusing on women, youth and local and
marginalised communities
SDG 13
CLIMATE ACTION
Take urgent action to combat climate
change and its impacts
125
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 13.1: SDG 13 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 13
0 2010 4030 50 60 908070 100
District StateRank
Hnahthial MZ 1 100
Khawzawl MZ 1 100
Mokokchung NL 1 100
Phek NL 1 100
Senapati MN 5 99
Ukhrul MN 6 91
Tengnoupal MN 7 89
South West Khasi Hills ML 8 86
West Garo Hills ML 9 80
Longleng NL 10 79
Majuli AS 11 77
Soreng SK 11 77
East Khasi Hills ML 13 76
Gomati TR 14 75
Charaideo AS 15 74
Ri Bhoi ML 15 74
Baksa AS 17 73
Hojai AS 17 73
Lawngtlai MZ 17 73
Darrang AS 20 72
Jorhat AS 20 72
Morigaon AS 20 72
West Khasi Hills ML 20 72
Dhubri AS 24 71
Goalpara AS 24 71
Sivasagar AS 24 71
South TR TR 24 71
Dibrugarh AS 28 70
Kamrup AS 28 70
Lakhimpur AS 28 70
Nalbari AS 28 70
Champhai MZ 28 70
Serchhip MZ 28 70
Siaha MZ 28 70
Dhemaji AS 35 69
Golaghat AS 35 69
Tinsukia AS 35 69
Upper Subansiri AR 38 68
Karbi Anglong AS 38 68
Changlang AR 40 67
Lower Dibang Valley AR 40 67
Namsai AR 40 67
Shi Yomi AR 40 67
Bishnupur MN 40 67
Chandel MN 40 67
Churachandpur MN 40 67
Imphal East MN 40 67
Imphal West MN 40 67
Jiribam MN 40 67
Kakching MN 40 67
Kangpokpi MN 40 67
Peren NL 40 67
Namchi SK 40 67
Biswanath AS 54 66
Sonitpur AS 54 66
Thoubal MN 54 66
West Jaintia Hills ML 54 66
Dimapur NL 54 66
Kohima NL 54 66
Mon NL 54 66
Wokha NL 54 66
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 13 ranges between 100 and 12 for the
121 districts included in the ranking and computation.
Phek [NL], Mokokchung [NL], Khawzawl [MZ] and
Hnahthial [MZ] are the top performing districts.
4 districts fall in the category of Achiever, 59 districts fall
in the category of Front Runners and 9 in the category
of Performers, while 49 districts are in the category of
Aspirants with scores less than 50.
1262023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 13.1: SDG 13 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Zunheboto NL 54 66
Tuensang NL 63 65
Tamenglong MN 64 64
Kiphire NL 65 63
Gangtok SK 66 61
Kamjong MN 67 60
Noney MN 68 58
Mangan SK 68 58
Upper Siang AR 70 55
Pherzawl MN 71 54
Saitual MZ 72 50
South Garo Hills ML 73 49
South West Garo Hills ML 74 47
North Garo Hills ML 75 46
East Jaintia Hills ML 76 45
Kolasib MZ 77 44
West TR TR 78 43
Khowai TR 79 42
Hailakandi AS 80 41
East Garo Hills ML 80 41
Bongaigaon AS 82 40
Lower Subansiri AR 83 39
Kamrup Metropolitan AS 83 39
Leparada AR 85 38
Tirap AR 85 38
Barpeta AS 85 38
Chirang AS 85 38
Nagaon AS 85 38
Udalguri AS 85 38
Sepahijala TR 85 38
Lower Siang AR 92 37
Kokrajhar AS 92 37
Aizawl MZ 92 37
Mamit MZ 92 37
Dhalai TR 92 37
East Kameng AR 97 36
West Siang AR 97 36
West Karbi Anglong AS 97 36
Lunglei MZ 97 36
North TR TR 97 36
Unakoti TR 97 36
Kamle AR 103 35
Kra Daadi AR 103 35
Longding AR 103 35
Cachar AS 103 35
Dima Hasao AS 103 35
East Siang AR 108 34
Kurung Kumey AR 108 34
Lohit AR 108 34
Pakke Kessang AR 108 34
Papum Pare AR 108 34
Siang AR 108 34
West Kameng AR 108 34
Anjaw AR 115 33
Dibang Valley AR 115 33
Tawa n g AR 115 33
Karimganj AS 115 33
South Salmara-Mankachar AS 115 33
Gyalshing SK 120 30
Pakyong SK 121 12
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
127
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 13.2: PERFORMANCE OF DISTRICTS IN SDG 13
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1282023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
13.1
Number of human lives lost due
to natural calamity per 10,000
population
0
This target corresponds to the global SDG target 13.1 which aims
to strengthen resilience and adaptive capacity to climate-related
hazards and natural disasters. The target has been set to 0 to
imply that all States/UTs must be adequately prepared to ensure
that no human life is lost due to natural calamities.
13.2 Change in forest area
This target corresponds to the global SDG targets 13.2 that aim
to integrate climate change measures into national policies,
strategies and planning and 15.2 that aim to promote the
implementation of sustainable management of all types of forests,
halt deforestation, restore degraded forests and substantially
increase afforestation and reforestation. Districts with an
increase/no change in area under forests have been awarded a
score of 100 while districts with a decrease in area under forests
have been assigned a score of 0.
13.1
Area under watershed management
as a percentage of total geographical
area
16.46
This target corresponds to the global SDG target 13.1 that aims
to strengthen resilience and adaptive capacity to climate-related
hazards and natural disasters in all countries. Average of the 5
best scores, after removing the outliers, has been set as the target.
129
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
130Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 13.1: PERFORMANCE OF DISTRICTS ON SDG 13
SDG Target 13.1 13.2 13.1
District
Number of human lives lost
due to natural calamity per 10,000 population
Change in forest area
Area under watershed management
as a percentage of total geographical area
SDG 13
Arunachal Pradesh
Anjaw 0.00 -8.00 0.07 33
Bichom Null Null Null *
Changlang 0.00 50.16 0.32 67
Dibang Valley 0.00 -7.44 0.04 33
East Kameng 0.00 -29.33 1.28 36
East Siang 0.00 -1.75 0.46 34
Kamle 0.00 -5.63 0.59 35
Keyi Panyor Null Null Null *
Kra Daadi 0.00 -4.27 0.69 35
Kurung Kumey 0.22 -21.70 1.19 34
Leparada 0.00 -10.66 2.45 38
Lohit 0.00 -2.54 0.14 34
Longding 0.00 -9.80 0.92 35
Lower Dibang Valley 0.00 12.66 0.36 67
Lower Siang 0.00 -9.02 1.80 37
Lower Subansiri 0.00 -14.99 2.57 39
Namsai 0.00 7.84 0.31 67
Pakke Kessang 0.00 -11.46 0.43 34
Papum Pare 0.00 -5.40 0.55 34
Shi Yomi 0.00 35.45 0.00 67
Siang 0.00 -1.75 0.14 34
Tawang 0.00 -6.84 0.00 33
Tirap 0.00 -37.78 2.39 38
Upper Siang 1.70 2.54 0.00 55
Upper Subansiri 0.00 16.23 0.51 68
West Kameng 0.00 -9.43 0.23 34
West Siang 0.00 -20.01 1.35 36
Assam
Bajali Null Null Null *
Baksa 0.01 7.43 2.99 73
Barpeta 0.02 -0.77 2.19 38
Biswanath 0.03 5.21 0.00 66
Bongaigaon 0.04 -1.47 3.33 40
Cachar 0.01 -16.77 0.90 35
Charaideo 0.00 0.47 3.72 74
Chirang 0.08 -14.38 2.72 38
Darrang 0.03 2.61 2.84 72
Dhemaji 0.04 15.36 1.29 69
Dhubri 0.02 1.94 2.28 71
Dibrugarh 0.02 0.64 1.48 70
Dima Hasao 0.05 -93.27 0.92 35
Goalpara 0.05 11.60 2.10 71
Golaghat 0.02 36.06 1.25 69
Hailakandi 0.02 -16.60 3.77 41
Hojai 0.01 0.52 2.97 73
Jorhat 0.00 18.79 2.82 72
Kamrup 0.01 6.30 1.51 70
Kamrup Metropolitan 0.02 -2.11 2.63 39
Karbi Anglong 0.02 22.88 0.77 68
Karimganj 0.02 -2.70 0.00 33
Kokrajhar 0.02 -3.16 1.81 37
Lakhimpur 0.01 11.05 1.72 70
Majuli 0.06 4.24 5.23 77
Morigaon 0.01 3.25 2.82 72
Nagaon 0.02 -0.02 2.19 38
Nalbari 0.03 0.08 1.69 70
Sivasagar 0.12 3.90 2.64 71
Sonitpur 0.03 -2.02 24.08 66
South Salmara-Mankachar 0.02 -1.94 0.00 33
Tamulpur Null Null Null *
Tinsukia 0.02 3.65 1.32 69
Udalguri 0.00 -3.33 2.43 38
West Karbi Anglong 0.00 -9.20 1.45 36
Manipur
Bishnupur 0.00 -1.17 28.81 67
Chandel 0.00 -22.32 19.33 67
Churachandpur 0.00 -78.00 17.90 67
Imphal East 0.00 -5.26 31.82 67
131Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 13.1: PERFORMANCE OF DISTRICTS ON SDG 13
SDG Target 13.1 13.2 13.1
District
Number of human lives lost
due to natural calamity per 10,000 population
Change in forest area
Area under watershed management
as a percentage of total geographical area
SDG 13
Imphal West 0.00 -1.49 29.12 67
Jiribam 0.00 -1.93 53.80 67
Kakching 0.00 -2.90 56.04 67
Kamjong 0.00 -21.29 13.00 60
Kangpokpi 0.00 -31.57 17.17 67
Noney 0.00 -16.79 12.00 58
Pherzawl 0.00 -59.89 10.07 54
Senapati 0.07 81.61 16.18 99
Tamenglong 0.00 -38.43 15.36 64
Tengnoupal 0.00 1.55 11.10 89
Thoubal 0.00 -0.95 16.03 66
Ukhrul 0.00 144.00 12.01 91
Meghalaya
East Garo Hills 0.07 -28.09 4.23 41
East Jaintia Hills 0.00 -20.76 5.85 45
East Khasi Hills 0.16 13.69 5.08 76
Eastern West Khasi Hills Null Null Null *
North Garo Hills 0.00 -15.37 6.29 46
Ri Bhoi 0.04 0.56 3.78 74
South Garo Hills 0.00 -5.28 7.57 49
South West Garo Hills 0.11 -4.59 7.30 47
South West Khasi Hills 0.10 10.10 10.07 86
West Garo Hills 0.04 12.72 6.65 80
West Jaintia Hills 0.15 -8.03 17.72 66
West Khasi Hills 0.46 12.11 4.09 72
Mizoram
Aizawl 0.05 -33.64 2.04 37
Champhai 0.00 86.69 1.58 70
Hnahthial 0.00 114.67 Null 100
Khawzawl 0.00 12.89 Null 100
Kolasib 0.00 -37.58 5.41 44
Lawngtlai 0.00 50.17 2.98 73
Lunglei 0.00 -30.66 1.09 36
Mamit 0.00 -21.96 1.69 37
Saitual 0.00 -17.56 Null 50
Serchhip 0.00 14.17 1.69 70
Siaha 0.00 104.54 1.77 70
Nagaland
Chumoukedima Null Null Null *
Dimapur 0.05 -3.48 44.42 66
Kiphire 0.54 -0.54 36.37 63
Kohima 0.09 -4.15 32.57 66
Longleng 0.00 5.26 6.27 79
Mokokchung 0.00 14.88 32.15 100
Mon 0.08 -18.30 23.96 66
Noklak Null Null Null *
Niuland Null Null Null *
Peren 0.00 -8.48 22.50 67
Phek 0.06 0.88 46.68 100
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang 0.19 -14.28 23.26 65
Wokha 0.06 -7.99 31.67 66
Zunheboto 0.07 -15.69 40.39 66
Sikkim
Gangtok 0.87 4.46 0.00 61
Gyalshing 0.42 -1.66 0.00 30
Mangan 1.37 1.45 0.62 58
Namchi 0.48 0.94 1.93 67
Pakyong 4.83 Null 4.08 12
Soreng 0.00 Null 8.82 77
Tripura
Dhalai 0.11 -44.58 2.32 37
Gomati 0.14 6.86 4.62 75
Khowai 0.21 -23.16 5.18 42
North Tripura 0.00 -18.88 1.14 36
Sepahijala 0.08 -7.35 2.62 38
South Tripura 0.04 11.60 2.43 71
Unakoti 0.18 -13.52 2.16 36
West Tripura 0.03 -6.28 4.77 43
Target 0 16.46 100
The Goal is aimed at protecting, restoring and
promoting sustainable use of terrestrial ecosystems;
sustainable management of forests; combating
desertification; and halting and reversing land
degradation in conjunction with integrating
ecosystems and biodiversity into national and local
planning. It also seeks to promote fair and equitable
sharing of the benefits arising from the utilisation
of genetic resources, and prevent poaching and
trafficking of protected species of flora and fauna.
Targets
15.1 By 2020, ensure the conservation, restoration
and sustainable use of terrestrial and inland
freshwater ecosystems and their services,
in particular forests, wetlands, mountains
and drylands, in line with obligations under
international agreements
15.2 By 2020, promote the implementation of
sustainable management of all types of forests,
halt deforestation, restore degraded forests
and substantially increase afforestation and
reforestation globally
15.3 By 2030, combat desertification, restore
degraded land and soil, including land
affected by desertification, drought and floods,
and strive to achieve a land degradation-
neutral world
15.4 By 2030, ensure the conservation of mountain
ecosystems, including their biodiversity, in
order to enhance their capacity to provide
benefits that are essential for sustainable
development
15.5 Take urgent and significant action to reduce
the degradation of natural habitats, halt the
loss of biodiversity and, by 2020, protect and
prevent the extinction of threatened species
15.6 Promote fair and equitable sharing of the
benefits arising from the utilisation of genetic
resources and promote appropriate access to
such resources, as internationally agreed
15.7 Take urgent action to end poaching and
trafficking of protected species of flora and
fauna and address both demand and supply
of illegal wildlife products
15.8 By 2020, introduce measures to prevent the
introduction and significantly reduce the
impact of invasive alien species on land and
water ecosystems and control or eradicate the
priority species
15.9 By 2020, integrate ecosystem and biodiversity
values into national and local planning,
development processes, poverty reduction
strategies and accounts
15.a Mobilize and significantly increase financial
resources from all sources to conserve and
sustainably use biodiversity and ecosystems
15.b Mobilize significant resources from all sources
and at all levels to finance sustainable forest
management and provide adequate incentives
to developing countries to advance such
management, including for conservation and
reforestation
15.c Enhance global support for efforts to combat
poaching and trafficking of protected species,
including by increasing the capacity of local
communities to pursue sustainable livelihood
opportunities
SDG 15
LIFE ON LAND
Protect, restore and promote sustainable use of
terrestrial ecosystems, sustainably manage forests,
combat desertification, and halt and reverse land
degradation and halt biodiversity loss
133
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) NER District SDG Index: Goal 15
FIGURE 15.1: SDG 15 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Anjaw AR 1 100
Dibang Valley AR 1 100
Kamle AR 1 100
Leparada AR 1 100
Lower Dibang Valley AR 1 100
Lower Siang AR 1 100
Siang AR 1 100
Upper Siang AR 1 100
Upper Subansiri AR 1 100
Charaideo AS 1 100
Dima Hasao AS 1 100
West Karbi Anglong AS 1 100
Jiribam MN 1 100
Kamjong MN 1 100
Kangpokpi MN 1 100
Noney MN 1 100
Pherzawl MN 1 100
Tengnoupal MN 1 100
West Jaintia Hills ML 1 100
Hnahthial MZ 1 100
Khawzawl MZ 1 100
Saitual MZ 1 100
Kiphire NL 1 100
Longleng NL 1 100
Peren NL 1 100
Gyalshing SK 1 100
Changlang AR 27 99
East Kameng AR 27 99
Kra Daadi AR 27 99
Kurung Kumey AR 27 99
Lohit AR 27 99
Namsai AR 27 99
Pakke Kessang AR 27 99
Chirang AS 27 99
Gangtok SK 27 99
Namchi SK 27 99
Soreng SK 27 99
Shi Yomi AR 38 98
West Siang AR 38 98
Cachar AS 38 98
Karimganj AS 38 98
Tinsukia AS 38 98
Pakyong SK 38 98
Papum Pare AR 44 97
Mangan SK 44 97
Unakoti TR 44 97
Hojai AS 47 96
Jorhat AS 47 96
Gomati TR 47 96
South Tripura TR 47 96
East Siang AR 51 95
East Khasi Hills ML 51 95
Khowai TR 51 95
North Tripura TR 51 95
Kamrup Metropolitan AS 55 94
Sepahijala TR 55 94
West Kameng AR 57 93
Hailakandi AS 57 93
Kamrup AS 57 93
Dhalai TR 57 93
East Garo Hills ML 61 92
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 15 ranges between 100 and 36
for the 121 districts included in the ranking and
computation. 26 districts fall in the category of Achiever,
87 districts fall in the category of Front Runners and
6 in the category of Performers, while 2 districts are
in the category of Aspirants with scores less than 50.
1342023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 15.1: SDG 15 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
North Garo Hills ML 61 92
South Garo Hills ML 61 92
Lower Subansiri AR 64 91
Kokrajhar AS 65 88
Dimapur NL 65 88
Dibrugarh AS 67 87
South West Garo Hills ML 67 87
South West Khasi Hills ML 67 87
West Garo Hills ML 67 87
West Khasi Hills ML 67 87
Wokha NL 67 87
West Tripura TR 67 87
Kolasib MZ 74 86
Sivasagar AS 75 85
Ri Bhoi ML 75 85
Lawngtlai MZ 75 85
Bongaigaon AS 78 84
Tamenglong MN 78 84
Ukhrul MN 78 84
Kohima NL 78 84
Baksa AS 82 83
Chandel MN 82 83
Aizawl MZ 82 83
East Jaintia Hills ML 85 82
Lunglei MZ 85 82
Longding AR 87 81
Tirap AR 87 81
Karbi Anglong AS 87 81
Goalpara AS 90 80
Serchhip MZ 90 80
Phek NL 90 80
Tawa n g AR 93 78
Lakhimpur AS 93 78
Udalguri AS 93 78
Sonitpur AS 96 77
Mokokchung NL 96 77
Nagaon AS 98 76
Senapati MN 98 76
Siaha MZ 98 76
Nalbari AS 101 75
Churachandpur MN 101 75
Champhai MZ 101 75
Dhemaji AS 104 74
Tuensang NL 104 74
Golaghat AS 106 73
Biswanath AS 107 72
Morigaon AS 107 72
Zunheboto NL 109 71
Mamit MZ 110 70
Imphal East MN 111 68
Imphal West MN 111 68
Mon NL 113 67
Kakching MN 114 56
Thoubal MN 114 56
Dhubri AS 116 55
Bishnupur MN 116 55
South Salmara-Mankachar AS 118 52
Majuli AS 119 50
Darrang AS 120 49
Barpeta AS 121 36
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
135
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 15.2: PERFORMANCE OF DISTRICTS IN SDG 15
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1362023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
15.1
Forest cover as a percentage of total
geographical area
33
National Afforestation and Eco-Development Board aims to achieve
33 percent of the geographical area in the country under forest
and tree cover.
15.3
Percentage of wasteland over total
geographical area
1.41
Global SDG target 15.3 aims to combat desertification, restore
degraded land and soil, including land affected by desertification,
drought and floods, and strives to achieve a land degradation-
neutral world by 2030. Average of the 5 best scores has been set
as the target.
15.7
Number of wildlife crime cases
reported per 1,000 sq kms of forest area
0
Global SDG target 15.7 calls for urgent action to end poaching
and trafficking of protected species of flora and fauna and address
both demand and supply of illegal wildlife products. The target
value has been set to 0 to imply that all crimes against wildlife
need to end.
137
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
138Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 15.1: PERFORMANCE OF DISTRICTS ON SDG 15
SDG Target 15.1 15.3 15.7
District
Forest cover as a percentage of
total geographical area
Percentage of wasteland over
total geographical area
Number of wildlife crime cases
reported per 1,000 sq kms of forest area
SDG 15
Arunachal Pradesh
Anjaw 68.62 Null 0.00 100
Bichom Null Null Null *
Changlang 84.49 2.22 0.00 99
Dibang Valley 66.51 Null 0.15 100
East Kameng 86.28 2.29 0.00 99
East Siang 86.24 8.39 0.00 95
Kamle 98.38 Null 0.00 100
Keyi Panyor Null Null Null *
Kra Daadi 69.59 3.33 0.00 99
Kurung Kumey 77.47 3.33 0.00 99
Leparada 88.07 Null 0.00 100
Lohit 75.26 2.41 0.00 99
Longding 65.37 25.71 0.00 81
Lower Dibang Valley 70.03 1.33 0.00 100
Lower Siang 88.69 Null 0.00 100
Lower Subansiri 89.91 13.32 0.00 91
Namsai 63.81 2.41 0.00 99
Pakke Kessang 90.44 2.29 0.00 99
Papum Pare 92.06 5.14 0.00 97
Shi Yomi 74.56 4.06 0.00 98
Siang 86.24 Null 0.00 100
Tawang 46.98 30.78 0.00 78
Tirap 79.53 25.71 0.00 81
Upper Siang 80.69 2.06 0.00 100
Upper Subansiri 92.67 1.62 0.00 100
West Kameng 85.62 10.8 0.00 93
West Siang 73.58 4.06 0.00 98
Assam
Bajali Null Null Null *
Baksa 24 Null 7.11 83
Barpeta 5.24 1.95 135.94 36
Biswanath 16.11 Null 0.00 72
Bongaigaon 20.76 3.21 3.99 84
Cachar 57.79 3.66 0.00 98
Charaideo 35.54 Null 0.00 100
Chirang 37.02 Null 1.42 99
Darrang 7.18 3.28 85.03 49
Dhemaji 11.7 1.72 8.41 74
Dhubri 5.42 5.21 46.88 55
Dibrugarh 22.57 1.93 5.27 87
Dima Hasao 82.68 Null 0.00 100
Goalpara 22.73 9.02 12.36 80
Golaghat 20.55 16.07 10.38 73
Hailakandi 58.22 10.84 0.00 93
Hojai 30.73 Null 0.00 96
Jorhat 32.09 3.29 7.07 96
Kamrup 31.43 5.65 7.24 93
Kamrup Metropolitan 48.51 Null 15.12 94
Karbi Anglong 76.85 26.39 0.13 81
Karimganj 46.38 3.99 1.17 98
Kokrajhar 36.73 16.23 2.57 88
Lakhimpur 14.56 2.15 3.22 78
Majuli 2.72 Null 0.00 50
Morigaon 12.94 1.48 22.67 72
Nagaon 18.93 9.89 8.75 76
Nalbari 10.81 2.35 0.00 75
Sivasagar 20.77 3.89 0.00 85
Sonitpur 23.86 11.47 21.47 77
South Salmara-Mankachar 3.99 Null 0.00 52
Tamulpur Null Null Null *
Tinsukia 41.11 4.03 0.63 98
Udalguri 20.46 Null 2.42 78
West Karbi Anglong 70.15 Null 0.00 100
Manipur
Bishnupur 4.42 2.06 51.33 55
Chandel 86.23 23.75 0.00 83
Churachandpur 79.01 33.59 0.00 75
Imphal East 13.67 15.97 0.00 68
Imphal West 7.24 5.85 0.00 68
139Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 15.1: PERFORMANCE OF DISTRICTS ON SDG 15
SDG Target 15.1 15.3 15.7
District
Forest cover as a percentage of
total geographical area
Percentage of wasteland over
total geographical area
Number of wildlife crime cases
reported per 1,000 sq kms of forest area
SDG 15
Jiribam 74.6 Null 0.00 100
Kakching 7.92 Null 7.22 56
Kamjong 86.8 Null 0.00 100
Kangpokpi 56.08 Null 0.00 100
Noney 87.38 Null 0.00 100
Pherzawl 86.53 Null 0.00 100
Senapati 75.27 33.27 0.00 76
Tamenglong 84.94 22.45 0.00 84
Tengnoupal 77.66 Null 0.00 100
Thoubal 3.07 16.33 0.00 56
Ukhrul 77.5 22.17 0.75 84
Meghalaya
East Garo Hills 93.76 11.82 0.00 92
East Jaintia Hills 65.14 25.5 0.00 82
East Khasi Hills 63.85 8.16 0.00 95
Eastern West Khasi Hills Null Null Null *
North Garo Hills 90.96 11.82 0.00 92
Ri Bhoi 85.1 20.79 0.00 85
South Garo Hills 86.68 11.81 0.00 92
South West Garo Hills 69.77 18.55 0.00 87
South West Khasi Hills 64.37 18.66 0.00 87
West Garo Hills 74.22 18.55 0.00 87
West Jaintia Hills 65.81 Null 0.00 100
West Khasi Hills 80.9 18.66 0.00 87
Mizoram
Aizawl 85.83 21.83 5.23 83
Champhai 83.17 31.52 9.57 75
Hnahthial 86.37 Null Null 100
Khawzawl 75.64 Null Null 100
Kolasib 85.62 11.83 22.98 86
Lawngtlai 80.09 17.72 10.16 85
Lunglei 88.42 18.3 19.20 82
Mamit 89.3 11.51 89.16 70
Saitual 82.35 Null Null 100
Serchhip 83.77 26.44 3.48 80
Siaha 90.76 22.7 Null 76
Nagaland
Chumoukedima Null Null Null *
Dimapur 50.04 16.71 0.00 88
Kiphire 71.85 Null 0.00 100
Kohima 74.5 22.09 0.00 84
Longleng 68.58 Null 0.00 100
Mokokchung 83.02 31.38 0.00 77
Mon 75.91 45 0.00 67
Noklak Null Null Null *
Niuland Null Null Null *
Peren 90.84 Null 0.00 100
Phek 73.66 27.01 0.00 80
Shamator Null Null Null *
Tseminyu Null Null Null *
Tuensang 53.6 35.9 0.00 74
Wokha 79.46 18.65 0.00 87
Zunheboto 90.01 38.79 0.00 71
Sikkim
Gangtok 74.99 2.86 0.00 99
Gyalshing 67.72 2.06 0.00 100
Mangan 30.53 0.88 0.00 97
Namchi 75.07 3.11 0.00 99
Pakyong 74.99 2.86 Null 98
Soreng 67.72 2.06 Null 99
Tripura
Dhalai 79.19 10.62 0.54 93
Gomati 74.95 6.57 0.00 96
Khowai 70.07 7.7 0.00 95
North Tripura 77.37 7.28 1.18 95
Sepahijala 62.22 8.99 0.00 94
South Tripura 73.11 7.12 0.00 96
Unakoti 62.9 5.68 0.00 97
West Tripura 63.11 14.47 13.98 87
Target 33 1.41 0 100
Peace, stability and effective governance based
on rule-of-law and upholding the principles of
equality, human rights and justice are prerequisites
for sustainable development. The 2030 Agenda
aims to significantly reduce all forms of violence,
and work with governments and communities to
end conflict and insecurity. Promoting rule-of-law
and human rights are key to this process, as are
reducing the flow of illicit arms and strengthening
the participation of developing countries in the
institutions of global governance. Goal 16 also
focuses on ending abuse, exploitation, trafficking,
corruption and bribery, and in the development of
accountable and transparent institutions.
Targets
16.1 Significantly reduce all forms of violence and
related death rates everywhere
16.2 End abuse, exploitation, trafficking and
all forms of violence against and torture
of children
16.3 Promote the rule of law at the national and
international levels and ensure equal access
to justice for all
16.4 By 2030, significantly reduce illicit financial
and arms flows, strengthen the recovery and
return of stolen assets and combat all forms
of organized crime
16.5 Substantially reduce corruption and bribery
in all their forms
16.6 Develop effective, accountable and
transparent institutions at all levels
16.7 Ensure responsive, inclusive, participatory
and representative decision-making at
all levels
16.8 Broaden and strengthen the participation
of developing countries in the institutions of
global governance
16.9 By 2030, provide legal identity for all,
including birth registration
16.10 Ensure public access to information and
protect fundamental freedoms, in accordance
with national legislation and international
agreements
16.a Strengthen relevant national institutions,
including through international cooperation,
for building capacity at all levels, in particular
in developing countries, to prevent violence
and combat terrorism and crime
16.b Promote and enforce non-discriminatory laws
and policies for sustainable development
SDG 16
PEACE, JUSTICE AND
STRONG INSTITUTIONS
Promote peaceful and inclusive societies for sustainable
development, provide access to justice for all and build
effective, accountable and inclusive institutions at all levels
METHODOLOGY & RESULTS
141
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 16.1: SDG 16 INDEX SCORE OF DISTRICTS
NER District SDG Index: Goal 16
0 2010 4030 50 60 908070 100
District StateRank
Kamjong MN 1 97
Noney MN 2 96
Hnahthial MZ 3 94
Pherzawl MN 4 93
Kangpokpi MN 5 90
Tengnoupal MN 6 86
Lawngtlai MZ 6 86
Serchhip MZ 6 86
Barpeta AS 9 85
Goalpara AS 9 85
South West Garo Hills ML 9 85
Lunglei MZ 9 85
Mamit MZ 9 85
Churachandpur MN 14 84
Ukhrul MN 14 84
Tamenglong MN 16 83
Champhai MZ 16 83
Khowai TR 16 83
Dhemaji AS 19 82
Karimganj AS 19 82
Lakhimpur AS 19 82
Aizawl MZ 19 82
Darrang AS 23 81
Dhalai TR 23 81
West Kameng AR 25 80
Kolasib MZ 25 80
Saitual MZ 25 80
Siaha MZ 25 80
Gomati TR 25 80
Changlang AR 30 79
Lower Dibang Valley AR 30 79
Cachar AS 30 79
Golaghat AS 30 79
Nalbari AS 30 79
Bishnupur MN 30 79
Imphal West MN 30 79
Sepahijala TR 30 79
Morigaon AS 38 78
Jiribam MN 38 78
Thoubal MN 38 78
North Garo Hills ML 38 78
Baksa AS 42 77
Chandel MN 42 77
Kakching MN 42 77
Senapati MN 42 77
Kokrajhar AS 46 76
Nagaon AS 46 76
Udalguri AS 46 76
North Tripura TR 46 76
West Tripura TR 46 76
Dibang Valley AR 51 75
West Garo Hills ML 51 75
Longding AR 53 74
Dibrugarh AS 53 74
Imphal East MN 53 74
Unakoti TR 53 74
Leparada AR 57 73
Dima Hasao AS 57 73
Hojai AS 57 73
Karbi Anglong AS 57 73
South West Khasi Hills ML 57 73
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
The score for Goal 16 ranges between 97 and 36 for the
121 districts included in the ranking and computation.
Kamjong [MN], Noney [MN] and Hnahthial [MZ] are the
top performing districts. 90 districts fall in the category
of Front Runners and 26 in the category of Performers,
while 5 district is in the category of Aspirants with
scores less than 50.
1422023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE 16.1: SDG 16 INDEX SCORE OF DISTRICTS
0 2010 4030 50 60 908070 100
District StateRank
Chirang AS 62 72
Dhubri AS 62 72
Jorhat AS 62 72
South Garo Hills ML 62 72
Gangtok SK 62 72
South Tripura TR 62 72
Tawa n g AR 68 71
Tirap AR 68 71
Bongaigaon AS 68 71
Namchi SK 68 71
East Kameng AR 72 70
Shi Yomi AR 72 70
Majuli AS 72 70
Dimapur NL 72 70
Kra Daadi AR 76 69
Tinsukia AS 76 69
Gyalshing SK 76 69
Upper Siang AR 79 68
South Salmara-Mankachar AS 79 68
Ri Bhoi ML 79 68
Anjaw AR 82 67
Lower Subansiri AR 83 66
Hailakandi AS 83 66
Sivasagar AS 83 66
Sonitpur AS 83 66
West Jaintia Hills ML 83 66
Mon NL 83 66
Biswanath AS 89 65
East Garo Hills ML 89 65
West Karbi Anglong AS 91 64
East Jaintia Hills ML 92 63
Mokokchung NL 92 63
Namsai AR 94 62
West Siang AR 94 62
East Khasi Hills ML 94 62
Tuensang NL 94 62
Zunheboto NL 94 62
Pakyong SK 94 62
East Siang AR 100 61
Siang AR 100 61
Kamrup AS 100 61
West Khasi Hills ML 100 61
Kiphire NL 100 61
Longleng NL 100 61
Wokha NL 106 60
Lohit AR 107 59
Upper Subansiri AR 107 59
Kohima NL 107 59
Phek NL 107 59
Khawzawl MZ 111 58
Peren NL 111 58
Pakke Kessang AR 113 57
Papum Pare AR 113 57
Kamle AR 115 50
Kamrup Metropolitan AS 115 50
Charaideo AS 117 49
Mangan SK 118 48
Kurung Kumey AR 119 47
Soreng SK 119 47
Lower Siang AR 121 36
Bichom AR NA
Keyi Panyor AR NA
Bajali AS NA
Tamulpur AS NA
Eastern West Khasi Hills ML NA
Chumoukedima NL NA
Noklak NL NA
Niuland NL NA
Shamator NL NA
Tseminyu NL NA
Aspir ant (0-4 9) Performer (50-64) Front Runner (65-99) Achiever (100)
0 2010 4030 50 60 908070 100
0102030405060708090100
143
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) FIGURE 16.2: PERFORMANCE OF DISTRICTS IN SDG 16
© 2022 Mapbox © Op enStreetMap
2023-24
2021-22
1442023-24NER DISTRICT SDG INDEX
Target Justification
SDG TargetIndicator TargetJustification of Target
16.1
Reported murders per 10,000
population
0.07
Global SDG target 16.1 aims to significantly reduce all forms of
violence and related death rates everywhere. Average of the 5
best scores has been set as the target.
16.2
Cognizable crimes against children
per 10,000 child population
0
Global SDG target 16.2 aims to end abuse, exploitation,
trafficking and all forms of violence against and torture of
children.
16.2
Number of missing children per
10,000 child population
0
Global SDG target 16.2 aims to end abuse, exploitation,
trafficking and all forms of violence against and torture of
children.
16.3
Ratio of working strength to
sanctioned strength of Judges
(District & Subordinate courts)
1
Global SDG target 16.3 aims to promote the rule of law at the
national and international levels and ensure equal access to
justice for all.
16.6
Common Service Centres providing
online services per 10,000
population
11.88
Global SDG target 16.6 aims to develop effective, accountable
and transparent institutions at all levels. Average of the 5 best
scores has been set as the target.
16.9 Percentage of births registered100
Global SDG target 16.9 aims to provide legal identity for all,
including birth registration by 2030.
16.9
Percentage of population covered
under Aadhaar
100
Global SDG target 16.9 aims to provide legal identity for all,
including birth registration by 2030.
16.9 Percentage of deaths registered100
Global SDG target 16.9 aims to provide legal identity for all,
including birth registration by 2030.
145
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
146Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 16.1: PERFORMANCE OF DISTRICTS ON SDG 16
SDG Target 16.1 16.2 16.2 16.3 16.6 16.9 16.9 16.9
District
Reported murders
per 10,000
population
Cognizable crimes
against children
per 10,000
population
Number of
missing children
per 10,000
population
Ratio of working strength
to sanctioned strength
of Judges (District &
Subordinate courts)
Common Service
Centres providing
online services per
10,000 population
Percentage of
births registered
Percentage
of population
covered under
Aadhaar
Percentage
of deaths
registered
SDG 16
Arunachal Pradesh
Anjaw 0.47 0.94 0.00 1.00 0.94 94.4 88 34.6 67
Bichom Null Null Null Null Null Null Null Null *
Changlang 0.54 1.08 0.40 1.00 10.05 97.6 112 56.5 79
Dibang Valley 0.00 0.00 0.00 1.00 0.00 96.5 92 28.9 75
East Kameng 0.64 0.79 0.00 1.00 15.72 81.3 84 22.2 70
East Siang 0.56 1.39 0.00 1.00 0.42 83.9 95 26.1 61
Kamle 0.45 0.45 0.00 0.00 0.45 Null Null Null 50
Keyi Panyor Null Null Null Null Null Null Null Null *
Kra Daadi 0.21 0.43 0.00 1.00 0.00 92.7 Null 30.7 69
Kurung Kumey 0.44 0.22 0.44 0.50 0.22 93.4 47 8.3 47
Leparada 0.00 1.49 0.00 1.00 0.50 Null Null Null 73
Lohit 0.40 1.61 0.00 1.00 3.01 93.0 42 50.8 59
Longding 0.35 0.35 0.00 1.00 3.53 88.7 Null 57.2 74
Lower Dibang Valley 0.00 1.66 0.00 1.00 4.81 92.6 107 53.6 79
Lower Siang 0.92 1.38 0.00 0.00 1.84 Null Null Null 36
Lower Subansiri 0.24 0.47 0.47 1.00 2.60 90.0 77 30.3 66
Namsai 0.94 0.42 0.21 1.00 3.02 89.8 Null 57.5 62
Pakke Kessang 0.00 0.83 0.00 0.00 0.83 Null Null Null 57
Papum Pare 0.57 2.78 0.00 1.00 2.94 75.4 114 21.6 57
Shi Yomi 0.00 0.75 0.00 0.00 Null Null Null Null 70
Siang 0.31 0.94 0.00 1.00 0.31 79.9 Null 23.2 61
Tawang 0.00 0.20 0.00 0.50 1.20 95.3 84 51.2 71
Tirap 0.18 0.00 0.36 1.00 4.70 91.1 49 64.8 71
Upper Siang 0.28 1.13 0.00 1.00 3.40 79.5 107 18.4 68
Upper Subansiri 0.39 0.52 0.00 1.00 0.65 78.9 78 10.5 59
West Kameng 0.13 0.64 0.00 1.00 3.70 97.3 98 48.5 80
West Siang 0.38 1.33 0.00 1.00 1.14 81.9 92 17.7 62
Assam
Bajali Null Null Null Null Null Null Null Null *
Baksa 0.16 0.78 0.17 0.89 5.68 97.9 Null 50.1 77
Barpeta 0.18 0.76 0.00 0.86 7.29 96.0 118 74.3 85
Biswanath 0.57 2.01 0.00 0.67 5.62 98.7 Null 62.5 65
Bongaigaon 0.28 1.80 0.53 1.00 7.73 95.2 69 69.1 71
Cachar 0.35 0.84 0.00 0.92 3.56 96.0 101 72.4 79
Charaideo 0.72 1.40 1.57 0.63 3.92 94.4 Null 50.6 49
Chirang 0.29 1.78 0.58 0.92 5.10 99.3 Null 72.7 72
Darrang 0.33 0.88 0.19 0.91 6.79 96.9 103 69.2
81
Dhemaji 0.25 1.30 0.31 1.00 10.71 98.4 106 47.2 82
Dhubri 0.25 1.92 1.49 0.94 7.98 96.4 108 73.1 72
Dibrugarh 0.42 1.10 0.05 0.89 3.97 93.9 92 72.3 74
Dima Hasao 0.23 0.61 0.00 0.78 2.85 95.0 Null 60.3 73
Goalpara 0.23 0.55 0.00 0.90 6.58 98.8 106 73.3 85
Golaghat 0.22 0.59 0.10 0.93 5.43 90.9 100 55.2 79
Hailakandi 0.20 1.44 2.06 1.00 4.25 96.6 104 60.3 66
Hojai 0.29 2.10 0.00 0.70 5.85 98.7 Null 79.7 73
Jorhat 0.40 0.70 0.35 0.92 4.92 92.8 86 57.2 72
Kamrup 0.33 1.34 1.14 0.93 6.36 91.4 63 52.4 61
Kamrup Metropolitan 0.59 3.37 1.67 0.98 2.54 95.2 Null 77.4 50
Karbi Anglong 0.38 1.06 0.00 0.90 4.10 93.0 89 60.7 73
Karimganj 0.26 0.59 0.00 1.00 3.10 98.2 104 72.6 82
Kokrajhar 0.42 1.03 0.30 1.00 5.66 97.1 92 69.5 76
Lakhimpur 0.34 1.15 0.00 1.00 6.62 98.7 103 67.1 82
Majuli 0.24 1.08 0.42 0.50 6.87 98.1 Null 59.3 70
Morigaon 0.31 2.58 0.00 1.00 7.14 96.8 111 74.3 78
Nagaon 0.31 0.87 0.41 0.94 5.57 99.2 88 66.0 76
Nalbari 0.25 1.11 0.00 1.00 6.30 97.1 93 55.0 79
Sivasagar 0.40 1.26 0.00 0.77 6.56 97.1 56 57.9 66
Sonitpur 0.47 1.56 0.00 0.93 4.26 96.0 55 77.9 66
South Salmara-Mankachar 0.29 1.48 0.50 0.57 5.49 97.6 Null 71.1 68
Tamulpur Null Null Null Null Null Null Null Null *
Tinsukia 0.44 1.38 0.21 0.94 3.29 92.1 88 64.3 69
Udalguri 0.30 0.66 0.20 1.00 5.45 96.1 Null 51.2 76
West Karbi Anglong 0.24 0.91 0.24 0.50 3.11 95.4 Null 43.5 64
Manipur
Bishnupur 0.13 0.38 0.13 0.75 11.46 83.6 112 24.4 79
Chandel 0.24 0.24 0.00 1.00 6.10 91.4 78 53.7 77
Churachandpur 0.39 0.47 0.00 1.00 13.53 87.4 101 52.5 84
Imphal East 0.19 0.49 0.36 0.63 9.36 86.1 114 32.8 74
147Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
Not included in ranking
Please refer to Pg. 15 for details
*
TABLE 16.1: PERFORMANCE OF DISTRICTS ON SDG 16
SDG Target 16.1 16.2 16.2 16.3 16.6 16.9 16.9 16.9
District
Reported murders
per 10,000
population
Cognizable crimes
against children
per 10,000
population
Number of
missing children
per 10,000
population
Ratio of working strength
to sanctioned strength
of Judges (District &
Subordinate courts)
Common Service
Centres providing
online services per
10,000 population
Percentage of
births registered
Percentage
of population
covered under
Aadhaar
Percentage
of deaths
registered
SDG 16
Imphal West 0.10 0.64 0.27 0.86 7.37 86.8 113 49.6 79
Jiribam 0.23 0.46 0.46 1.00 4.79 Null Null Null 78
Kakching 0.21 0.69 1.10 1.00 8.57 Null Null Null 77
Kamjong 0.00 0.00 0.00 1.00 10.36 Null Null Null 97
Kangpokpi 0.15 0.15 0.00 1.00 7.85 Null Null Null 90
Noney 0.20 0.20 0.00 1.00 11.99 Null Null Null 96
Pherzawl 0.00 0.00 0.00 1.00 7.50 Null Null Null 93
Senapati 0.04 0.07 0.00 0.67 3.36 94.5 79 75.4 77
Tamenglong 0.00 0.00 0.00 1.00 9.13 90.4 78 51.8 83
Tengnoupal 0.17 0.83 0.00 1.00 7.43 Null Null Null 86
Thoubal 0.29 0.62 0.36 0.75 11.98 87.2 112 40.4 78
Ukhrul 0.15 0.37 0.00 1.00 12.45 87.3 86 49.1 84
Meghalaya
East Garo Hills 0.00 1.44 0.07 0.43 8.71 81.4 68 45.9 65
East Jaintia Hills 0.73 2.11 0.49 0.80 18.79 83.0 86 43.5 63
East Khasi Hills 0.17 1.74 0.00 0.43 5.04 77.4 79 55.3 62
Eastern West Khasi Hills Null Null Null Null Null Null Null Null *
North Garo Hills 0.00 1.05 0.00 0.80 19.87 79.5 Null 43.8 78
Ri Bhoi 0.39 2.12 0.42 0.71 12.63 85.9 81 51.1 68
South Garo Hills 0.49 1.26 0.00 0.83 13.14 92.0 68 53.8 72
South West Garo Hills 0.17 0.45 0.11 0.80 20.67 87.7 Null 71.4 85
South West Khasi Hills 0.20 1.31 0.10 0.60 15.13 80.3 Null 49.5 73
West Garo Hills 0.15 1.78 0.00 0.75 7.17 92.9 87 65.8 75
West Jaintia Hills 0.48 1.84 0.15 0.63 9.55 81.7 86 55.7 66
West Khasi Hills 0.33 3.14 0.00 0.63 23.03 79.2 66 49.0 61
Mizoram
Aizawl 0.38 1.31 0.00 0.86 7.08 99.3 116 86.2 82
Champhai 0.28 1.39 0.00 0.44 9.87 100.0 113 98.3 83
Hnahthial 0.00 0.70 0.00 Null 11.23 Null Null Null 94
Khawzawl 0.54 2.98 0.00 Null 7.87 Null Null Null 58
Kolasib 0.60 1.55 0.12 0.50 12.27 99.8 115 96.3 80
Lawngtlai 0.25 0.59 0.00 0.40 12.13 99.3 115 85.4 86
Lunglei 0.15 0.91 0.00 0.31 12.37 100.0 113 86.6 85
Mamit 0.12 1.51 0.00 0.40 15.17 99.1 129 88.4 85
Saitual 0.20 0.79 0.00 Null 6.72 Null Null Null 80
Serchhip 0.15 1.68 0.00 0.50 12.54 100.0 103 93.4 86
Siaha 0.00 0.71 0.00 0.60 4.07 97.5 118 75.3 80
Nagaland
Chumoukedima Null Null Null Null Null Null Null
Null *
Dimapur 0.59 0.64 0.15 0.67 6.85 80.2 116 61.6 70
Kiphire 0.00 0.14 0.00 0.50 4.59 72.3 64 28.1 61
Kohima 0.14 0.24 1.75 1.00 2.13 78.3 78 42.8 59
Longleng 0.20 0.00 0.00 0.50 6.54 67.5 76 12.7 61
Mokokchung 0.10 0.15 0.00 0.67 1.18 85.6 68 29.7 63
Mon 0.00 0.12 0.00 0.67 4.52 71.4 64 50.9 66
Noklak Null Null Null Null Null Null Null Null *
Niuland Null Null Null Null Null Null Null Null *
Peren 0.21 0.11 0.00 0.50 5.99 78.7 49 19.3 58
Phek 0.06 0.18 0.00 0.50 2.14 70.3 67 31.2 59
Shamator Null Null Null Null Null Null Null Null *
Tseminyu Null Null Null Null Null Null Null Null *
Tuensang 0.00 0.28 0.00 0.50 5.60 66.0 76 26.5 62
Wokha 0.00 0.06 0.00 0.50 2.04 78.9 52 47.5 60
Zunheboto 0.00 0.14 0.07 1.00 1.49 51.6 67 51.0 62
Sikkim
Gangtok 0.09 2.73 0.18 1.00 1.00 95.9 107 68.4 72
Gyalshing 0.42 2.37 0.00 0.67 1.67 97.6 116 83.1 69
Mangan 0.23 3.66 1.83 0.25 1.14 98.1 93 76.3 48
Namchi 0.07 2.52 0.20 0.60 1.02 96.8 102 87.2 71
Pakyong 0.16 2.18 0.16 0.80 0.78 Null Null Null 62
Soreng 0.15 2.32 0.00 0.00 0.77 Null Null Null 47
Tripura
Dhalai 0.45 0.45 0.11 0.92 5.76 94.2 117 81.0 81
Gomati 0.16 0.82 0.26 0.90 7.27 92.9 Null 70.8 80
Khowai 0.34 0.52 0.00 1.00 6.62 94.8 Null 83.9 83
North Tripura 0.43 0.77 0.24 0.89 5.27 93.5 86 85.9 76
Sepahijala 0.25 0.33 0.29 0.89 6.19 95.3 Null 67.4 79
South Tripura 0.34 0.51 0.63 0.80 6.22 91.7 79 75.2 72
Unakoti 0.22 1.23 0.47 0.88 5.89 91.7 Null 71.1 74
West Tripura 0.25 0.50 0.50 0.90 4.16 94.9 82 88.1 76
Target 0.07 0 0 1 11.88 100 100 100 100
THE WAY FORWARD:
With less than five years remaining to achieve the
Sustainable Development Goals (SDGs), expediting
focused efforts to ensure inclusive development for
all is imperative. The North Eastern Region District
SDG Index and Dashboard serves as a valuable tool
to identify critical areas of development needs and
prioritise those farthest behind. It aims to enhance
analytical understanding of sectoral issues, fill data
gaps, and guide future action plans in the region. This
unique policy tool provides essential insights at the
district level, highlighting critical gaps and informing
resource allocation decisions. The Index serves as
a reliable reference for the NE States to assess the
comparative progress of districts across various SDGs,
including health, education, gender, economic growth,
institutions and environment.
Over the past four years, the North Eastern States have
successfully intensified the momentum of localising
SDGs and measuring progress at the district level
through the first edition of the NER District SDG Index
and Dashboard. A few States have also initiated setting
up SDG cells/coordination centres to institutionalise
these goals. Sustaining this progress is key to bridging
the performance gap in the short term and positioning
districts/states as top Performers in the long run.
It is worth noting that MDoNER has designed a new
scheme, Prime Minister's Development Initiative for
North East Region (PM-DevINE), based on the findings
of the first NER District SDG Index. This scheme
focuses on infrastructure development, industry
promotion, and social development projects while
enhancing livelihood opportunities for youth and
women. It provides targeted support to address
development gaps and accelerate progress on the
SDGs in the North Eastern Region.
Looking ahead, NITI Aayog and MDoNER are
committed to ensure:
a) Institutionalisation of SDGs in NE States through
the whole of the government approach:
The second edition of the index can be used as a tool
by the NE States to
•
Establish SDGCAC with support and guidance
from MDoNER and NITI Aayog to strengthen
governance, implementation, and monitoring of
SDG progress.
•
Develop State SDG Action Plans by leveraging
data from the index to assess district performance,
identify gaps, and set a foundation for targeted
interventions in alignment with national and state
initiatives.
•
Set clear targets and assign responsibilities to
specific departments, ensuring accountability and
a structured approach to addressing SDG-related
challenges.
•
Design and implement targeted interventions
using evidence-based insights to close identified
gaps, improve outcomes, and track progress
effectively.
b) Investment in data infrastructure and capacities
(including for citizen-generated data) to
improve data accessibility, support evidence-
based decision-making and accurate solution
identification. It is essential to integrate emerging
technologies like Big Data, AI, and Machine
Learning with traditional data sources while
ensuring their ethical use. There is a need to
enhance analytics and data capacities to identify
marginalized groups, understand challenges, and
design targeted SDG interventions.
c) Integrating SDG targets into government budgets
to ensure impact-driven and results-oriented
financial planning. SDG costing and financing gap
analyses are needed to assess resource needs and
identify funding shortfalls. Innovative financing
tools such as the SDG Investor Map and CSR
matchmaking platforms to mobilize additional
investments can be explored in this direction.
FROM ANALYSIS TO ACTION
CHAPTER 4
1502023-24NER DISTRICT SDG INDEX
d) Recognise the role of partnerships, including
South-South Cooperation, as a key strategy to
accelerate SDG progress. Fostering cross-learning
among Himalayan states and countries to share
best practices has the potential to address common
implementation challenges. Knowledge exchange
on effective strategies can help policymakers adopt
innovative, region-specific solutions for sustainable
development.
The continued collaboration between NITI Aayog, the
nodal ministry for SDG implementation, MDoNER,
State governments, other development partners,
and the private sector will be crucial in ensuring the
effective implementation and monitoring of SDGs. This
partnership will focus on strengthening institutional
structures at the state and district levels, aligning them
with the SDG agenda, and working towards achieving
the goals outlined in Agenda 2030.
151
CONTEXT & OVERVIEWMETHODOLOGY & RESULTS
STATE PROFILE
STATE PROFILES
III
153
© 2022 Mapbox © OpenStreetMap
State_Map
Arunachal Pradesh
Performance Category
Front Runner
Performer
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Arunachal Pradesh.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
59.26%
(16 Districts)
33.33%
(9 Districts)
7.41%
(2 Districts)
FIGURE AR.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORESAspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) ARUNACHAL PRADESH
DISTRICT-WISE PERFORMANCE
FIGURE AR.2: OVERALL PERFORMANCE OF DISTRICTS IN ARUNACHAL PRADESH
1542023-24NER DISTRICT SDG INDEX
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
52.00%
40.00%
16.00%
68.00%
72.00%
64.00%
56.00%84.00%
4.00% 20.00%
44.00%20.00%
88.00%
88.00%
100.00%
32.00%
32.00%12.00%
8.00%
100.00%
8.00%
20.00%
36.00%
20.00%
76.00%
56.00%
48.00%
84.00%
28.00%
12.00%
32.00%
8.00%
4.00%
36.00%
36.00%
36.00%44.00%
FIGURE AR.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE AR.1: OVERALL PERFORMANCE OF DISTRICTS IN ARUNACHAL PRADESH
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Lower Dibang Valley 23 1 73.36 67.67
Tawang 36 2 72.07 68.73
East Siang 51 3 70.79 68.80
Papum Pare 59 4 70.14 68.87
Changlang 63 5 69.93 68.53
West Kameng 64 6 69.86 66.93
Kurung Kumey 71 7 69.00 62.13
Namsai 72 8 68.93 65.60
East Kameng 78 9 68.21 58.27
West Siang 80 10 68.07 68.07
Lohit 81 11 68.00 64.67
Dibang Valley 83 12 67.93 64.80
Upper Siang 85 13 67.79 67.40
Leparada 88 14 67.36 63.80
Upper Subansiri 91 15 67.14 65.40
Lower Subansiri 100 16 65.86 68.47
Lower Siang 107 17 64.14 60.87
Shi Yomi 109 18 63.43 58.60
Kra Daadi 111 19 63.21 55.60
Pakke Kessang 112 20 63.14 59.73
Anjaw 113 21 63.07 63.60
Tirap 116 22 61.93 66.20
Siang 117 23 61.71 64.00
Kamle 120 24 58.86 57.40
Longding 121 25 58.71 66.60
Bichom N/A N/A N/A N/A
Keyi Panyor N/A N/A N/A N/AAspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100)
155
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) ASSAM
DISTRICT-WISE PERFORMANCE FIGURE AS.2: OVERALL PERFORMANCE OF DISTRICTS IN ASSAM
© 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
ERROR
Front Runner
Performer
Assam
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Assam.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
5.71%
(2 Districts)
88.57%
(31 Districts)
5.71%
(2 Districts)
FIGURE AS.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1562023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) FIGURE AS.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1 81.82%
63.64%
100.00%
100.00%
57.58% 24.24%
12.12%
9.09%
96.97%
63.64%
9.09%
39.39%
6.06%
60.61%
75.76%
87.88%
78.79%21.21%
3.03%
100.00%
18.18%
100.00%
78.79%
9.09%
9.09%3.03%
36.36%
60.61%
15.15%
36.36%
39.39%
3.03%
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Dibrugarh 17 1 74.29 68.33
Sivasagar 20 2 74.00 68.33
Jorhat 21 3 73.79 69.67
Nalbari 28 4 72.86 69.47
Goalpara 30 5 72.79 69.47
Hojai 32 6 72.36 N/A
Kamrup Metropolitan 38 7 71.86 71.73
Tinsukia 41 8 71.79 67.60
Golaghat 44 9 71.50 67.00
Lakhimpur 47 10 71.43 68.80
Dima Hasao 50 11 70.93 62.67
Charaideo 53 12 70.71 N/A
Karimganj 54 13 70.64 69.47
Karbi Anglong 55 14 70.57 63.87
Morigaon 55 14 70.57 67.40
Dhemaji 58 16 70.21 66.33
Sonitpur 59 17 70.14 68.60
Kamrup 61 18 70.07 69.07
Cachar 65 19 69.79 67.53
Bongaigaon 67 20 69.36 67.47
Hailakandi 67 20 69.36 67.27
Nagaon 70 22 69.21 67.33
Biswanath 76 23 68.50 N/A
Chirang 77 24 68.29 69.07
Dhubri 84 25 67.86 64.33
Darrang 87 26 67.43 N/A
Majuli 88 27 67.36 N/A
Kokrajhar 91 28 67.14 66.00
Barpeta 94 29 66.79 64.00
Baksa 97 30 66.29 65.33
Udalguri 102 31 65.71 66.73
West Karbi Anglong 108 32 63.86 N/A
South Salmara-Mankachar 118 33 59.71 N/A
Bajali N/A N/A N/A N/A
Tamulpur N/A N/A N/A N/A
TABLE AS.1: OVERALL PERFORMANCE OF DISTRICTS IN ASSAM
157
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) MANIPUR
DISTRICT-WISE PERFORMANCE © 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
Front Runner
Performer
Manipur
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Manipur.© 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
Front Runner
Performer
Manipur
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Manipur.
FIGURE MN.2: OVERALL PERFORMANCE OF DISTRICTS IN MANIPUR
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
25%
(4 Districts)
75%
(12 Districts)
FIGURE MN.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1582023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 16.25%
25.00%
12.50%
18.75%6.25%
100.00%
43.75%
6.25%
68.75%
25.00%
18.75%
50.00%
43.75%
68.75%
50.00%
18.75%
37.50%
75.00%
31.25%
62.50%
62.50%
37.50%
50.00%
12.50%
12.50% 87.50%
25.00%
100.00%
43.75%
100.00%
75.00%
50.00%
37.50%
25.00%
12.50%
FIGURE MN.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE MN.1: OVERALL PERFORMANCE OF DISTRICTS IN MANIPUR
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Imphal West 24 1 73.21 72.13
Imphal East 27 2 72.93 70.87
Kakching 38 3 71.86 N/A
Jiribam 43 4 71.64 N/A
Thoubal 48 5 71.29 68.93
Tengnoupal 57 6 70.43 N/A
Bishnupur 66 7 69.43 69.27
Senapati 73 8 68.71 66.93
Ukhrul 75 9 68.64 65.27
Kamjong 96 10 66.43 N/A
Chandel 99 11 65.93 67.47
Churachandpur 103 12 65.36 66.53
Kangpokpi 104 13 64.86 N/A
Noney 106 14 64.43 N/A
Tamenglong 115 15 62.07 64.93
Pherzawl 118 16 59.71 N/A
159
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) MEGHALAYA
DISTRICT-WISE PERFORMANCE FIGURE ML.2: OVERALL PERFORMANCE OF DISTRICTS IN MEGHALAYA
© 2022 Mapbox © OpenStreetMap
State_Map
Performance Category
ERROR
Front Runner
Performer
Null
Meghalaya
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Meghalaya.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
8.33%
(1 District)
83.33%
(10 Districts)
8.33%
(1 District)
FIGURE ML.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1602023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
54.55%
63.64%
54.55%
66.67%
54.55%
18.18%
27.27%
27.27%
45.45%
36.36%
27.27%
16.67%
45.45%
72.73%
72.73%9.09%
72.73%
81.82%
90.91%
63.64%
90.91%
16.67%
18.18%
9.09% 63.64%
18.18%
9.09%
36.36%
27.27%
9.09%
100.00%
72.73%27.27%
TABLE ML.1: OVERALL PERFORMANCE OF DISTRICTS IN MEGHALAYA
FIGURE ML.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
East Khasi Hills 26 1 73.00 66.27
South West Garo Hills 41 2 71.79 63.40
West Garo Hills 44 3 71.50 63.80
Ri Bhoi 69 4 69.29 62.80
West Jaintia Hills 73 5 68.71 64.27
East Garo Hills 81 6 68.00 63.00
West Khasi Hills 88 7 67.36 63.60
South West Khasi Hills 93 8 67.00 61.93
North Garo Hills 95 9 66.64 56.87
South Garo Hills 101 10 65.79 59.20
East Jaintia Hills 114 11 63.00 63.33
Eastern West Khasi Hills N/A N/A N/A N/A
161
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) MIZORAM
DISTRICT-WISE PERFORMANCE OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM
© 2022 Mapbox © Op enStreetMap
State_Map
Performance Category
Front Runner
Mizoram
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Mizoram.
OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM
© 2022 Mapbox © Op enStreetMap
State_Map
Performance Category
Front Runner
Mizoram
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Mizoram.
FIGURE MZ.2: OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM© 2022 Mapbox © Op enStreetMap
State_Map
Performance Category
Front Runner
Mizoram
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Mizoram.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
100.00%
(11 Districts)
Aspirant Performer Front Runner Achiever Not included in computation
FIGURE MZ.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1622023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 190.91%
9.09%
81.82%
18.18% 72.73%
9.09%
72.73%18.18%
100.00%
63.64%
72.73%
9.09% 36.36%36.36%
100.00%
81.82%
90.91%
90.91%
63.64%
9.09%
9.09%
9.09%
9.09%
90.91%
36.36%
18.18%
27.27%
27.27%
9.09%
18.18%
9.09%
54.55%45.45%
9.09%
FIGURE MZ.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE MZ.1: OVERALL PERFORMANCE OF DISTRICTS IN MIZORAM
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Hnahthial 1 1 81.43 N/A
Champhai 2 2 79.86 71.93
Kolasib 9 3 76.50 72.27
Aizawl 11 4 76.07 71.27
Serchhip 12 5 75.64 74.87
Saitual 13 6 75.36 N/A
Khawzawl 17 7 74.29 N/A
Siaha 34 8 72.14 68.27
Lunglei 51 9 70.79 72.87
Mamit 79 10 68.14 71.47
Lawngtlai 86 11 67.71 63.40
163
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) NAGALAND
DISTRICT-WISE PERFORMANCE FIGURE NL.2: OVERALL PERFORMANCE OF DISTRICTS IN NAGALAND
© 2022 Mapbox © O penStreetMap
State_Map
Performance Category
ERROR
Front Runner
Performer
Nagaland
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Nagaland.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
12.5%
(2 Districts)
31.25%
(5 Districts)
56.25%
(9 Districts)
FIGURE NL.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1642023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1 54.55%
9.09%
81.82%
72.73%27.27%
63.64%
18.18%
45.45%
90.91%
54.55%
81.82% 18.18%
18.18%
36.36%
100.00%
100.00%
100.00%
100.00%
72.73%
18.18%
27.27%
27.27%
63.64%18.18%
18.18% 81.82%
9.09% 72.73%
18.18%
FIGURE NL.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE NL.1: OVERALL PERFORMANCE OF DISTRICTS IN NAGALAND
District Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Mokokchung 4 1 78.43 62.27
Kohima 6 2 76.93 64.07
Dimapur 10 3 76.29 63.67
Phek 25 4 73.14 58.27
Longleng 28 5 72.86 59.07
Peren 34 6 72.14 60.53
Wokha 44 7 71.50 59.33
Mon 62 8 70.00 55.93
Kiphire 98 9 66.07 53.00
Tuensang 105 10 64.57 55.87
Zunheboto 110 11 63.36 54.53
Chumoukedima N/A N/A N/A N/A
Niuland N/A N/A N/A N/A
Noklak N/A N/A N/A N/A
Shamator N/A N/A N/A N/A
Tseminyu N/A N/A N/A N/A
165
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) SIKKIM
DISTRICT-WISE PERFORMANCE FIGURE SK.2: OVERALL PERFORMANCE OF DISTRICTS IN SIKKIM
© 2022 Mapbox © OpenStreetMap
State_Map
Sikkim
Performance Category
ERROR
Front Runner
Map based on Longitude (generated) and Longitude (generated) and Latitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and States. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_States.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Sikkim.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Aspirant Performer Front Runner Achiever Not included in computation
100%
(6 Districts)
FIGURE SK.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1662023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 116.67%
100.00%
33.33% 33.33%
50.00%
100.00%
100.00%
66.67%
83.33%
100.00%
100.00%
100.00%
50.00%33.33%
100.00%
100.00%
16.67%
66.67% 33.33%
33.33%
16.67%
83.33%
33.33% 16.67%
33.33%
16.67%
83.33%
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Gangtok 8 1 76.64 75.87
Namchi 14 2 75.21 74.80
Mangan 31 3 72.50 72.00
Pakyong 37 4 72.00 N/A
Soreng 38 5 71.86 N/A
Gyalshing 49 6 71.14 71.87
FIGURE SK.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE SK.1: OVERALL PERFORMANCE OF DISTRICTS IN SIKKIM
167
CONTEXT & OVERVIEWSTATE PROFILE
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) Not Available (N/A) TRIPURA
DISTRICT-WISE PERFORMANCE FIGURE TR.2: OVERALL PERFORMANCE OF DISTRICTS IN TRIPURA
© 2022 Mapbox © Op enStreetMap
State_Ma p
Tripura
Performance Category
Front Runner
Map bas ed on Longitude (generated) and L ongitude (generated) and L atitude (generated). For pane Longitude (generated): Color shows details about Performance Category.
Details are shown for District and St ates. For pane Longitude (generated) (2): Color shows details about STATE (NER_All_St ates.shp). The data is filtered on Attribute, which
keeps Composite Score. The view is filtered on States, which keeps Tripura.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
100%
(8 Districts)
Aspirant Performer Front Runner Achiever Not included in computation
FIGURE TR.1: PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY - COMPOSITE SCORES
1682023-24NER DISTRICT SDG INDEX
Aspirant (0-49) Performer (50-64) Front Runner (65-99) Achiever (100) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SDG 16
SDG 15
SDG 13
SDG 12
SDG 11
SDG 10
SDG 9
SDG 8
SDG 7
SDG 6
SDG 5
SDG 4
SDG 3
SDG 2
SDG 1
87.50%
87.50%
62.50%
37.50%
25.00%75.00%
62.50%
37.50%
12.50%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
62.50%
100.00%
12.50%
12.50%
37.50%
FIGURE TR.3: GOAL-WISE PERCENTAGE OF DISTRICTS IN EACH PERFORMANCE CATEGORY
TABLE TR.1: OVERALL PERFORMANCE OF DISTRICTS IN TRIPURA
Districts Overall Rank in NER 2023-24 Rank within state 2023-24 Score 2023-24 Score 2021-22
Gomati 3 1 78.79 75.73
West Tripura 5 2 77.64 75.67
South Tripura 7 3 76.71 72.40
Sepahijala 15 4 75.07 72.60
Khowai 16 5 74.64 71.93
North Tripura 17 6 74.29 75.73
Unakoti 22 7 73.71 73.47
Dhalai 33 8 72.29 72.60
169
CONTEXT & OVERVIEWSTATE PROFILE
METADATA &
INDICATOR TABLES
IV
GOAL 1: END POVERTY Percentage of beneficiaries covered under National Food Security Act (NFSA), 2013
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people
in vulnerable situations, including infants, to safe, nutritious and sufficient food all year round
Relevant NIF Indicator 2.1.2: Proportion of beneficiaries covered under National Food Security Act 2013
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: END POVERTY Headcount ratio as per the Multi-Dimensional Poverty Index (%)
Indicator Data Source
NITI Aayog
National Multi-Dimensional Poverty Index (Baseline Report based on NFHS-5 (2019–2021))
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity Non-periodic
Relevant Global Target
1.2: By 2030, reduce at least by half the proportion of men, women and children of all ages living
in poverty in all its dimensions according to national definitions
Relevant NIF Indicator
1.2.2: Proportion of men, women and children of all ages living in poverty in all its dimensions
according to national definitions
Relevant Global Indicator
1.2.2: Proportion of men, women and children of all ages living in poverty in all its dimensions
according to national definitions
Indicator Interpretation Higher value means lower performance (–)
GOAL 1: END POVERTY
Persons offered employment as a percentage of persons who demanded employment under
Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)
Indicator Data Source
Ministry of Rural Development
[MGNREGA MIS Report]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant Global Indicator
1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing
children, unemployed persons, older persons, persons with disabilities, pregnant women,
newborns, work-injury victims and the poor and the vulnerable
Relevant NIF Indicator
1.3.3: Persons offered employment as a percentage of persons who demanded employment under
Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)
Indicator Interpretation Higher value means higher performance (+)
× 100
Families/persons identified under NFSA
Accepted no. of persons/families covered under NFSA
× 100
Persons offered employment under MGNREGA
Persons who demanded employment under MGNREGA
1722023-24NER DISTRICT SDG INDEX
GOAL 1: END POVERTY Percentage of Self-Help Groups (SHGs) provided credit linkage
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant NIF Indicator 1.3.4: Number of Self-Help Groups (SHGs) provided bank credit linkage
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: END POVERTY
Percentage of women receiving benefits under Pradhan Mantri Matru Vandana Yojana (PMMVY)
or any other maternity related State schemes against target
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 115
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including
floors, and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant Global Indicator
1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing
children, unemployed persons, older persons, persons with disabilities, pregnant women,
newborns, work-injury victims and the poor and the vulnerable
Relevant NIF Indicator
1.3.5: Proportion of the population (out of total eligible population) receiving social protection
benefits under Pradhan Mantri Matru Vandana Yojana (PMMVY)
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: END POVERTY
Percentage of affordable houses completed against sanctioned (rural + urban) under Pradhan
Mantri Awas Yojana (PMAY) and related State schemes
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
1.4: By 2030, ensure that all men and women, in particular the poor and the vulnerable, have
equal rights to economic resources, as well as access to basic services, ownership and control
over land and other forms of property, inheritance, natural resources, appropriate new technology
and financial services, including microfinance
Relevant Global Indicator 1.4.1: Proportion of population living in households with access to basic services
Relevant NIF Indicator 1.4.1: Proportion of population living in households with access to basic services
Indicator Interpretation Higher value means higher performance (+)
× 100
No. of SHGs provided credit linkage in the district
Total no. of SHGs in the district
× 100
No. of beneficiaries paid under PMMVY and other State schemes in the FY 2023–24
No. of beneficiaries enrolled under PMMVY and other State schemes in the FY 2023–24
× 100
No. of houses completed under PMAY and State schemes (rural & urban)
Total no. of houses sanctioned for construction under PMAY & State schemes (rural & urban)
173
METADATA
GOAL 1: NO POVERTY
Percentage of households with any usual member covered by a health scheme or health
insurance
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including floors,
and by 2030 achieve substantial coverage of the poor and the vulnerable
Relevant Global Indicator
1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing
children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns,
work-injury victims and the poor and the vulnerable
Relevant NIF Indicator
1.3.1: Percentage of households with any usual member covered by a health scheme or health
insurance
Indicator Interpretation Higher value means higher performance (+)
GOAL 1: NO POVERTY
Hospital beds empanelled under Pradhan Mantri Jan Arogya Yojana (PMJAY) or related State
schemes per 10,000 eligible population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Number per 10,000 eligible population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
1.3: Implement nationally appropriate social protection systems and measures for all, including floors,
and by 2030 achieve substantial coverage of the poor and the vulnerable
Indicator Interpretation Higher value means higher performance (+)
GOAL 2: ZERO HUNGER Percentage of Fair Price Shops (FPS) covered under online transaction system for PDS in the district
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people in
vulnerable situations, including infants, to safe, nutritious and sufficient food all year round
Indicator Interpretation Higher value means higher performance (+)
× 10,000
No. of beds in the hospitals empanelled under PMJAY or related State schemes in the district
Total no. of people identified as eligible for PMJAY or related State schemes in the district
× 100
No. of FPS covered under online transaction system for PDS in the district
Total no. of FPS for PDS in the district
1742023-24NER DISTRICT SDG INDEX
GOAL 2: ZERO HUNGER
Percentage of Anganwadi centres in the district with anthropometric measurement devices
(height, weight)
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls,
pregnant and lactating women and older persons
Indicator InterpretationHigher value means higher performance (+)
GOAL 2: ZERO HUNGER Percentage of Anganwadis with own buildings
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls,
pregnant and lactating women and older persons
Indicator InterpretationHigher value means higher performance (+)
GOAL 2: ZERO HUNGER Percentage of children under age 5 years who are stunted
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally agreed targets on
stunting and wasting in children under 5 years of age, and address the nutritional needs of adolescent girls,
pregnant and lactating women and older persons
Relevant Global Indicator
2.2.1: Prevalence of stunting (height for age ≤2 standard deviation from the median of the World Health
Organization (WHO) Child Growth Standards) among children under 5 years of age
Relevant NIF Indicator2.2.1: Percentage of Children under age 5 years who are stunted
Indicator InterpretationHigher value means lower performance (–)
× 100
No. of Anganwadi centres in the district with anthropometric measurement devices (height, weight)
Total no. of Anganwadi centres in the district
× 100
No. of Anganwadi centres with own buildings
Total no. of Anganwadi centres in the district
175
METADATA
GOAL 2: ZERO HUNGER Percentage of children under age 5 years who are underweight
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally
agreed targets on stunting and wasting in children under 5 years of age, and address the
nutritional needs of adolescent girls, pregnant and lactating women and older persons
Relevant NIF Indicator 2.1.1: Percentage of children aged under 5 years who are underweight
Indicator Interpretation Higher value means lower performance (–)
GOAL 2: ZERO HUNGER Percentage of pregnant women aged 15–49 years who are anaemic (<11.0 g/dL)
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 99
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally
agreed targets on stunting and wasting in children under 5 years of age, and address the
nutritional needs of adolescent girls, pregnant and lactating women and older persons
Relevant Global Indicator 2.2.3: Prevalence of anaemia in women aged 15–49 years, by pregnancy status (percentage)
Relevant NIF Indicator 2.2.3: Prevalence of anaemia in women aged 15–49 years, by pregnancy status (percentage)
Indicator Interpretation Higher value means lower performance (–)
GOAL 2: ZERO HUNGER Percentage of children aged 6–59 months who are anaemic (<11.0 g/dL)
Indicator Data Source
Ministry of Health & Family Welfare
[National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
2.2: By 2030, end all forms of malnutrition, including achieving, by 2025, the internationally
agreed targets on stunting and wasting in children under 5 years of age, and address the
nutritional needs of adolescent girls, pregnant and lactating women and older persons
Relevant NIF Indicator 2.2.5: Percentage of children age 6–59 months who are anaemic (Hb < 11.0 g/dL)
Indicator Interpretation Higher value means lower performance (−)
1762023-24NER DISTRICT SDG INDEX
GOAL 2: ZERO HUNGER Average yield of rice (kg/ha)
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Kg/Hectare
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in
particular women, indigenous peoples, family farmers, pastoralists and fishers, including through
secure and equal access to land, other productive resources and inputs, knowledge, financial
services, markets and opportunities for value addition and non-farm employment
Relevant NIF Indicator 2.3.1: Agriculture productivity of wheat and rice (in kg per hectare)
Indicator Interpretation Higher value means higher performance (+)
GOAL 2: ZERO HUNGER Productivity of fruits and vegetables (kg/ha)
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Kg/Hectare
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in
particular women, indigenous peoples, family farmers, pastoralists and fishers, including through
secure and equal access to land, other productive resources and inputs, knowledge, financial
services, markets and opportunities for value addition and non-farm employment
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of pregnant women who completed 4 (ANCs) in the district
Indicator Data Source Ministry of Health and Family Welfare
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 119
Data Periodicity Annual
Relevant Global Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births
Relevant NIF Indicator
3.1.4: Percentage of women aged 15–49 years with a live birth, for last birth, who received ANC,
four times or more (period for 5 years/1 year)
Indicator Interpretation Higher value means higher performance (+)
Total production of rice (kg)
Area under rice cultivation (Ha)
Total production of fruits and vegetables (kg)
Area under cultivation of fruits and vegetables (Ha)
177
METADATA
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of births attended by skilled health personnel
Indicator Data Source Ministry of Health and Family Welfare
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 119
Data Periodicity Annual
Relevant Global Target 3.1: By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births
Relevant Global Indicator 3.1.2: Proportion of births attended by skilled health personnel
Relevant NIF Indicator 3.1.3: Percentage of births attended by skilled health personnel (period 1 year)
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of children aged 9–11 months fully immunized
Indicator Data Source Ministry of Health and Family Welfare
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 119
Data Periodicity Annual
Relevant Global Target
3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all
countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and
under-5 mortality to at least as low as 25 per 1,000 live births
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
Relevant Global Indicator
3.b.1: Proportion of the target population covered by all vaccines included in their national
programme
Relevant NIF Indicator
3.b.1: Percentage of children aged 12–23 months fully immunized (BCG, Measles and three doses
of Pentavalent vaccine)
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Infant Mortality Rate
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Per 1,000 live births
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all
countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and
under-5 mortality to at least as low as 25 per 1,000 live births
Indicator Interpretation Higher value means lower performance (–)
× 1,000
Infant deaths (< 1 year) during the given year
Total live births during the given year
1782023-24NER DISTRICT SDG INDEX
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of functional newborn facilities (SNCU, NBSU, NBCC) per 10,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of new HIV infections per 1,000 uninfected population
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Per 1,000 uninfected population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases
and combat hepatitis, waterborne diseases and other communicable diseases
Relevant Global Indicator
3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key
populations
Relevant NIF Indicator 3.3.1: Number of new HIV infections per 1,000 uninfected population
Indicator Interpretation Higher value means lower performance (–)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Percentage of TB cases successfully treated among TB cases notified to the national health
authorities
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 98
Data Periodicity Annual
Relevant Global Target
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases
and combat hepatitis, water-borne diseases and other communicable diseases
Relevant NIF Indicator
3.8.1 (f): Percentage of TB cases successfully treated (cured plus treatment completed) among TB
cases notified to the national health authorities during a specified period
Indicator Interpretation Higher value means higher performance (+)
× 10,000
No. of functional newborn facilities (SNCU, NBSU, NBCC)
Total population of the district (2011)
× 1,000
New HIV infections
Uninfected population
× 100
No. of TB case successfully treated out of the new cases notified in the reference year
Total no. of TB cases notified (Public + Private) in the reference year
179
METADATA
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of suicide deaths reported per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Per 1,00,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through
prevention and treatment and promote mental health and well-being
Relevant Global Indicator 3.4.2: Suicide mortality rate
Relevant NIF Indicator 3.4.2. Suicide mortality rate (per 1,00,000 population)
Indicator Interpretation Higher value means lower performance (–)
GOAL 3: GOOD HEALTH AND
WELL-BEING
Number of de-addiction centres (public and private) per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–24
Data Unit Per 1,00,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.5: Strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and
harmful use of alcohol
Relevant Global Indicator
3.5.1: Coverage of treatment interventions (pharmacological, psychosocial and rehabilitation and
aftercare services) for substance use disorders
Relevant NIF Indicator 3.5.1: Number of persons treated in de-addiction centres
Indicator Interpretation Higher value means higher performance (+)
GOAL 3: GOOD HEALTH AND
WELL-BEING
First Referral Units (FRUs) per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Per 1,00,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.8: Achieve universal health coverage, including financial risk protection, access to quality
essential health-care services and access to safe, effective, quality and affordable essential
medicines and vaccines for all
Indicator Interpretation Higher value means higher performance (+)
No. of suicides reported during reference year in the district
Total population (2011)
× 1,00,000
No. of de-addiction centres (public and private) in the district
Total population (2011)
× 1,00,000
No. of FRUs in the district
Total population (2011)
× 1,00,000
1802023-24NER DISTRICT SDG INDEX
GOAL 3: GOOD HEALTH AND
WELL-BEING
Total physicians, nurses and midwives per 10,000 population
Indicator Data Source State
Computation Approach
Data Period 2023–2024
Data Unit Number per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
3.c: Substantially increase health financing and the recruitment, development, training and
retention of the health workforce in developing countries, especially in least developed countries
and small island developing States
Relevant Global Indicator 3.c.1: Health worker density and distribution
Relevant NIF Indicator 3.c.1: Health worker density
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Average annual dropout rate at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education - Plus (UDISE+)]
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and
secondary education leading to relevant and effective learning outcomes
Indicator Interpretation Higher value means lower performance (–)
GOAL 4: QUALITY EDUCATION Ratio of female to male enrolment at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education - Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Ratio
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.5: By 2030, eliminate gender disparities in education and ensure equal access to all levels of
education and vocational training for the vulnerable, including persons with disabilities, indigenous
peoples and children in vulnerable situations
Relevant Global Indicator
4.5.1: Parity indices (female/male, rural/urban, bottom/top wealth quintile and others such
as disability status, indigenous peoples and conflict-affected, as data become available) for all
education indicators on this list that can be disaggregated
Relevant NIF Indicator 4.5.1: Gender Parity Indices (GPI) for primary/secondary/higher secondary/tertiary education
Indicator Interpretation Higher value means higher performance (+)
No. of (Registered doctors + AYUSH practitioners + ANM +
Registered nurses and midwives + Lady health volunteers)
Total population (2011)
× 10,000
Female enrolment at secondary level
Male enrolment at secondary level
181
METADATA
GOAL 4: QUALITY EDUCATION
Percentage of students in Grade 8 achieving at least a minimum proficiency level in terms of
nationally defined learning outcomes to be attained at the end of the grade
Indicator Data Source
Ministry of Education
[National Achievement Survey, 2021]
Computation Approach
Data Period (Year) 2021
Data Unit Percentage
Districts Covered 116
Data Periodicity 3 Years
Relevant Global Target
4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and
secondary education leading to relevant and effective learning outcomes
Relevant Global Indicator
4.1.1: Proportion of children and young people (a) in grades 2/3; (b) at the end of primary; and (c)
at the end of lower secondary achieving at least a minimum proficiency level in (i) reading and (ii)
mathematics, by sex
Relevant NIF Indicator
4.1.1: Percentage of students in grade 3, 5, 8 and 10 achieving at least a minimum proficiency
level in terms of nationally defined learning outcomes to be attained by pupils at the end of each
of above grades
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Percentage of schools with computers available
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.a: Build and upgrade education facilities that are child, disability and gender sensitive and
provide safe, non-violent, inclusive and effective learning environments for all
Relevant Global Indicator 4.a.1: Proportion of schools offering basic services, by type of service
Relevant NIF Indicator 4.a.1: Proportion of schools with access to: (b) computers for pedagogical purposes
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Percentage of schools with access to electricity
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.a: Build and upgrade education facilities that are child, disability and gender sensitive and
provide safe, non-violent, inclusive and effective learning environments for all
Relevant Global Indicator 4.a.1: Proportion of schools offering basic services, by type of service
Relevant NIF Indicator 4.a.1: Proportion of schools with access to: (a) electricity
Indicator Interpretation Higher value means higher performance (+)
No. of students of class 8 achieving desired score as per NAS assessment
standards in Maths & Language
Total no. of students of class 8 who participated in NAS
× 100
No. of schools with computers available
Total no. of schools
× 100
No. of schools with electricity
Total no. of schools
× 100
1822023-24NER DISTRICT SDG INDEX
GOAL 4: QUALITY EDUCATION Percentage of trained teachers at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
*Teachers with Basic teacher's training/B.Ed./D.El.Ed./M.Ed or equivalent (not less than two years)/Diploma/degree in special
education at secondary level
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.c: By 2030, substantially increase the supply of qualified teachers, including through
international cooperation for teacher training in developing countries, especially least developed
countries and small island developing States
Relevant Global Indicator 4.c.1: Proportion of teachers with the minimum required qualifications, by education level
Relevant NIF Indicator
4.c.1: Proportion of trained teacher, by education level (primary, upper primary, elementary,
secondary and higher secondary education), (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 4: QUALITY EDUCATION Pupil Teacher Ratio at secondary level (Class 9–10)
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education - Plus (UDISE+)]
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Ratio
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
4.c: By 2030, substantially increase the supply of qualified teachers, including through
international cooperation for teacher training in developing countries, especially least developed
countries and small island developing States
Indicator Interpretation Higher value means lower performance (–)
GOAL 5: GENDER EQUALITY Crimes against women per 10,000 female population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau, Crime in India 2022]
Computation Approach
Data Period (Year) 2022
Data Unit Number of cases per 10,000 female population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
5.2: Eliminate all forms of violence against all women and girls in the public and private spheres,
including trafficking and sexual and other types of exploitation
Relevant NIF Indicator 5.1.4: Rate of crimes against women per 1,00,000 female population
Indicator Interpretation Higher value means lower performance (–)
No. of trained teachers* at secondary level
Total no. of teachers at secondary level
× 100
No. of cases registered under crime against women during reference year
Female population in the district (Census 2011)
× 10,000
183
METADATA
GOAL 5: GENDER EQUALITY Sex ratio at birth
Indicator Data Source Ministry of Health and Family Welfare [Health Management Information System]
Computation Approach Directly from data source
Data Period (Year) 2023–2024
Data Unit Female per 1,000 males
Districts Covered 119
Data Periodicity Annual
Relevant Global Target 5.1: End all forms of discrimination against all women and girls everywhere
Relevant NIF Indicator 5.1.3: Sex Ratio at Birth (per 1,000 male live births)
Indicator Interpretation Higher value means higher performance (+)
GOAL 5: GENDER EQUALITY Percentage of sexual crimes against women to total crimes against women
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
5.2: Eliminate all forms of violence against all women and girls in the public and private spheres,
including trafficking and sexual and other types of exploitation
Relevant Global Indicator
5.2.2: Proportion of women and girls aged 15 years and older subjected to sexual violence by
persons other than an intimate partner in the previous 12 months, by age and place of occurrence
Relevant NIF Indicator
5.2.2: Proportion of women and girls aged 18–49 years subjected to sexual violence by persons
other than an intimate partner in the previous 12 months
5.2.3: Per lakh women who have experienced sexual crimes during the year
(per 1,00,000 females)
Indicator Interpretation Higher value means lower performance (-)
GOAL 5: GENDER EQUALITY Unmet need for family planning for currently married women aged 15–49 years
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
5.6: Ensure universal access to sexual and reproductive health and reproductive rights as agreed
in accordance with the Programme of Action of the International Conference on Population and
Development and the Beijing Platform for Action and the outcome documents of their
review conferences
Relevant NIF Indicator
5.6.1: Unmet need for family planning for currently married women aged 15–49 years (in
percentage)
Indicator Interpretation Higher value means lower performance (–)
No. of cases registered under sexual crime against women during reference year
No. of cases registered under crime against women during reference year
× 100
1842023-24NER DISTRICT SDG INDEX
GOAL 5: GENDER EQUALITY Exclusive women Self-Help Groups (SHGs) in bank-linked SHGs
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 120
Data Periodicity Annual
Relevant Global Target
5.a: Undertake reforms to give women equal rights to economic resources, as well as access to
ownership and control over land and other forms of property, financial services, inheritance and
natural resources, in accordance with national laws
Relevant NIF Indicator 5.a.5: Exclusive women SHGs in bank-linked SHGs (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of rural population using an improved drinking water source
Indicator Data Source Department of Drinking Water and Sanitation, Ministry of Jal Shakti
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 6.1: By 2030, achieve universal and equitable access to safe and affordable drinking water for all
Relevant Global Indicator 6.1.1: Proportion of population using safely managed drinking water services
Relevant NIF Indicator 6.1.2: Percentage of population using an improved drinking water source (Rural)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of rural population getting safe and adequate drinking water within premises
through Piped Water Supply (PWS)
Indicator Data Source Department of Drinking Water and Sanitation, Ministry of Jal Shakti
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 6.1: By 2030, achieve universal and equitable access to safe and affordable drinking water for all
Relevant Global Indicator 6.1.1: Proportion of population using safely managed drinking water services
Relevant NIF Indicator
6.1.1: Percentage of households getting safe and adequate drinking water within premises
through Piped Water Supply (PWS)
Indicator Interpretation Higher value means higher performance (+)
No. of bank-linked women SHGs
Total no. of SHGs in the district
× 100
Total population having quality affected drinking water
Total population (Census 2011)
× 1001–((
Population having PWS (fully covered)
Total population (Census 2011)
× 100
185
METADATA
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of population living in households that use an improved sanitation facility
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant Global Indicator 6.2.1: Proportion of population using (a) safely managed sanitation services
Relevant NIF Indicator 6.2.1: Proportion of households having access to toilet facility (Urban & Rural), (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of individual household toilets constructed against target (SBM(G))
Indicator Data Source State
Computation Approach
Data Period (Year) 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant Global Indicator 6.2.1: Proportion of population using (a) safely managed sanitation services
Relevant NIF Indicator 6.2.1: Proportion of households having access to toilet facility (Urban & Rural), (in percentage)
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of schools with functional toilet facility for girls
Indicator Data Source
Ministry of Education
[Unified-District Information System for Education – Plus (UDISE+)]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant NIF Indicator 6.2.3: Proportion of schools with separate toilet facility for girls
Indicator Interpretation Higher value means higher performance (+)
Number of toilets constructed under SBM(G) during the reference year covered
Number of toilets targeted to be constructed under SBM(G) during the reference year
× 100
No. of school with functional toilet facility for girls
Total no. of schools in the district
× 100
1862023-24NER DISTRICT SDG INDEX
GOAL 6: CLEAN WATER AND
SANITATION
Percentage of GPs/villages verified as ODF (SBM(G)) in the district
Indicator Data Source
Ministry of Jal Shakti
[Swachh Bharat Mission Gramin Dashboard]
Computation Approach Directly from data source
Data Period (Year) As on 31 March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant NIF Indicator 6.2.2: Percentage of Districts achieving Open Defecation Free (ODF) target
Indicator Interpretation Higher value means higher performance (+)
GOAL 6: CLEAN WATER AND
SANITATION
Stage of groundwater extraction (%)
Indicator Data Source
Central Ground Water Board, Ministry of Jal Shakti
[National Compilation on Dynamic Ground Water Resources of India]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Percentage
Districts Covered 86
Data Periodicity Non-periodic
Relevant Global Target
6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure
sustainable withdrawals and supply of fresh-water to address water scarcity and substantially
reduce the number of people suffering from water scarcity
Relevant Global Indicator
6.4.2: Level of water stress: freshwater withdrawal as a proportion of available
freshwater resources
Relevant NIF Indicator 6.4.2: Percentage ground water withdrawal against availability
Indicator Interpretation Higher value means lower performance (–)
GOAL 7: AFFORDABLE AND CLEAN
ENERGY
Percentage of villages/GPs electrified
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 7.1: By 2030, ensure universal access to affordable, reliable and modern energy services
Relevant Global Indicator 7.1.1: Proportion of population with access to electricity
Relevant NIF Indicator 7.1.1: Percentage of households electrified
Indicator Interpretation Higher value means higher performance (+)
No. of village/GPs electrified
Total no. of villages/GPs
× 100
187
METADATA
GOAL 7: AFFORDABLE AND CLEAN
ENERGY
Percentage of households using clean fuel for cooking
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target 7.1: By 2030, ensure universal access to affordable, reliable and modern energy services
Relevant Global Indicator 7.1.2: Proportion of population with primary reliance on clean fuels and technology
Relevant NIF Indicator 7.1.2: Percentage of household using clean cooking fuel
Indicator Interpretation Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Percentage of loans disbursed to MSMEs against sanctioned
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.3: Promote development-oriented policies that support productive activities, decent job creation,
entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-,
small- and medium-sized enterprises, including through access to financial services
Relevant NIF Indicator 8.3.3: Outstanding Credit to MSME (in INR crore)
Indicator Interpretation Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Number of victims of human trafficking per 10,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and
human trafficking and secure the prohibition and elimination of the worst forms of child labour,
including recruitment and use of child soldiers, and by 2025 end child labour in all its forms
Relevant NIF Indicator 8.7.1: Human trafficking cases per 10,00,000 population
Indicator Interpretation Higher value means lower performance (–)
No. of loans disbursed to MSMEs
No. of loans sanctioned to MSMEs
× 100
Total no. of victims trafficked (male and female)
Total population (Census 2011)
× 10,000
1882023-24NER DISTRICT SDG INDEX
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Percentage of households covered with a bank account under Pradhan Mantri Jan Dhan Yojana
(PMJDY) against target
Indicator Data Source
Ministry of Finance
[Pradhan Mantri Jan Dhan Yojana – District-wise Household Report]
Computation Approach Directly from data source
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 94
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all
Relevant Global Indicator
8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution
or with a mobile money service provider
Relevant NIF Indicator
8.10.2: Number of accounts (including deposit and credit accounts) of scheduled commercial banks
per 1,000 population
Indicator Interpretation Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Number of bank branches including Business Correspondents (BCs) in Urban, Semi-urban and Rural
areas per 10,000 population
Indicator Data Source State
Computation
Approach
Data Period (Year) As on 31st March 2024
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage
and expand access to banking, insurance and financial services for all
Relevant Global Indicator 8.10.1: (a) Number of commercial bank branches per 10,000 adults
Relevant NIF Indicator 8.10.1: (a) Number of banking outlets per 100,000 population
Indicator
Interpretation
Higher value means higher performance (+)
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Automated Teller Machines (ATMs) per 10,000 population
Indicator Data Source Reserve Bank of India [Database on Indian Economy]
Computation Approach
Data Period (Year) As on31st March 2024
Data Unit Per 10,000 population
Districts Covered 114
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all
Relevant Global Indicator 8.10.1: (b) Number of ATMs per 100,000 adults
Relevant NIF Indicator 8.10.1: (b) ATMs per 100,000 population
Indicator Interpretation Higher value means higher performance (+)
No. of bank branches including BCs in Urban, Semi-urban and Rural areas
Total population (Census 2011)
× 10,000
Total no. of ATMs
Total population (Census 2011)
× 10,000
189
METADATA
GOAL 8: DECENT WORK AND
ECONOMIC GROWTH
Percentage of women account holders in Pradhan Mantri Jan Dhan Yojana (PMJDY)
Indicator Data Source Ministry of Finance [Pradhan Mantri Jan Dhan Yojana –District wise Household Report]
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to
banking, insurance and financial services for all
Relevant Global Indicator
8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution
or with a mobile money service provider
Relevant NIF Indicator 5.a.7: Percentage of women having an account at a formal financial institution
Indicator Interpretation Higher value means higher performance (+)
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Percentage of habitations with access to all weather roads under PMGSY and other State schemes
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.1: Develop quality, reliable, sustainable and resilient infrastruc-ture, including regional and
transborder infrastructure, to support economic development and human well-being, with a focus on
affordable and equitable access for all
Relevant Global Indicator 9.1.1: Proportion of the rural population who live within 2 km of an all-season road
Relevant NIF Indicator 9.1.1: Proportion of the rural population who live within 2 km of an all-season road
Indicator Interpretation Higher value means higher performance (+)
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Surfaced road as a percentage of total road length
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.1: Develop quality, reliable, sustainable and resilient infrastructure, including regional and
transborder infrastructure, to support economic development and human well-being, with a focus on
affordable and equitable access for all
Indicator Interpretation Higher value means higher performance (+)
PMJDY accounts opened by women
Total no. of PMJDY accounts
× 100
No. of habitations with access to all weather roads under PMGSY and other State schemes
Total no. of habitations
× 100
Total length of surfaced road in the district
Total length of road in the district
× 100
1902023-24NER DISTRICT SDG INDEX
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Percentage of GPs/villages with internet connection (broadband or cellular)
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.c: Significantly increase access to information and communications technology and strive to provide
universal and affordable access to the Internet in least developed countries by 2020
Relevant Global Indicator 9.c.1: Proportion of population covered by a mobile network, by technology
Relevant NIF Indicator 9.c.1: Number of Internet Subscription as percentage of total population
Indicator Interpretation Higher value means higher performance (+)
GOAL 9: INDUSTRY, INNOVATION
AND INFRASTRUCTURE
Percentage of villages covered by a mobile network
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
9.c: Significantly increase access to information and communications technology and strive to provide
universal and affordable access to the Internet in least developed countries by 2020
Relevant Global Indicator 9.c.1: Proportion of population covered by a mobile network, by technology
Indicator Interpretation Higher value means higher performance (+)
GOAL 10: REDUCED INEQUALI-
TIES
Percentage of women representatives in PRIs, ULBs, District Autonomous Councils, VCs, VECs
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 105
Data Periodicity Annual
Relevant Global Target
10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective
of age, sex, disability, race, ethnicity, origin, religion or economic or other status
Relevant NIF Indicator 10.2.2: Proportion of seats held by women in (a) national parliaments and (b) local governments,
Indicator Interpretation Higher value means higher performance (+)
No. of GPs/villages with internet connection (broadband or cellular)
Total no. of GPs/villages
× 100
No. of villages covered by a mobile network
Total no. of villages
× 100
No. of women representatives in PRIs, ULBs, District Autonomous Councils, VCs, VECs
Total no. of representatives in PRIs, ULBs, District Autonomous Councils, VCs, VECs
× 100
191
METADATA
GOAL 10: REDUCED IN-
EQUALITIES
Women offered employment as a percentage of total employment demanded by women under MGNREGA
Indicator Data Source Ministry of Rural Development [MGNREGA MIS Report]
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory
laws, policies and practices and promoting appropriate legislation, policies and action in this regard
Indicator InterpretationHigher value means higher performance (+)
GOAL 10: REDUCED IN-
EQUALITIES
Persons with Disabilities (PwDs) offered employment as a percentage of total employment demanded by
PwDs under MGNREGA
Indicator Data Source Ministry of Rural Development [MGNREGA MIS Report]
Computation
Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory
laws, policies and practices and promoting appropriate legislation, policies and action in this regard
Indicator
Interpretation
Higher value means higher performance (+)
GOAL 11: SUSTAINABLE
CITIES AND COMMUNITIES
Houses completed under Pradhan Mantri Awas Yojana (PMAY) and/or other schemes as a
percentage of net demand assessment (Urban)
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.1: By 2030, ensure access for all to adequate, safe and affordable housing and basic services and
upgrade slums
Indicator InterpretationHigher value means higher performance (+)
No. of women who were offered employment under MGNREGA during reference period
No. of women who demanded employment under MGNREGA during reference period
× 100
No. of persons with disability who were offered employment under MGNREGA during reference period
No. of persons with disability who demanded employment under MGNREGA during reference period
× 100
No. of houses constructed and completed under PMAY (Urban) and related State schemes
No. of houses sanctioned for construction under PMAY (Urban) and related State schemes
× 100
1922023-24NER DISTRICT SDG INDEX
GOAL 11: SUSTAINABLE
CITIES AND COMMUNITIES
Deaths due to road accidents per 1,00,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2022
Data Unit Per 1,00,000 population
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.2: By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all,
improving road safety, notably by expanding public transport, with special attention to the needs of those in
vulnerable situations, women, children, persons with disabilities and older persons
3.6: By 2020, halve the number of global deaths and injuries from road traffic accidents
Relevant Global Indicator3.6.1: Death rate due to road traffic injuries
Relevant NIF Indicator 3.6.1 & 11.2.2: People killed/injured in road accidents (per 100,000 population)
Indicator InterpretationHigher value means lower performance (-)
GOAL 11: SUSTAINABLE
CITIES AND COMMUNITIES
Percentage of wards with waste collection
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special
attention to air quality and municipal and other waste management
Relevant Global Indicator
11.6.1: Proportion of municipal solid waste collected and managed in controlled facilities out of total
municipal waste generated, by cities
Relevant NIF Indicator 11.6.2: Percentage of wards with 100% door-to-door waste collection
Indicator InterpretationHigher value means higher performance (+)
Deaths due to road traffic accidents during reference year
Total population of the district (census 2011)
× 1,00,000
Total no. of wards with waste collection
Total no. of wards
× 100
193
METADATA
GOAL 11: SUSTAINABLE CITIES AND
COMMUNITIES
Percentage of individual household toilets constructed against target (SBM(U))
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.1: By 2030, ensure access for all to adequate, safe and affordable housing and basic services
and upgrade slums
6.2: By 2030, achieve access to adequate and equitable sanitation and hygiene for all and end
open defecation, paying special attention to the needs of women and girls and those in vulnerable
situations
Relevant Global Indicator 6.2.1: Proportion of population using (a) safely managed sanitation services
Relevant NIF Indicator 6.2.1: Proportion of households having access to toilet facility (Urban and Rural)
Indicator Interpretation Higher value means higher performance (+)
GOAL 11: SUSTAINABLE CITIES AND
COMMUNITIES
Percentage of Municipal Solid Waste (MSW) treated out of total MSW generated
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 79
Data Periodicity Annual
Relevant Global Target
11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying
special attention to air quality and municipal and other waste management
Relevant Global Indicator
11.6.1: Proportion of municipal solid waste collected and managed in controlled facilities out of
total municipal waste generated, by cities
Relevant NIF Indicator 11.6.1: Percentage of waste processed
Indicator Interpretation Higher value means higher performance (+)
No. of IHHL units constructed
No. of IHHL units targeted to be constructed
× 100
Total MSW treated (tonnes/day)
Total MSW generated (tonnes/day)
× 100
1942023-24NER DISTRICT SDG INDEX
GOAL 12: SUSTAINABLE
CONSUMPTION AND PRODUCTION
Area under jhum cultivation as a percentage of total area under agriculture
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 92
Data Periodicity Annual
Relevant Global Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources
Indicator Interpretation Higher value means lower performance (–)
GOAL 12: SUSTAINABLE
CONSUMPTION AND PRODUCTION
Percentage of area under micro/minor irrigation in the district
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 12.2: By 2030, achieve the sustainable management and efficient use of natural resources
Indicator Interpretation Higher value means higher performance (+)
GOAL 12: SUSTAINABLE
CONSUMPTION AND PRODUCTION
Plastic waste generated per 10,000 population (tonnes/annum)
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Tonnes per 10,000 population per annum
Districts Covered 111
Data Periodicity Annual
Relevant Global Target
12.5: By 2030, substantially reduce waste generation through prevention, reduction, recycling
and reuse
Indicator Interpretation Higher value means lower performance (–)
Area under Jhum cultivation
Area under agriculture
× 100
Area under micro/minor irrigation in the district
Area under agriculture
× 100
Quantity of plastic waste generated during the reference year
Total population of the district (Census 2011)
× 10,000
195
METADATA
GOAL 13: CLIMATE ACTION Number of human lives lost due to natural calamity per 10,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) 2023
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target
13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters
in all countries
Relevant Global Indicator
13.1.1: Number of deaths, missing persons and directly affected persons attributed to disasters
per 1,00,000 population
Relevant NIF Indicator
13.1.1: Number of deaths, missing persons and directly affected persons attributed to disasters
per 1,00,000 population
Indicator Interpretation Higher value means lower performance (–)
GOAL 13: CLIMATE ACTION Change in forest area
Indicator Data Source Ministry of Environment Forest & Climate Change [Forest Survey of India 2023]
Computation Approach Directly from data source
Data Period (Year) 2021-23
Data Unit Square Kilometre
Districts Covered 119
Data Periodicity 2 years
Relevant Global Target
13.2: Integrate climate change measures into national policies, strategies and planning
15.2: By 2020, promote the implementation of sustainable management of all types of forests,
halt deforestation, restore degraded forests and substantially increase afforestation and
reforestation globally
Relevant NIF Indicator 15.2.1: Progress towards sustainable forest management
Indicator Interpretation
Districts with an increase/no change in area under forests have been awarded a score of 100
while districts with a decrease in area under forests have been assigned a score of 0
GOAL 13: CLIMATE ACTION Area under watershed management as a percentage of total geographical area
Indicator Data Source State
Computation Approach
Data Period (Year) 2023–2024
Data Unit Percentage
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters
in all countries
Indicator Interpretation Higher value means higher performance (+)
No. of deaths due to natural calamities during the reference year
Total population of the district (Census 2011)
× 10,000
Area covered under integrated watershed management in the district (sq. km)
Total geographical area of the district (sq. km)
× 100
1962023-24NER DISTRICT SDG INDEX
GOAL 15: LIFE ON LAND Forest cover as a percentage of total geographical area
Indicator Data Source Ministry of Environment, Forest & Climate Change [Forest Survey of India 2023]
Computation Approach Directly from data source
Data Period (Year) 2023
Data Unit Percentage
Districts Covered 121
Data Periodicity 2 years
Relevant Global Target
15.1: By 2020, ensure the conservation, restoration and sustainable use of terrestrial and inland
freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands,
in line with obligations under international agreements
Relevant Global Indicator 15.1.1: Forest area as a proportion of total land area
Relevant NIF Indicator 15.1.1: Forest cover as a percentage of total geographical area
Indicator Interpretation Higher value means higher performance (+)
GOAL 15: LIFE ON LAND Percentage of wasteland over total geographical area
Indicator Data Source
Department of Land Resources, Ministry of Rural Development & National Remote Sensing Centre,
Indian Space Research Organisation [Wastelands Atlas of India 2019]
Computation Approach
Total area under wasteland in the district
Total geographical area of the district
× 100
Total area under wasteland includes the following categories*:
Land with Dense Scrub
Land with Open Scrub
Shifting Cultivation - Current Jhum
Shifting Cultivation - Abandoned Jhum
Under-utilised/degraded forest (Scrub domain)
Under-utilised/degraded forest (Agriculture)
Degraded pastures/grazing land
Degraded land under plantation crop
Mining wastelands
Industrial wastelands
*Those categories (as classified in the Wasteland Atlas) which are predominantly due to human interventions and/or those that are
commonly found in the 8 States of the NER have been considered to estimate the numerator.
Data Period (Year) 2015-16
Data Unit Percentage
Districts Covered 90
Data Periodicity Non-periodic
Relevant Global Target
15.3: By 2030, combat desertification, restore degraded land and soil, including land affected by
desertification, drought and floods, and strive to achieve a land degradation-neutral world
Relevant Global Indicator 15.3.1: Proportion of land that is degraded over total land area
Relevant NIF Indicator 15.3.1: Proportion of land that is degraded over total land area
Indicator Interpretation Higher value means lower performance (–)
197
METADATA
GOAL 15: LIFE ON LAND Number of wildlife crime cases reported per 1,000 sq. km of forest area
Indicator Data Source State
Computation Approach
Data Period (Year) 2023
Data Unit Number per 1,000 sq. km of forest area
Districts Covered 115
Data Periodicity Annual
Relevant Global Target
15.7: Take urgent action to end poaching and trafficking of protected species of flora and fauna
and address both demand and supply of illegal wildlife products
15.c: Enhance global support for efforts to combat poaching and trafficking of protected species,
including by increasing the capacity of local communities to pursue sustainable
livelihood opportunities
Relevant Global Indicator 15.7.1 & 15.c.1: Proportion of traded wildlife that was poached or illicitly trafficked
Relevant NIF Indicator 15.7.1 & 15.c.1: Number of cases registered under the Wildlife Protection Act, 1972
Indicator Interpretation Higher value means lower performance (–)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Reported murders per 10,000 population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau – Crime in India 2022]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Per 10,000 population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 16.1: Significantly reduce all forms of violence and related death rates everywhere
Relevant Global Indicator 16.1.1: Number of victims of intentional homicide per 1,00,000 population, by sex and age
Relevant NIF Indicator 16.1.1: Number of victims of intentional homicide per 1,00,000 population
Indicator Interpretation Higher value means lower performance (−)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Cognizable crimes against children per 10,000 population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau – Crime in India 2022]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Per 10,000 child population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of children
Relevant NIF Indicator 16.2.1: Proportion of crime committed against children during the year (per lakh children)
Indicator Interpretation Higher value means lower performance (–)
No. of wildlife crime cases reported in the district during the reference period
Total forest area in the district (sq. km)
× 1,000
1982023-24NER DISTRICT SDG INDEX
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Number of missing children per 10,000 population
Indicator Data Source
Ministry of Home Affairs
[National Crime Records Bureau – Crime in India 2022]
Computation Approach Directly from data source
Data Period (Year) 2022
Data Unit Per 10,000 child population
Districts Covered 121
Data Periodicity Annual
Relevant Global Target 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of children
Relevant Global Indicator
16.2.2: Number of victims of human trafficking per 1,00,000 population by sex, age and form of
exploitation
Relevant NIF Indicator 8.7.2: Number of missing children
Indicator Interpretation Higher value means lower performance (–)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Ratio of working strength to sanctioned strength of Judges (District & Subordinate courts)
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Ratio
Districts Covered 118
Data Periodicity Annual
Relevant Global Target
16.3: Promote the rule of law at the national and international levels and ensure equal access to
justice for all
Relevant NIF Indicator 16.3.3: Number of Judges (all levels) per lakh population
Indicator Interpretation Higher value means higher performance (+)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Common Service Centres (CSCs) providing online services per 10,000 population
Indicator Data Source State
Computation Approach
Data Period (Year) As on 31st March 2024
Data Unit Per 10,000 population
Districts Covered 120
Data Periodicity Annual
Relevant Global Target 16.6: Develop effective, accountable and transparent institutions at all levels
Relevant NIF Indicator 16.6.3: Number of government services provided online to citizens
Indicator Interpretation Higher value means higher performance (+)
Working strength of judges in the district court and sub-ordinate courts
Sanctioned strength of judges in the district court and sub-ordinate courts
No. of CSCs in the district
Total population of the district (Census 2011)
× 10,000
199
METADATA
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Percentage of births registered
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target 16.9: By 2030, provide legal identity for all, including birth registration
Relevant Global Indicator
16.9.1: Proportion of children under 5 years of age whose births have been registered with a
civil authority, by age
Relevant NIF Indicator 16.9.1: Percentage of births registered
Indicator Interpretation Higher value means higher performance (+)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Percentage of population covered under Aadhaar
Indicator Data Source Unique Identification Authority of India Dashboard
Computation Approach Directly from data source
Data Period (Year) Data accessed as on July 2024
Data Unit Percentage
Districts Covered 82
Data Periodicity Live data
Relevant Global Target 16.9: By 2030, provide legal identity for all, including birth registration
Relevant NIF Indicator 16.9.2: Proportion of population covered under Aadhaar
Indicator Interpretation Higher value means higher performance (+)
GOAL 16: PEACE, JUSTICE AND
STRONG INSTITUTIONS
Percentage of deaths registered
Indicator Data Source Ministry of Health & Family Welfare [National Family Health Survey-5]
Computation Approach Directly from data source
Data Period (Year) 2019–2021
Data Unit Percentage
Districts Covered 104
Data Periodicity 3 years
Relevant Global Target 16.9: By 2030, provide legal identity for all, including birth registration
Relevant Global Indicator
17.19.2: Proportion of countries that (b) have achieved 100 percent birth registration and 80
percent death registration
Indicator Interpretation Higher value means higher performance (+)
2002023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of bene -
ficiaries
covered
under NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employ -
ment as a
percentage
of persons
who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses
completed
against
sanctioned
(rural +ur -
ban) under
PMAY and
related State
schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds
empanelled
under PM -
JAY or re -
lated State
schemes
per 10,000
eligible
population
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employment
as a per -
centage of
persons who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Arunachal Pradesh
Anjaw100.0013.0999.981.209.17100.0017.58.2310098991910013353
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang100.0014.3999.972.1742.4299.7140.510.49100959924210037460
Dibang Valley100.0010.1199.9914.294.90100.0028.733.62100100100145100251657
East Kameng100.0022.05100.005.470.0099.9425.112.00100761005010021551
East Siang100.008.11100.008.3396.00100.0030.530.49100100100896100271468
Kamle100.00Null99.991.1921.4399.23Null2.95100Null10012199Null054
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi100.0018.91100.0020.3669.0598.9724.03.331008410020699920062
Kurung Kumey100.0011.1499.988.8560.5899.0713.414.01100100100961998660
Leparada100.00Null100.007.749.2099.23Null20.16100Null1008999Null954
Lohit100.0012.39100.0014.7831.25100.0031.915.24100100100153110028660
Longding100.0020.9799.980.003.8797.4223.87.9510079100049719350
Lower Dibang Valley100.009.0899.998.9421.5199.5636.8
15.8710010010092210033759
Lower Siang100.00Null100.007.5185.1099.83Null8.44100Null100885100Null366
Lower Subansiri100.006.3995.7712.11117.7299.8424.519.9410010001210010020955
Namsai100.0022.1199.997.326.8299.2530.912.4810076100779927553
Pakke Kessang100.00Null100.008.370.00100.00Null16.18100Null10080100Null753
Papum Pare100.0013.7699.993.9933.1999.7026.957.2210097100433100232860
Shi Yomi100.00Null100.004.320.0099.68Null6.18100Null10040100Null251
Siang100.009.1599.894.1384.3885.6126.127.061001009848486221263
Tawang100.008.4699.932.9577.33100.0033.517.631001009837710030864
Tirap100.0014.7899.981.3666.6799.7530.84.51100949916710027161
Upper Siang100.008.7499.960.7589.0899.2734.616.98100100991899931766
Upper Subansiri100.0019.71100.003.7226.2899.3521.55.69100821004269917154
West Kameng100.004.7499.937.2373.61100.0038.315.811001009877410035765
West Siang100.0013.8599.939.5545.9899.6626.618.861009698104610022860
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa94.1115.6099.8918.3247.9681.4369.04.0557929718488167158
Barpeta94.6219.1299.9239.8770.7898.0058.912.1761839840719857564
Biswanath88.5022.0999.9134.7466.1778.6268.47.1516769835667967255
Bongaigaon92.8117.3999.9531.7269.3896.5157.612.9947889932699755561
201
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of bene -
ficiaries
covered
under NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employ -
ment as a
percentage
of persons
who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses
completed
against
sanctioned
(rural +ur -
ban) under
PMAY and
related State
schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds
empanelled
under PM -
JAY or re -
lated State
schemes
per 10,000
eligible
population
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count ratio
as per the
Multi-Di -
mensional
Poverty
Index
Persons
offered
employment
as a per -
centage of
persons who
demanded
employment
under
MGNREGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage
of house -
holds with
any usual
member
covered by
a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Cachar92.6030.5899.8444.4367.4389.7657.922.77465596446790551058
Charaideo92.4620.1099.9740.6478.3192.9064.94.1745819941789363163
Chirang94.2216.7999.8840.1584.8382.0561.54.0458899740858259164
Darrang92.0723.6599.9734.7946.2796.7853.78.4242729935469751356
Dhemaji93.6313.7399.9938.4846.3578.5666.89.53539710038467965360
Dhubri94.1726.0299.9135.9449.7196.3859.411.7857669836509657558
Dibrugarh90.7212.2699.9448.3677.9791.2858.853.333210099487891562666
Dima Hasao90.0213.6299.6922.1760.3284.1461.925.27279793226084601257
Goalpara92.2718.3499.8844.0951.9394.4171.112.6943859744529469561
Golaghat91.1914.6099.9640.1560.0282.7969.315.4035959940608368661
Hailakandi94.6836.2299.9237.7672.7891.0553.65.3761419838739151157
Hojai93.6314.1399.8944.7772.0593.2967.417.4953969745729366766
Jorhat92.0711.4999.8543.3665.5386.1460.116.83421009643668658762
Kamrup92.5012.7199.9637.2158.0593.9647.018.81
45999937589444861
Kamrup Metropolitan88.495.6399.8934.1146.6967.1245.5156.821610097344767427960
Karbi Anglong91.5916.2099.9841.9067.6589.3654.128.513891100426889511361
Karimganj93.0632.9399.9935.8180.4291.4464.49.55494910036809162359
Kokrajhar92.2018.9299.9933.4576.4488.8450.217.01438410033768947760
Lakhimpur91.8314.0699.9240.5669.4083.2867.015.4940969841698365662
Majuli91.7914.4199.9347.61100.9078.5260.88.67409598481007959365
Morigaon94.4922.4699.9630.8875.5787.1462.54.4260759931768760161
Nagaon93.5820.8499.8340.1664.1893.6459.414.2553799640649457661
Nalbari93.2711.2499.9639.3591.0990.7052.518.22511009939919150866
Sivasagar92.4510.2899.9743.1989.2485.2260.712.41451009943898558566
Sonitpur88.3219.9499.9139.2492.9685.1166.922.03148198399385651061
South Salmara-Mankachar95.6928.2499.7414.9382.5497.8268.23.6868619415839866061
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia91.2517.6699.9737.8362.5082.8060.012.9536879938638358559
Udalguri92.4719.1699.8625.8471.4074.9470.66.0545839726717569258
West Karbi Anglong86.3724.0999.8834.0630.7580.0963.112.710719734318061547
2022023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
men-
sional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual member
covered by a
health scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
Percentage
of bene -
ficiaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
mensional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percent -
age of
Self-
Help
Groups
(SHGs)
provided
credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual mem -
ber covered
by a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Manipur
Bishnupur100.006.9199.9750.9773.572.699.355.71100100995174342757
Chandel100.0014.7499.511.327.7817.8216.1750.85100948818181110053
Churachandpur100.0015.3599.9716.1128.8811.7218.21928.3510093991629121410058
Imphal East100.005.1999.9297.4370.988.357.0548.901001009897718210072
Imphal West100.002.12100.009.0198.688.3015.7516.6010010010099981110066
Jiribam100.00Null100.0076.9216.281.54Null2906.98100Null10077162Null10066
Kakching100.00Null99.9828.4473.041.26Null688.51100Null9928731Null10067
Kamjong100.00Null99.903.603.40NullNull369.69100Null9843NullNull10061
Kangpokpi100.00Null99.8114.2921.720.00Null166.26100Null9614220Null8453
Noney100.00Null99.6721.112.34NullNull322.06100Null92212NullNull10063
Pherzawl100.00Null98.990.001.7310.93Null1302.08100Null760211Null10048
Senapati100.0015.6099.9920.008.820.0015.4485.271009210020901110054
Tamenglong100.0018.50100.008.283.342.9716.8493.10100851008331210051
Tengnoupal100.00Null99.8434.208.3012.22Null404.17
100Null9634812Null10059
Thoubal100.007.4699.9970.3386.2519.3519.1206.601001001007086191410074
Ukhrul100.0017.8799.9540.3211.69Null17.0632.4110086994012Null1210064
Meghalaya
East Garo Hills100.0014.9699.9234.75166.7638.0771.925.5810094983510038701268
East Jaintia Hills100.0043.79100.0059.6673.0227.5974.116.191002210060732873758
East Khasi Hills100.0024.10100.0056.9572.5023.9047.171.6610071100577224443563
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
North Garo Hills100.0013.2699.9640.7242.2629.1660.811.67100989941422959459
Ri Bhoi100.0031.6799.9576.46113.8634.2866.820.131005299761003465967
South Garo Hills100.009.77100.0058.1614.0312.6479.520.4810010010058141378959
South West Garo Hills100.0018.2799.9841.7495.6722.9775.112.361008510042962374565
South West Khasi Hills100.0040.9899.9964.26216.4437.5772.319.5210029100641003871964
West Garo Hills100.008.0099.9837.8947.8830.1777.930.9710010099384830771463
West Jaintia Hills100.0052.0899.9974.53236.3134.4765.626.3510011007510034641261
West Khasi Hills100.0052.4899.9869.716.1747.1560.121.7910009970647581049
Mizoram
Aizawl100.000.87100.007.7459.5595.6537.539.2510010010086096341964
Champhai100.001.5199.9016.5235.6479.4064.915.241001009817367963662
Hnahthial100.00Null100.004.170.0083.73Null141.19100Null1004084Null7160
Khawzawl100.00Null100.0015.1416.9859.66Null160.43100Null100151760Null8162
Kolasib100.005.2599.9812.7222.7995.1861.117.2710010010013239559762
Lawngtlai100.0021.63100.005.4211.9880.0231.323.651007710051280271152
203
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE I: PERFORMANCE OF DISTRICTS ON SDG 1
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
benefi -
ciaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
men-
sional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percentage
of Self-Help
Groups
(SHGs) pro -
vided credit
linkage
Percentage of
women receiv -
ing benefits
under PMMVY
or any other
maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual member
covered by a
health scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
Percentage
of bene -
ficiaries
covered
under
NFSA
Head
count
ratio as
per the
Multi-Di -
mensional
Poverty
Index
Persons
offered em -
ployment as a
percentage of
persons who
demanded
employment
under MGN -
REGA
Percent -
age of
Self-
Help
Groups
(SHGs)
provided
credit
linkage
Percentage
of women
receiving
benefits under
PMMVY or any
other maternity
related State
schemes
against target
Percentage
of affordable
houses com -
pleted against
sanctioned
(rural +urban)
under PMAY
and related
State schemes
Percentage of
households
with any
usual mem -
ber covered
by a health
scheme
or health
insurance
Hospital
beds empan -
elled under
PMJAY or
related State
schemes
per 10,000
eligible
population
SDG 1
Lunglei100.005.1599.984.8718.2193.0146.522.911001009951893431059
Mamit100.009.29100.0012.8733.7472.5561.713.6510010010013347360661
Saitual100.00Null100.0019.8238.3975.29Null216.88100Null100203875Null10072
Serchhip99.123.3099.9916.1846.7482.9158.821.159410010016478356963
Siaha99.926.90100.0010.9449.5889.5144.228.9199100100115090411363
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur100.007.2399.3592.54104.9819.865.780.0610010085931002004067
Kiphire100.0028.1999.3095.55100.0051.238.841.651006183961005142064
Kohima100.006.5099.65100.00124.1413.3826.782.451001009210010013234171
Longleng100.0026.9099.9196.6295.617.6638.328.08100649897968351364
Mokokchung100.007.2299.93100.00146.9087.2622.347.341001009810010087182378
Mon100.0022.9599.8585.5475.4359.3539.321.591007496867559361067
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNull
NullNullNullNullNullNullNullNull*
Peren100.0017.4698.8577.2079.9012.985.434.67100877377801301656
Phek100.0017.2899.3096.33100.8011.5924.932.0710088839610012211564
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang100.0029.2199.89100.0078.3762.1422.038.1210058981007862181866
Wokha100.0011.99100.00100.0080.4316.0120.640.061001001001008016161966
Zunheboto100.0020.3199.9791.4477.9516.8818.122.901008099917817131061
Sikkim
Gangtok100.002.1299.9815.09Null96.2029.9592.121001009915Null962610077
Gyalshing100.002.7799.9919.73Null98.8819.944.5210010010020Null99152165
Mangan100.005.1799.8712.59Null100.0024.533.141001009713Null100201664
Namchi100.002.9099.9929.16Null94.8520.866.5010010010029Null95163368
Pakyong100.00Null100.0027.72Null95.74Null20.79100Null10028Null96Null967
Soreng100.00Null99.9926.28Null99.75Null4.36100Null10026Null100Null165
Tripura
Dhalai100.0021.8999.9963.3434.7294.1544.229.8910076100633594411465
Gomati100.009.06100.0071.0850.6891.9629.920.6510010010071519226969
Khowai100.0017.2799.9953.2541.5893.3944.123.1210088100534293411066
North Tripura100.0017.8599.9952.9345.1497.5928.720.061008610053459825964
Sepahijala100.0012.2799.9955.4253.2595.7031.616.3510010010055539628767
South Tripura100.0011.8999.9980.5255.3190.2237.328.32100100100815590341372
Unakoti100.0024.9299.9968.9950.5898.0028.020.541006910069519824965
West Tripura100.006.0099.9958.0265.2494.9828.184.79100100100586595244273
Target10012.43100.00100.00100100.00100196.89100100
100100100100100100100
2042023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of Fair Price
Shop (FPS)
covered
under online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
Percentage
of Fair Price
Shop (FPS)
covered un -
der online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Arunachal Pradesh
Anjaw100.00100.0077.8423.616.019.757.11683.893705.05100100751007310047272272
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang98.06100.0070.7026.325.060.665.33368.056139.40971006793553135783666
Dibang Valley100.00100.0094.1216.916.039.088.61800.943885.711001009310073731312366
East Kameng53.81100.0053.9335.714.213.151.72024.784502.533810048667710055372761
East Siang95.70100.0086.1024.610.332.851.52783.915573.62941008497858556603377
Kamle82.61100.0057.69NullNullNullNull2900.903681.617710053NullNullNullNull642263
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi82.61100.0062.9228.814.52.062.03005.983777.147710059867610040672270
Kurung Kumey66.67100.0053.8529.213.9Null62.43000.003651.0156100488478Null40672262
Leparada97.44100.0054.79NullNullNullNull2514.314373.249710049NullNullNullNull522665
Lohit100.00100.0088.2424.512.933.252.53199.415920.861001008798808454733579
Longding82.81100.0046.8815.813.819.138.42639.531932.3777100411007810075561171
Lower Dibang Valley90.91100.0079.89
14.39.719.651.52472.245121.2788100771008610056513076
Lower Siang74.36100.0047.39NullNullNullNull2358.634992.586610041NullNullNullNull472957
Lower Subansiri85.19100.0054.9530.78.122.152.43098.484777.398010050808910054702872
Namsai85.19100.0061.8828.717.752.659.23418.56662.6980100578670474479463
Pakke Kessang100.00100.0080.18NullNullNullNull2046.634379.1210010078NullNullNullNull382668
Papum Pare97.70100.0068.7729.715.618.653.43028.315366.889710065837410053673275
Shi Yomi92.00100.0053.96NullNullNullNull2501.283435.488910048NullNullNullNull522062
Siang74.26100.0063.0121.38.815.424.93220.385343.7966100591008810094733279
Tawang100.00100.0068.5330.49.057.489.62966.395002.20100100658187370663063
Tirap91.89100.0061.6038.616.024.148.42189.174322.868910057587310060422667
Upper Siang97.06100.0071.7930.412.022.451.02947.194673.129610068818110056652875
Upper Subansiri74.65100.0056.1836.819.237.960.43164.852704.78661005163677543711661
West Kameng89.33100.00100.0024.213.418.266.62775.305041.8086100100997910034603076
West Siang88.44100.0069.9224.516.216.845.62529.144750.008510066987310064522874
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa100.00100.0041.2541.234.065.378.62575.8311695.271001003450382216546954
Barpeta100.00100.0086.7429.826.247.663.52812.0913548.741001008583535738618073
Biswanath100.00100.0058.5142.741.045.179.82549.2213290.681001005446246114537959
Bongaigaon100.00100.0096.1346.235.351.277.22845.8512922.071001009636355018627664
205
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage
of Fair Price
Shop (FPS)
covered
under online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
Percentage
of Fair Price
Shop (FPS)
covered un -
der online
transaction
system for
PDS in the
District
Percentage
of anganwa -
di centres in
the district
with anthro -
pometric
measure -
ment devic -
es (height,
weight
measure -
ment)
Percentage
of anganwa -
dis with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years who
are under -
weight
Percentage
of pregnant
women
aged 15-49
years who
are anaemic
(<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0
g/dl)
Average
yield of rice
(kg/ha)
Productivity
of fruits and
vegetables
(kg/ha)
SDG 2
Cachar100.00100.0046.3328.738.244.061.82094.9713818.731001004086296341398264
Charaideo100.00100.0090.8739.034.861.669.72539.7616601.311001009057362929539866
Chirang100.00100.0016.5042.739.754.170.42715.0112335.75100100746264428587354
Darrang100.00100.0079.5242.033.151.666.82872.1112639.941001007748394933637565
Dhemaji100.00100.0067.4437.225.761.773.12176.9413281.691001006462542924427861
Dhubri100.00100.0093.4448.537.869.773.13102.6714978.671001009330301424708961
Dibrugarh100.00100.0096.5127.332.047.266.42762.6812054.571001009690425734597172
Dima Hasao100.00100.0034.2630.621.743.373.12258.6416296.441001002680626524449666
Goalpara100.00100.0098.4738.935.449.260.72949.6113992.901001009857355342658370
Golaghat100.00100.0083.0426.325.576.775.12764.5414632.76100100819354021598666
Hailakandi100.00100.0052.9842.942.458.759.52728.6315746.561001004746213544589360
Hojai100.00100.0060.2639.328.451.456.83407.3314419.931001005656494948798569
Jorhat100.00100.0076.9838.733.256.474.12911.8815206.281001007458393923649065
Kamrup100.00100.0085.4422.6
19.766.572.92959.4713682.3810010084100662024658171
Kamrup Metropolitan100.00100.0065.8925.425.056.480.42988.2014834.211001006295553913668869
Karbi Anglong100.00100.0040.3131.628.242.167.52577.7715147.701001003378496732549067
Karimganj100.00100.0081.7729.152.941.964.12050.8513836.29100100808506837388265
Kokrajhar100.00100.0026.4434.635.259.574.72120.0613083.621001001869353322407755
Lakhimpur100.00100.0030.7638.534.442.369.31962.7810865.451001002358376730356457
Majuli100.00100.0079.2635.422.2Null73.02523.8712931.75100100776761Null24527670
Morigaon100.00100.0088.5443.230.548.053.32853.5014410.951001008745455653628570
Nagaon100.00100.0099.7338.932.462.468.62515.2913193.3310010010057412831527865
Nalbari100.00100.0059.2327.526.753.271.02681.4312661.171001005489524627577567
Sivasagar100.00100.0090.7226.125.954.367.52644.5115750.141001009093544332569373
Sonitpur100.00100.0073.6736.721.947.369.42940.9310301.631001007163625729656168
South Salmara-Mankachar100.00100.0073.4538.927.937.669.63012.0113865.111001007057507629678270
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia100.00100.0091.2932.832.271.766.41805.5112559.031001009074411034317462
Udalguri100.00100.0030.7333.832.563.977.62594.0011806.951001002371412517547056
West Karbi Anglong100.00100.0039.7940.931.138.879.02523.5414336.271001003351437415528561
2062023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage of
pregnant wom -
en aged 15-49
years who
are anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Average
yield of
rice (kg/
ha)
Produc -
tivity of
fruits and
vegetables
(kg/ha)
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percent -
age of
children
under age
5 years
who are
stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage
of pregnant
women aged
15-49 years
who are anae -
mic (<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Aver -
age
yield
of rice
(kg/
ha)
Produc -
tivity of
fruits
and veg -
etables
(kg/ha)
SDG 2
Manipur
Bishnupur100.00100.0032.9215.511.739.042.41983.485260.5410010025100827369363168
Chandel100.00100.0013.4734.014.720.342.41621.359914.791001003717610069255967
Churachandpur100.00100.0027.5325.19.851.841.11208.4010859.681001001996864871136466
Imphal East100.00100.0019.5518.414.427.450.32208.8913080.3810010010100779657437773
Imphal West100.00100.0026.6215.610.239.541.81646.3912573.5010010018100857270267472
Jiribam100.00100.0010.61NullNullNullNull1528.7419490.641001000NullNullNullNull2210064
Kakching100.00100.0041.48NullNullNullNull4642.7910839.9710010035NullNullNullNull1006480
Kamjong100.00100.0015.83NullNullNullNull1517.4111494.341001006NullNullNullNull226859
Kangpokpi100.00100.0017.89NullNullNullNull1772.3712411.141001008NullNullNullNull307362
Noney100.00100.0035.16NullNullNullNull798.679397.2110010027NullNullNullNull05657
Pherzawl100.00100.0018.06NullNullNullNull1285.8411664.231001008NullNullNullNull156958
Senapati100.00100.0027.8027.312.918.348.51771.5410814.5610010019908010060306471
Tamenglong100.00100.0031.7727.119.331.437.0783.9211224.13100100249067887706668
Tengnoupal100.00100.0023.87NullNullNullNull1620.3311441.45
10010015NullNullNullNull256862
Thoubal100.00100.0026.2931.514.932.039.74561.6311236.4810010018787687731006677
Ukhrul100.00100.0026.5727.116.025.734.61528.2310433.221001001890739980226272
Meghalaya
East Garo Hills99.68100.0029.6139.726.529.128.01939.8213378.641001002155529290357969
East Jaintia Hills100.00100.0046.5549.823.646.547.22201.005071.601001004026585962433057
East Khasi Hills90.20100.0052.8044.623.843.739.01947.0112177.38871004741586474357264
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
North Garo Hills100.00100.0067.5635.615.840.830.22741.7112229.381001006466747087597277
Ri Bhoi25.00100.0064.2342.529.665.045.73369.2212465.7301006047462364787455
South Garo Hills76.62100.0031.7229.820.833.733.62174.549537.71691002483648382425667
South West Garo Hills100.00100.0049.5332.226.437.835.53345.2810163.921001004476537679776074
South West Khasi Hills100.00100.0070.9551.427.663.261.31870.1112106.561001006822502641337257
West Garo Hills51.68100.0064.1839.526.326.730.23018.029266.21361006055539787675568
West Jaintia Hills98.67100.0075.2348.728.364.654.61885.889414.23981007229492351335657
West Khasi Hills100.00100.0075.4959.031.149.656.21910.9018165.161001007304353493410061
Mizoram
Aizawl99.31100.00100.0025.39.633.444.01216.485895.389910010095868466133575
Champhai100.00100.00100.0027.213.115.738.32994.005689.78100100100907910075663483
Hnahthial100.00NullNullNullNullNullNull1283.5535993.36100NullNullNullNullNullNull1510072
Khawzawl100.00NullNullNullNullNullNull1792.298034.36100NullNullNullNullNullNull304759
Kolasib100.00100.00100.0030.412.643.853.81865.344783.7310010010081806452322871
Lawngtlai89.93100.00100.0032.716.946.555.3
1775.52418.94871001007572595030264
Lunglei89.19100.00100.0026.511.127.545.71521.992729.038610010092839664221673
Mamit100.00100.00100.0026.413.929.945.51279.8247.221001001009278916415071
207
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE II: PERFORMANCE OF DISTRICTS ON SDG 2
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percentage
of children
under age
5 years who
are stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage of
pregnant wom -
en aged 15-49
years who
are anaemic
(<11.0 g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Average
yield of
rice (kg/
ha)
Produc -
tivity of
fruits and
vegetables
(kg/ha)
Percentage of
Fair Price Shop
(FPS) covered
under online
transaction
system for PDS
in the District
Percentage of
anganwadi centres
in the district with
anthropometric
measurement devic -
es (height, weight
measurement)
Percent -
age of an -
ganwadis
with own
buildings
Percent -
age of
children
under age
5 years
who are
stunted
Percentage
of children
under age
5 years
who are
under -
weight
Percentage
of pregnant
women aged
15-49 years
who are anae -
mic (<11.0
g/dl)
Percentage
of children
aged 6-59
months who
are anaemic
(<11.0 g/dl)
Aver -
age
yield
of rice
(kg/
ha)
Produc -
tivity of
fruits
and veg -
etables
(kg/ha)
SDG 2
Saitual100.00NullNullNullNullNullNull1417.273.11100NullNullNullNullNullNull19040
Serchhip100.00100.00100.0031.814.443.443.21667.2214927.1310010010077776568278878
Siaha92.31100.00100.0043.817.630.046.41504.392306.739010010043709163221466
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur100.00100.0051.6228.329.832.948.93063.151274.50100100468746855968867
Kiphire100.00100.0082.8436.925.019.555.22354.4910058.1010010081635510050475973
Kohima100.00100.0064.9728.322.13.938.42922.868920.6510010061876110075645378
Longleng100.00100.0060.4934.125.730.540.42375.1914054.251001005671549072488375
Mokokchung100.00100.0052.0031.422.911.535.52462.857945.1210010046786010079504773
Mon100.00100.0063.0335.523.327.039.42286.049398.801001005967599773455673
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren100.00100.0061.8334.920.726.451.02825.7910968.161001005768649856616574
Phek100.00100.0074.4928.015.618.244.92981.2611699.58
10010071887410065666982
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang100.00100.0059.5637.134.220.038.82413.691805.2210010055623710074491165
Wokha100.00100.0051.6826.328.029.845.42554.7510163.721001004693509164536073
Zunheboto100.00100.0060.5744.044.540.834.92412.067469.681001005642177080494462
Sikkim
Gangtok97.44100.0061.2417.813.0Null49.81817.763581.95971005710079Null58312168
Gyalshing97.47100.0071.6025.219.3Null67.11974.684089.9297100689667Null33362465
Mangan94.52100.0091.0531.815.326.953.51511.383314.35931009077759753222069
Namchi99.42100.0079.5224.87.2Null56.51968.034116.2499100779791Null48362472
Pakyong95.81100.0083.02NullNullNullNull1872.173614.619410081NullNullNullNull332166
Soreng95.63100.0085.06NullNullNullNull1971.433674.099410083NullNullNullNull362267
Tripura
Dhalai100.00100.0087.2145.727.675.481.22882.8014227.35100100863850312638460
Gomati100.00100.0094.8822.729.052.870.73334.5915358.7310010094100484628779176
Khowai100.00100.0091.6147.024.763.773.43314.3116965.5610010091345625247610067
North Tripura100.00100.0088.8826.232.255.352.53011.2015956.841001008893414254679475
Sepahijala100.00100.0093.3534.521.055.872.13497.0215611.761001009369634126819274
South Tripura100.00100.0094.6325.521.657.159.63455.8816590.631001009495623844809879
Unakoti100.00100.0091.7831.832.076.762.83263.6317362.301001009177420397410069
West Tripura100.00100.0086.0530.321.256.254.53386.4314992.471001008481634051788976
Target100100100.0023.72.625.221
411416919.32100100100100100100100100100100
2082023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Arunachal Pradesh
Anjaw41.9178.3365.850.001.890.00Null4.724.720.0028.3540645710060100Null988306367
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang43.9190.8783.640.971.010.51120.728.770.670.0012.554285791003289100911202860
Dibang Valley3.0393.7576.740.003.750.00102.7412.490.000.0066.2209071100100100100850010068
East Kameng111.3999.3993.180.002.060.08179.521.590.001.5919.38100999110066981001000434376
East Siang86.86100.0098.7212.351.950.4988.1030.621.392.7847.8886100989862908755247510080
Kamle23.5376.1238.780.001.800.00Null9.020.000.0021.20216123
10058100Null91004750
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi70.5580.4631.610.000.860.00Null0.000.000.0013.7070681410027100Null100003051
Kurung Kumey72.36100.0090.770.000.880.00425.000.000.000.0013.44711008810028100100100003065
Leparada41.7698.9689.370.002.480.05Null4.960.000.0028.784098871007999Null98006466
Lohit76.8799.1598.7419.131.611.0583.1020.092.012.0121.50769998895178817335544871
Longding36.7675.4987.515.250.530.00Null1.770.000.0012.8935608410017100Null100002852
Lower Dibang Valley51.5099.3086.992.161.480.52Null7.400.001.8524.785099841004789Null940505567
Lower Siang32.0098.9961.9012.662.300.14Null27.570.000.0036.76309852987397Null60008259
Lower Subansiri38.0898.0432.2710.911.890.02102.702.360.002.3640.1436971410060991001000648969
Namsai80.4397.92105.117.610.833.7696.676.251.041.0413.7680971001002720969518283063
Pakke Kessang15.00100.0036.040.003.310.00Null16.530.000.0041.331210019100100100Null78009260
Papum Pare45.8899.96113.064.621.811.5754.1731.710.570.5741.40441001001005867485310159263
Shi Yomi18.7984.2183.0222.221.500.00Null7.510.000.0023.291674798548100Null93005255
Siang21.9078.3370.440.002.190.00Null9.400.000.0032.8919646310070100Null90007358
Tawang44.8581.3772.6015.222.200.02115.152.000.002.0022.6043696594701001001000545068
Tirap64.4681.0280.660.000.900.5289.517.231.810.0021.86636976100298988943204863
Upper Siang67.6199.2285.5811.172.270.06
90.240.002.832.8340.7767998210072998910050779184
Upper Subansiri71.85100.0039.120.001.040.29194.3410.450.001.3124.1771100231003394100880355464
West Kameng68.7899.0879.752.601.530.09118.1812.750.001.2720.146898741004998100850344568
West Siang74.4499.7489.668.221.520.17113.271.901.901.9026.477410087100499610010033515977
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa87.1699.9868.6528.660.590.00116.075.890.000.118.148710060771910010096031860
Barpeta91.4999.7685.119.920.350.03111.606.550.180.188.449110081100119910095351864
Biswanath95.0199.96100.849.100.590.01Null21.220.000.4910.539510010010019100Null710132362
Bongaigaon90.9699.9372.787.610.690.09112.7225.040.140.277.359110066100229810064271661
209
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mortality
Rate
Number
of
functional
new born
facilities
(SNCU,
NBSU,
NBCC)
per
10,000
popula -
tion
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percent -
age of
TB cases
suc-
cessfully
treated
among
TB cases
notified
to the
national
health
authori -
ties
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number
of de-ad -
diction
centres
(public
and pri -
vate) per
1,00,000
popula -
tion
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Cachar91.0699.72106.974.160.400.02112.224.660.630.127.229110010010013100100981131666
Charaideo92.22100.0066.7313.350.350.01Null16.570.440.227.9292100589711100Null78861757
Chirang84.4191.3278.439.060.830.04106.9318.250.000.218.15848673100279910076061861
Darrang95.0899.9977.276.700.590.06110.3413.460.650.329.9995100711001999100841192264
Dhemaji90.3699.9682.407.500.640.03111.2410.061.460.449.11901007810020991008926122067
Dhubri92.5285.3395.219.720.490.01107.1011.330.140.147.669276941001610010087341763
Dibrugarh91.5799.9681.235.850.340.05115.6110.560.230.158.609110076100
119910088441963
Dima Hasao62.3283.8968.328.390.980.01112.742.340.470.4717.33617460100311001001008133862
Goalpara92.3599.9286.129.070.780.07113.758.230.200.308.909210082100259810092381966
Golaghat93.1799.9472.9816.980.520.06114.136.470.280.288.45931006692179910095581863
Hailakandi90.1098.5799.746.650.650.05116.079.860.150.157.959098100100219910089341765
Hojai96.0797.2496.834.870.350.03Null8.700.210.324.089695961001199Null9149961
Jorhat84.2299.9993.7311.620.480.05117.048.000.220.2210.68841009299159910093462365
Kamrup93.5199.9587.4110.830.490.12119.2818.190.590.669.68931008410016981007610182165
Kamrup Metropolitan132.4899.78121.984.390.260.31121.4424.485.260.329.72100100100100893100659292172
Karbi Anglong71.8597.0193.936.610.860.05112.200.000.150.009.207195921002899100100302064
Karimganj92.3797.3188.917.100.470.05119.833.420.490.086.449296861001599100100921465
Kokrajhar86.4499.0376.5710.810.560.04112.381.690.000.2310.268698701001899100100062364
Lakhimpur94.9199.9984.676.680.580.02111.525.661.060.108.89951008110018100100961931966
Majuli92.9699.29108.4817.050.780.02Null4.780.000.6014.2993991009225100Null980163265
Morigaon82.9098.5085.129.120.610.06111.2325.280.100.108.18829881100199910064231861
Nagaon89.4498.4480.105.240.410.24107.676.130.210.218.60899775100139510096461963
Nalbari91.99100.0091.237.670.480.06110.231.300.130.3912.23921008910015991001002112767
Sivasagar92.7399.9765.4214.160.350.13113.69
38.130.290.4311.659310056961197100435122658
Sonitpur83.8998.1173.464.970.270.03112.830.000.460.155.79839766100999100100841362
South Salmara-Mankachar83.1975.3470.608.760.340.00Null3.060.180.003.7383606310011100Null10030853
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia95.8299.4579.296.440.480.01120.157.611.050.386.21969974100151001009318101365
Udalguri86.2899.7265.3222.290.570.02112.3814.430.000.248.398610056851810010082061859
West Karbi Anglong62.2769.4587.297.250.950.01Null3.050.000.347.8961508410030100Null100091755
2102023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully
immu -
nized
Infant
Mortality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by
skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mor-
tality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Manipur
Bishnupur118.6398.0494.993.030.290.0961.542.532.530.4210.0710097941009985710044112267
Chandel23.4296.8083.2316.000.480.3680.490.001.201.2020.702195799315927810021324661
Churachandpur50.3895.66118.6434.970.170.7687.690.001.291.7213.014993100685848610023462962
Imphal East27.1199.8984.254.850.290.3384.900.735.090.9723.0925100801009938310089265169
Imphal West135.1299.9381.623.520.150.4762.331.935.601.3526.29100100771005905810098375875
Jiribam3.2568.7527.050.000.460.0795.454.562.280.006.160498100159995984001347
Kakching43.3882.8484.280.000.270.0579.810.692.060.6912.484272801009997710036192760
Kamjong40.5557.0743.5020.730.210.0811.110.002.070.006.01393029877980
1003601340
Kangpokpi22.2174.8739.902.680.260.1070.500.520.520.005.8820592410089867100901345
Noney64.3966.8665.140.000.590.0281.820.001.970.0011.2063465610019100801003402557
Pherzawl60.9285.5020.8915.380.240.00Null0.002.420.006.0560760948100Null1004201349
Senapati38.2888.65201.650.490.350.1690.730.000.700.358.9736811001001197901001292060
Tamenglong35.3962.3694.3929.980.450.0168.750.000.001.1110.033338937514100651000302252
Tengnoupal34.1292.6730.720.000.000.0067.573.301.650.0013.533288121000100641002903050
Thoubal73.9299.3094.130.000.250.0881.870.363.260.3623.707399931008988010057105370
Ukhrul37.7284.0963.610.000.220.4970.830.000.740.7411.423674541007906710013202553
Meghalaya
East Garo Hills71.4177.97101.7316.430.890.0587.012.060.006.8619.1471641009328998510001004271
East Jaintia Hills43.3482.16110.3522.990.731.7092.824.070.006.5114.154271100842364929901003164
East Khasi Hills90.6881.5976.5528.810.440.8585.046.420.614.6018.509070707614828395111004167
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
North Garo Hills84.6566.7485.6125.140.760.0181.882.320.006.9710.8184458281241008010001002465
Ri Bhoi83.4265.1395.6420.860.580.3189.507.340.775.0210.748343948719938894141002467
South Garo Hills64.2555.58104.3220.240.910.0288.157.030.005.6213.7763271008829100879401003065
South West Garo Hills92.6787.75109.0429.160.680.0292.619.010.006.2012.5092801007622100929101002871
South West Khasi Hills60.5439.09104.9433.910.500.0681.5514.120.00
17.1414.52590100701699798201003258
West Garo Hills72.9468.4185.1624.310.450.0788.117.520.214.0812.65724881821499879341002864
West Jaintia Hills34.3874.26124.6917.550.511.6687.009.920.376.2516.243258100911665858961003662
West Khasi Hills91.2270.23106.8119.981.370.1492.9911.120.655.8917.7391511008844979287111003973
Mizoram
Aizawl89.7299.92135.2617.610.331.4985.5516.871.910.5434.7889100100911068847833157768
Champhai77.0198.2897.0910.322.780.7791.725.561.391.3922.397697961008984919724385076
Hnahthial75.9897.9199.7016.742.810.35Null28.080.003.5129.147597100929093Null590956576
Khawzawl66.8898.5177.5818.591.360.49Null32.550.000.0022.78669872904390Null52005056
Kolasib69.1297.0799.2314.230.950.1893.339.532.382.3819.53689599963096939042644374
Lawngtlai46.1473.3074.2017.311.700.1471.4313.570.000.8511.6244566792549768830232655
Lunglei62.5482.9787.9310.421.590.0888.814.550.000.7623.76617285100519887980215366
211
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE III: PERFORMANCE OF DISTRICTS ON SDG 3
RAW VALUESINDEX SCORE (Normalised values)
District
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully
immu -
nized
Infant
Mortality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
Percent -
age of
pregnant
women
who com -
pleted
4 ANCs
in the
district
Percent -
age of
births
attended
by
skilled
health
person -
nel
Percent -
age of
children
aged
9-11
months
fully im -
munized
Infant
Mor-
tality
Rate
Number of
functional
newborn
facilities
(SNCU,
NBSU,
NBCC) per
10,000
population
Number
of new
HIV infec -
tions per
1,000
unin -
fected
popula -
tion
Percentage
of TB cases
successfully
treated
among TB
cases notified
to the na -
tional health
authorities
Number
of suicide
deaths
reported
per
1,00,000
popula -
tion
Number of
de-addic -
tion centres
(public and
private) per
1,00,000
population
First
Referral
Units
(FRUs)
per
1,00,000
popula -
tion
Total phy -
sicians,
nurses
and mid -
wives per
10,000
popula -
tion
SDG 3
Mamit60.1179.0885.927.851.850.09225.588.110.002.3219.575966821005998100920634369
Saitual64.1599.7492.5212.790.990.26Null15.810.001.9819.176310091983295Null800534265
Serchhip61.3999.7697.8011.930.610.1888.896.121.533.0627.536010097992096889627836175
Siaha51.6487.6891.1025.292.830.4695.2014.140.001.7719.0950808981909095820484268
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur36.0995.86106.5413.150.884.72Null22.021.960.9814.29349310097280Null6934263251
Kiphire53.3989.0442.636.561.890.47Null1.352.702.7019.055282271006090Null10047734267
Kohima36.0697.5074.5513.641.471.32Null5.211.890.4718.61349668964772Null
9733134160
Longleng25.4495.0047.423.011.580.3298.040.007.921.9820.40239234100519398100100544572
Mokokchung53.8698.5364.437.831.230.5457.821.543.600.5118.2452985510039895310063144064
Mon17.9977.1557.861.231.920.3283.280.002.800.4010.8315624710061938110049112459
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren19.7474.6648.786.171.680.6075.400.004.202.1014.9117583510054877210074573363
Phek23.4489.3146.404.531.410.3996.640.613.060.6118.4821823210045929610054174162
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang15.4494.6547.684.021.311.8479.529.334.670.9319.691391341004261779082254460
Wokha29.2597.8950.043.910.960.3093.650.603.011.2014.2527973710031949310053323163
Zunheboto25.0596.8946.081.200.710.2392.000.003.550.7116.7023953210023959110062193762
Sikkim
Gangtok70.1099.8473.652.510.680.1592.7237.822.280.0060.2969100671002297924340010066
Gyalshing85.7599.4959.3035.712.090.0788.7453.020.001.4028.7485994967679987180386461
Mangan81.0596.5548.0886.211.830.0986.0816.020.002.2941.418094340589884790629262
Namchi85.3899.3263.3218.060.750.0382.6948.350.680.0026.2285995491249981261205857
PakyongNullNullNull0.000.000.1186.1563.933.12
1.560.78NullNullNull1000988405542148
SorengNullNullNull0.000.000.0382.9746.320.000.000.15NullNullNull100099812900039
Tripura
Dhalai71.0794.48106.599.350.690.57119.1516.130.000.5316.2170911001002288100790143664
Gomati85.2199.3293.147.630.420.33153.2715.610.000.4715.478599911001393100800133464
Khowai82.5398.5184.686.790.340.4492.5819.230.000.6112.00829881100119192740172661
North Tripura91.8697.62121.606.770.480.2841.6911.980.000.2410.85929610010015943486062459
Sepahijala80.6998.14111.623.170.440.27269.2317.080.000.4213.2980971001001494100780112964
South Tripura79.2199.4992.553.920.650.1493.9619.250.000.4516.25799991100219793740123664
Unakoti75.5293.61112.9110.650.400.2449.6914.470.000.3614.107590100100139543820103158
West Tripura134.5599.9183.3521.980.390.94111.4526.030.110.3324.521001007985138010063295462
Target100100100113.1301003.55.73.7045100100100100100100100100100100100100
2122023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Arunachal Pradesh
Anjaw35.620.8569.516.2291.8991.677.70210517918010050
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang27.331.096035.8488.5589.1113.72411003529877410067
Dibang Valley17.141.1881.534.7886.96100.003.246610070288510010078
East Kameng20.931.0166.533.5345.2995.809.04571004626379010065
East Siang10.221.0183.551.8597.5393.377.97831007347978410083
Kamle27.491.368522.7839.2497.969.07401007614309510065
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi20.751.2974.518.8048.8791.447.24571005910418010064
Kurung Kumey34.991.036936.3688.8994.814.74221005029878810068
Leparada11.811.047342.8663.4997.325.77791005637589410075
Lohit17.251.206849.0669.8188.0611.58661004844657210071
Longding14.371.0257.536.7942.4590.3912.98731003130337710064
Lower Dibang Valley20.650.968167.0079.0094.268.0457726963768710075
Lower Siang20.620.987050.0059.4689.965.4957885245537610067
Lower Subansiri16.790.918256.5287.6887.176.2667387152867010069
Namsai21.080.9575.528.4469.1988.1410.4756676021647210063
Pakke Kessang27.521.847020.7543.40100.0010.614010052123410010063
Papum Pare29.311.088051.6863.0394.738.38361006846578810071
Shi Yomi23.161.5064.528.2133.3395.4512.1751
1004320238910061
Siang16.851.058025.0050.9391.865.22671006817438110068
Tawang15.261.768071.1979.6692.5810.37701006868768310081
Tirap20.390.9672.540.2861.1192.4910.3758715634558210065
Upper Siang19.410.897737.8076.3895.457.5860306331738910064
Upper Subansiri8.091.0870.541.6029.2094.6213.74881005235188710069
West Kameng26.021.1171.552.9267.9292.659.94441005448638310070
West Siang18.921.067938.7897.2892.845.94611006632978310077
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa25.391.0678.584.8488.3562.127.82461006583861110070
Barpeta29.421.307958.7183.8965.3212.12361006654811910065
Biswanath31.451.186959.2688.2178.5914.10311005055865010067
Bongaigaon31.961.246565.3688.1965.6114.67301004462861910063
213
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
Average annual
drop-out rate at
secondary level
(Class 9-10)
Ratio of
female to male
enrolment at
secondary level
(Class 9-10)
Percentage
of students in
grade 8 achiev -
ing at least
a minimum
proficiency
level in terms
of nationally
defined learning
outcomes to
be attained at
the end of the
grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Assam
Cachar27.061.1364.567.1990.2069.9718.03421004364893010067
Charaideo23.291.197995.2098.4461.989.22511006695981110074
Chirang27.241.166461.4383.8773.7013.07411004257813810066
Darrang18.871.267080.6690.6873.1210.63621005279893710074
Dhemaji11.241.067659.0590.8372.2910.00801006155893510074
Dhubri24.551.2972.549.6068.9269.5918.15481005644642910063
Dibrugarh19.431.0869.575.7497.2374.5710.34601005173974010074
Dima Hasao14.941.037755.3789.3772.488.30711006351883510073
Goalpara29.021.4067.564.1789.1372.8615.91371004860873610067
Golaghat23.571.0967.577.3391.2571.009.45501004875903210071
Hailakandi22.711.256949.9569.9968.9615.08521005045652710063
Hojai28.251.486279.3491.0763.5315.17391003977901410066
Jorhat22.651.0480.563.6995.6876.057.64521006960954410074
Kamrup34.851.1379.583.3192.7079.4710.02221006781925210073
Kamrup Metropolitan13.821.028570.8596.5380.268.24741007668965410081
Karbi Anglong25.781.0763.576.0286.4165.9910.77451004173842010066
Karimganj26.721.4360.564.4382.7469.5717.16421003661802910064
Kokrajhar20.281.0871.567.3668.3269.2813.89581005464632810067
Lakhimpur21.391.1073.558.5488.4971.997.71551005754873410070
Majuli16.590.9079.569.8689.6467.885.9767
326767882510064
Morigaon29.391.3973.579.8890.2276.3314.32361005778894410072
Nagaon30.051.5368.564.2588.1869.3610.16341004960862810065
Nalbari18.801.1084.553.6787.9967.847.91621007549862510071
Sivasagar20.021.038694.6397.7365.196.22591007794971810078
Sonitpur31.511.266973.6385.5875.9913.50311005071834410068
South Salmara-Mankachar27.241.5573.555.2873.9362.0114.03411005750701110061
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia30.681.136973.3094.8875.4813.25331005070944210070
Udalguri16.891.177167.2890.5163.9711.85661005364891510070
West Karbi Anglong33.801.136258.6888.0872.0712.30251003954863410063
2142023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average
annual
dropout
rate at
secondary
level (Class
9-10)
Ratio of
female
to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency level
in terms of nationally defined
learning outcomes to be at -
tained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage
of trained
teachers at
secondary
level (Class
9-10)
Pupil Teach -
er Ratio at
secondary
level (Class
9-10)
Average annual
dropout rate at
secondary level
(Class 9-10)
Ratio of fe -
male to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency
level in terms of nationally
defined learning outcomes
to be attained at the end of
the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Manipur
Bishnupur20.010.9674.540.9275.2583.7910.8059755935716210066
Chandel25.921.0980.514.3593.4869.649.1244100695922910063
Churachandpur33.431.028430.3767.5676.3810.94261007423624510061
Imphal East18.170.988243.9577.3483.277.2263857138746110070
Imphal West0.001.0085.555.5686.4883.517.731001007751846110082
Jiribam21.781.1952.529.63100.0067.3914.345410023221002410060
Kakching30.470.948050.6076.7980.049.3933646845735310062
Kamjong1.921.08789.9427.9593.1810.82100100650168410066
Kangpokpi24.640.9780.520.7556.9874.669.8147796912504110057
Noney32.220.917118.5736.4370.2311.7029425310263010042
Pherzawl41.930.957617.6923.0881.885.62569619115710045
Senapati4.920.988126.7073.8681.929.5696876919705810071
Tamenglong16.881.0970.516.6136.9089.559.8366100528277610061
Tengnoupal29.751.027221.7169.7469.429.18351005513652810057
Thoubal8.180.9674.549.1177.2286.2611.2188735944746810072
Ukhrul22.511.077842.7351.9873.719.55531006537443810062
Meghalaya
East Garo Hills14.571.1543.524.4423.0476.8617.0572100916114610051
East Jaintia Hills38.611.4659.516.4330.2676.3611.3313100357194510046
East Khasi Hills11.161.267234.2653.6968.589.33811005527462610062
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNullNullNull
NullNull*
North Garo Hills44.011.264314.4321.5375.6813.4201008594310038
Ri Bhoi16.931.3961.520.2434.3865.3910.82661003812241910051
South Garo Hills30.701.22469.8013.7676.118.823310013004410041
South West Garo Hills29.251.135012.7114.3873.6710.013610019313810043
South West Khasi Hills26.301.295310.4321.5966.507.464310024192110043
West Garo Hills25.361.205315.2324.0861.709.7746100246121010043
West Jaintia Hills20.561.5063.517.8128.0260.9611.885710041917810047
West Khasi Hills32.131.303810.3217.0269.9711.97291000143010038
Mizoram
Aizawl0.001.1178.567.3499.2178.3610.641001006564994910082
Champhai20.261.1362.579.0398.1374.8110.27581004077984110073
Hnahthial32.501.21Null46.3893.4883.208.4328100Null41926110070
Khawzawl24.731.14Null41.3595.4967.368.5347100Null35952310067
215
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE IV: PERFORMANCE OF DISTRICTS ON SDG 4
RAW VALUESINDEX SCORE (Normalised values)
District
Average
annual
dropout
rate at
secondary
level (Class
9-10)
Ratio of
female
to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency level
in terms of nationally defined
learning outcomes to be at -
tained at the end of the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage
of trained
teachers at
secondary
level (Class
9-10)
Pupil Teach -
er Ratio at
secondary
level (Class
9-10)
Average annual
dropout rate at
secondary level
(Class 9-10)
Ratio of fe -
male to male
enrolment at
secondary
level (Class
9-10)
Percentage of students in
grade VIII achieving at least
a minimum proficiency
level in terms of nationally
defined learning outcomes
to be attained at the end of
the grade
Percentage of
schools with
computers
available
Percentage of
schools with
functional
electricity
Percentage of
trained teachers
at secondary
level (Class
9-10)
Pupil Teacher
Ratio at second -
ary level (Class
9-10)
SDG 4
Kolasib23.341.1566.545.0498.5895.289.22511004639988910075
Lawngtlai29.450.925716.4456.4078.4410.763647317494910046
Lunglei24.571.0263.540.4578.4778.506.51481004134755010064
Mamit39.961.066840.1679.5392.597.07101004834768310064
Saitual29.851.10Null63.0599.5187.217.1535100Null59997010077
Serchhip23.130.926943.0496.9687.688.1251515037967110065
Siaha0.000.986327.9995.9082.0810.18100894020955810072
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur0.371.058094.8396.4974.988.781001006894964110086
Kiphire27.881.1566.572.1872.9365.6110.99401004669691910063
Kohima0.001.048086.9189.0974.867.051001006885874110083
Longleng14.631.2271.594.5044.0473.777.10721005494353810071
Mokokchung14.220.9682.592.1994.1479.335.3573737291935210079
Mon26.681.1666.582.8469.9757.369.9142100468165010062
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren15.990.927569.3675.7269.068.3469486066722710063
Phek25.521.107888.4691.8874.245.45451006587914010075
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNull
Null*
Tuensang21.881.2164.587.2468.3177.509.07541004386634710070
Sikkim
Gangtok14.401.037991.77100.0088.447.227310066911007310086
Gyalshing19.661.016994.3096.3788.034.58601005094967210082
Mangan22.411.057680.0097.2785.495.33531006178976610079
Namchi18.831.037191.4499.1787.035.54621005391997010082
Pakyong24.070.98Null93.7298.9589.634.724985Null93997610083
Soreng22.861.02Null96.13100.0084.343.6952100Null961006310085
Tripura
Dhalai11.891.056228.0257.2991.8211.77791003920508110067
Gomati11.980.997642.6794.9590.1613.8679956136947710077
Khowai14.121.017653.8996.6185.469.67731006149966610078
North Tripura13.861.1472.544.6568.8289.6610.78741005639647610073
Sepahijala13.211.0077.550.3171.2388.369.03751006445677310075
South Tripura11.601.0084.540.7582.8491.3412.6079987534808010078
Unakoti13.331.1070.555.1781.9686.6614.94751005250796910075
West Tripura3.521.0081.586.6991.0388.6410.3099987085907310088
Target3.2110010010010030100100100100100100100100
2162023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Arunachal Pradesh
Anjaw4.1481850.006.847.4775870794866
BichomNullNullNullNullNullNullNullNullNullNull*
Changlang2.2496268.756.745.38710059804674
Dibang Valley0.007780.004.661.910045100866279
East Kameng4.371189100.009.791.47510040719276
East Siang6.7493180.9517.694.2629451479570
Kamle0.901161100.00Null78.69510040Null7978
Keyi PanyorNullNullNullNullNullNullNullNullNullNull*
Kra Daadi0.42636100.0016.587.798040508855
Kurung Kumey0.009710.0016.486.3100100100508787
Leparada8.1892080.00Null77.1549052Null7868
Lohit5.9899264.2914.670.86610061567171
Longding1.4286750.007.355.6927470785674
Lower Dibang Valley4.2390190.914.974.5768445857573
Lower Siang5.6292366.67Null58.4689160Null5970
Lower Subansiri3.3396671.438.5Null811005774Null78
Namsai1.52100280.008.771.49110052747278
Pakke Kessang6.51833100.00Null89.7636340Null9064
Papum Pare17.7498034.6720.372.8010079387358
Shi Yomi3.081192100.00Null94.28310040Null9579
Siang1.96871100.005.086.0897540858775
Tawang1.4410290.0014.699.3921001005610090
Tirap0.38934100.0010.666.4989540686774
Upper Siang4.21105685.7111.977.67610049647873
Upper Subansiri2.6289533.3317.380.2858380488175
West Kameng2.2891050.0017.078.6878770487974
West Siang9.8791472.0015.583.4448857538465
Assam
BajaliNullNullNullNullNullNullNullNullNullNull*
Baksa2.6592924.1912.5100.08593856210085
Barpeta7.1596523.3512.3100.060100866310082
Biswanath6.3496119.905.3100.064
100888410087
Bongaigaon7.7794319.8616.199.95698885110079
217
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Cachar11.9296920.0215.6100.033100885310075
Charaideo6.7894922.378.3100.062100877510085
Chirang6.8396224.079.899.762100867010083
Darrang16.5395321.6314.8100.07100875510070
Dhemaji5.9796632.507.199.866100817810085
Dhubri9.0497123.0011.5100.049100866510080
Dibrugarh6.0891816.208.7100.06690907410084
Dima Hasao2.9092433.339.7100.08492807110085
Goalpara13.6094119.477.4100.02397887810077
Golaghat3.8293913.0010.9100.07896926710087
Hailakandi9.4094433.118.6100.04798807410080
Hojai13.1395916.9213.299.926100906010075
Jorhat7.5491434.5010.4100.05889796810079
Kamrup16.4796738.1317.6100.07100774710066
Kamrup Metropolitan16.1593524.418.8100.0995857310073
Karbi Anglong1.8097620.699.3100.090100887210090
Karimganj7.9095317.028.699.555100907410084
Kokrajhar7.9996131.1210.099.955100817010081
Lakhimpur7.7995018.559.8100.056100897010083
Majuli8.2089028.3611.6100.05481836510076
Morigaon11.6496121.726.599.934100878010080
Nagaon8.3996920.2612.3100.053100886310081
Nalbari9.6992330.4913.2100.04591826010076
Sivasagar6.6998018.148.399.362100897510085
Sonitpur12.7190517.615.8100.02886898210077
South Salmara-Mankachar10.4095317.258.099.641100907610081
TamulpurNullNullNullNullNullNullNullNullNullNull*
Tinsukia6.9894128.9811.0100.06197836710081
Udalguri6.2795617.1214.6100.065100905610082
West Karbi Anglong2.7790125.007.199.48484857810086
2182023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Manipur
Bishnupur1.6980865.0020.051.0905561395159
Chandel0.259310.0011.01.3999410067172
Churachandpur0.8794980.008.716.19510052741667
Imphal East2.1190875.0016.797.4888755499875
Imphal West3.2793055.8112.59.082946762963
Jiribam1.41119666.67Null76.99210060Null7782
Kakching2.33109682.35Null28.48710051Null2967
Kamjong0.0011930.00Null3.6100100100Null476
Kangpokpi0.11976100.00Null14.39910040Null1463
Noney0.009880.00Null21.1100100100Null2180
Pherzawl0.98781100.00Null0.0944640Null045
Senapati0.15934100.008.520.0999540742066
Tamenglong0.239140.008.48.3998910075874
Tengnoupal1.6996220.00Null34.29010088Null3478
Thoubal2.8288169.236.070.3847858827175
Ukhrul0.76100580.0012.740.39610052624170
Meghalaya
East Garo Hills4.3589036.8421.087.8758178368872
East Jaintia Hills6.971050146.6726.092.26110012219357
East Khasi Hills4.8493737.1833.089.173967809067
Eastern West Khasi HillsNullNullNullNullNullNullNullNullNullNull*
North Garo Hills2.81998166.6725.288.8841000248959
Ri Bhoi5.1595432.1427.087.37110081188872
South Garo Hills3.4792692.3125.387.6809245238866
South West Garo Hills1.1795525.0030.499.79310085810077
South West Khasi Hills3.0698075.0026.285.58310055218669
West Garo Hills6.2791641.7619.779.6658975408070
West Jaintia Hills3.8697427.7829.392.47810083119373
West Khasi Hills7.4795668.4225.893.95810059229467
Nagaland
Aizawl3.2596735.4824.099.882100792710078
Champhai2.5197221.0511.2100.086100876610088
Hnahthial2.1088937.50Null97.1
888178Null9886
Khawzawl6.0590650.00Null100.0668670Null10080
219
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE V: PERFORMANCE OF DISTRICTS ON SDG 5
RAW VALUESINDEX SCORE (Normalised values)
District
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Crimes against women
per 10,000 female
population
Sex ratio at birth
Percentage of sexual
crimes against women
to total crimes against
women
Unmet need for family
planning for currently
married women aged
15-49 years
Exclusive women SHGs
in bank linked SHGs
Kolasib2.68104012.5015.699.885100935310086
Lawngtlai2.8696790.9117.3100.084100454810075
Lunglei1.7397033.3315.4100.090100805310085
Mamit2.89923100.0017.099.98491404810073
Saitual1.6010370.00Null100.091100100Null10098
Serchhip3.72109650.0015.9100.079100705210080
Siaha2.1483850.0022.599.98864703210071
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNull*
Dimapur0.7290254.5514.392.5968567579380
Kiphire0.2888766.6717.395.5988060489676
Kohima0.9791540.009.1100.09589767210086
Longleng0.859710.004.396.695100100879796
Mokokchung0.329730.006.4100.0981001008110096
Mon0.519670.003.785.597100100898694
NoklakNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNull*
Peren0.7097666.676.277.29610060817883
Phek0.3884150.006.596.3986570809782
ShamatorNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNull*
Tuensang0.519300.0012.9100.097941006110090
Wokha0.129960.003.2100.0991001009010098
Zunheboto0.439300.002.891.49894100929295
Sikkim
Gangtok6.9296494.7417.7100.061100434610070
Gyalshing5.51101875.004.3100.069100558710082
Mangan6.32871100.0012.8100.06475406110068
Namchi5.9885278.575.2100.06669538410074
Pakyong7.11Null100.00Null100.060Null40Null10067
Soreng4.42Null100.00Null100.075Null40Null10072
Tripura
Dhalai3.5992540.914.0100.08092758810087
Gomati5.9097733.8712.1100.0
67100806310082
Khowai2.3794350.004.1100.08798708810088
North Tripura5.42100146.856.1100.069100728210085
Sepahijala3.25101323.6815.3100.082100865410084
South Tripura3.7594836.5917.3100.079100784810081
Unakoti7.8595438.329.7100.056100777110081
West Tripura3.2598733.332.5100.082100809210091
Target09500099.4100100100100100100
2202023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Arunachal Pradesh
Anjaw100.0089.8486.8100.0090.54100.00Null100837210086100Null90
BichomNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Changlang100.0089.9782.3100.0076.81100.000.661008363100661009987
Dibang Valley100.0091.7795.0100.0073.91100.00Null100868910061100Null90
East Kameng100.0095.3475.6100.0046.15100.002.631009249100201009479
East Siang100.0090.8783.9100.0062.35100.000.881008566100441009885
Kamle100.0092.00Null100.0045.57100.00Null10087Null10020100Null81
Keyi PanyorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Kra Daadi100.0092.8389.3100.0078.95100.00Null100887710069100Null89
Kurung Kumey100.0092.7678.3100.0061.62100.00Null100885410043100Null81
Leparada100.0092.92Null100.0079.37100.00Null10088Null10069100Null92
Lohit100.0092.1383.7100.0095.28100.000.731008766100931009892
Longding100.0092.5883.5100.0061.32100.00Null100886510043100Null83
Lower Dibang Valley100.0091.1589.9100.0088.00100.000.331008579100821009992
Lower Siang100.0094.02Null100.0058.11100.00Null10090Null10038100Null86
Lower Subansiri100.0092.8982.8100.0087.59100.002.331008864100821009590
Namsai100.0090.6775.1100.0081.99100.00Null100844710073100Null84
Pakke Kessang100.0092.14Null100.0058.49100.00Null10087Null10039100Null85
Papum Pare100.0093.1175.7100.0059.66100.001.281008949100401009782
Shi Yomi100.0093.20Null100.0076.92100.00Null10089Null10066100Null
91
Siang100.0093.4791.2100.0037.96100.00Null10089811008100Null80
Tawang100.0089.0581.7100.0085.34100.00Null100826110078100Null87
Tirap100.0090.2486.7100.0064.34100.001.751008472100471009686
Upper Siang100.0095.7491.8100.0068.25100.00Null100938310053100Null88
Upper Subansiri100.0094.2080.9100.0056.00100.000.611009060100351009983
West Kameng100.0089.7588.9100.0069.58100.000.1110083771005510010088
West Siang100.0093.7887.7100.0072.79100.001.031009074100601009889
Assam
BajaliNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Baksa100.0073.9368.993.8386.65100.003.49100573492801009279
Barpeta99.4376.1463.795.6390.09100.0029.6898602394851003170
Biswanath87.6663.6476.693.6485.53100.00Null5540519279100Null69
Bongaigaon95.9171.0272.593.3090.58100.0025.7685524291861004071
221
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Cachar100.0074.2457.695.5591.82100.003.29100571194881009277
Charaideo94.9863.1275.993.0597.96100.00Null8239499197100Null76
Chirang97.1051.8177.196.2483.21100.002.7589205295751009475
Darrang72.7272.4767.993.6690.25100.0042.71054329286100052
Dhemaji89.3565.4670.894.3893.05100.004.0561433893901009174
Dhubri99.6666.2661.894.7784.51100.0029.7299441993771003066
Dibrugarh99.1770.0675.395.1995.94100.007.6397504894941008281
Dima Hasao100.0074.0383.894.8281.11100.001.01100576693721009884
Goalpara100.0070.7075.395.1791.39100.0020.82100514894871005176
Golaghat95.0569.2973.194.7393.65100.005.4282494393911008778
Hailakandi100.0064.2760.096.4167.68100.003.62100411695521009271
Hojai99.8565.6263.194.0893.29100.00Null9943229290100Null74
Jorhat96.7157.6980.494.9496.48100.009.3588305993951007878
Kamrup99.0261.2668.794.2596.29100.0033.9196363492951002168
Kamrup Metropolitan100.0077.1765.295.6596.32100.00Null10062279495100Null80
Karbi Anglong99.0157.8975.292.4584.14100.002.4896304890771009476
Karimganj100.0068.1061.596.1781.21100.002.94100471995721009375
Kokrajhar97.1371.1872.295.6475.64100.005.6389524194641008775
Lakhimpur99.8772.8674.294.1587.23100.0010.26100554692811007678
Majuli100.0081.1265.693.6888.03100.00Null10069279282100Null78
Morigaon99.7749.8862.394.6887.36100.0025.2199172093811004165
Nagaon96.4164.7866.193.8389.19100.0028.8687412892841003266
Nalbari99.9872.3568.194.3192.76100.0024.11100543393891004473
Sivasagar99.1280.8682.394.5394.89100.004.1997686393921009086
Sonitpur92.7467.6772.294.6187.78100.0010.4473464193821007673
South Salmara-Mankachar100.0074.1459.094.6882.18100.00Null10057149374100Null73
TamulpurNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tinsukia87.9472.7766.794.3995.97100.006.6756553093941008573
Udalguri96.8663.8273.894.7290.76100.008.9088404593861007976
West Karbi Anglong100.0046.1876.792.4982.07100.00Null10010519073100Null71
2222023-24NER DISTRICT SDG INDEX
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Percentage
of individual
household toi -
lets constructed
against target
(SBM(G))
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/villages
verified as ODF
(SBM(G)) in the
district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Manipur
Bishnupur100.0069.8652.6100.0068.65100.005.67100500100541008770
Chandel100.0067.6785.2100.0088.26100.00Null100466910083100Null83
Churachandpur100.0079.0581.2100.0094.01100.006.181006560100911008686
Imphal East100.0077.2059.5100.0071.76100.007.981006215100581008174
Imphal West100.0068.4658.7100.0080.11100.0010.971004813100711007472
Jiribam100.0039.89Null100.0074.53100.00Null1000Null10062100Null72
Kakching100.0077.81Null100.0081.55100.00Null10063Null10073100Null87
Kamjong100.0067.20Null100.0065.84100.00Null10045Null10050100Null79
Kangpokpi100.0080.58Null100.0053.40100.00Null10068Null10031100Null80
Noney100.0066.52Null100.0069.29100.00Null10044Null10055100Null80
Pherzawl100.0048.09Null100.0064.62100.00Null10014Null10048100Null72
Senapati100.0070.8784.4100.0087.22100.00Null100526710081100Null83
Tamenglong100.0073.5877.9100.0099.63100.00Null100565310099100Null85
Tengnoupal100.0086.66Null100.0053.95100.00Null10078Null10032100Null82
Thoubal100.0076.1461.3100.0072.49100.009.841006018100591007774
Ukhrul100.0071.7081.4100.0044.93100.00Null100536110019100Null72
Meghalaya
East Garo Hills100.0081.5283.971.8469.83100.006.93100696663551008477
East Jaintia Hills100.0052.0783.676.3357.20100.002.28100206569371009569
East Khasi Hills100.0063.8480.984.5878.91100.002.58100406080691009477
Eastern West Khasi HillsNullNullNullNUllNullNullNullNullNull
NullNullNullNullNull*
North Garo Hills100.0074.8184.966.4768.27100.003.59100586856531009275
Ri Bhoi100.0078.0885.359.7272.85100.006.17100646947601008675
South Garo Hills100.0080.1088.476.9671.25100.001.59100677670581009681
South West Garo Hills100.0076.9471.437.5751.73100.0017.65100624018291005958
South West Khasi Hills100.0071.3589.657.6685.02100.001.71100527844781009678
West Garo Hills100.0065.9986.364.5858.89100.004.15100437153391009071
West Jaintia Hills100.0064.8975.183.2064.95100.004.45100424778481009072
West Khasi Hills100.0074.3087.874.4872.06100.001.74100577466591009679
Mizoram
Aizawl100.0089.9996.1100.0094.69100.0014.061008392100921006791
Champhai100.0091.7998.3100.0080.52100.003.031008696100711009392
Hnahthial100.0087.62Null100.0075.36100.00Null10079Null10064100Null89
Khawzawl100.0092.09Null100.0076.69100.00Null10087Null10066100Null90
Kolasib100.0091.7296.8100.0066.31100.001.301008693100501009790
Lawngtlai100.0089.6290.3100.0067.99100.003.621008380100531009287
Lunglei100.0090.4395.6100.0074.65100.004.101008491100631009190
223
INDICATOR TABLES
Aspirant (0-49)
Performer (50-64)
Front Runner (65-99)
Achiever (100)
Not included in ranking Please refer to Pg. 15 for details
* TABLE VI: PERFORMANCE OF DISTRICTS ON SDG 6
RAW VALUESINDEX SCORE (Normalised values)
District
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Percentage
of individual
household toi -
lets constructed
against target
(SBM(G))
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/villages
verified as ODF
(SBM(G)) in the
district
Stage of
groundwater
extraction (%)
Percentage of
rural population
using an im -
proved drinking
water source
Percentage of
rural population
getting safe
and adequate
drinking water
within premises
through Piped
Water Supply
(PWS)
Percentage
of population
living in house -
holds that use
an improved
sanitation
facility
Toilets
constructed
against target -
SBM(G)
Percentage of
schools with
functional toilet
facility for girls
Percentage of
GPs/Villages
verified as ODF
in the district
Stage of
groundwater
extraction (%)
SDG 6
Mamit100.0091.4092.7100.0078.68100.002.061008685100681009591
Saitual100.0090.25Null100.0089.16100.00Null10084Null10084100Null94
Serchhip100.0092.1398.2100.0092.61100.006.191008796100891008694
Siaha100.0091.8391.5100.0084.70100.005.781008682100771008790
Nagaland
ChumoukedimaNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Dimapur100.0077.5081.1100.0092.80100.003.981006360100891009186
Kiphire100.0089.3683.1100.0072.18100.006.431008264100591008584
Kohima100.0079.4187.4100.0093.09100.0010.511006673100901007586
Longleng100.0083.2086.6100.0088.99100.001.331007272100841009789
Mokokchung100.0074.6996.7100.0089.06100.000.621005893100841009990
Mon100.0079.0186.4100.0092.08100.005.111006571100881008888
NoklakNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
NiulandNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Peren100.0079.9789.4100.0083.24100.000.901006778100751009888
Phek100.0081.3790.1100.0058.12100.006.431006979100381008582
ShamatorNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
TseminyuNullNullNullNullNullNullNullNullNullNullNullNullNullNull*
Tuensang100.0076.6492.0100.0065.02100.0010.091006183100481007681
Wokha100.0082.3488.5100.0079.46100.001.381007176100701009788
Zunheboto100.0080.7688.9100.0032.35100.008.061006877
10001008175
Sikkim
Gangtok100.0085.9985.0100.0099.55100.009.291007768100991007889
Gyalshing100.0081.1788.9100.0097.83100.004.631006977100971008990
Mangan100.0079.8283.8100.0098.95100.002.581006666100981009489
Namchi100.0077.3491.7100.0096.77100.009.781006282100951007788
Pakyong100.0074.23Null100.0096.67100.003.6010057Null100951009291
Soreng100.0077.50Nu