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1
National Health mission:
Impact and Learnings for future
A NITI Aayog Study
Conducted by
Department of Community Medicine & School of Public Health
Postgraduate Institute of Medical Education and Research (PGIMER)
Chandigarh
2
TEAM
Technical Advisor
Dr Rajesh Kumar, Former Dean (Academics), Professor and Head
Principal Investigator
Dr Madhu Gupta, Professor of Community Medicine
Co-Investigators
Dr PVM Lakshmi, Professor of Epidemiology
Dr. Shankar Prinja, Additional Professor of Health Economics
Project Staff
Dr Ekta Sharma, Project Coordinator
Dr Ruby Nimesh, Consultant
Dr Ekta Thakur, Project Associate
Dr Aarti Goyal, Project Associate
3
ACKNOWLEDGMENTS
This study was carried out with the financial support of NITI Aayog, Government of India, and conducted
by Department of Community Medicine & School of Public Health Postgraduate Institute of Medical
Education and Research (PGIMER) Chandigarh.
We gratefully acknowledge the contributions made by the NITI Aayog officers, Dr. V.K. Paul (Member
NITI Aayog), Mr. Alok Kumar, Adviser (Health and Nutrition NITI Aayog), Dr. K. Madan Gopal (Sr.
Consultant NITI Aayog), Dr. Nina Badgyain (Consultant NITI Aayog) for showing their interest in the
study and necessary guidance throughout the study.
We also acknowledge our gratitude to the senior residents, PGIMER, Chandigarh, including Dr. Garima
Sangwan and Dr. Kirtan Raina, who rendered their help during the period of this study.
Special thanks to other research staff of PGIMER Chandigarh including Dr. Adarsh Bansal (Project
officer) for conducting a systematic review on impact of NHM strategies on reproductive and adolescent
health, Dr. Shivani Aloona (Research Officer) for conducting a systematic review on impact of NHM
strategies on neonatal and infant health, Dr. Atul Sharma (Project officer) for working on analysis and
comparison of public sector utilization for health services, out-of-pocket expenditures on hospitalization
of under-five children and delivery cases and associated catastrophic rates using NSSO 60
th
round and
71
st
round data.
4
DISCLAIMER
The Organization Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh
has received the financial assistance under the Research Scheme of NITI Aayog (RSNA-2018) to
prepare this report. While due care has been exercised to prepare the report using the data from various
sources, NITI Aayog does not confirm the authenticity of data and accuracy of the methodology to
prepare the report. NITI Aayog shall not be held responsible for findings or opinions expressed in the
document. This responsibility completely rests with the
PGIMER, Chandigarh. 5
CONTENTS
Sr.
No.
Items Page No.
Executive summary
1. Introduction 14-18
2. Objectives 18
3. Methods 19-35
4.
Results
35-59
60-84
60-63
63-70
70-84
Systematic Review
Secondary Data Analysis
Input/process Indicators
Health Output/Outcome indicators
Impact Indicators and Health Inequalities
5. Discussion 85-89
6. Conclusion 89-92
7 Recommendations 93-96
8 References 281-303
6
9. Annexures
Annexure 1:PRISMA Checklist
Annexure 2: Protocols for systematic review
Annexure 3: MeSH Strategy
Annexure 4: Flow diagram of studies included in systematic review
Annexure 5: Results of total studies included in systematic review
Annexure 6: Characteristics of good quality studies
Annexure 7: Maternal health indicators of women aged 15-49 years
who had had a live birth in the five years preceding the survey.
Annexure 8: Contraceptive methods currently used for family
planning by married women aged 15-49 years.
Annexure 9: Immunization of children aged 12-23 months who
received specific vaccines at any time before the survey.
Annexure 10: Child health indicators of children under 5 years of
age in 2 weeks preceding the survey.
Annexure 11: The Interrupted Time Series (ITS) estimates of pre
slope, post slope and change at state and national level.
97-99
100-133
134-158
159-167
168-261
262-274
275
276
277
278
279-280
7
LIST OF TABLES
Table No. Title Page No.
Table 1 Targets of National Rural Health Mission, National Health Policy
and Sustainable Development Goals
15
Table 2 Grading of studies based upon quality 23-24
Table 3 The variables selected for regression analysis 32-33
Table 4 Number of studies reviewed and included in systematic review 56
Table 5 Health indicators for women aged 15-49 years who had a live
birth in the five years preceding the survey
69
Table 6 Child health indicators of children under 5 years of age in 2005 and
2015
70
Table 7 Infant mortality rate and Neonate mortality rate (per 1000 live
births) of children born in the three years preceding the survey
78
Table 8 Health inequalities for infant mortality rate for children born in the
three years preceding the survey
81
Table 9 Health inequalities for neonate mortality rate for children born in
three years preceding the survey
84
8
LIST OF FIGURES
Figure
No.
Title Page
No.
Figure 1 Main Strategies of National Health Mission 16
Figure 2 Timeline of major strategies implemented under National Health Mission
from 2005 to 2019
23
Figure 3 Relation between thickness of arrow and strength of evidence 25
Figure 4 Flow chart showing the studies reviewed under systematic review and per
PRISMA guidelines
36
Figure 5 Forest plot of studies on institutional deliveries 38
Figure 6 Meta-analysis of studies with outcome as prevalence of low birth weight
babies
42
Figure 7 Meta-analysis of studies with outcome as Exclusive breast feeding
43
Figure 8 Meta-analysis of studies on full immunization coverage
45
Figure 9 Meta-analysis of studies with outcome as recovered children under NRC 46
Figure 10 Meta-Analysis of studies on CPR 49
Figure 11 Meta-analysis of 5 cross sectional studies on WIFS 50
Figure 12 Meta-analysis of 4 RCTs on WIFS 50
Figure 13 Meta-analysis of studies on usage of sanitary napkins
51
Figure 14 Meta-analysis of 15 studies on awareness of menstrual hygiene 52
Figure 15 Meta-analysis of 10 cross sectional studies on ARSH 53
Figure 16 Impact of NHM strategies: Evidence from literature 59
Figure 17 Allocation of funds for NRHM 60
Figure 18 Out of pocket expenditure and public health expenditure 61
Figure 19 Per capita public health expenditure 61
Figure 20 Number of Patient Beds/1000 population 62 9
Figure 21 Trend showing number of ANMs and ASHAs per 10,000 population (2005-
2019)
62
Figure 22 Trend showing doctors and nursing staff per 10,000 population in PHCs
and CHCs (2005-2018)
63
Figure 23 Utilization of public sector for outpatient care 63
Figure 24 Utilization of public sector for hospitalization 64
Figure 25 Out-of-pocket expenditure for under-five child hospitalization 65
Figure 26 Out-of-pocket expenditure on institutional deliveries 65
Figure 27 Catastrophic health expenditure on under-five child hospitalization 67
Figure 28 Catastrophic health expenditure on institutional deliveries 68
Figure 29 Health indicators for women aged 15-49 years who had a live birth in the
five years preceding the survey
68
Figure 30 Percentage of children for various child health indicators in 2005 and 2015 70
Figure 31 Trend of Maternal Mortality Ratio 1997-2017 71
Figure 32 Trend of under-five mortality rate in India, from 2005 to 2019 72
Figure 33 Trend of under-five mortality rate in Indian states, from 2008 to 2016 73
Figure 34 Trend of infant mortality rate in India, from 2005 to 2017. 73
Figure 35 Trend of infant mortality rate as per interrupted time series analysis in
India, from 2005 to 2017.
74
Figure 36 Trend of infant mortality rate in bigger states in India, from 2005 to 2017 75
Figure 37 Trend of infant mortality rate in smaller states in India, from 2005 to 2017 75
Figure 38 Trend of neonatal mortality rate in India, from 2005 to 2019.
76
Figure 39 Trend of neonatal mortality, infant mortality and under five mortality in India,
from 2007 to 2019.
77
Figure 40 Infant Mortality Rate and Neonatal Mortality Rate per 1,000 live births in
2005 and 2015.
77
Figure 41 Trend of Total Fertility Rate in India, from 2007 to 2017. 78
Figure 42 Comparison of infant mortality rate among urban and rural areas in 2005
and 2015.
79 10
Figure 43 Comparison of infant mortality rate among EAG and Non-EAG states in 2005
and 2015.
79
Figure 44 Caste wise health inequalities for infant mortality rate in 2005 and 2015 80
Figure 45 Wealth wise health inequalities for infant mortality rate in 2005 and 2015
80
Figure 46 Comparison of neonate mortality rate among urban and rural areas in 2005
and 2015.
82
Figure 47 Comparison of neonatal mortality rate among EAG and Non-EAG states in
2005 and 2015.
82
Figure 48 Caste wise health inequalities for neonate mortality rate in 2005 and 2015.
83
Figure 49 Wealth wise health inequalities for neonate mortality rate in 2005 and 2015 83
11
LIST OF ABBREVIATIONS
ANC Antenatal Care
ANM Auxiliary Nurse Midwife
ARI Acute Respiratory Infections
ARSH Adolescent Reproductive Sexual Health
AFHCs Adolescent Friendly Health Clinics
ASHA Accredited Social Health Activist
AYUSH Ayurveda Yoga Unani Siddha and Homeopathy
BCC Behaviour Change Communication
CPR Contraceptive Prevalence Rate
DLHS District Level Household Survey
ENMR Early Neonatal Mortality Rate
EBF Exclusive Breast Feeding
FBNC Facility Based Newborn Care
FLWs Frontline Health Workers
FP Family Planning
HBPNC Home based Post Neonatal Care
GDP Gross Domestic Product
ICDS Integrated Child Development Scheme
IMR Infant Mortality Rate
IMNCI Integrated Management of Neonatal and Childhood Illness
JSY Janani Suraksha Yojana
JSSK Janani Shishu Suraksha Karyakram
LBW Low Birth Weight
MCH Maternal and Child Health
MDM Mid Day Meal
MHS Menstrual Hygiene Scheme
MMR Maternal Mortality Ratio 12
MMUs Mobile Medical Units
MOs Medical Officers
MOHFW Ministry of Health and Family Welfare
NFHS National Family Health Survey
NHM National Health Mission
NSSO National Sample Survey Organization
NHP National Health Policy
NMR Neonatal Mortality Rate
NRCs Nutrition Rehabilitation Centres
NRHM National Rural Health Mission
NRHM National Urban Health Mission
OOPE Out of Pocket Expenditure
PHC Primary Health Centre
PNC Postnatal Care
PNMR Perinatal mortality Rate
SBR Still Birth Rate
SDG Sustainable Development Goals
SNCUs Sick New-born Care Units
SRS Sample Registration System
RBSK Rashtriya Bal Swasthya Karyakram
RHS Rural Health Statistics
RKSK Rashtriya Kishore Swasthya Karyakram
RMNCH+A Reproductive Maternal New-born Child and Adolescent Health
TFR Total Fertility Rate
U5MR Under Five Mortality Rate
UNICEF United Nations International Children’s Emergency Fund
VHND Village Health Nutrition Day
VHSNCs Village Health, Sanitation and Nutrition Committee 13
WHO World Health Organization
WIFS Weekly Iron Folic Supplementation 14
INTRODUCTION
The National Rural Health Mission (NRHM) was launched in 2005 by the Government of India
throughout the country, with a special focus on 18 states, to improve the accessibility, affordability and
availability of health care especially to those residing in the rural areas, poor and women. The specific
goals were reducing Maternal Mortality Ratio (MMR) to 100 per 1,00,000 births, Infant Mortality Rate
(IMR) to 30 per 1000 births, and Total Fertility Rate (TFR) to 2.1 within seven years of its implementation
i.e., by the year 2012, which were later extended to be achieved by the year 2020 under National Health
Mission. NRHM goals also included prevention and reduction of anaemia in women aged 15-49;
reducing mortality from communicable/non-communicable diseases, emerging diseases, injuries;
reducing household out-of-pocket expenditure; reducing incidence and mortality from TB by half;
reducing prevalence of Leprosy to below 1 per 10,000 population and incidence to zero in all districts;
annual malaria incidence to be less than 1/1000 population; less than 1% microfilaria prevalence in all
districts and Kala-azar elimination by 2015, less than 1 case per 10,000 in all endemic blocks. Qualitative
goals were having decentralized, community owned, inter-sectoral health delivery systems which could
address issues of water, sanitation, education, nutrition, social and gender equality. In 2013, the
government of India launched the National Health Mission (NHM) which subsumed the NRHM and
additionally launched the National Urban Health Mission (NUHM). The mission committed to raise the
government spending to health from 0.9% to 2-3% of GDP. The mission was extended in 2018 to
continue until 2020.
In 2017, the government has also brought out the National Health Policy (NHP), which aimed at
attainment of the highest possible level of health and well-being for all, at all ages, through a preventive
and promotive health care orientation in all developmental policies and universal access to good quality
health care services without anyone having to face financial hardship as a consequence [1]. The
sustainable development goals were also launched to replace the millennium development goals at the
global level during 2015 [2]. The targets of NRHM, NHP and Sustainable Development Goals (SDGs)
are listed below in the table 1 [2-4]. It was envisaged that NHM strategies will help in reaching SDGs at
the national level. 15
Table 1. Targets of National Rural Health Mission (NRHM), National Health Policy (NHP) and
Sustainable Development Goals (SDGs).
NRHM 2012 NHP targets SDG 2030
Maternal Mortality Ratio /lakh live
births
100 100 by 2020 <70
Neonatal Mortality rate
/1000 live births
- 16 by 2025 <12
Infant Mortality Rate
/1000 live births
30 28 by 2019 < 20
Under 5 Mortality Rate
/1000 live births
- 23 by 2025 <25
Total Fertility Rate 2.1 2 by 2025 -
The major NHM strategies to achieve the goals were health system strengthening by providing free
medicines and diagnostics, infrastructure development, national ambulance services, national mobile
services; human resource strengthening by providing additional Auxiliary Nurse Midwives (ANMs),
Medical Officers (MOs) etc.; flexible financing; communitization including provision of Accredited Social
Health Activists (ASHAs) in each village; improved management; implementing programs like
reproductive maternal neonatal childhood and adolescent health, communicable and non -
communicable diseases; and monitoring the progress. The main strategies and interventions of NHM
and time of launch are summarized in Figure 1 and 2. 16
Figure 1: Main strategies of National Health Mission
1
Maternal and Child Health;
2
Auxiliary Nurse Midwives;
3
Medical Officers;
4
Human Resource;
5
Accredited Social Health Activist;
6
Village
Health Nutrition Day;
7
Village Health Sanitation and Nutrition Committee;
8
Panchayat Raj Institutions;
9
District level Project Management Unit;
10
Block level Project Management Unit;
11
Financial Management Group;
12
National Health System Resource Centre;
13
State Health System
Resource Centre;
14
Family Planning;
15
Janani Suraksha Yojana;
16
Janani Shishu Suraksha Karyakram;
17
Facility Based New-born Care;
18
Sick Newborn Care Unit;
19
Nutrition Rehabilitation Centre;
20
Home based Post-natal Care;
21
Integrated Management of Neonatal and
Childhood Illness;
22
Rashtriya Bal Swasthya Karyakram;
23
Acute Respiratory Infection;
24
Weekly Iron Folic Acid Supplementation;
25
Rashtriya
Kishore Swasthya Karyakram;
26
Adolescent Friendly Health Clinics;
27
Menstrual Hygiene Scheme;
28
Indian Public Health Standard;
29
Common Review Mission;
30
Joint Review Mission.
17
Figure 2. Timeline of major strategies implemented under National Health Mission from 2005 to
2019.
As NHM has completed about 15 years (2005-2020) there is a need to review the impact of NHM on
health measures so that learnings from NHM can be utilized to further improve the outcomes for
achieving Universal Health Coverage (UHC) by 2030. Most of the earlier studies have evaluated the
effectiveness of NRHM strategies in improving the maternal and child health (MCH) outcomes, and most
of these studies were state specific. A planning commission of India evaluated the implementation of
NRHM conducted in seven states in 2011, and observed some improvements in the availability and
utilization of maternal and child health services in rural areas. However, this evaluation lacked the
comparison of the situation before the implementation of the NRHM [4]. A qualitative study by Gupta et
al (2017) in Haryana highlighted that there was increase in the demand and utilization of MCH services
after the implementation of NRHM strategies especially recruitment of accredited social health activists
at the village level in the state of Haryana [5]. Carvalho et al (2014)
and Randive et al (2013)
reported
positive impact of Janani Suraksha Yojana (JSY) on child immunization and institutional delivery rate, 18
respectively [6, 7]. A study by Prinja et al (2014) showed that the ambulance services led to increase in
institutional delivery rate [8]. Study by Gupta et al (2017) reported increase in utilization of allocated
NRHM funds for MCH strategies which correlated with improvement in health indicators. However,
implementation of NRHM was found to be partial [5]. Review of existing literature indicated that many
studies have been done on assessing the impact of NHM on health, but most of these studies had
focused on some of its components, therefore, a comprehensive evaluation was required.
This assessment was done as part of a larger study, which was proposed by NITI Ayog, to carry out
impact of NHM components in improving the health outcomes, in quantifiable terms so that lessons can
be learnt on what has worked and what has not worked with a specific focus on financing, human
resources and governance, and study the success of the NHM in achieving its said objectives while
focusing on areas of improvements and actionable recommendations in context to the framework
of Ayushman Bharat and India’s commitment for SDG Goals, UHC and Health Equity. There were
three components of the larger study including:
1. Impact of NHM on health outcomes
2. Impact of NHM on Health care spending and finances.
3. Impact of NHM on Health systems, Governance and HRH
We have focused on the first component and assessed the impact of NHM on health outcomes by
synthesizing the existing evidence and performing secondary data analysis using national level data
sources such as National Sample Survey Organization (NSSO), National Family Health Survey (NFHS),
Sample Registration System (SRS), and Rural Health Statistics (RHS).
OBJECTIVES
1. To synthesize the evidence on impact of National Health Mission on health outcomes by
conducting the systematic review.
2. To evaluate the impact of National Health Mission on health care utilization, heath outcomes
and health care inequalities by secondary data analysis.
19
METHODS
Evaluation Framework
We have considered the logic model i.e., Input-process-output-outcome-impact model for evaluation [9].
Inputs include the various NHM strategies (e.g., number of ASHAs recruited), the processes include the
implementation of strategies/activities (e.g., number of ASHA’s trained in providing reproductive and
child health care), outputs include the activities done/completed (e.g., number of pregnant women
contacted by ASHA’s in the village and counselled for institutional deliveries), outcomes include the
coverages (e.g., institutional delivery rate) and impact includes the effect on the mortality rates (e.g.,
reduction in maternal mortality ratio). The underlying principle of the logic model evaluation framework
is that unless the inputs and processes are in place you might not achieve outputs, and unless you
achieve the particular outputs you might not achieve outcomes and the resultant impact of the program.
Objective wise methodology is described below
Methodology of Objective 1
To synthesize the evidence on impact of National Health Mission on health outcomes by
conducting the systematic review.
Study design
We did systematic review to synthesize the evidence on impact of National Health Mission’s strategies
on health outcomes, as per Preferred Reporting Items for Systematic Reviews and Meta-Analysis
(PRISMA) guidelines. The PRISMA checklist is presented in Annexure 1 and protocol of the systematic
review as per the outcome variables is presented in Annexure 2.
Eligibility Criteria of studies
Publication period considered 20
Studies published between the years 2005 and 2019 were searched.
Geographical area
All states and union territories of India.
Participants
Pregnant women, antenatal women, postpartum women, neonates, infants, children up-to the
age group of 5 years , women in reproductive age group (15-49 years), eligible couples,
adolescents, ASHA workers, ANMs.
Interventions
NHM strategies considered for review included:
• Health System Strengthening: Availability of free Medicines, free Diagnostics and free diet in
the health facilities, National Ambulance services, National Mobile Medical Units (NMMUs),
Infrastructure development
• Human Resource Strengthening: Availability of Medical Officers (MOs), specialists, Auxiliary
Nurse Midwives (ANMs).
• Communitization: Accredited Social Health Activist (ASHA), Village Health Nutrition Day
(VHNDs), Village Health, Sanitation and Nutrition Committee (VHNSCs).
• Reproductive health strategies: Family planning services, newer contraceptives.
• Maternal health strategies: Janani Suraksha Yojana (JSY), Janani Shishu Suraksha Karyakram
(JSSK).
• Neonatal Health strategies: Facility Based Newborn Care (FBNC).
• Child health strategies: Immunization, Nutritional Rehabilitation Centres (NRCs), Home Based
Post Neonatal Care (HBPNC), Integrated Management of Neonatal and Childhood Illness
(IMNCI), Rashtriya Bal Swasthya Karyakram (RBSK), Acute Respiratory Infection (ARI) and
Diarrhoea control. 21
• Adolescent health strategies: Weekly Iron Folic Supplementation (WIFS), Rashtriya Kishor
Swasthya Karyakram (RKSK), Adolescent Friendly Health Clinics (AFHC), Menstrual Hygiene
Scheme (MHS)
NHM strategies NOT considered for review were:
Strategies like Communicable and Non communicable disease and monitoring progress (IPHS,
CRM, and JRM) have not been considered in this review.
Other interventions considered for review were:
• Road connectivity
• Mobile connectivity
• Water supply
• Sanitation
Comparisons
As applicable depending upon the study design.
Outcome
The outcome variables were:
Maternal Mortality Ratio (MMR)
Institutional delivery rate
Perinatal Mortality Rate (PNMR)
Neonatal Mortality Rate (NMR)
Infant Mortality Rate (IMR)
Under 5 Mortality Rate (U5MR) 22
Total fertility rate (TFR)
Contraceptive Prevalence Rate (CPR)
Full immunization coverage
Decrease in nutrition among children
Increase in Vitamin A supplementation
Early detection and treatment of childhood illnesses
Proportion of adolescents utilizing Adolescent Reproductive and Sexual Health (ARSH) services
Proportion of girls aware of menstrual hygiene and using sanitary napkins
Geographical, socioeconomic maternal health inequalities
Geographical, socioeconomic and gender child health inequalities
Study design
Studies with any study design such as randomized control trials, cluster randomized control trials, quasi
experimental, before-after studies, cohort, case control, cross sectional and qualitative studies were
included.
Information Sources
Studies were searched systematically using databases like PubMed, EMBASE, Google and Google
Scholar, and databases of agencies like Ministry of Health and Family Welfare (MoHFW), National
Health Systems Resource Centre (NHSRC), United Nations International Children’s Emergency Fund
(UNICEF), World Health Organization (WHO). Unpublished studies or grey literature, non-human
studies, studies with a focus on other countries, published in language other than English or as abstract
only were excluded in this review. 23
Search
Medical Subject Headings (MeSH) words in relevance to each strategy and outcomes were prepared
for searching potential studies. (Annexure 3). The search strategy was prepared by two researchers
independently. The cross references given in the selected articles were also searched to identify more
relevant articles. Further, hand-searching of the contents of reputed public health journals and
conference proceedings was conducted.
Study Selection
A two-stage screening process was followed based on pre-defined and explicit inclusion and exclusion
criteria:
1. First stage: Articles were included based on the title and abstract
2. Second stage: Selected Articles were further screened and included based on the full-text
Criteria for assessing the quality of the studies
The quality of eligible studies was assessed based on three criteria:
1. Indexing of journal in PubMed or Scopus.
2. Studies having sufficient sample size.
3. Confounding variables controlled in the analysis.
The studies were graded on the basis of above criteria as explained below:
Table 2. Grading of studies based upon quality.
Quality Description
(+++) Very Good Studies fulfilling all the three criteria.
(++) Good Studies fulfilling any two criteria. 24
(+) Adequate Studies fulfilling any one criteria
Data collection process
The data was extracted from the selected studies by two independent reviewers using standard data
extraction forms. The discrepancy between the two researchers was resolved by involving the third
reviewer.
Data analysis and synthesis of results
The statistical analysis approach developed by Cochrane collaborations was applied to
synthesize data [10].
The possibility of conducting a meta-analysis was kept open depending upon the
availability of studies with similar intervention and outcome and study design. The pooling of results
was undertaken after considering clinical and methodological heterogeneity using statistical
software Review Manager version 5.1 (RevMan) or STATA for meta-analysis.
Logic model was used to synthesize the evidence from good quality studies and the pathways for the
impact of the NHM strategies on health care utilization, health inequalities and maternal and child
mortality were identified. As per this framework, NRHM's interventions are the inputs leading to the
outputs, outputs in turn leads to outcomes and outcomes lead to impact of the program. The outputs are
relatively immediate effects that are expected to happen due to inputs and processes such as
improvement in availability of MCH facilities. The outcomes represent the objective of interventions such
as increase in utilization of MCH facilities and impact refers to the health indicators such as reduction in
mortality indicators. In the framework the arrows have been used for showing the relation between input,
output, outcome and impact. The thickness of the arrows indicates the strength of evidence (determined
by the quality criteria of the studies) of that intervention on the outputs as shown in Figure 3 below.
Figure 3. Relation between thickness of arrow and strength of evidence. 25
Methodology of Objective 2
To evaluate the impact of National Health Mission on health care utilization, health outcomes and
health care inequalities by secondary data analysis.
For objective 2, we did secondary data analysis and used logic model evaluation framework for
measuring the impact of NHM on health outcomes. The input, process, output, outcome and impact
indicators were obtained from available national level data sources (rural health statistics, national family
health surveys, national sample survey organization, sample registration system, census, national
health accounts etc.). These indicators were compared from the status before the year 2005 (pre NHM
period), and after the year 2015 (post NHM period). For the analysis, if the recent data was available
after the year 2015, it was accordingly used (like National Health Accounts).
Data sources
Indicators related to financing such as public health expenditure and out of pocket health expenditure
as percentage of the total health expenditure, and per capita public health expenditure were computed
using National Health Accounts (NHA) data [11]. The primary data on public and private sector utilization
and associated out-of-pocket expenditure on hospitalization and deliveries were obtained from National
Sample Survey Organization (NSSO), 60th (2004), 71st (2014) and 75
th
(2018) round data [12, 13].
NSSO conducts recall based household surveys on various topics including health, consumer
expenditure and employment.
Arrow thickness Strength of evidence
Very strong
Strong
Intermediate
Weak 26
The set of information on health system strengthening and human resources was obtained from Rural
Health Statistics (RHS) reports, year 2005 to 2018 [14, 15], ASHA updates, year 2010 to 2019 [16] and
Registers of Professional Councils [14, 15].
The status of National Health Mission’s outcome indicators (also known as dependent variables) and
predictor variables were obtained from the nationally representative demographic survey, National
Family Health Survey (NFHS), round 3 (2005-06) [17] and National Family Health Survey, round 4
(2015-16) [18]. Data was collected from:
109,041 households and 124,385 women, interviewed in NFHS round 3 [17]
628,892 households and 689,246 women, interviewed in NFHS round 4
[18]
Information on neonatal mortality rate was obtained from NFHS. Data on infant mortality rate was
obtained from NFHS and Sample Registration System (SRS) [17-19]. Latest Child Mortality Estimates
were used for child health indicators as obtained from SRS or Unicef’s mortality estimates. Data on
maternal mortality ratio was obtained from SRS year 1990 to 2016 [19].
The information on socio-demographic variables, road density, telephone density and health worker
density were collected from NFHS [17, 18], Ministry of Road transport & Highway [20, 21], Department of
Telecommunications [22], Rural Health Statistics, Registers of Professional Councils [14, 15] and ASHA
updates [16], respectively.
Input/process indicators
Financing indicators
Total health expenditure: Total health expenditure constitutes current and capital expenditures
incurred by Government and Private Sources including external funds.
Out of pocket expenditure (OOPE): Out-of-Pocket Expenditures on Healthcare (OOPE) are payments
made by an individual at the point of receiving healthcare goods and services. 27
Catastrophic health expenditure for hospitalization: Catastrophic health expenditure for
hospitalization (or delivery) is defined as the health expenditure of a household due to hospitalization
(or delivery) being above 25% of the usual household consumption expenditure over last one year from
the date of survey.
Health System strengthening and Human Resource indicators
Hospital beds: Number of government hospital beds per 1000 population.
Auxiliary Nurse Midwife (ANMs): Number of ANMs per 10,000 population in rural areas.
Accredited Social Health Activist (ASHA): Number of ASHAs per 10,000 population.
Doctors: Number of doctors (Allopathic doctors, AYUSH doctors, dental surgeons) per 10,000
population in primary health centres (PHCs) and community health centres (CHCs).
Nurses: Number of nurses per 10,000 population in PHCs and CHCs.
Health Output/Outcome indicators
Maternal Health Indicators
First Trimester Registration: First antenatal care visit during first three months of pregnancy.
Three ANC Check-ups: Women getting at least 3 Antenatal care check-ups during pregnancy.
Adequate ANC: The antenatal care was termed adequate if any four of these seven criteria were met.
1. Weighed during Pregnancy
2. Blood pressure taken during pregnancy
3. Told about complications during pregnancy
4. Told about place to go in case of complications
5. Urine sample taken during pregnancy
6. 100 IFA tablets given during pregnancy
7. Blood sample taken during pregnancy
Two Doses of Tetanus Toxoid Injection: Two doses of tetanus toxoid injection one month apart before
delivery if the woman has not previously been vaccinated. One dose of tetanus toxoid injection if the
woman had two doses of tetanus toxoid injection in the previous pregnancy within 3 years of the current
pregnancy. 28
100 Iron Folic Acid Tablets: Received 100 iron folic acid tablets during the pregnancy for the most
recent live birth.
Anaemia during Pregnancy: Woman with haemoglobin of less than 11mg/dl was considered to be
anaemic.
Institutional Delivery: Delivery in public, private, NGO / Trust hospital or health facility.
Postnatal Check-up: The woman who received a postnatal check-up.
Child Health Indicators
Breast feeding within an hour: Provision of mother's breast milk to infants within one hour of birth is
referred to as “early initiation of breastfeeding”
Exclusive Breastfeeding: Infant received only breast milk for first six months of life. This was estimated
for infants who were in the age group of 6-12 months.
Fully Immunized Children: To be called fully immunized, a child aged 12-23 months must have received
one dose of BCG vaccine, which protects against tuberculosis, three doses of DPT vaccine, which protects
against diphtheria, pertussis (whooping cough), and tetanus toxoid injection, three doses of polio vaccine
and one dose of measles vaccine. Children aged 12-23 months who received specific vaccines (BCG,
DPT1, DPT3, Measles and vitamin A1) at any time before the survey, ascertained by either vaccination
card or mother’s report.
Acute Respiratory Infection Incidence: Children under five years of age with symptoms of short, rapid
breathing which is chest-related and/or difficult breathing which is chest-related in the 2 weeks preceding
the survey.
Diarrhoea Incidence: Children under five years of age with diarrhoea at any time in the 2 weeks
preceding the survey.
Diarrhoea Treatment or Advice: Children under five years of age with diarrhoea at any time in the 2
weeks preceding the survey, for whom advice or treatment was sought.
Number of days after Treatment for Diarrhoea was sought: Days after which advice or treatment for
diarrhoea was sought for children under five years of age.
Reproductive Health Indicators
Family Size: Total number of children alive at the time of the survey who were given birth by women. 29
Contraception Rate: The currently married women aged 15-49 years who currently use any method of
contraception (female sterilization, male sterilization, condom, intra uterine devices and contraceptive
pills).
Impact Indicators
Infant Mortality Rate (IMR): Number of deaths per 1000 live births of children at ages 0 to 11 months
for three years preceding the survey.
Neonate Mortality Rate (NMR): Number of deaths per 1000 live births of children at age 0 to 1 month
for three years preceding the survey.
Maternal Mortality Ratio (MMR): Number of maternal deaths per lakh live births.
Covariates
Socio-Demographic variable: The socio demographic variables are given below:
Type of House: Houses were categorized into three groups: kuccha house, pukka house and kuccha
pukka house. If wall, roof and floor of house were pukka then house was considered as pukka, kuccha
pukka if any of two (wall, roof and floor) are pukka and if any of two (wall, roof and floor) are kuccha, house
is defined as kuccha.
Cooking Fuel: Cooking fuel used by respondents has been categorized into three categories:
LPG/electricity, kerosene and biomass.
Availability of Toilet (Sanitation): Toilet facility used by household is classified into two categories: No
toilet facility and availability of toilet facility.
Source of Drinking Water: Improved sources of drinking water include piped water, public taps,
standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, and community reverse
osmosis (RO) plants.
Religion: Religion has been categorized into four groups: Hindu, Muslim, Christian and others (Sikh, Jain,
Buddhist, Jewish, Parish etc.)
Caste: Caste of respondent has been categorized into four groups: scheduled caste (SC), scheduled tribe
(ST), other backward class (OBC) and others (general). 30
Maternal Age: Current maternal age is classified in 5-year groups: (15-19), (20-24), (25-29), (30-34), (35-
39), (40-44) and (45-49) years.
Maternal Education: This is a standardized variable providing level of education in the categories: no
education, primary, secondary and higher.
Wealth Index: The wealth index is a composite measure of a household's cumulative living standard. The
wealth index is calculated using data on a household’s ownership of selected assets, such as televisions
and bicycles; materials used for housing construction; and types of water access and sanitation facilities.
It is categorized into five groups: poorest, poorer, middle, richer and richest.
Place of Residence: Whether the respondent is a usual resident of urban or rural area.
Road Density: It is kilometres of roads for 1, 00,000 population in the particular state. It excludes roads
constructed under Jawahar Rozgar Yojana (JRY) and Pradhan Mantri Gram Sadak Yojana (PMGSY).
Telephone Density: It is number of telephone connections for every hundred individuals living within the
particular state.
Health Worker Density: Health worker density is defined as number of doctors, dental surgeons, AYUSH
practitioners, ANMs, GNMs, LHVs, pharmacist who are registered in India and health worker (male),
health assistant and ASHAs, working in government sector; per 10,000 population in the particular state.
States: The focus of this study is on less developed Empowered Action Group (EAG) states of India,
namely, Rajasthan, Bihar, Uttar Pradesh, Madhya Pradesh, Odisha, Chhattisgarh, Uttaranchal and
Jharkhand; and Non-Empowered Action Group (Non-EAG) states.
Data Analysis
The data was analyzed using Microsoft Excel (MS-Excel), Statistical Package for Social Sciences
(SPSS), version 22, R software, version 3.5.2, Review Manager, version 5.1 (RevMan), Software for
Statistics and Data (STATA), version 13.
The NSSO 60
th
round (2004) data on expenditure was inflated year wise up to 2014 using annual
Consumer Price Index from the year 2004-05 to 2014-15. The formula used for this is given below: 31
Inflated Expenditure = (((((((((((Total*1.042) *1.058) *1.063) *1.083) *1.108) *1.119) *1.088) *1.093)
*1.109) *1.063) *1.058).
The NSSO 60
th
round (2004), 71
st
round (2014) and and 75
th
round (2018) data on expenditure was
adjusted for five confounders including religion, caste, household sanitation, and household drinking
water source and wealth status of the household. The data was subjected to cleaning and consistency
check before analysis.
By using RHS 2005 to 2019 data, number of patient beds per 1000 population in pre NHM and post
NHM period were compared. Number of ANMs (per 10,000 population), number of doctors in PHCs and
CHCs (per 10,000 population) and number of ASHA workers were estimated. Health worker’s density
(per 10,000 population) was also included in the analysis.
Data files of NFHS round 3 and NFHS round 4 were screened to select the common outcome variables
related to maternal, child (under-five) and reproductive health. The selected variables from both the data
files were merged, recoded and computed to develop indicators which can be compared between pre
NHM and post NHM period. Logistic regression was done to find out the change in the dependent
variables including maternal, child and reproductive health indicators. Poisson regression was used for
family size, negative binomial regression was done for IMR, NMR and number of days after treatment
was sought for diarrhoea. The socio demographic variables, telephone density, road density and health
worker density were adjusted to see the impact of NHM. For IMR and NMR analysis, telephone density
and health worker density were not included due to ill fit in the model. The analysis was done at all India
level to study the impact of NHM on IMR and NMR. The objective of NHM was also to reduce health
inequalities across states and various groups, hence the data was also analysed across following
domains:
1. EAG states versus Non-EAG states
2. Rural area versus Urban area
3. Caste
4. Wealth Index 32
The impact of NFHS 4 was compared with NFHS 3 for various indicators after controlling effect of social
demographic variables, road, telephone and health facilities.
Control for Confounding variables
For adjusting the confounding variables, regression methods were used. The primary exposure variable/
independent variable was pre and post NHM period. The dependent variables that were studied as per
the indicator group, confounders that were adjusted and the regression method that was used, are
presented in the table 3 below.
Table 3. The variables selected for regression analysis.
Independent
Variable
Indicator
Group
Dependent Variables Regression Covariates
Pre NHM
and Post
NHM
Maternal
Health
First trimester Registration
Three ANC Check-up
Adequate ANC care
Anaemia During
Pregnancy
100 Iron folic acid
Small size of child
Breastfeeding within one
hour
Institutional Delivery
2 Tetanus Toxoid Injection
Exclusively Breastfeeding
Postnatal Check-up
Logistic
Age
Education
Place of Residence
Religion
Caste
Type of House
Sanitation
Safe Water Supply
Cooking fuel
Wealth Index
Road Density
Telephone density
Health Worker
density
Family
Planning
Female Sterilization
Male sterilization
Condom
Intra Uterine devices
Contraceptive Pills
Contraception rate
Family Size Poisson
Child Health
Acute Respiratory
Infection
Diarrhoea
Diarrhoea Treatment or
Advice
Logistic
Number of days after
which treatment was
sought for diarrhoea
Negative
Binomial 33
BCG
DPT1
DPT3
Measles
Vitamin A1
Fully Immunized
Logistic
Age
Education
Place of Residence
Religion
Caste
Type of House
Sanitation
Safe Water Supply
Cooking fuel
Wealth Index
Road Density
Telephone density
Health Worker
density
Institutional Delivery
Infant Mortality rate
Neonate Mortality Rate
Negative
Binomial
Age
Education
Place of Residence
Religion
Caste
Type of House
Sanitation
Safe Water Supply
Cooking fuel
Wealth Index
Road Density
An interrupted time series (ITS) was also done using SRS data to evaluate the impact of the NHM
implementation on mortality. The NHM was implemented in the entire country in order to improve the
coverage of various health indicators. In such a scenario, the possibility of conducting a randomized
control trial which is being considered as gold standard for evaluating the impact of an intervention was
ruled out due to the absence of control group. This difficulty was dealt by utilizing the technique of
interrupted time series (ITS). This procedure helps to compute the change in the slopes of IMR before
and after the introduction of NHM with a two-step segmented time series regression analysis. The year
wise data obtained on IMR from SRS was divided into two parts, namely pre intervention data and post
intervention data. As the advent of NHM was considered to be the year 2005, hence this was treated as
the cut-off point. However, choosing 2005 as the cut-off point is quite early to measure the impact of
NHM implementation especially on mortality indicators, as initial few years might be utilized to develop
programme strategies and to make it functional. Therefore, we have used year 2009 as the cut-off point
especially for measuring the impact on IMR. In order to evaluate the impact and comparing the time 34
trends before and after intervention, we have utilized the method of ITS along with auto regressive
integrated moving average (ARIMA) model. This methodology of segmented time-series regression
analysis works in two steps. Firstly, the time series modelling adjusts for components like non-
stationarity, seasonality (depending upon the data) and auto-correlation. Secondly, the multiple linear
regression helps to calculate the estimates for change in level and trend separately, considering the
adjusted time series as an outcome variable in the regression equation [23]. A change in level is defined
as the difference between the observed level at the first intervention time point and that predicted by the
pre-intervention time trend, and a change in trend is defined as the difference between post- and pre-
intervention slopes. Finally, a positive (negative) change in level and slope indicates an increase
(reduction) in outcome variable. As stated earlier, the outcome variables in our analysis was IMR. The
following equation summarizes this multiple linear regression approach:
??????=�+ �
1�+�
2??????ℎ??????�??????+ �
3??????��??????�????????????�??????�� (1)
As a part of this analysis, the adjusted time series of outcome variable is included in the first variable
‘Y’. The time variable ‘t’ includes the time points of observations. The phase variable is coded as 0 and
1 for pre and post-intervention period respectively. Finally, the fourth variable ‘Interaction’ takes zero
value up to year 2005, beyond which it takes up the same value as that of variable ‘t’. Now, the coefficient
�
1of time ‘t’ yields the slope of the regression line pre-intervention, �
2 represents the change in intercept
and coefficient �
3of ‘interaction’ gives the change in slope from pre- to post-intervention.
It is important to note that in order to evaluate the impact of the intervention using ITS method, the
sufficient number of observations before and after the intervention was available only in case of IMR at
the national and state level [23]. In fact, the MMR reported in the various surveys provide the data in a
span of three years which resulted in the insufficient observations for utilizing the technique of ITS.
Although, the U5MR is not reported at the intervals of three years but the data on this indicator was
available 2008 onwards constituting only 9 observations to the present date. Apart from this, this was
not available before the inception of intervention rendering this to be inappropriate for the comparison
purpose. Hence, the impact of the NHM is evaluated only considering the IMR at national and state
level. These estimates of pre slope, post slope and change at the juncture for all the states are computed 35
by applying ARIMA (1, 0, 0) while adjusting for trend, auto correlation imbibed in the data before
evaluating the estimate of change using a regression model mentioned in equation 1.
RESULTS
FINDINGS OF SYSTEMATIC REVIEW
Total 101,290 studies were identified that had reported the effect of NHM/NRHM on maternal (n=2759),
child (n=82023), adolescent (n=1062), reproductive (n=6261) health, and health inequalities (n=9185)
through systematic review as per the search strategy, as shown in Table 3. After removal of duplicates,
there were total 49,666 studies (2083 on maternal health, 40285 on child health, 2987 on reproductive
health, 488 on adolescent health and 3823 on health inequalities) that were eligible for screening. Out
of these, total 46,469 studies (1803 studies on maternal health, 37687 studies on child health, 2857
studies on reproductive health , 383 studies on adolescent health and 3739 studies on health
inequalities) were excluded based on title and abstract. The abstracts of remaining studies that had
reported the NHM/NRHM effect on maternal health (n= 280), child health (2598), reproductive health
(n=130), adolescent health (n=105) and health inequalities (n=84) were preliminarily selected for full text
review as per the inclusion criteria. On the basis of review of full length studies, total 2809 studies were
excluded as per the exclusion criteria (217 studies on maternal, 2385 on child, 81 studies on
reproductive, 54 on adolescent health and 72 on health inequalities). Therefore total 388 studies were
included in the final analysis as shown in figure 4. The results of all these studies have been explained
in annexure 5.
36
Figure 4. Flow chart showing the studies reviewed under systematic review and per PRISMA
guidelines.
As shown in above figure, out of total 388 studies; 63 studies focused on impact of NHM on maternal
health, 213 studies on child health, 51 studies on adolescent health, 41 studies on reproductive health
and 12 studies on health inequalities. The characteristics of these studies have been explained in
annexure 5.
The result of the systematic review is presented for the studies published during the period from
2005-13 (during NRHM implementation), and 2013-2019 (corresponding to NHM implementation).
Findings of studies reviewed for maternal health outcomes
Of the 65 studies identified for maternal health, 46 (25 pooled) were on institutional delivery and 19 on
maternal mortality ratio.
Institutional delivery 37
The description of the studies which were pooled and not pooled are given in Annexures 5.1.2 and
5.1.2.3 respectively. There were 25 studies [24-48] which were pooled and 21 studies which were not
pooled [7, 44, 49-67].
Systematic review of studies on maternal health published before the year 2013, found that institutional
deliveries increased after introduction of Janani Suraksha Yojana (JSY) as cash incentives under JSY
had positive association with institutional deliveries[7, 26, 31-34, 54]. But not all beneficiaries of JSY had
opted for institutional deliveries [31, 32, 34]. Also, cash incentives were not provided to all beneficiaries.
Coverage of JSY was also reported to be low during the early implementation period [32]. The reason
for this had been cited as low awareness among beneficiaries, not having the required documents to
prove the eligibility or administrative weakness in early stage of implementation [32]. It is also reported
that JSY scheme had increased the number of institutional deliveries without making effort to promote
quality antenatal care (ANC) and early detection and treatment of complications [53]. Studies published
after 2013, have shown that JSY was effective in increasing the institutional delivery rate [47, 48, 68].
Significant increase in institutional deliveries was also observed after the introduction of free referral
transport [8]. In the EAG states as a whole, there was an increase of 13%- 40% points in the uptake of
institutional delivery in during NHM period [64]. ASHA had played significant role in increasing
institutional deliveries by behaviour change and communication. There were 3 studies on ASHAs which
showed that ASHAs have also played a major role in improving maternal health by enhancing the
knowledge of pregnant women/mothers [45, 69, 70]. Positive relationship was found between visit of
ASHA and utilization of maternal health services [65].
The pooled institutional delivery rate from 25 studies [24-48] with number of pregnant women ranging
from 147 to 182869 was found to be 71.2% from the year 2007-2018 after meta-analysis done in this
study. (Figure 5). Of these 25 studies, 16 were on JSY, 3 on ASHA, 2 on birth preparedness and
complication readiness and 2 on referral transport, 1 on Janani Sishu Suraksha Karyakaram and 1 on
antenatal care. 38
Figure 5. Forest plot of studies on institutional deliveries.
Heterogeneity= 99.69% (very high because of sample size variability)
Maternal Mortality Ratio
Systematic review of 19 studies [57, 58, 61, 71-86] on maternal health found that during NHM period
there has been decline in MMR. The detailed description has been given in annexure 5.1.1. The decline
in MMR was observed in 16/19 studies. Results from 16 studies found that range of MMR reduction
varied from 7% to 71.1% during NHM period after implementation of strategies like JSY, referral
transport, institutional deliveries. On the contrary, increase in maternal deaths reported in the tertiary
care hospitals due to increase in the load of institutional delivery in three studies, indicating poor quality
of intranatal services [84-86].
Overall (I^2 = 99.69%, p = 0.00)
Govil D et al.(2013)
Limm et al(2010)
Mukhopadhyay et al.(2016)
Sidney K et al.(2014)
Mukhopadhyay DK et al.(2016)
Farah N. et al, (2015)
Ved R et al.(2012)
Vikram K et al.(2011)
Kilaru A. et al.(2010)
Siddaiah A et al.(2018)
Kumar S et al. (2017)
Sidney K et al.(2012)
Strehlow MC at el. (2016)
Khes SP et al.(2017)
Kaur H. et al.(2015)
Uttekar BP et al.(2007)
Kumar et al(2015)
Mukhopadhyay DK et al.(2013)
Mandal DK et al(2010)
Study
Amudhan S et al(2013)
Salve H et al. (2017)
Nipte D. et al.(2015)
Sinha S. et al. (2012)
Seth A et al. (2017)
Panja TK et al.(2012)
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
-.50.511.5 39
Findings of studies reviewed for child health outcomes
It is reported that NHM has been successful in reducing neonatal, infant mortality, under five mortality
and perinatal mortality rate over a period of time, through implementation of the schemes like Home
based Post Neonatal Care (HBPNC), Facility Based Newborn Care (FBNC), Sick Newborn Care Units
(SNCUs), Integrated Management of Neonatal And Childhood Illness (IMNCI), Essential Newborn Care
(ENC) training, JSY, ASHA.
Neonatal Mortality Rate
Three studies reported impact of NRHM/NHM on neonatal mortality [57, 87, 88] (Annexure 5.2.2). Eight
studies were focused upon specific strategies of NHM and neonatal mortality rate as an outcome [89-
96] (Annexure 5.2.3). Six studies were having essential newborn care practices as an intervention [70,
97-101] (Annexure 5.2.4). Four studies were based upon FBNC [102-105] (Annexure 5.2.5). IMNCI was
an intervention in eight studies [94, 106-112] (Annexure 5.2.6 and 5.2.11). Secondary data was
analysed in 5 studies [113-117] and ten studies were found with HBPNC by ASHAs as an intervention
[69, 118-126] (Annexure 5.2.7). In a recent study by Bora et al (2018), it is reported that for reaching
sustainable development goal 3 target for 2030 for the NMR and the U5MR, the estimated NMR for India
for the period 2015-16 is about 2.4 times higher, while the estimated U5MR is about double [117]. They
have done the district wise analysis and observed that only 9% districts have already reached the NMR
SDG targets (12/1000 live births), while 1/3 (177) will not be able to achieve this target. Majority of the
high districts are located in EAG states, but a few also fall in rich and advance states.
Six studies were found reporting early neonatal mortality as an outcome (annexure 5.1.1) [57, 87, 90,
127-130]. The studies published before 2013 period reported that average annual rate reduction (AARR)
in early neonatal mortality rate (ENMR) was found to be more (4.3) in post NRHM than pre NRHM period
(-3.8). Average annual rate reduction (AARR) in early neonatal mortality rate (ENMR) in three epochs
(pre-NRHM 2002-05, early post NRHM 2006-09, and later post NRHM 2010-13) was -3.8, 2.5 and 4.3
[57]. Decline in ENMR for rural areas was 6 points (19%) from 2005 to 2013, and in urban areas it was
5 points (31%). Post 2013 period, ENMR declined from 28 to 22, indicating a point decline of 6 and 40
percentage decline of 21%. The maximum point decline was seen in Orissa (13 points) and minimum in
Himachal Pradesh and Jharkhand (2 and 0 point each) [131]. The NMR declined from 37 to 28 indicating
a point decline of 9 and percentage decline of 24% [57, 88, 95, 131]. The maximum point decline was
seen in Orissa and Chhattisgarh (16 and 14 points, respectively) and minimum in Jharkhand (2 point).
The maximum percentage decline is seen in Punjab (47%) and minimum in Jharkhand (7%). National
NMR had declined from 37 (2005) to 31(2011) to 28(2013) per 1000 live births. NMR has declined in
almost all the states [131].
NMR was lower in those who received a visit by community health worker on day one by than in those
who received no visit [106, 108]. Neonatal mortality was significantly lower when the child’s village was
closer to the district hospital [106]. Neonatal tetanus mortality rate fell from 1·6 per 1000 live births in
2000 to less than 0·1 per 1000 live births in 2015 [132]. Average annual decline in mortality rates from
2000 to 2015 was 3·3% for neonates. ASHA had played a significant role in improving the neonatal
health through home based preventive and curative neonatal care, prioritizing and addressing neonatal
and maternal problems, and community mobilization efforts to increase the utilization of neonatal health
care services [95, 106, 108, 118]. There was reduction in neonatal mortality through participatory
meetings of ASHA with women’s groups as NMR was 30 per 1000 live-births in the intervention group
and 44 per 1000 live-births in the control group [95]. Home visits by community health workers were
associated with a reduced risk of mortality during the neonatal period. HBPNC by ASHA was found to
be an effective strategy as due to this 74% mothers started breastfeeding within the first hour, 87% fed
colostrum, and 58% mothers exclusively breastfed their newborn. Significant increase in trend of unsafe
newborn care practices (bathing baby before 48 hours, unclean cord) with regards to early bathing and
cord care with fewer visits by ASHA was found. Regarding Facility based new born care (FBNC), it
was found that there has been improvement in newborn care and survival rate (74.4%- 85%) due to
provision of manpower & equipment’s in SNCU during NHM implementation period. Only 22.8% of the
newborn care corners (NBCCs) were found to be fully functional, majority (68.4%) were partially
functional, and 9% were non-functional [102]. As per evidence form Jabalpur, MP, NMR was reduced
by 12% after provision of SNCU. Estimated neonatal deaths averted were 111(7%) out of 1590 41
admissions compared to 200(19.1%) out of 1048 admissions in previous year (p value <0.001).
Improved survival and reduced morbidity after establishment SNCUs was reported [96]. Referral out
(5%-1.7%), death rate (11.6%-9.6%), LAMA (9%-3.7%) rates were decreased after SNCU was
functional [92, 96, 102-105]. Also it was found in one study that all the health personnel were not fully
trained in Navjat Shishu Suraksha Karyakram (NSSK) [105]. Regarding Essential New Born Care
(ENBC) it was found that in the year 2011, none of the CHCs have fully equipped facility based newborn
care services (including newborn corner and newborn care stabilization unit [97], but studies published
after 2013 period showed that, safe childbirth checklist (SCC) were used in 86% of the observed
deliveries in intervention facilities in a study conducted in Rajasthan [70]. 65% newborns were breastfed
within an hour after birth and 5.9% were prelacteal fed [100]. Trained anganwadi workers had enhanced
the knowledge of childhood illness and their management as compared to IMNCI untrained counterparts
[108]. However, implementation of IMNCI had no effect on inequities in neonatal mortality [94].
The metanalysis, done as part of this study, of the pooled studies published between 2008 to 2016 found
the prevalence of low birth babies (10 studies pooled) to be 28%, and exclusive breast feeding (26
studies pooled) to be 47%, indicating that prevalence of low birth weight babies did not reduce and
exclusive breast feeding did not improve much after implementation of the neonatal health strategies
[133-142]. (Annexure 5.2.8).
42
Figure 6: Meta analysis of studies with outcome as prevalence of low birth weight babies
Infant Mortality Rate
There were sixteen studies which reported IMR as an outcome [143-158] (Annexure 5.2.9). As per
Khurmi et al study (2015), annual rate of reduction of IMR was nearly 2 percent in 2000-05 and its
previous years, but after implementation NRHM it has been accelerated to 4 percent in 2005-10 and
nearly 6 percent in 2011 [143-147]. IMR declined from 58 to 40 (for India indicating a point decline of 18
and a percentage decline of 31%. The maximum point decline was seen in Orissa (24 points) and
minimum in Mizoram (increased by 15 points) [131]. The maximum percentage decline was seen in
Tamil Nadu (43%) and minimum in Mizoram (increased by 75%).
Study published before the year 2013 showed that, 48.6% ASHAs were unaware of preventive actions
to be taken for Vitamin A and 20% of the ASHAs did not feel the need for referral for a child with diarrhoea
who is unable to drink or breast feed. Also ASHA-investigator agreement on the need to assess infants
was found to be intermediate. ASHAs had played a major role for improving knowledge of mothers 43
regarding infant care and creating awareness about exclusive breast feeding [69, 119-122]. There has
been improvement in rate of exclusive breastfeeding as the pooled prevalence of exclusive breast
feeding was found to be 47% from the year 2008-18.
Figure 7: Meta analysis of studies with outcome as Exclusive breast feeding
There were 26 studies which reported exclusive breastfeeding as an outcome [98, 159-181] (Annexure
5.2.13). Post 2013 publication period, it was found that average score of the ASHAs in child health care
was 87%, around 81% of children in immunization were motivated by ASHAs and 80.93% knew about
exclusive breast feeding correctly. Also 5.41% of the ASHA had poor, 83.78% had average and 10.81%
had good level of knowledge score regarding HBPNC respectively [125]. It was also found that, all of 44
the ASHA’s helped in immunization and 24.65% gave advice to mothers about breast feeding [126]. So
overall, it was observed that that during the early implementation of the ASHA’s scheme, her knowledge
related to vitamin A supplementation, early diagnosis and prompt referral of children suffering with
diarrhea/pneumonia was poor, and gradually with further trainings her knowledge and skills were
improved especially related to immunization but it needs to be further improved for home based post
natal care and exclusive breast feeding.
Role of IMNCI
Fourteen studies were found focused upon Integrated Management of Neonatal and Childhood Illness
(IMNCI) [70, 89, 94, 97, 101, 106-110, 112, 117, 155, 182]. The existing evidence indicated that IMNCI
implementation could reduce the infant mortality rate in an experimental setting (adjusted hazard ratio
of IMR 0.85, 95% confidence interval 0.77 to 0.94, were significantly lower in the intervention clusters of
IMNCI than in control clusters) as per Bhandari et al study (2012) [94]; and improved the skills of the
health care workers in implementation settings as per Thummakomma et al (2016) and Chishty et al
study (2016) [106, 111]. Sensitivity of IMNCI criterion in correctly identifying sick infants of age 0-2
months was 90.02%, specificity was 63.10%, positive predictive value being 92.44% and negative
predictive value is 55.79% as per Thummakomma et al (2016) study [106].
Under 5 Mortality Rate
Nine studies reported under 5 mortality rate [115, 158, 180, 183-188] (Annexures 5.2.15). NHM’s child
health strategies like NRCs, immunization, management of ARI and diarrhoea has played a significant
role in reducing Under Five Mortality Rate (U5MR). U5MR fell at a mean rate of 3.7% per year between
2001-2012, from 96/1000 live births to 57.3/1000 live births. The number of districts with >80
deaths/1000 live births also reduced from 384 to 80 districts in the same period [115]. Average annual
decline in U5MR from 2000-15 was 5.4%, annual decline from 2000-05 was 4.5%, and annual decline
from 2005-15 was 5.9%. Decline in mortality rate from pneumonia was found to be 63%, decline in 45
diarrhea rate was 66% and decline in measles mortality rate was 3.3 to 0.3/1000 live births [132].
Proportion of Under 5 Mortality in Vitamin A supplemented children vs. non supplemented was 8.4%
vs.11.4% [186].
Studies on immunization coverage (annexure 5.2.15) found that strategies under NRHM such as Mission
Indradhanush, financial assistance from JSY had played a significant role in improving vaccination
coverage [6, 63, 188-207]. Meta analysis of 16 studies found the pooled immunization coverage among
children to be 77% from the year 20014-19 (Figure 8). The improved vaccination coverage was also
found to be associated with decrease in ARI and diarrhea in children as the incidence was less in
immunized children than non-immunized children [189, 192-195].
Figure 8: Meta analysis of studies on full immunization coverage
46
Studies on National Rehabilitation Centers (NRCs) showed that NRCs were good initiative under NHM
as percentage of pooled recovered children under NRCs was 77% as per metaanalysis of the studies
from the year 2012-18 (Figure 9) [208-222].
Figure 9: Meta analysis of studies with outcome as recovered children under NRC
Studies published after the year 2013 showed that , only 25% of the children in India received vitamin A
supplementation (VAS), rural children (72%) and children of educated mothers were more likely to
receive vitamin A supplementation than others (urban- 28.2%). There was an Increase in the mean full
VAS coverage in seven states from 44.7% to 67.3%. Also there was 40.3% annual decrease in the
number of poor children who did not receive two VAS doses [186, 223-225] (Annexure 5.2.16).
Other child health strategies like rashtriya bal swasthaya karyakaram (RBSK) has also played an
important role in screening, early diagnosis and management of severe illnesses like heart disease, birth 47
defects [226, 227]. However, its impact on reduction on under 5 child mortality is not documented in the
existing literature.
Perinatal mortality
Fourteen studies reported perinatal mortality rate as an outcome [26, 52, 127, 228-238]. The studies
have been described in annexure 5.2.1. Singh S et al (2017), has reported that in rural areas of India,
hospital deliveries have increased during 2005–2013 from 24.4% to 69.7% and PNMR has declined
from 40 to 28 per 1000 births. At the national level, in the rural areas, relative increase in hospital
deliveries was 185.7% and relative decline in PNMR was 30% and it was significantly correlated. At the
state level, there was significant correlation between the rise in hospital delivery rate and decline in
PNMR (r 0.4, p 0.04) [52]. There is further evidence that have shown that increase in institutional delivery
rate had reduced the perinatal mortality rate [declined from 41.3 to 34.6 (p=0.008) deaths per 1,000
births in Belgaum and from 47.4 to 40.8 (p=0.09) in Nagpur) and still births (declined from 22.5 to 16.3
per 1,000 births in Belgaum and from 29.3 to 21.1 in Nagpur (both p=0.002)] in southern and central
India, respectively [239]. Earlier it was reported that implementation of JSY had impact on reducing
perinatal mortality due to increase in institutional deliveries, antenatal check-up, and referral of the
women. The studies published before 2013 showed that, JSY payment was associated with a reduction
of 3·7 perinatal deaths per 1000 pregnancies due to increase in institutional deliveries, antenatal check-
up, and referral of the women [26]. There is also evidence that essential newborn care trainings for
those involved in conducting deliveries (medical officers, nurses, ANMs, informal birth attendants) had
reduced the perinatal mortality rate from 52 per 1000 to 36 per 1000, and hence considered effective in
reducing the PMR [231].
Still birth rate
There was a total of 25 studies which reported still birth rate as an outcome [68, 90, 127, 128, 182, 228-
230, 233, 234, 237, 240-250]. The studies have been described in annexure 5.2.1. The studies that used
the data between 2005-13 showed that the range of Still Birth Rate (SBR) was between 33.7 to 47 per 48
1000 births. [228, 229, 237, 238, 240, 244]. Essential Newborn care training was found to be associated
with reduction in SBR from 23 to 15.9 per 1000 live births [228].
Evidence from the studies published after 2013 showed that, the range of SBR was between 15.4 to
26.5 per 1000 births [246, 247, 249]. Annual decline rate of SBR was found to be 4.5% (from 31.3 to
23.8 per thousand live births) from the year 2010 to 2016 in one of the study [247]. State specific results
are on still births especially from Bihar are obtained from Dandona et al study, (2017, 2019) [131, 249].
Incidence of stillbirths was 21.2 per 1,000 births in Bihar state in the year 2014-15 and it declined to 15.4
per 1000 births in 2016, higher proportion of births was stillborn among those women for whom the
delivery was deferred. [249]. It was also found that in rural communities of India, there was a significant
reduction in SBR from 23 to 15.7 per 1000 births and the rate of stillbirths by delivery attendant
decreased significantly for nurses/midwives but not for physicians [250].
Findings of studies reviewed for reproductive health outcomes
Studies published after the year 2013 found that TFR has been declined after the implementation of
NRHM due to increase in the contraceptive prevalence rate (CPR), and increase in literacy rates [251-
258] (Annexure 5.3.1). This is close to the target of achieving at least 60% CPR to attain the goal of total
fertility rate of 2. The prevalence of contraceptive usage was found to be less among tribal population
[259]. The knowledge about contraception was found to be high among males and females, but
acceptance was poor among males. The tracking of eligible couples and motivating them for using
contraception for spacing as well as delay in first pregnancy was an effective strategy implemented by
ASHA. ASHAs performance was increased upto 1.13 times for eligible couples and 1.14 times for
couples having two or less children after introduction of an incentive. From April 1, 2013, a new scheme
was introduced in “ASHA INCENTIVE SCHEME” for promoting family planning—permanent sterilization.
It is an incentive of Rs. 1,000 given to an ASHA who motivates and promotes couples having two or less
than two children to undergo permanent sterilization [260]. Incentive based performance showed a
significant impact on motivation of eligible couples for using contraceptive methods by ASHAs. It was 49
also found that the engagement of male counterparts have improved the performance of ASHA program
(statistically non-significant) which unveils the complementarity of male and female CHWs in increased
demand for MNCH services [122, 260-262]. ASHA's capacity was found to be low in motivating family
planning cases for restricting high fertility in rural areas (30.49%). Meta-analysis of 22 studies [236, 259,
263-281]found the pooled CPR to be 54% from the year 2007-17 (Figure 10). (Annexure 5.3.2)
Figure 10: Meta-Analysis of studies on CPR
Result of studies reviewed for adolescent health outcomes
There has also been improvement in adolescent health indicators due to NRHM strategies such as
Weekly Iron and Folic Acid Supplementation (WIFS), Adolescent Reproductive and Sexual Health
(ARSH) and Menstrual Hygiene Scheme (MHS). WIFS program is a good initiative and compliance was
also found to be satisfactory [282-290] Annexures 5.4.1 - 5.4.3). Studies published before the year 2013
showed significant decline in anemia due to WIFS revealing that IFA daily is an effective strategy of
reducing the anemia in adolescents [92, 287]. Studies published after 2013 showed less knowledge 50
about anemia among adolescent girls [291]. It was also found that reduction of anemia was more among
adolescent boys as compared to adolescent girls. The compliance to the WIFS program was 85.8%
[292]. Pooled prevalence of anemia among adolescents was found to be 43% from the year 2008-17
(Figure 11). Also meta-analysis of 4 RCTs found 2% pooled reduction in anemia from the year 2009-16
(Figure 12).
Figure 11: Meta-analysis of 5 cross sectional studies on WIFS
Figure 12: Meta analysis of 4 RCTs on WIFS
51
Studies published before 2013 had shown poor knowledge about menstruation. It was also found that
the usage of sanitary pads was more in urban as compared to rural areas. However studies published
after 2013 found that in post NRHM period usages of sanitary napkins had been increased. And the
pooled prevalence of usage of sanitary napkins was found to be 58% from the year 2012-19, after meta-
analysis (Figure 13) [178, 293-308]. Also the girls were less aware of government providing sanitary
napkins on subsidized rates [72, 298, 309-311].
Figure 13: Meta-analysis of studies on usage of sanitary napkins
NRHM has also raised the awareness about menstrual hygiene among adolescents. However, the
knowledge about menarche was more among urban girls as compared to the girls living in a slum.
Meta analysis of 15 studies found the pooled awareness of menstrual hygiene to be 43 % from the
year 2011-19 (Figure 14).
Overall (I^2 = 98.96%, p = 0.00)
Mamilla 2019
Study
Jain et al 2017
Chaudhary & Gupta 2019
Rana et al 2015
Kansal et al 2016
Deshpande et al 2018
Agarwal et al 2017
Vijayshree et al 2016
Udayar et al 2016
Dudeja et al 2016
Krishnaleela 2018
Paria et al 2014
Paul et al 2014
Shah et al 2013
Thakre et al 2012
Ramchandra et al 2016
0.58 (0.46, 0.70)
0.84 (0.77, 0.89)
ES (95% CI)
0.79 (0.74, 0.83)
0.43 (0.39, 0.48)
0.39 (0.34, 0.44)
0.28 (0.25, 0.32)
0.60 (0.50, 0.69)
0.15 (0.11, 0.20)
0.78 (0.72, 0.83)
0.78 (0.73, 0.83)
0.91 (0.86, 0.94)
0.55 (0.48, 0.62)
0.55 (0.51, 0.59)
0.74 (0.70, 0.78)
0.32 (0.26, 0.40)
0.49 (0.44, 0.54)
0.69 (0.65, 0.73)
100.00
6.21
Weight
6.27
6.27
6.27
%
6.30
6.07
6.28
6.26
6.27
6.29
6.20
6.28
6.29
6.19
6.26
6.29
0.58 (0.46, 0.70)
0.84 (0.77, 0.89)
ES (95% CI)
0.79 (0.74, 0.83)
0.43 (0.39, 0.48)
0.39 (0.34, 0.44)
0.28 (0.25, 0.32)
0.60 (0.50, 0.69)
0.15 (0.11, 0.20)
0.78 (0.72, 0.83)
0.78 (0.73, 0.83)
0.91 (0.86, 0.94)
0.55 (0.48, 0.62)
0.55 (0.51, 0.59)
0.74 (0.70, 0.78)
0.32 (0.26, 0.40)
0.49 (0.44, 0.54)
0.69 (0.65, 0.73)
100.00
6.21
Weight
6.27
6.27
6.27
%
6.30
6.07
6.28
6.26
6.27
6.29
6.20
6.28
6.29
6.19
6.26
6.29
-.50.511.5 52
Figure 14: Meta analysis of 15 studies on awareness of menstrual hygiene
ARSH program was found to be a good initiative under NHM and the pooled awareness of Adolescent
Friendly Health Clinics (AFHCs) was found to be 49% from the year 2009-18, after doing meta-analysis
of 10 studies (Figure 15) [312-319] (Annexure 5.4.4).
Overall (I^2 = 98.44%, p = 0.00)
Chaudhary & Gupta 2019
Paul et al 2014
Nagaraj 2016
Ramchandra et al 2016
Ray et al 2012
Dudeja et al
Shah et al 2013
Mamilla 2019
Study
Syed 2017
Vijaykeerthi et al 2016
Paria et al 2014
Sivakami et al 2019
Kansal et al 2016
Prateek et al 2011
Deshpande et al 2018
0.43 (0.34, 0.52)
0.64 (0.59, 0.68)
0.73 (0.69, 0.76)
0.30 (0.25, 0.35)
0.15 (0.12, 0.18)
0.42 (0.35, 0.49)
0.56 (0.50, 0.63)
0.40 (0.32, 0.47)
0.60 (0.51, 0.68)
ES (95% CI)
0.67 (0.60, 0.74)
0.46 (0.40, 0.51)
0.38 (0.34, 0.42)
0.40 (0.38, 0.42)
0.27 (0.24, 0.30)
0.20 (0.16, 0.26)
0.24 (0.17, 0.33)
100.00
6.74
6.76
6.70
6.80
6.58
6.60
6.54
6.45
Weight
6.60
6.69
6.76
6.83
6.78
%
6.70
6.47
0.43 (0.34, 0.52)
0.64 (0.59, 0.68)
0.73 (0.69, 0.76)
0.30 (0.25, 0.35)
0.15 (0.12, 0.18)
0.42 (0.35, 0.49)
0.56 (0.50, 0.63)
0.40 (0.32, 0.47)
0.60 (0.51, 0.68)
ES (95% CI)
0.67 (0.60, 0.74)
0.46 (0.40, 0.51)
0.38 (0.34, 0.42)
0.40 (0.38, 0.42)
0.27 (0.24, 0.30)
0.20 (0.16, 0.26)
0.24 (0.17, 0.33)
100.00
6.74
6.76
6.70
6.80
6.58
6.60
6.54
6.45
Weight
6.60
6.69
6.76
6.83
6.78
%
6.70
6.47
-.50.511.5 53
Figure 15: Meta-analysis of 10 cross sectional studies on ARSH
Result of studies reviewed for health inequalities
Studies published after the year 2013 period showed that, the inequalities related to institutional delivery
among rich and poor declined at steeper rate in post NRHM time period due to JSY and free ambulance
services [5, 45, 61, 64, 73, 80, 320-330] (Annexure 5.5). Secondary data analysis of the DLHS data
(round 1, 2, 3 and 4) by Vellakkal S et al (2017), have shown that socioeconomic inequalities for
institutional deliveries and ANCs have been reduced in the EAG and NE states. In the EAG states as a
whole, the uptake of ANC for the lowest, middle and highest wealth tertiles decreased by 5.3%(=-0.
053; P<0.001), 8.0% (=-0.080; P <0.001) and 15.1% (=-0.151; P<0.001), respectively. In the NE
states, there was no significant effects for the uptake of ANC for the lowest and middle wealth tertiles,
but negative effects for the highest wealth tertiles (=-0.131; P <0.001). However, in the late post- NRHM
period 2011–12, there was considerable improvement in the uptake of ANC, particularly for the lowest
socioeconomic tertiles. Effects were stronger for institutional delivery than antenatal care [64]. 54
ASHA had played a role in increasing the utilization of MCH services among poor women [45]. Utilization
of MCH services such as ANC among Scheduled Caste (SC), Scheduled Tribe (ST) women was less in
comparison to Muslims women. Contraception rate was still low among ST and Muslims [328]. Women
belonging to SC/ST and Other Backward Class (OBC) were less likely, as compared to General Caste
women, to participate in at least 4 ANC visits [45]. Positive relationship between visits by a community
health worker and likelihood of utilizing critical maternal health services was seen. However, significant
social inequalities still exist in association of community health worker visits [45].
As per Gupta et al study (2016) in Haryana, the geographical and socioeconomic differences between
urban and rural areas, and between rich and poor were significantly (p<0.05) reduced for pregnant
women who had an institutional delivery. (geographical difference declining from 22% to 7.6%;
socioeconomic from 48.2% to 13%), post-natal care within 2 weeks of delivery (2.8% to 1.5%; 30.3%to
7%); and for children with full vaccination (10% to 3.5%, 48.3% to 14%) and who received oral
rehydration solution (ORS) for diarrhea (11% to -2.2%; 41% to 5%). Inequalities between male and
female children were significantly (p<0.05) reversed for full immunization (5.7% to -0.6%) and BCG
immunization (1.9 to -0.9 points), and a significant (p<0.05) decrease was observed for oral polio vaccine
(4.0% to 0%) and measles vaccine (4.2% to 0.1%) [61].
In a qualitative study by Gupta et al, (2017), it was reported than an improvement in overall health
infrastructure through an increased availability of accredited social health activists, free ambulance
services, and free treatment facilities in rural areas was observed, which had increased the demand and
utilization of MCH services, especially for those related to institutional delivery, even by the poor families.
Service providers felt that acute shortage of human resources was a major health system level barrier. 55
Overall program managers, service providers and community representatives believed that NHM had a
role in improving MCH outcomes and in
reduction of geographical and socioeconomic inequalities, through improvement in accessibility,
availability and affordability of the MCH services in the rural areas and for the poor. Any reduction in
gender-based inequalities, however, was linked to the adoption of small family sizes and an increase in
educational levels [5].
Result of studies reviewed for other interventions like road and mobile connectivity
There were total 1, 07,823 studies that had reported the effect of interventions other than NRHM such
as road connectivity, mobile connectivity, water supply and sanitation on MCH outcomes. After removal
of duplicates, there were total 42,982 studies that were eligible for screening. Out of these, 223 studies
were selected after excluding the studies based on title and on abstract and 198 studies were excluded
based on exclusion criteria. Therefore, total 25 studies were included in the final analysis. Out of these
25 studies, only 18 studies were identified as good quality studies [261, 300, 331-352] (annexures 5.6.1
– 5.6.2).
Systematic review on variables other than NHM such as road connectivity, mobile connectivity, water
supply and sanitation found that mobile connectivity in form of health messages or as a tool to talk with
higher health officers had increased the knowledge and awareness related to maternal and child health
among people and front line health workers, which led to increase in early initiation of breastfeeding and
ANC utilization [333, 335, 339]. There was increase in health reporting services. It was also found that
women offered positive feedback regarding the voice messages as they described them as informative,
entertaining, and a service that they would recommend to friends. Surface road connectivity was also
found to be having positive impact on utilization of ANC and PNC services. Due to decrease in distance,
there had been increase in the chances of institutional deliveries as well as increase in immunization
among children and pregnant mothers. Pradhan Mantri Gram Sadak Yojna had also increased the
connectivity of villages with health facilities. This had also improved the chances of availability of health
care worker and ambulance services at village level [353]. Total sanitation program and NRHM in 56
coordination with other departments had increased the safe water supply which had reduced the water
borne illness and enteric infections [347, 348].
Pathways leading to reduction in Maternal and child mortality
Pathways leading to reduction in Maternal and child mortality
We have also tried to reason out how the NHM schemes might have led to the reduction in MCH mortality
and improved the MCH outcomes using good quality studies identified in the final step of the systematic
review. So, based upon the duplication, inclusion, exclusion and quality criteria a total 92 studies i.e. on
maternal health (n=18), child health (n=49), adolescent health (n=7), reproductive health (n=10), health
inequalities (n=7) were identified to construct pathways to understand the impact of NHM on health
outcomes as per logic model. (Table 4).
Table 4. Number of studies reviewed and included for construction of pathways leading to MCH
outcomes.
Strategies Studies
Reviewed
Studies Included Quality Studies
Maternal health 2759 63
Institutional delivery=44
MMR
1
=19
18
Institutional delivery=14
MMR=4
Child health 82023
NMR
2
= 19536
IMR
3
= 19,350
U5MR
4
=14,569
PNMR
5
= 28,568
213
NMR = 40
IMR=66
U5MR= 66
PNMR=41
49
NMR= 13
IMR= 15
U5MR=16
PNMR= 5
Adolescent health 1062 51
WIFS
6
=12
ARSH
7
=14
MHS
8
=25
7
ARSH=3
WIFS=2
MHS= 2
Reproductive health 6261 49
CPR
9
=27
TFR
10
=9
Utilization
rate/barriers=13
10
CPR=10
TFR=0
Health inequalities 9185 12 8
Total 101290 388 92
57
1
Maternal Mortality Ratio;
2
Neonatal Mortality Rate;
3
Infant Mortality Rate;
4
Under 5 Mortality Rate;
5
Perinatal Mortality Rate;
6
Weekly Iron
Folic Acid Supplementation;
7
Adolescent Reproductive Sexual Health;
8
Menstrual Hygiene Scheme;
9
Contraceptive Prevalence Rate;
10
Total
Fertility Rate
Pathways to understand the impact of NHM on health outcomes as per logic model is shown in Figure
16. The inputs (n=89) which included NHM strategies like communitization, RMNCHA+, health system
strengthening, human resources strengthening and social determinants of the health such as income,
education, female literacy, occupation, road connectivity, mobile users, caste and area. Processes (n=4)
include the implementation of these activities like number of ASHA’s trained in providing reproductive
and child health care, provision of incentives for institutional delivery and free treatment, outputs (n=4)
include the activities done/completed like number of pregnant women contacted by ASHA’s in the village
and counselled for institutional deliveries, increase in availability, affordability and accessibility of MCH
facilities in rural areas, outcomes include the coverages such as increase in institutional delivery rate,
increase in utilization of MCH facilities in rural areas and impact (n=80) includes the effect on the
mortality rates like reduction in maternal mortality rate, infant mortality rate, in MCH geographical,
socioeconomic and gender based inequalities.
The evidence for accredited health activists is denoted by thick arrow, which shows that ASHA had
played a significant role in improving MCH outcomes by behaviour change and communication [69].
Both ASHA [5, 45, 63, 65, 69, 95, 354, 355] and maternal health intervention such as JSY[7, 26, 30-34,
54, 73, 74, 127] were (denoted by thick arrow) were found to be very effective in increasing the
institutional delivery rate among pregnant women as compared to village health nutrition day (denoted
as dotted arrow) [80]. Due to behaviour change communication and motivation, the pregnant women
were empowered with adequate knowledge regarding the health sector plans of NRHM (free ambulance
services, free hospital deliveries, free treatment, and financial incentives for hospital deliveries) which
enabled them to take decisions regarding institutional delivery [5]. As a result, the community was
mobilized to use the MCH facilities in rural areas [5]. These factors, along with other NRHM interventions
Janani Shishu Suraksha Karyakram (JSSK) [80], child health interventions such as facility based
newborn care (FBNC) [70, 89, 97, 101, 182], Integrated Management of Neonatal and Childhood
Illness(IMNCI) [70, 89, 94, 97, 101, 106-110, 112, 117, 155, 182] home based postnatal care [90, 99, 58
119, 122, 125, 126], immunization coverage [190, 191, 194, 198, 201, 204, 205, 356], the availability of
health facilities and doctors in rural areas and the free ambulance service [36, 41, 55], free medicines
further improved the accessibility and affordability of MCH services and benefitted poor pregnant women
and children whereas mobile medical units (MMUs) were perceived to be less effective in improving the
accessibility of health services in rural areas as denoted by dotted arrow [80]. There is weak evidence
for reproductive health strategies such as family planning in improving maternal health outcomes
(denoted by dotted arrow) [259, 260, 265, 266, 273, 277, 357-360]. The diagram also shows that the
increase in institutional delivery rate was mainly due to ASHA and JSY (denoted by thick arrow). Also
due to community mobilization (denoted by thick arrow) there was increase in utilization of MCH facilities
in rural areas which led to improvement in antenatal and postnatal care [45]. The increased utilization
of MCH facilities and other factors like increase in accessibility of MCH facilities in rural areas [5], led to
improvement in child health indicators such as early diagnosis and treatment of children, reduction in
ARI, diarrhoea burden [61, 204] and malnutrition [221, 222] whereas there is weak evidence for other
child health interventions such as RBSK [226, 227] and RKSK in provision of early diagnosis as well as
treatment of childhood illnesses. There is weak evidence for adolescent health interventions like WIFS
(denoted by dotted arrow) in reduction of anaemia among adolescents [282, 298, 311, 361-364]. Though
NRHM interventions had improved the utilization of MCH services, there is weak evidence for provision
of equal child health care facilities for girls and boys (denoted by dotted arrow) [5]. All these inputs and
outputs had implications on improving MCH outcomes, on declining mortality rates and on bridging the
socioeconomic, geographical and gender based MCH inequalities [5, 61, 63, 64, 73, 80, 321, 327, 361].
59
Figure 16. Impact of NHM Strategies: Evidence from Literature.
60
FINDINGS FROM SECONDARY DATA ANALYSIS
INPUT/PROCESS INDICATORS
Allocation of funds for NHM
The fund allocated to NRHM in the year 2005-06 was Rs 6788 crore and it increased to Rs 30,130 crore
in the year 2018-19 under NHM. (Figure 17). The allocated fund had increased every year, however,
allocation of fund had been declined by 0.7% (17,310 crore to 17,188 crore) in the financial year 2011-
12 to 2012-13 and by 2% (30,802 crore to 30,130 crore) in the year 2017-18 to 2018-19 [88, 365]. The
trend of inflation adjusted budget have shown that budget allocation increased from 2005-06 to 2008-
09, and declined in the year 2009-10 and 2011-12. After that there was an increased allocation up to
the year 2017-18, which later declined in the year 2018-19.
Figure 17. Allocation of funds under NHM.
Data source: India Expenditure Budget, Volume 2, Ministry of Health and Family Welfare; Union Budget, Government of
India.
Public and out of pocket health Expenditure and Per Capita Public Health Spending
6788
8207
9947
1205012070
15258
13310
17188
18206
18609
19122
22198
30802
30130
0
5000
10000
15000
20000
25000
30000
35000
Rupees
Budget (In crores) Budget (Inflation Adjusted) 61
Out of the total health expenditure, the percentage of the public health expenditure had increased from
24% to 32% from the year 2004 to 2016. In the same period, the percentage of out of pocket health
expenditure had declined from 68% to 59 %. (Figure 18).
Figure 18. Out of pocket health expenditure and public health expenditure.
Data source: National Health Account year 2004 to 2016.
The per capita public health expenditure had increased from Rs 579 in 2004 to Rs 1418 in 2016. (Figure
19).
Figure 19. Per capita public health expenditure.
Data source: National Health Account year 2004 to 2016; Indian National Rupee; per capita public health expenditure in
different years inflated to 2016 value.
Health system strengthening and human resources
68 66 64 63 65
62 61
59
24
26 27 27 27
30
31
32
0
10
20
30
40
50
60
70
80
2004 2006 2008 2010 2012 2014 2015 2016
% of total health
expenditure
OOP health expenditurePublic health expenditure
579
1151
1321
1418
0
200
400
600
800
1000
1200
1400
1600
2004 2006 2008 2010 2012 2014 2015 2016
Per capita public health expenditure
Linear (Per capita public health expenditure)
INR 62
Number of government hospital beds per 1000 population in rural and urban areas (including CHCs) in
India increased from 0.4 in 2005 to 0.6 in 2015. (Figure 20).
Figure 20. Number of Patient Beds/1000 population.
Data source: Rural Health Statistics year 2005-2015.
Number of ASHA workers per 10,000 population increased from 1.31 in 2005 to 7.40 in 2019. The
number of ANMs per 10,000 population increased from 1.22 in 2005 to 1.69 in 2018. (Figure 21).
Figure 21. Trend showing number of ANMs and ASHAs per 10,000 population (2005-19).
Data source: ANMs data obtained from Rural Health Statistics year 2005-2018; ASHAs data obtained from ASHA updates
2005-2019.
The number of nursing staff increased from 0.26 in 2005 to 0.65 in 2018, in PHCs and CHCs per 10,000
population. Number of doctors in PHCs and CHCs per 10,000 population also increased from 0.22 in 2005
to 0.24 in 2017. (Figure 22).
0.4
0.6
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
20052015
Per 1000 Population
20052015
0.00
2.00
4.00
6.00
8.00
200520062007200820092010201120122013201420152016201720182019
PER 10,000
POPULATION
ANM ASHA 63
Figure 22. Trend showing doctors and nursing staff per 10,000 population in PHCs and CHCs
(2005-2018).
Data source: Rural Health Statistics year 2005 to 2018.
HEALTH OUTPUT/OUTCOME INDICATORS
Utilization of public sector for outpatient care
The utilization of public sector facilities for outpatient care services was higher in rural areas than urban
areas, with an increase in utilization in both rural and urban settings over the years. The rate of increase,
between years 2004 and 2014, was higher in rural areas (6.7%) in comparison to the urban areas (2.6%).
However, between 2014 and 2018, the rate of change in urban areas (5.7%) surpassed the increase in
rural areas (4.4%). This increase in public sector utilization was observed equally among both males
(10.1%) and females (9.6%), but in the initial years, the increase was higher among females (6%) as
compared to males (4%). (Figure 23).
Figure 23. Utilization of public sector for outpatient care.
Data source: NSSO round 60
th
(2004), round 71
th
(2014), round 75
th
(2018)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
20052006200720082009201020112012201320142015201620172018
Doctors Nurses
Per 10,000
population
21.2
18.1 19.8 20.8
27.9
20.7
23.7
26.2
32.5
26.2
29.9 30.4
0
20
40
60
80
100
Rural Urban Male Female
Public Sector Utilization (%)
200420142018 64
Utilization of public sector for hospitalization
A higher utilization rate of public sector facilities for hospitalization was observed in rural areas in 2014
as compared to 2004 (increase of 7%), while the same declined by 3.5% in urban areas during this
period. Between 2014 and 2018 however, whereas these utilization rates declined in rural areas by
around 5%, the rates in urban areas remained almost the same. Overall, utilization of public sector was
always higher in rural areas as compared to urban settings. A similar pattern was observed in the rates
of utilization among females and males. While the rates of utilization among females declined by 4% in
the later years, following an initial surge of 7% between 2004 and 2014, utilization by males declined by
almost 4% between 2004 and 2014, followed by an increase of the same amount between 2014 and
2018. (Figure 24).
Figure 24. Utilization of public sector for hospitalization.
Data source: NSSO round 60th (2004), round 71th (2014), round 75
th
(2018)
Out-of-pocket expenditure for under-five child hospitalization
It was found that while the expenses at public health sector facilities for under five child hospitalization
were lowered by Rs. 2741 in 2014 when compared to 2004, these increased by Rs. 1264 between 2014
and 2018. Expenses at private health facilities increased by around Rs. 5000 between 2004 to 2014 but
only by Rs. 1500, between 2014 and 2018. (Figure 25).
43.8
39.140.5
43
50.3
35.536.9
50
45.7
35.3
40.9
46.1
0
20
40
60
80
100
Rural UrbanMaleFemale
Public Sector Utilization (%)
200420142018 65
Figure 25. Out-of-pocket expenditure for under-five child hospitalization.
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; Indian National Rupee.
Out-of-pocket expenditure on institutional deliveries
The mean expenditure on institutional deliveries at public sector facilities increased marginally (by Rs.
55) in 2004-2014 period, expenses at private health facilities increased by around Rs 7000 in this period.
No increase in mean expenditure on deliveries in 2014-18 period was observed at public sector facilities,
however deliveries in private sector facilities had to spend an additional Rs. 8000 on an average.. (Figure
26).
Figure 26. Out-of-pocket expenditure on institutional deliveries.
6104
12024
3363
17192
4627
18510
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
Public Sector FacilitesPrivate Sector Facilites
INR
200420142018
2714
11198
2769
18521
2767
26476
0
5000
10000
15000
20000
25000
30000
Public Sector Facilites Private Sector Facilites
INR
200420142018 66
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; Indian National Rupee.
Catastrophic health expenditure on under-five child hospitalization
Catastrophic health expenditure due to hospitalizations at public health facilities reduced from 24.2% in
2004 to 14.5% in 2014, and further to 9.6% in 2018, whereas it stayed almost the same (around 40%)
between 2004-2018 at private health facilities (Figure 27).
Figure 27. Catastrophic health expenditure on under-five child hospitalization.
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; catastrophic health expenditure is > 25% of the
total household consumption expenditure.
Catastrophic health expenditure on institutional deliveries
The public sector has also successfully managed the financial risk to households due to catastrophic
health expenditure on delivery between 2004-18, which increased substantially from 32% to 74% at
private sector facilities in the same period (Figure 28).
24.2
40.3
14.5
42.8
9.6
39.5
0
5
10
15
20
25
30
35
40
45
Public Sector FacilitesPrivate Sector Facilites
Percentage (%)
200420142018 67
Figure 28. Catastrophic health expenditure on institutional deliveries.
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; catastrophic health expenditure is > 25% of the
total household consumption expenditure.
Maternal Health Indicators
There was significant increase in the proportion of first trimester registration from 57.3% to 67.4%, in
institutional delivery rate from 41.6% to 87.7% and proportion of women who received post-natal check-
up from 42.4% to 72.3% from the year, 2005 to 2015. However, there was decline in contraception rate
(from 56.3% to 52.9%) in the same period. (Figure 29).
Figure 29. Health indicators for women aged 15-49 years who had a live birth in the five years
preceding the survey.
Data source: NFHS data round 3 and 4; adjusted percentage of NFHS 4 for place of residence, maternal age, education,
religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density, road
density, telephone-density.
8.2
32.8
8.1
61.8
7.5
74.1
0
10
20
30
40
50
60
70
80
Public Sector FacilitesPrivate Sector Facilites
Percentage (%)
200420142018
57.3
41.642.4
56.3
67.4
87.7
72.3
52.9
0
20
40
60
80
100
First trimester
registration
Institutional deliveryPost natal check upContraception rate
Percentage (%)
2005 2015 68
The odds of getting registered in first trimester of pregnancy was two times higher in post NHM period
as compared to pre NHM period after adjusting for the effect of confounders. Similarly, the odds of
having institutional delivery and postnatal check-ups was 11.5 and 3.5 times higher in post NHM period
as compared to pre NHM period, respectively. However, the odds of contraception rate was lower in
post NHM period as compared to pre NHM period after adjusting for the effect of confounders. (Table
5).
Table 5. Health indicators for women aged 15-49 years who had a live birth in the five years
preceding the survey.
Health Indicators
Adjusted Odds
Ratio
95% Confidence
Interval
p-value
First trimester Registration 2.0 (1.896,2.082) <0.01*
Institutional Delivery 11.5 (10.855,12.142)
<0.01*
Postnatal Check-ups 3.5 (3.377, 3.688)
<0.01*
Contraception Rate 0.9 (0.851, 0.895)
<0.01*
Data source: NFHS data round 3 and 4; *significant; adjusted for place of residence, maternal age, education, religion, caste,
wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density, road density, telephone-
density.
Child Health Indicators
The adjusted proportions of children exclusive breastfed and fully immunized in post-NHM period increased
as compared to pre-NHM period and adjusted proportions of children suffering from acute respiratory
infection decreased in post NHM period. However, the proportion of children suffering from diarrhoea
remained same before and after NHM period. (Figure 30).
Figure 30. Percentage of children for various child health indicators in 2005 and 2015. 69
Data source: NFHS data round 3 and 4; adjusted percentage of NFHS4 for institutional delivery, place of residence, maternal age,
education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density,
road density, telephone- density.
The odds of exclusive breastfeeding was 2 times in post NHM period as compared to pre NHM period,
after adjusting for confounders. Likewise, the odds of being fully immunized was 1.8 times higher in post
NHM period as compared to pre NHM period. (Table 6).
Table 6. Child health indicators of children under 5 years of age in 2005 and 2015.
Child Health Adjusted Odds Ratio
95% Confidence
Interval
p-value
Exclusive Breastfeeding 2.1 (1.756, 2.509) <0.01*
Fully Immunized 1.8 (1.618, 1.910) <0.01*
Acute Respiratory Infection (ARI) 0.5 (0.417, 0.491) <0.01*
Diarrhoea 1.0 (0.961,1.068) 0.633
Data source: NFHS data round 3 and 4; *significant; adjusted for institutional delivery, place of residence, maternal age,
education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density,
road density, telephone- density.
IMPACT INDICATORS
Maternal Mortality Ratio
The national MMR declined from 254 in the year 2004-06, to 167 in the year 2011-13, to 122 in the year
2015-17. Empowered Action Group (EAG) states and Assam also witnessed a decline from 246 to 175
in the same time period. It was also declined for South states total and other states total from 93 to 72
and 115 to 90 respectively. (Figure 31). Maternal mortality ratio declined by 52% from 2004-06 to 2015-
5.9
43.7
5.4
9.0
11.6
57.7
2.5
9.1
0
10
20
30
40
50
60
70
Exclusive BreastfeedingFully Immunized ARIDiarrhea
Percentage (%)
2005 2015 70
17, with 34.3% decline till 2011-13 and 26.9% decline during 2011-13 to 2015-17. Rate of decline per
year was 12.7 points during 2004-06 to 2011-13 and 11.3 points post 2011-13.
Figure 31. Trend of Maternal Mortality Ratio 1997-2017.
Source: SRS data
Child Health Outcomes
Under five mortality rate
Under five mortality rate declined from 78 to 37 per thousand live births from 2005 to 2019 (Unicef’s
child mortality estimates). [Figure 32]. Overall there is 52.6% reduction in U5MR from 2005 to 2019, with
33.3% during NRHM period (2005-12) and 28.8% during NHM period (2013-2019). Rate of decline per
year was 3.7 points before and 2.5 points after the year 2013.
398
167
122
0
100
200
300
400
500
600
1997-981999-012001-032004-062007-092010-122011-132014-162015-17
INDIA EAG And Assam Total South States Total Other Total
Rate of decline 12.7
points per year
Rate of decline 11.3
points per year 71
Figure 32. Trend of under five mortality rate in India, from 2005 to 2019.
Source: Unicef’s Child Mortality estimates; SRS data
Among the states, maximum reduction was seen in Assam, where U5MR had declined from 88 to 75
per thousand live births by 2012 to 52 per 1000 live births by 2016, as per SRS data. Rate of decline
per year increased from 2.6 points during 2008-12 to 5.25 points after the year 2013 in Assam. Minimum
reduction was seen in the state of Kerala which varied from 14 to 11 in the same time period, as it
already had very low U5MR. States where rate of decline increased per year after the year 2013 were
Gujarat (2.4 to 3 points), HP (1.4 to 3.5 points), Jammu and Kashmir (2.4 to 3.5), Jharkhand (3.0 to 3.75)
and West Bengal (0.8 to 2 points). In Orissa, pace of decline was also high at 4.0 points per year, which
remained the same after the year 2013. Similarly, in Madhya Pradesh pace of decline remained the
same (3.8 to 3.5 points). States where the pace of decline of U5MR reduced after the year 2013, included
Punjab, Rajasthan, Tamil Nadu, Haryana, Bihar, Andhra Pardesh, Chattisgarh, Karnataka. (Figure 33).
78
52
37
0
10
20
30
40
50
60
70
80
90
200520062007200820092010201120122013201420152016201720182019
U5MR
Rate of decline 3.7 points
per year
Rate of decline 2.5 points
per year 72
Figure 33. Trend of under five mortality rate in Indian states, from 2008 to 2016.
Source: SRS data
Infant Mortality rate
The infant mortality rate had declined from 58 per 1000 live births to 40 per thousand live births during
2005-13 (NRHM period) and to 33 per 1000 live births during 2013-17 (NHM period). [Figure 34].
Figure 34. Trend of infant mortality rate in India, from 2005 to 2017.
Source: SRS data
The interrupted time series analysis from the Sample Registration System (SRS) data had shown that
the rate of decline in IMR was 2.42 infant deaths per 1000 live births per annum before 2013 and it
accelerated to 2.10 infant deaths per 1000 live births per annum after the year 2013-17. (Figure 35).
69
64
59
55 52 49
45 43
34
88
87
83
78 75 73
66
62
52
14 14 15 13 13 12 13 13 11
0
50
100
200820092010201120122013201420152016
India Assam Orissa
Punjab Rajasthan Tamil Nadu
Haryana Kerala Uttar Pradesh
Bihar
58
40
33
0
10
20
30
40
50
60
70
2005200620072008200920102011201220132014201520162017
Rate of decline 2.6
points per year
Rate of decline 1.8
points per year 73
Figure 35. Trend of infant mortality rate as per interrupted time series analysis in India, from 2005
to 2017.
Data source: Sample Registration System; Interrupted Time series analysis; Year 1: 2005, Year 9: 2013, Year
13: 2017
The rate of decline for IMR was found to be sharper in post intervention period almost in every state
except a few, as per SRS data. Among the set of bigger states, the maximum reduction was seen in the
state of Orissa, where IMR had reduced from 51 to 41 infant deaths per 1000 live births from the year
2013-17. The minimum reduction was demonstrated by the state of Kerala which varied from 12 to 10
in the same time period. The trends of IMR for the set of smaller states/ UTs of the country had bit
different picture from the bigger and country level estimates. From the year 2013 to 2017, Arunachal
Pradesh and Manipur had witnessed an increase in IMR from 32 to 36 and from 10 to 11 per 1000 live
births, respectively. Among Union Territories (UTs), Andaman & Nikobar and Puducherry had shown
maximum decline in IMR from 24 to 16 and 17 to 10 respectively in the same time period. (Figure 36
and 37).
74
Figure 36. Trend of infant mortality rate in bigger states in India, from 2005 to 2017.
Source: SRS
data
Figure 37. Trend of infant mortality rate in smaller states in India, from 2005 to 2017.
Source: SRS data
0
10
20
30
40
50
60
70
80
2005200620072008200920102011201220132014201520162017
IMR trend in bigger states
India Assam Bihar Gujarat
Haryana Karnataka Kerala Madhya Pradesh
Odisha Punjab Rajasthan Tamil Nadu
Telangana Uttar Pradesh West Bengal
0
10
20
30
40
50
60
70
200520062007200820092010201120122013201520162017
IndiaArunachal Pradesh ManipurTripura
Andaman &Nicobar Chandigarh Daman &Diu Puducherry 75
Neonatal Mortality
Overall the neonatal mortality reduced from 38 per thousand live births to 22 per thousand live births,
with a percentage decline of 42.1% from 2005 to 2019, as per Unicef’s Child mortality estimates. The
rate of decline per year was 1.4 points from 2005 to 2013 and 1.0 from 2013 to 2019. (Figure 38).
Figure 38. Trend of neonatal mortality rate in India, from 2005 to 2019.
Source: Unicef’s Child Mortality estimates; SRS data
While the under-five mortality rate reduced from 78 to 37 (52.6% decline), infant mortality rate from 58
to 33 (43.1% decline), neonatal mortality rate reduced from 38 to 22 per thousand live births (42.1%
decline). The percentage decline was 26.3%, 31% and 33.3% during NHM period (2005-13), and 21.4%,
17.5% and 28.8% during NHM period for under-five mortality rate, infant mortality rate and neonatal
mortality rate, respectively.
Figure 39. Trend of neonatal mortality, infant mortality and under five mortality in India, from
2007 to 2019.
38
28
22
0
5
10
15
20
25
30
35
40
200520062007200820092010201120122013201420152016201720182019
Rate of decline 1.4
points per year
Rate of decline 1.0
points per year 76
Source:
Unicef’s Child Mortality estimates, SRS data
The analysis of NFHS 3 and NFHS 4 data showed that the infant mortality rate and neonatal mortality rate
had reduced significantly in post NHM period as compared to pre NHM period. Rate of decline was 0.9
points per year for IMR and it was 0.4 points per year for NMR. (Figure 40).
Figure 40. Infant Mortality Rate and Neonatal Mortality Rate per 1,000 live births in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index, type
of housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
The adjusted infant mortality rate as well as neonatal mortality rate in post-NHM period had been
reduced as compared to pre-NHM period. The risk of infant death was significantly lower in post NHM
period as compared to pre NHM period (RR=0.8). [p<0.01]. Similarly, the risk of neonate death was
38
28
22
78
52
37
58
40
33
0
10
20
30
40
50
60
70
80
90
200520062007200820092010201120122013201420152016201720182019
NMR U5MR IMR
45.1
31.6
36.1
27.0
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Mortality Rate / 1,000 Live
Births
20052015
Rate of decline 0.9 points per year Rate of decline 0.4 points per year
Infant Mortality Rate Neonatal MortalityRate 77
significantly lower in post NHM period as compared to pre NHM period after adjusting for confounders
(RR=0.9). (Table 7).
Table 7. Infant mortality rate and Neonate mortality rate (per 1000 live births) of children born in
the three years preceding the survey.
Adjusted Risk Ratio 95% Confidence Interval p-value
Infant Mortality Rate 0.8 (0.749,0.857)
<0.01*
Neonate Mortality Rate 0.9 (0.789, 0.925)
<0.01*
Data source: NFHS data round 3 and 4; *significant; adjusted for maternal age, education, religion, caste, wealth index, type of
housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Total Fertility Rate
Total fertility rate has declined from 2.82 to 2.24 from 2007 to 2017. The percentage decline was 20.6%
in this period, with 15.6% decline till 2013 and 5.9% decline after 2013. (Figure 41).
Figure 41. Trend of Total Fertility Rate in India, from 2007 to 2017.
Source: SRS data
Impact of NHM on health inequalities
Geographical inequalities in IMR
IMR declined in both urban and rural areas from 2005 to 2015. The extent of decline was slightly higher
in rural (9.0 points) as compared to urban areas (8.6 points). The inequalities in IMR in the urban and rural
2.82
2.38
2.24
0
0.5
1
1.5
2
2.5
3
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
TFR 78
areas declined from 15.9 points in 2005 to 15.5 points in 2015 after adjustment for confounders. (Figure
42).
Figure 42. Comparison of infant mortality rate among urban and rural areas in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS 4 for maternal age, education, religion, caste, wealth
Index, type of housing, availability of toilet, safe water supply, cooking fuel, road density.
The extent of decline in IMR was almost similar in EAG (12.1 points) and non EAG states (12.3 points)
from 2005 to 2015. Inequalities in IMR between EAG and Non-EAG states increased from 14.9 points in
2005 to 15.1 points in 2015 after adjustment for confounders. (Figure 43).
Figure 43. Comparison of infant mortality rate among EAG and Non-EAG states in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index,
type of housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Socioeconomic inequalities in IMR
Caste wise inequalities
34.0
25.4
49.9
40.9
0
10
20
30
40
50
60
20052015
IMR/1,000 Live
Births
Urban
Rural
52.7
40.6
37.8
25.5
0
10
20
30
40
50
60
20052015
IMR/1,000 Live Births
EAG
Non EAG 79
The Infant mortality rate reduced in all the castes, reduction being the higher among scheduled tribes (ST)
by 12 points from 2005 to 2015. Caste wise inequalities in IMR between schedule caste (SC) and general
category reduced from 11.9 points in 2005 to 10.0 points in 2015. (Figure 44).
Figure 44. Caste wise health inequalities for infant mortality rate in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, wealth index, type of
housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Income wise inequalities
Infant mortality rate reduced in all the quintile groups, reduction being the highest in the poorer quintile
(12.5 points) and the least in richer quintile (4.3 points) from 2005 to 2015. The inequality in IMR between
the poorest and richest quintile group reduced from 29.3 points to 28.4 points from 2005 to 2015. (Figure
45).
Figure 45. Wealth wise health inequalities for infant mortality rate in 2005 and 2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, type of housing, availability
of toilet, place of residence, safe water supply, cooking fuel, road density.
50.8
38.8
45.9
36.0
47.7
40.9
38.9
28.8
0
10
20
30
40
50
60
20052015
IMR/1,000 Live Births
ST
SC
OBC
Others
55.5
47.155.9
43.4
46.9
37.6
35.2
30.9
26.3
18.7
0
10
20
30
40
50
60
20052015
IMR/1,000 Live Births
Poorest
Poorer
Middle
Richer
Richest 80
The infant mortality rate had reduced significantly in post NHM as compared to pre NHM period. The
adjusted risk was significantly less for urban area as well as for rural area in post NHM as compared to
pre NHM period. (p<0.01). Likewise, the adjusted risk was less for EAG states as well as for Non-EAG
states in post NHM period as compared to pre NHM period. (p<0.01). [Table 8].
Table 8. Health Inequalities of infant mortality rate (per 1000 live births) for children born in the
three years preceding the survey.
Infant Mortality Rate
Adjusted
Risk Ratio
95% Confidence
Interval
p-value
Place of Residence
Urban 0.8 (0.640, 0.867)
<0.01*
Rural 0.8 (0.761, 0.883)
<0.01*
States
EAG States 0.8 (0.710, 0.837)
<0.01*
Non-EAG States 0.7 (0.600, 0.759)
<0.01*
Caste
Schedule Caste 0.8 (0.683, 0.901)
<0.01*
Schedule Tribe 0.8 (0.624, 0.933)
<0.01*
Other Backward Class 0.9 (0.775, 0.949)
<0.01*
Others 0.8 (0.639, 0.855)
<0.01*
Wealth Index
Poorest 0.9 (0.757, 0.953)
<0.01*
Poorer 0.8 (0.680, 0.888)
<0.01*
Middle
0.8 (0.686, 0.937)
<0.01*
Richer
0.9 (0.726, 1.060
0.176
Richest
0.7 (0.512, 0.889)
<0.01*
*Significant; Source: NFHS data round 3 and 4; adjusted for maternal age, education, religion, type of housing, availability of
toilet, safe water supply, cooking fuel, road density.
Geographical inequalities in NMR
NMR declined in both urban and rural areas from 2005 to 2015. The extent of decline in NMR was higher
in urban (5.5 points) as compared to rural areas (4.2 points) from 2005 to 2015. The inequalities in NMR
in the urban and rural areas increased from 10.7 points in 2005 to 12 points in 2015 after adjustment for
confounders. (Figure 46).
81
Figure 46. Comparison of neonate mortality rate among urban and rural areas in 2005 and 2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index, type of
housing, availability of toilet, safe water supply, cooking fuel, road density.
Neonatal mortality rate reduced with higher reduction in Non-EAG states (8.1 points) as compared to EAG
states (6.0 points) from 2005 to 2015. Inequalities in NMR between EAG and Non-EAG states increased
from 7.8 points in 2005 to 9.9 points in 2015 after adjustment for confounders. (Figure 47).
Figure 47. Comparison of neonatal mortality rate among EAG and Non-EAG states in 2005 and
2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index, type of
housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Socioeconomic inequalities in IMR
Caste wise inequalities
24.2
18.7
34.9
30.7
0
10
20
30
40
50
20052015
NMR/1,000 Live Births
Urban
Rural
35.8
29.8
28.0
19.9
0
10
20
30
40
50
20052015
NMR/1,000 Live Births
EAG
Non EAG 82
NMR reduced in all the castes, reduction being the least in other backward caste (OBC) (2.9 points) and
the highest in other caste (7.1 points) category, from 2005 to 2015. (Figure 30). Caste wise inequalities in
NMR between schedule tribe (ST) and general category remained almost same in 2005 (9.7 points) and
2015 (10 points). (Figure 48).
Figure 48. Caste wise health inequalities for neonate mortality rate in 2005 and 2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4. for maternal age, education, religion, wealth index, type of housing,
availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Income wise inequalities in NMR
NMR reduced in all the quintile groups, reduction being poorest quintile was 4.5 points and poorer quintile
was 6.2 points from 2005 to 2015. However, the inequality in NMR between the poorest and richest quintile
group increased from 19.5 points to 22 points from 2005 to 2015. (Figure 49).
Figure 49. Wealth wise health inequalities for neonate mortality rate in 2005 and 2015.
37.2
30.4
29.6
25.7
33.0
30.1
27.5
20.4
0
5
10
15
20
25
30
35
40
45
50
20052015
NMR/1,000 Live Births
ST
SC
OBC
Others
38.9
34.439.1
32.9
31.8
29.1
25.5
25.5
19.4
12.4
0
5
10
15
20
25
30
35
40
45
20052015
NMR/1,000 Live Births
Poorest
Poorer
Middle
Richer
Richest 83
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, type of housing, availability
of toilet, place of residence, safe water supply, cooking fuel, road density.
Neonatal mortality rate reduced significantly in post NHM period as compared to pre NHM period. The risk
was significantly less for urban area (RR=0.7) as well as for rural area (RR=0.9) in post NHM as compared
to pre NHM period. (p<0.01). Similarly, the risk was significantly less for EAG states (RR=0.8) as well as
for Non-EAG states (RR=0.7) in post NHM period as compared to pre NHM period. (Table 9).
Table 9. Health inequalities for neonate mortality rate (per 1000 live births) for children born in
three years preceding the survey.
Neonate Mortality Rate
Adjusted Risk
Ratio
95% Confidence
Interval
p-value
Place of Residence
Urban 0.7 (0.645, 0.922)
<0.01*
Rural 0.9 (0.806, 0.962)
<0.01*
States
EAG States 0.8 (0.754, 0.918)
<0.01*
Non-EAG States 0.7 (0.620, 0.817)
<0.01*
Caste
Schedule Caste 0.9 (0.737, 1.023)
0.092
Schedule Tribe 0.8 (0.635, 1.053) 0.119
Other Backward Class 0.9 (0.809, 1.029) 0.134
Others 0.7 (0.626,0.877) <0.01*
Wealth Index
Poorest 0.9 (0.772, 1.014) 0.080
Poorer 0.8 (0.717, 0.989) 0.036*
Middle
0.9 (0.760, 1.102) 0.349
Richer
1.0 (0.798, 1.247) 0.982
Richest
0.7 (0.498, 0.819) <0.01*
*Significant; Source: NFHS data round 3 and 4; adjusted for maternal age, education, religion, type of housing, availability of
toilet, safe water supply, cooking fuel, road density.
84
DISCUSSION
The results of this study have shown that there has been increase in utilization of public health services
and reduction in OOPE and for MCH services post NRHM implementation period. There is improvement
in availability and accessibility of health facilities after NRHM implementation. The human resources as
well as infrastructure has also been strengthened in post NRHM period. MCH coverage indicators have
shown improvement and overall mortality statistics (MMR and IMR) has registered a significant decline
after NRHM implementation.
In this study, we have used logic model evaluation framework to evaluate the impact of National Health
Mission on health care utilization, heath care inequalities and health outcomes by conducting a
systematic review and secondary data analysis. The logic model is helpful in showing the
interrelationship among different components such as between program input and activities and desired
outcomes. It also helps in understanding the complex mechanisms of whole interventions that how they
work. The simplicity of logic model is one of its strength as well as weakness. However due to its
simplicity it may also omits the details for clarity of the representation [366].
Earlier studies have used the logical model evaluation framework for assessing the effectiveness of
interventions and showed the interrelationship among different components [61, 80, 367, 368]. By
applying this approach to explain the results of this study, it was found that there has been considerable
increase in inputs and processes that provides the link in improving the output in terms of improved
MCH coverage indicators and ultimately outcomes and impact in terms of reduction in MCH inequalities
and mortality. There is no ‘control’ population for establishing the cause and effect relationship, therefore
the assessment of effect of interventions by measuring the inputs, processes, outputs, outcomes, and
impact over a longer time horizon is considered as a best available option [61].
The results of present study shows that out of the total health expenditure, the percentage of the public
health expenditure had increased from 24% to 32% from the year 2004 to 2016. In the same period, the
percentage of out of pocket health expenditure had declined from 63% to 59%. Also the per capita public
health expenditure had increased from Rs 579 in 2004 to Rs 1418 in 2016. Our results also revealed 85
that expenses at public sector facilities were lower in 2014 when compared to 2004 and the mean
expenditure on deliveries at public sector facilities increased marginally (by Rs. 129) in 2004-2014
period, whereas the expenses at private health facilities increased by around Rs 7000 in this period.
The catastrophic health expenditure due to deliveries at private health facilities, increased significantly
in this period. Also the catastrophic health expenditure due to hospitalization and institutional deliveries
for the household presented a marginal decline from 2004 to 2014. These findings are indicative of the
success of NRHM’s policies and programs in reducing out of pocket expenditures for institutional
delivery in public sector facilities. Increased public health spending in the post-NRHM period and
introduction of strategies such as the JSY and JSSK has contributed positively toward reducing out of
pocket expenditures [6, 57, 102, 369].
The results of present study also shows that there is improvement in availability and accessibility and of
health facilities after NRHM implementation. The human resources as well as health infrastructure has
also been strengthened in post NRHM period. Our results from logistic regression analysis found that in
post NRHM period there has been increase in number of ANMs, medical officers as well as increase in
number of beds in rural and urban areas hospitals. The evidence which was synthesized from previous
literature also validated these findings and concluded that post NRHM period there has been
strengthening of health system due to improvement in health facilities, availability of ASHA, ANMs,
Nurses and MOs, availability of free medicines and diet and free ambulance services [5]. Based on the
achievements of NHM since 2005, it has been a guiding framework for strengthening the Indian health
system [57]. The output indicators like first trimester registration, institutional delivery and post-natal
check-up also increased significantly post NRHM period. The evidence showed that the NRHM
interventions such as cash incentives for hospital deliveries (Janani Suraksha Yojna) [7, 26, 30-34, 54,
73, 74, 127], free diagnostics, treatment and diet (Janani Shishu Suraksha Karyakram) [80], and
appointment of Accredited Social Health Activists (ASHAs) [5, 45, 63, 65, 69, 95, 354, 355] led to
improvement in antenatal care, institutional delivery rate and postnatal care. We also found that various
child health indicators like exclusive breastfeeding and full immunization coverage improved significantly
in post NRHM period whereas acute respiratory infections reduced significantly to 2.5% from 2005 to 86
2015. The child health strategies of NHM/NRHM like IMNCI, immunization, micronutrient
supplementation along with early diagnosis and treatment by RBSK improved the affordability,
accessibility of health services which improved the child health indicators [70, 89, 94, 97, 101, 106-110,
112, 117, 155, 182, 190, 191, 194, 198, 201, 204, 205, 226, 227, 356].
Regarding the impact indicators, it was found that neonatal and infant mortality rate reduced significantly
in post NHM as compared to pre NHM period. Both NMR and IMR reduced significantly from 31.6 to 27
neonatal deaths per 1000 live births and 45.1 to 36.1 infant deaths per 1000 live births from 2005 to
2015, respectively .The results from interrupted time series also found that NHM had contributed to
reduce the infant mortality rate at the national level. The IMR reduced at the rate of 2.2% per year in
comparison to the 1.6 % on yearly basis in pre NRHM period. The various maternal and child health
interventions by NHM had succeeded well in declining maternal as well as child mortality rate.
Manifestations of impact of NHM can be observed in declining trends of infant, child and maternal
mortality indicators [4, 26, 34, 57].
Additionally, the logic regression analysis also looked at the health inequalities and found that in the
post NRHM period there has been reduction socioeconomic and geographic inequalities for IMR. The
infant mortality rate reduced with similar rate of reduction in urban and rural areas, among various caste
categories, the wealth quintiles, and EAG and non-EAG states. Neonatal mortality rate reduced with
highest rate of reduction in non-EAG states as compared to EAG states. However, the inequalities in
NMR did not reduce across socioeconomic and geographic gradients post NHM period. It was also
evident from the literature that some of the indicators are even better in rural areas as compared to
urban area like receiving ORS for diarrhoea, and immunization among female children during the NRHM
time period [80]. Inequalities related to institutional delivery among rich and poor also declined at steeper
rate in post NRHM time period [64]. MCH inequalities reduced due to more awareness regarding MCH
services by ASHA, free ambulances and diet during hospital stay [5].
We also found from the evidence that interventions other than NRHM such as road connectivity, mobile
connectivity and water sanitation had positive impact on health care utilization and has increased the 87
chances of full vaccination, maternal health services utilization. However, the secondary data used for
analysis in this study was adjusted for confounders like place of residence, maternal age, education,
religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health
worker density, road density, and telephone-density. Therefore it is unlikely that other interventions like
road connectivity, mobile connectivity, water sanitation and health were much effective in improving
MCH outcomes.
Strength and limitations of the study
The strength of this study is its integrated approach and holistic review of NRHM interventions related
to maternal and child health. To the best of our knowledge, this was the first kind of study to evaluate
the impact of NHM on health care utilization, inequalities and outcomes all together by using a logic
model evaluation framework at national level. We did the holistic review of impact of NRHM interventions
on health outcomes as well as the impact of interventions other than NRHM such as impact of road
connectivity, mobile connectivity, water supply and sanitation on MCH outcomes at national level. Also
our study has given due consideration to both pre and post intervention duration to have precise
comparisons. The estimates of slope for pre, post and change at the juncture are robust and precise in
comparison to the simple percentage decline over the years. The findings from the current study can be
generalized, as we did the analysis for assessing the impact of NRHM on health outcomes post NRHM
period at national level.
Our study has few limitations. Meta-analysis was not possible for each intervention due to heterogeneity
of studies, hence formal narrative synthesis was done. For trend analysis, the appropriate number of
data points remains the issue to limit the present analysis with respect to IMR only. In the absence of
suitable control, we could not use the randomized control trials design which are considered to be the
gold standards for the evaluation of intervention based studies. Also the inter-state comparison was not
done due to variation in socio demographic and developmental characteristics of a particular state. The
magnitude of the slope is valid only with respect to the previous period of the same state.
Public Health implications of the study 88
The results of this study have important public health implications as it was found that the public health
system can improve access, affordability, and effectiveness of health care delivery especially among
rural population, poor, women and children. The results of this study have shown that due to NRHM
schemes there has been significant improvement in MCH outcomes, therefore these schemes should
be further continued with special focus on poor women and children of rural areas. The schemes aiming
at improving child health such as RBSK and on adolescent health such as WIFS, MHS needs to be
strengthened. However, the investments in NRHM had been far below the requirements i.e.1.2% of GDP
for investing in health where goal was to increase it up to 2-3%.The further investments are likely to
strengthen HR, institutions and supplies leading to universal health coverage for treatment, prevention
and promotion and to attain NHP goals by 2025. However achievement of universal health coverage
requires the more rigorous planning, stringent enforcement of laws, consistent monitoring, optimum
health service delivery and innovative technologies. Hence, it can be stated that NRHM has played a
role through influencing health system in terms of improving MCH outcomes and reducing the MCH
inequalities. Therefore it is recommended that NHM should be continued with doubling of resources.
CONCLUSIONS
Evidence from the systematic review
Among maternal health care strategies, JSY strategy had a strong evidence in providing
financial incentives and promoting institutional delivery and reducing perinatal mortality.
JSSK had a role in providing free diagnostics there by increasing the affordability.
However, because of increase in the number of institutional deliveries the mortality in the
institutes reported to have increase in the tertiary care hospitals indicating poor quality
of intranatal and newborn care services.
Among the communitization component of NHM, ASHA scheme had a strong evidence
of reducing maternal mortality and perinatal mortality, through the pathway of contacting
the pregnant women at the household level in the villages, behavior change
communication, empowering and mobilizing them to the health facilities mainly for 89
institutional deliveries. VHND and VHNSC had weak evidence in bringing these health
outcomes.
Among child health strategies, FBNC, HBPNC, IMNCI and immunization had a strong
evidence in increasing the availability, affordability and accessibility of child health
services especially for the rural and poor community. RBSK and micronutrient
supplements had a weak evidence in improving the child health outcomes
Adolescent health strategies including WIFS, MHS, RKSK, AFHS had weak evidence in
improving the reproductive, maternal and child health outcomes.
Strategies under health system strengthening including increased infrastructure, free
drugs and medicines, free referral services, increased human resources (MOs,
specialists, ANMs) had a strong evidence in improving the availability affordability and
accessibility of MCH services, leading to community mobilization to use public facilities
leading to increase in the utilization of MCH services leading to early diagnosis and
treatment of child hood illnesses, improved antenatal and postnatal care leading
ultimately to improved MCH outcomes.
Evidence for use mobile medical units was weak in improving the MCH outcomes.
Evidence from secondary data analysis
Maternal mortality ratio (MMR) declined by 52%, from 257 per lakh live births in 2004-06
to 122 per lakh live births, in 2015-17. Nearly, 34.3% decline in MMR occurred during
NRHM period (2004-06 to 2011-13) and 26.9% decline during NHM period (2011-13 to
2015-17). Rate of decline per year was 12.7 points during 2004-06 to 2011-13, and it
was 11.3 points post 2011-13.
Under five mortality rate (U5MR) declined from 78 to 37 per thousand live births from
2005 to 2019, as per Unicef’s child mortality estimates. Overall, there is 52.6% reduction
in U5MR from 2005 to 2019, with 33.3% during NRHM period (2005-12) and 28.8% 90
during NHM period (2013-2019). Rate of decline per year was 3.7 points before and 2.5
points after the year 2013.
Rate of decline in U5MR per year increased from 2.6 points during 2008-12 to 5.25 points
after the year 2013, in Assam. Minimum reduction was seen in the state of Kerala which
varied from 14 to 11 in the same time period, as it already had very low U5MR. States
where rate of decline increased per year after the year 2013 were Gujarat (2.4 to 3
points), HP (1.4 to 3.5 points), Jammu and Kashmir (2.4 to 3.5), Jharkhand (3.0 to 3.75)
and West Bengal (0.8 to 2 points).
The infant mortality rate (IMR) had declined from 58 per 1000 live births to 40 per
thousand live births during 2005-13 (NRHM period) and to 33 per 1000 live births during
2013-17 (NHM period). The interrupted time series analysis have shown that the rate of
decline in IMR was 2.42 infant deaths per 1000 live births per annum before 2013, and
it accelerated to 2.10 infant deaths per 1000 live births per annum after the year 2013-
17. There was lot of interstate variability in IMR.
Overall the neonatal mortality reduced from 38 per thousand live births to 22 per
thousand live births, with a percentage decline of 42.1% from 2005 to 2019, as per
Unicef’s Child mortality estimates. The rate of decline per year was 1.4 points from 2005
to 2013 and 1.0 from 2013 to 2019.
Overall, the rate of decline per year for NMR was slower than the rate of decline in IMR
and U5MR.
The percentage decline was less for NMR (42.1%) as compared with IMR (43.1%) and
U5MR (52.6%), from 2005-19. However, the percentage decline for NMR (21.4%) was
higher as compared with IMR (17.5%) during NHM period (2013-17). This could be
attributed to better implementation of facility based new born care including sick new
born care units as evidenced from systematic review. 91
Total fertility rate has declined from 2.82 to 2.24 from 2007 to 2017. The percentage
decline was 20.6% in this period, with 15.6% decline till 2013 and 5.9% decline after
2013.
NHM has led to the improvement in the MCH outcomes. Also post NRHM period there
has been increase in the human resources and infrastructure and due to increase in
affordability, accessibility there is better access of MCH services.
There has been reduction in out of pocket expenditure (OOPE) for MCH and MCH
indicators have shown improvement which has led to reduction in IMR, NMR and MMR.
However, human resources and infrastructure are still half of the requirement. Also MCH
practices and utilization of services are still not optimum. Despite reduction in
expenditure, OOPE is still high.
Though the mortality indicators for maternal and child health have been declined, the
IMR, NMR and MMR is still high. The NHM has worked in both supply and demand side
components of public health system. Despite, the evidences on improved status of public
health system and decline in the targeted health indicators, the goal of equitable,
affordable and quality health care is still not fully achieved.
92
RECOMMENDATIONS
Maternal Health strategies
It is recommended to strengthen the implementation of successful schemes like ASHA,
Janani Suraksha Yojana, Janani Shishu Suraksha Karyakram, which have shown to be
associated with improvement in maternal health indicators. More focus should be given
for JSY implementation as there was high variability in implementation of JSY from state
to state. Also there was low coverage of JSY due to the inadequate funds for JSY and
delayed payments which should be taken into consideration. Increase in the hospital
based maternal mortality indicated poor quality of intranatal maternal care services.
Hence, there is need to focus on providing quality maternal health care services
especially during intranatal period. Laqshay strategy might have led to improvement in
the intranatal health care practices, which need to be evaluated in the near future.
Child health strategies
All facility based newborn care centers including NBCC, NBSU and SNCU should be
strengthened, and monitored by experts regularly to check the equipment status and
ensure that health personnel are following standard guidelines. Training regarding NSSK
should be provided to all the health personnel involved in newborn care. Health care
personnel in the delivery points should be sensitized or reoriented time to time regarding
various knowledge and skill for newborn care. It was found that there is an increased risk
of stillbirths in deferred and referred deliveries in addition to demographic and clinical
risk factors for ante-partum and intrapartum stillbirths which highlight the aspects of
health care that need attention in addition to improving skills of health providers to reduce
stillbirths. In case of referrals, partnership with private sector for improved quality of care
in referrals should be encouraged. It is also recommended to further strengthen the
implementation of immunization services, home based post-natal check-ups, integerated 93
management of childhood and neonatal illnesses, Nutritional Rehabilitation Centers, as
these were evidenced to have strong association with improving the child health
outcomes. Strategies like micronutrient supplementation, RBSK need to be further
evaluated for their effectiveness in improving the child health outcomes.
Reproductive Health strategies
The reproductive health indicators had definitely improved after inception of ASHA
worker in rural community. There is also an urgent need for such a change in urban area
for proper coverage of urban population. There is a need to take corrective measure on
tribal population as well as for EAG states as the prevalence of contraceptive usage was
found to be less among tribal population.
Adolescent Health strategies
Adolescent health strategies after merging with school health program can have better
performance so as to involve teachers, also to educate the children as well as
adolescents and counsel them according to their needs. Training should be given to
mothers as well as the teachers about menstrual hygiene as they are the primary source
of information. ARSH strategy needs to be advertised more effectively specially the focus
should be on RTI/STI and not only on HIV. NRHM has raised the awareness about
menstrual hygiene among adolescents but there is less awareness of government
scheme of distribution of sanitary napkins on subsidized rates. It can be advertised more
effectively by strengthening the IEC activities such as regular awareness campaigns,
community based awareness activities.
Communitization
Periodical refresher training and continuous capacity-building to improve knowledge and
skills of ASHAs should be conducted for the ASHA workers. ANMs and ASHAs should
also be employed to track the nutritional status of every child after their discharge from 94
the NRC and also for community based follow up and appropriate feedback to the
mothers. Also training of community health workers to address potential biases in quality
and quantity of their house visits based on socioeconomic, class and caste is
recommended so that inequalities can be reduced. The incentives can be increased for
ASHAs to mobilize the people of ST, SC and other minor communities. Microteaching
using video recording is an effective technique for improving home-based postnatal care
skills of the health care workers and a feasible option for supportive supervision. This
supervisory tool has public health implications in terms of scaling it up in routine program
settings to improve maternal and newborn survival. Greater coverage of ante-partum,
intrapartum and early postnatal health interventions in combination with promotion of
health care seeking behavior and links between communities and health facilities in
areas with lesser use of health care services should be enhanced.
Health system strengthening
It is recommended to strengthen the implementation of successful schemes like free
ambulance service, free medicine and diagnostic facilities, increased human resource
especially doctors and nurses as these have been evidenced to be associated with
improvement in maternal and child health outcomes. The schemes like medical mobile
units need to be reviewed again for their impact and utility, as these were found to be
weakly associated with improvement in MCH indicators. Resources spent upon this
strategy can be diverted to more effective strategies like free ambulance services. It is
also recommended to increase percentage of state budget on health to 8%, increase the
per capita public health expenditure in health from INR 1418 to INR 3000, increase the
number of beds in government hospitals & CHCs from 0.6 to at least 1 per 1000
population, increase the number of doctors, nurses and ANMs per 10,000 population in 95
government health facilities as per IPHS, and to establish one Arogya Kendra per 1000
population with one full time Health Promoter/Community Health Worker.
96
ANNEXURES
ANNEXURE 1. PRISMA CHECKLIST.
Section/topic # Checklist item
Page No.
TITLE
Title 1 Identify the report as a systematic review, meta-analysis, or
both.
N/A
ABSTRACT
Structured
summary
2 Provide a structured summary including, as applicable:
background; objectives; data sources; study eligibility
criteria, participants, and interventions; study appraisal and
synthesis methods; results; limitations; conclusions and
implications of key findings; systematic review registration
number.
N/A
INTRODUCTION
Rationale 3 Describe the rationale for the review in the context of what is
already known.
7
Objectives 4 Provide an explicit statement of questions being addressed
with reference to participants, interventions, comparisons,
outcomes, and study design (PICOS).
8
METHODS
Protocol and
registration
5 Indicate if a review protocol exists, if and where it can be
accessed (e.g., Web address), and, if available, provide
registration information including registration number.
annexure 2
Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-
up) and report characteristics (e.g., years considered,
language, publication status) used as criteria for eligibility,
giving rationale.
9-12
Information
sources
7 Describe all information sources (e.g., databases with dates
of coverage, contact with study authors to identify additional
studies) in the search and date last searched.
12-13
Search 8 Present full electronic search strategy for at least one
database, including any limits used, such that it could be
repeated.
13 and annexure
3
Study selection 9 State the process for selecting studies (i.e., screening,
eligibility, included in systematic review, and, if applicable,
included in the meta-analysis).
13 97
Section/topic # Checklist item
Page No.
Data collection
process
10 Describe method of data extraction from reports (e.g.,
piloted forms, independently, in duplicate) and any
processes for obtaining and confirming data from
investigators.
14
Data items 11 List and define all variables for which data were sought
(e.g., PICOS, funding sources) and any assumptions and
simplifications made.
11-12
Risk of bias in
individual
studies
12 Describe methods used for assessing risk of bias of
individual studies (including specification of whether this
was done at the study or outcome level), and how this
information is to be used in any data synthesis.
N/A
Summary
measures
13 State the principal summary measures (e.g., risk ratio,
difference in means).
N/A
Synthesis of
results
14 Describe the methods of handling data and combining
results of studies, if done, including measures of
consistency (e.g., I
2
) for each meta-analysis.
14 and Annexure
4
Risk of bias
across studies
15 Specify any assessment of risk of bias that may affect the
cumulative evidence (e.g., publication bias, selective
reporting within studies).
N/A
Additional
analyses
16 Describe methods of additional analyses (e.g., sensitivity or
subgroup analyses, meta-regression), if done, indicating
which were pre-specified.
N/A
RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility,
and included in the review, with reasons for exclusions at
each stage, ideally with a flow diagram.
13
Study
characteristics
18 For each study, present characteristics for which data were
extracted (e.g., study size, PICOS, follow-up period) and
provide the citations.
27-28 and
annexure 4
Risk of bias
within studies
19 Present data on risk of bias of each study and, if available,
any outcome level assessment (see item 12).
N/A
Results of
individual
studies
20 For all outcomes considered (benefits or harms), present,
for each study: (a) simple summary data for each
intervention group (b) effect estimates and confidence
intervals, ideally with a forest plot.
Annexure 4and 5
Synthesis of
results
21 Present results of each meta-analysis done, including
confidence intervals and measures of consistency.
Annexure 4 (N/A) 98
Section/topic # Checklist item
Page No.
Risk of bias
across studies
22 Present results of any assessment of risk of bias across
studies (see Item 15).
N/A
Additional
analysis
23 Give results of additional analyses, if done (e.g., sensitivity
or subgroup analyses, meta-regression -see Item 16).
N/A
DISCUSSION
Summary of
evidence
24 Summarize the main findings including the strength of
evidence for each main outcome; consider their relevance to
key groups (e.g., healthcare providers, users, and policy
makers).
53-58
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of
bias), and at review-level (e.g., incomplete retrieval of
identified research, reporting bias).
56-57
Conclusions 26 Provide a general interpretation of the results in the context
of other evidence, and implications for future research.
58
FUNDING
Funding 27 Describe sources of funding for the systematic review and
other support (e.g., supply of data); role of funders for the
systematic review.
N/A
99
ANNEXURE 2. PROTOCOLS FOR SYSTEMATIC REVIEW
The review protocols were registered with an open-access electronic database-PROSPERO
(International prospective register of systematic reviews). The protocol details are given below:
2.1. Impact of National Health Mission on Maternal Mortality Ratio of India: A systematic review
Review Question
Do National Health Mission strategies had any impact on maternal mortality ratio of India?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE
databases and Google Scholar. MeSH terms will be used to search the references and the reference
lists of all identified articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
maternal mortality ratio will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on maternal mortality
ratio.
Participants/population
Pregnant/antenatal, postpartum women.
Intervention(s), Exposure(s)
The exposure refers to any strategy of National Health Mission (NHM) India focussing on maternal
mortality ratio (MMR) of India. The main aim of NHM interventions such as Accredited Social Health
Activist (ASHA), Janani Suraksha Yojana (JSY), Janani Shishu Suraksha Karyakaram (JSSK), referral
transport is to promote institutional deliveries for reducing maternal mortality ratio. These might be in the
form of counselling, advertising, communitization, incentive or any other method of promoting 100
institutional deliveries such as collaborating with nongovernmental organizations, private sectors and
public sector undertakings through public private partnerships or reaching out to rural and poor and
other marginalized populations.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcome for this review is: Decrease in maternal mortality ratio.
Secondary outcome(s)
The secondary outcome for this review is: Increase in rate of institutional deliveries.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion.
3. Methods: Including the study design, study duration, sequence generation, allocation
concealment, and blinding.
4. Participants: Number and socio-demographics.
5. Interventions: Total groups or arms, and intervention details.
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection).
7. Results: Number of participants allocated in each group, sample size, missing data, summary
data, effect size estimates, and subgroup analysis (if applicable).
8. Other: Sources of funding.
9. Key conclusions.
10. Limitations.
11. Comments by the review authors.
12. Implications/Recommendations.
Two reviewers will extract the data independently and discuss with the other reviewers in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment 101
For this review, quality assessment would be conducted primarily for included studies focussing primarily
on maternal mortality ratio. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing impact of each strategy of NHM on maternal mortality ratio.
Meta-analysis will be conducted depending on availability of eligible studies. Minimum 5 studies will be
pooled and the results will be interpreted by using summary measures like risk ratio (in case of RCTs)
or percentages (in case of cross-sectional studies). The research findings will be aggregated to examine
the effectiveness of the interventions in focus under National Health Mission. The different interventions
will be pooled separately and the results will be described for each intervention. The results of those
studies which primarily focused upon maternal mortality ratio without referring to any particular
intervention will not be pooled for meta-analysis and will be narrated in the results. Finally,
recommendations will be made according to results obtained after extracting the results from each
eligible study. Subgroup analysis will be conducted as per the nature of the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Maternal
Mortality Ratio, Institutional Deliveries, Institutional Delivery Rate.
102
2.2. Impact of National Health Mission on Perinatal mortality rate of India: A Systematic Review
Registration ID: CRD42020147992
Review Question
In India, what is the impact of National Health Mission strategies on perinatal mortality rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
perinatal mortality rate will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on perinatal mortality
rate in India.
Participants
Neonates, antenatal/pregnant women, post-natal women.
Intervention(s), Exposure(s)
The exposure refers to any strategy focusing on improving perinatal health under the various strategies
implemented under National Health Mission, India. These interventions might be in the form of
counselling, advertising or any other method of improving neonatal health (such as collaborating with
nongovernmental organizations, private sectors and public sector undertakings) through public private
partnerships or reaching out to rural and poor and other marginalized populations.
Comparator(s)/control 103
Not applicable
Primary outcome(s)
The primary outcome for this review is: Perinatal mortality rate
Secondary outcome(s)
The secondary outcomes include: Stillbirth rate, Early Neonatal mortality rate.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion.
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding.
4. Participants: Number and socio-demographics.
5. Interventions: Total groups or arms, and intervention details.
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection).
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable).
8. Other: Sources of funding.
9. Key conclusions.
10. Limitations.
11. Comments by the review authors.
12. Implications/Recommendations. 104
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on perinatal mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on perinatal mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focused upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission strategies,
perinatal mortality rate.
105
2.3. Impact of National Health Mission on neonatal mortality rate of India: A Systematic Review
Review Question
In India, what is the impact of newborn health strategies under National Health Mission on neonatal
mortality rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
neonatal mortality rate will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on neonatal mortality in
India.
Participants
Neonates, antenatal/pregnant women, post-natal women.
Intervention(s), Exposure(s)
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on neonatal mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case 106
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focussed upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcome for this review is: Neonatal mortality rate
Secondary outcome(s)
The secondary outcomes include:
Breast feeding practices
Newborn care practices
Prevalence of LBW
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details 107
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on neonatal mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on neonatal mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focussed upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after 108
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Child health
strategies, Neonatal mortality rate.
2.4. Impact of National Health Mission on infant mortality rate of India: A Systematic Review
Review Question
In India, what is the impact of child health strategies under National Health Mission on infant mortality
rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
infant mortality rate will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on infant mortality in
India.
Participants
Women in reproductive age group (15-49 years)/eligible couples, Newborns, Infants, ASHA workers,
ANMs, Anganwadi workers, Service providers.
109
Intervention(s), Exposure(s)
The exposure refers to any strategy focusing on improving infant health under the Child Health
Programme implemented under National Health Mission, India. These interventions might be in the form
of counselling, advertising or any other method of improving infant health (such as collaborating with
nongovernmental organizations, private sectors and public sector undertakings) through public private
partnerships or reaching out to rural and poor and other marginalized populations.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcome for this review is: Infant mortality rate
Secondary outcome(s)
The secondary outcomes include:
Prevalence of exclusive breast feeding
Increased knowledge of ASHAs in HBPNC
Increase in immunization coverage
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details 110
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on infant mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on infant mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focused upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after 111
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Child health
strategies, Infant mortality rate.
112
2.5 Impact of National Health Mission on under 5 child mortality rate of India: A Systematic
Review
Review Question
In India, what is the impact of child health strategies under National Health Mission on under 5 child
mortality rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
mortality rate in children under 5 years will be included for review. In addition grey literature will be hand
searched and evidence including reports from government and non-governmental agencies and reports
from international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on child mortality in
India.
Participants
Children up-to the age group of 5 years.
Intervention(s), Exposure(s)
The exposure refers to any strategy focusing on improving child health under the Child Health
Programme implemented under National Health Mission, India. These interventions might be in the form
of counselling, advertising or any other method of improving child health (such as collaborating with
nongovernmental organizations, private sectors and public sector undertakings) through public private
partnerships or reaching out to rural and poor and other marginalized populations.
Comparator(s)/control 113
Not applicable
Primary outcome(s)
The primary outcome for this review is:
Under 5 child mortality rate
Secondary outcome(s)
The secondary outcomes include:
Increase in immunization coverage
Decrease in malnutrition
Increase in Vitamin A supplementation
Incidence of pneumonia and diarrhoea
Early detection and treatment of diseases
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection) 114
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on child mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on under five mortality
rate. The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5
studies will be pooled and the results will be interpreted by using summary measures like risk ratio (in
the case of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study
findings. The research findings will be aggregated to examine the effectiveness of the interventions in
focus under the National Health Mission. The different interventions will be pooled separately and the
results will be described for each intervention. The results of those studies which primarily focused upon
neonatal mortality rate without referring to any particular intervention will not be pooled for meta-analysis
and will be narrated in the results. Finally, recommendations will be made according to results obtained
after extracting the results from each eligible study. Subgroup analysis will be conducted as per the
nature of the data obtained.
Subject index terms 115
National Rural Health Mission, National Urban Health Mission, National Health Mission, Child health
strategies, U 5 child mortality rate.
2.6. Impact of National Health Mission on total fertility rate of India: A systematic review
Review Question
In India,
1. Do the family planning program under National Health Mission had any impact on total fertility
rate?
2. Do the family planning program under National Health Mission had any impact on contraceptive
prevalence rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE and
CINAHL. The reference lists of all identified articles on interventions will be checked to identify relevant
studies. In addition, citations tracking of prominent researchers working in the field of family planning
will be conducted to identify relevant articles. Further, hand-searching of the contents of reputed
obstetric/public health journals and conference proceedings will also be conducted. Relevant articles
and reports will be searched in Google, Google Scholar, and in databases of agencies such as UNICEF
and WHO.
Types of studies to be included
Both quantitative and qualitative studies focussing upon impact of NHM strategies on family planning or
contraceptive usage will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on family planning and contraceptive prevalence in India.
Participants
Women in reproductive age group (15-49 years)/ eligible couples.
Intervention(s), Exposure(s) 116
The exposure refers to any strategy focusing on birth control under the reproductive health program
implemented by the Ministry of Health and Family Welfare, India. These interventions might be in the
form of counselling, advertising, communitization or any other method of promoting family planning
methods (such as collaborating with nongovernmental organizations, private sectors and public sector
undertakings through public private partnerships or reaching out to rural and poor and other marginalized
populations.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcomes for this review are:
Total fertility rate
Contraceptive prevalence rate
Secondary outcome(s)
The secondary outcomes include:
Total unmet need
Gaps in strategies for family planning under National Health Mission.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details 117
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing
primarily on total fertility rate in India. However, systematic data extraction would be conducted for all
relevant sources. For this review, quality assessment would be conducted primarily on total fertility
rate and contraceptive prevalence rate in India. However, systematic data extraction would be
conducted for all relevant sources. The Cochrane risk of bias tool will be used to assess the internal
validity. The quality assessment will be done by two reviewers and any disagreement between
reviewers judgement will be resolved by the third reviewer. Depending upon the study design the risk
of bias will be assessed. In randomized control trials the clarity in description of randomization,
allocation concealment and blinding will be assessed. The study will be assessed critically on the
basis of methodology followed in the study. The studies will be segregated in terms of low, moderate
and high risk of bias. The studies with minimal risk of bias will be pooled for meta-analysis.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on total fertility rate. The
meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies will
be pooled and the results will be interpreted by using summary measures like risk ratio (in the case of 118
RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focused upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g. urban and
rural settings, education status) on outcomes such as contraceptive prevalence rate will be summarized
by relevant measures (e.g., rate ratios).
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Total Fertility
Rate, Family Planning, Contraceptive Prevalence Rate.
119
2.7 Level of awareness and utilization of Adolescent Reproductive and Sexual Health Services
clinics in India: A systematic review
Review Question
In India,
1) What is the level of awareness and utilization of adolescent reproductive and sexual health
service clinics in India?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE. The
reference lists of all identified articles on interventions will be checked to identify relevant studies. In
addition, citations tracking of prominent researchers working in the field of adolescent health will be
conducted to identify relevant articles. Further, hand-searching of the contents of reputed public health
journals and conference proceedings will also be conducted. Relevant articles and reports will be
searched in Google, Google Scholar, and in databases of agencies such as WHO.
Types of studies to be included
Both quantitative and qualitative studies focusing upon awareness of adolescent reproductive and
sexual health service (ARSH) clinics implemented as a strategy under national health mission (NHM)
for providing information regarding sex, stages of development, RTI/STI or menstrual hygiene to the
adolescent age group will be included for review. In addition, grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on level of awareness and utilization of adolescent reproductive and
sexual health service clinics in India.
Intervention(s), Exposure(s)
The exposure refers to the awareness and utilization of ARSH services under NHM implemented by the
Ministry of Health and Family Welfare, India by adolescents for any purpose related to their health. The
purpose may be for procuring sanitary napkins or asking for any guidance from counsellors.
Comparator(s)/control 120
In case a randomized control study or a quasi-experimental study has been conducted the controls will
include those adolescents which will not be given the above stated intervention.
Primary outcome(s)
The primary outcomes for this review are:
Awareness and utilization of adolescent reproductive and sexual health service clinics
Secondary outcome(s)
Nil
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA/STROBE guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding (if applicable)
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations 121
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing
primarily on awareness of ARSH clinics among adolescents in India. However, systematic data
extraction would be conducted for all relevant sources. The Cochrane risk of bias tool will be used to
assess the internal validity. The quality assessment will be done by two reviewers and any
disagreement between reviewers judgement will be resolved by the third reviewer. Depending upon
the study design the risk of bias will be assessed. In randomized control trials the clarity in description
of randomization, allocation concealment and blinding will be assessed. The study will be assessed
critically on the basis of methodology followed in the study. The studies will be segregated in terms
of low, moderate and high risk of bias. The studies with minimal risk of bias will be pooled for meta-
analysis.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of ARSH clinics on awareness and utilization by
adolescents in India. A meta-analysis will be conducted depending on the availability of eligible studies.
Minimum 5 studies will be pooled and the results will be interpreted by using summary measures like
risk ratio (in the case of RCTs) or percentages (in the case of cross-sectional studies). The research
findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The results of those studies which primarily focused upon the ARSH strategy
will be pooled for meta-analysis. Finally, recommendations will be made according to results obtained
after extracting the results from each eligible study. Subgroup analysis will be conducted as per the
nature of the data obtained.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g. Urban
and rural settings, education status) on outcomes such as utilization of ARSH clinics will be summarized
by relevant measures (e.g. proportions). 122
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, adolescent
reproductive and sexual health (ARSH), Adolescent health, Anaemia
2.8 Level of awareness and utilization of Menstrual Hygiene Scheme in India: A systematic review
Registration ID: CRD42020148116
Review Question
In India,
1) What is the level of awareness regarding menstrual hygiene among adolescents in India?
2) What is the utilization rate of sanitary napkins among adolescents in India?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE. The
reference lists of all identified articles on interventions will be checked to identify relevant studies. In
addition, citations tracking of prominent researchers working in the field of adolescent health will be
conducted to identify relevant articles. Further, hand-searching of the contents of reputed public health
journals and conference proceedings will also be conducted. Relevant articles and reports will be
searched in Google, Google Scholar, and in databases of agencies such as WHO.
Types of studies to be included
Both quantitative and qualitative studies focusing upon awareness of menstrual hygiene or utilization
rate of sanitary napkins among adolescent age group published after the launch of national rural health
mission (NRHM) will be included for review. In addition, grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies like UNICEF will also be included.
Condition or domain being used
This systematic review focuses on level of awareness regarding menstrual hygiene and utilization rate
of sanitary napkins among adolescents in India.
Intervention(s), Exposure(s)
The exposure refers to the awareness generation regarding menstrual hygiene that may be through
information education and communication by organizing camps in schools or in residential areas. In 123
case of cross-sectional studies assessment of the knowledge and awareness about menstrual hygiene
program being implemented under NHM by the Ministry of Health and Family Welfare, India will be done.
Apart from this the usage of sanitary napkins will be assessed as these are provided at subsidized rates
under menstrual hygiene scheme.
Comparator(s)/control
In case a randomized control study or a quasi-experimental study has been conducted the controls will
include those adolescents which will not be given the above stated intervention.
Primary outcome(s)
The primary outcomes for this review are:
Awareness about menstrual hygiene
Utilization rate of sanitary napkins among adolescents
Secondary outcome(s)
Nil
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA/STROBE guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding (if applicable)
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection) 124
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implication recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on awareness generation regarding menstrual hygiene or utilization of sanitary napkins among
adolescents in India. However, systematic data extraction would be conducted for all relevant sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g., urban
and rural settings, education status) on outcomes such as utilization of sanitary napkins will be
summarized by relevant measures (e.g. proportions).
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Menstrual
Hygiene, Menstrual Hygiene Scheme, Adolescent health.
125
2.9 Impact of weekly iron and folic acid supplementation on prevalence of anaemia among
adolescents in India: A systematic review
Review Question
In India,
1) Does the Weekly Iron and Folic acid supplementation program under National Health Mission
had any impact on reducing anaemia in adolescents?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE. The
reference lists of all identified articles on interventions will be checked to identify relevant studies. In
addition, citations tracking of prominent researchers working in the field of adolescent health will be
conducted to identify relevant articles. Further, hand-searching of the contents of reputed public health
journals and conference proceedings will also be conducted. Relevant articles and reports will be
searched in Google, Google Scholar, and in databases of agencies such as UNICEF and WHO.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of weekly supplementation of iron and
folic acid (WIFS) program implemented as a strategy under national health mission (NHM) on
prevalence of anemia among adolescents in India will be included for review. In addition, grey literature
will be hand searched and evidence including reports from government and non-governmental agencies
and reports from international agencies will also be included.
Condition or domain being used
This systematic review focuses on prevalence of anaemia among adolescents after the launch of WIFS
program in India.
Intervention(s), Exposure(s)
The exposure refers to the intake of iron and folic acid supplementation in any dose under the WIFS
program under NHM implemented by the Ministry of Health and Family Welfare, India. These
interventions might be in the form of tablets or syrups provided to the adolescents by public sector
undertakings or nongovernmental organizations, private sectors or through public private partnerships.
Comparator(s)/control 126
In case a randomized control study or a quasi-experimental study has been conducted the controls will
include those adolescents which will not be given the above stated intervention.
Primary outcome(s)
The primary outcome for this review is:
Prevalence of anaemia
Secondary outcome(s)
The secondary outcomes include:
Improvement in body mass index
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA/STROBE guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding (if applicable)
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions 127
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on prevalence of anaemia among adolescents after the implementation of WIFS program in India.
However, systematic data extraction would be conducted for all relevant sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data.
The research findings will be aggregated to examine the effectiveness of the interventions in focus under
WIFS program.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g., urban
and rural settings, education status) on outcomes such as prevalence of anaemia will be summarized
by relevant measures (e.g., rate ratios, mean difference).
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Weekly Iron and
Folic Acid Supplementation (WIFS), Adolescent health, Anaemia.
128
2.10. Impact of Road Connectivity, Mobile Connectivity and Others Variables on Health
Outcomes in India: A Systematic Review
Review Question
In India,
1) Do Road Connectivity, Mobile Connectivity and other variables such as water supply, sanitation and
nutrition, had any impact on health outcomes?
Methods
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE
databases and Google Scholar. MeSH terms will be used to search the references and the reference
lists of all identified articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of variables such as road connectivity
and mobile connectivity on health outcomes will be included for review. In addition grey literature will be
hand searched and evidence including reports from government and non-governmental agencies and
reports from international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of variables such as road connectivity and mobile connectivity
on health outcomes.
Participants/population
Pregnant/antenatal, postpartum females, health workers, children, adolescents.
Intervention(s), Exposure(s)
The exposure refers to any variables focusing on health outcomes. These variables might be any social
or infrastructural, impacting health outcomes.
Comparator(s)/control
Not applicable
Primary outcome(s) 129
The primary outcome for this review is: Impact on health outcomes.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation
concealment, and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary
data, effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
Two reviewer will extract the data independently and discuss with the other reviewers in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focussing on
impact of road and mobile connectivity on health outcomes. However, systematic data extraction would
be conducted for all relevant sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data
The research findings will be aggregated to examine the effectiveness of the road and mobile
connectivity and other variables in focus of health outcomes.
Subject index terms 130
Road connectivity, mobile connectivity, water supply, nutrition, health outcomes.
2.11. Impact of National Health Mission on maternal and child health inequalities in India: A
Systematic Review
Review Question
What is the impact of National Health Mission on maternal and child health inequalities in India?
Methods
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE
databases and Google Scholar. MeSH terms will be used to search the references and the reference
lists of all identified articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies
on health inequalities (maternal and child health) will be included for review. In addition grey
literature will be hand searched and evidence including reports from government and non-
governmental agencies and reports from international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission on maternal and child health
inequalities.
Participants/population
Mothers, pregnant females, postpartum females, children
Intervention(s), Exposure(s)
The exposure refers to any strategy of National Health Mission India focusing on maternal and child
health inequalities. These interventions might be in the form of counselling, advertising,
communitization, incentive or any other method of promoting maternal and child health such as
collaborating with nongovernmental organizations, private sectors and public sector undertakings 131
through public private partnerships or reaching out to rural and poor and other marginalised
population.
Comparator(s)/control
Not applicable
Primary outcome(s)
Impact on maternal and child health inequalities after launch of National Health Mission in India.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation
concealment, and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary
data, effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
Two reviewer will extract the data independently and discuss with the other reviewers in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing
primarily on maternal and child health inequalities. However, systematic data extraction would be
conducted for all relevant sources. 132
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under
National Health Mission.
Subject index terms
Health inequalities, maternal health inequalities, child health inequalities, National Rural Health
Mission, National Urban Health Mission, National Health Mission, Janani Suraksha Yojana,
Accredited Social Health Activist, Janani Shishu Surakhsha Karyakram, referral transport.
ANNEXURE 3. MeSH STRATEGY.
Maternal Health
Keywords
MeSH
Maternal mortality
ratio AND India
(("maternal mortality"[MeSH Terms] OR ("maternal"[All Fields] AND
"mortality"[All Fields]) OR "maternal mortality"[All Fields]) AND ("Ratio
(Oxf)"[Journal] OR "ratio"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"National Health
Mission" impact on
"Maternal mortality
ratio" AND "India"
"National Health Mission"[All Fields] AND ("Impact (Am Coll
Physicians)"[Journal] OR "impact"[All Fields]) AND "Maternal mortality ratio"[All
Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Birth preparedness
and complication
readiness AND
maternal mortality
ratio AND India
(("parturition"[MeSH Terms] OR "parturition"[All Fields] OR "birth"[All Fields])
AND preparedness[All Fields] AND complication[All Fields] AND readiness[All
Fields]) AND (("maternal mortality"[MeSH Terms] OR ("maternal"[All Fields]
AND "mortality"[All Fields]) OR "maternal mortality"[All Fields]) AND ("Ratio
(Oxf)"[Journal] OR "ratio"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Janani Suraksha
Yojana
"Janani Suraksha Yojana"[All Fields] AND "India"[All Fields]
Janani Shishu
Suraksha Karyakram
“Janani Shishu Suraksha Karyakram"[All Fields] AND "India"[All Fields])
Antenatal care OR
Postnatal care OR
Intranatal care AND
("prenatal care"[MeSH Terms] OR ("prenatal"[All Fields] AND "care"[All Fields])
OR "prenatal care"[All Fields] OR ("antenatal"[All Fields] AND "care"[All
Fields]) OR "antenatal care"[All Fields]) OR ("postnatal care"[MeSH Terms] OR
("postnatal"[All Fields] AND "care"[All Fields]) OR "postnatal care"[All Fields])
Maternal mortality
ratio AND India
OR (Intranatal[All Fields] AND care[All Fields]) AND (("maternal
mortality"[MeSH Terms] OR ("maternal"[All Fields] AND "mortality"[All Fields])
OR "maternal mortality"[All Fields]) AND ("Ratio (Oxf)"[Journal] OR "ratio"[All
Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"free ambulance"
AND "maternal
mortality ratio" AND
"India"
"free ambulance"[All Fields] AND "maternal mortality ratio"[All Fields] AND
"India"[All Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
(ASHA role) AND
Maternal mortality
(("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All Fields]) AND
("role"[MeSH Terms] OR "role"[All Fields])) AND ("maternal mortality"[MeSH
Terms] OR ("maternal"[All Fields] AND "mortality"[All Fields]) OR "maternal
mortality"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
((ASHA worker) AND
Maternal health) AND
India
((("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All Fields]) AND
("occupational groups"[MeSH Terms] OR ("occupational"[All Fields] AND
"groups"[All Fields]) OR "occupational groups"[All Fields] OR "worker"[All
Fields])) AND ("maternal health"[MeSH Terms] OR ("maternal"[All Fields] AND
"health"[All Fields]) OR "maternal health"[All Fields])) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
((ASHA) AND
maternal mortality
ratio) AND India
(("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All Fields]) AND
(("maternal mortality"[MeSH Terms] OR ("maternal"[All Fields] AND
"mortality"[All Fields]) OR "maternal mortality"[All Fields]) AND ("Ratio
(Oxf)"[Journal] OR "ratio"[All Fields]))) AND ("india"[MeSH Terms] OR
"india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
referral transport
AND maternal
mortality AND India
((("referral and consultation"[MeSH Terms] OR ("referral"[All Fields] AND
"consultation"[All Fields]) OR "referral and consultation"[All Fields] OR
"referral"[All Fields]) AND ("biological transport"[MeSH Terms] OR
("biological"[All Fields] AND "transport"[All Fields]) OR "biological transport"[All
Fields] OR "transport"[All Fields])) AND ("maternal mortality"[MeSH Terms] OR
("maternal"[All Fields] AND "mortality"[All Fields]) OR "maternal mortality"[All
Fields])) AND ("india"[MeSH Terms OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"Prahdhan Mantri
Matritva Vandana
Yojana" AND
"maternal mortality
ratio" AND "India"
(mantri[All Fields] AND matritva[All Fields] AND vandana[All Fields] AND
("Yojana"[Journal] OR "yojana"[All Fields])) AND "maternal mortality ratio"[All
Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"Prahdhan Mantri
Surakshit Matritva
Abhiyan" AND
"maternal mortality
ratio" AND "India"
(Mantri[All Fields] AND Surakshit[All Fields] AND Matritva[All Fields] AND
Abhiyan[All Fields]) AND "maternal mortality ratio"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"Prahdhan Mantri
Matritva Sahyog
Yojna" AND
"maternal mortality
ratio" AND "India"
(Mantri[All Fields] AND Matritva[All Fields] AND Sahyog[All Fields] AND
Yojna[All Fields]) AND "maternal mortality ratio"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
NEWBORN AND CHILD HEALTH
Neonatal Mortality
rate (NMR)
"Infant mortality"[MeSH Terms] OR ("infant"[All Fields] AND "mortality"[All
Fields]) OR "infant mortality"[All Fields] OR ("neonatal"[All Fields] AND
"mortality"[All Fields]) OR "neonatal mortality"[All Fields]
Facility based
newborn care
(FBNC)
Facility[All Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All
Fields] OR "newborn"[All Fields]) AND care[All Fields]
Essential newborn
care
Essential[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All
Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"newborn"[All Fields]) AND care[All Fields]
Special New Born
Care Units (SNCUs)
Special[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All Fields]
AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "newborn"[All
Fields]) AND care[All Fields] AND unit[All Fields]
New Born Baby
Corners (NBCCs)
New[All Fields] AND ("parturition"[MeSH Terms] OR "parturition"[All Fields] OR
"born"[All Fields]) AND ("infant, newborn"[MeSH Terms] OR ("infant"[All Fields]
AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "baby"[All Fields]
OR "infant"[MeSH Terms] OR "infant"[All Fields]) AND corners[All Fields]) OR
"NBCC"[All Fields]
Breast feeding
practices
Breast feeding practices"[All Fields] AND "India"[MeSH Terms]
Navjat Shishu
Shuraksha
Karyakaram (NSSK)
Navjat[All Fields] AND shishu [All Fields] AND suraksha [All Fields] AND
karyakram [All Fields]) OR NSSK[All Fields]
Home based
newborn care by
ASHA (HBNC)
Home [All Fields] AND BASED[All Fields] AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All
Fields] OR "newborn"[All Fields]) AND CARE[All Fields] AND ("ASHA"[Journal]
OR "ASHA Suppl"[Journal] OR "asha"[All Fields]
Infant and Young
Child Feeding
Practices AND
India
Infant[Title] AND Young[Title] AND Child[Title] AND Feeding[Title] AND
Practices[Title] AND india[Title]
Home based
newborn care by
ASHA AND India
(Home[All Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All
Fields] OR "newborn"[All Fields]) AND care[All Fields] AND ("ASHA"[Journal]
OR "ASHA Suppl"[Journal] OR "asha"[All Fields])) AND ("india"[MeSH Terms]
OR "india"[All Fields])
Integrated
management of
neonatal and
childhood illness
AND Children AND
India
(Integrated[All Fields] AND ("organization and administration"[MeSH Terms]
OR ("organization"[All Fields] AND "administration"[All Fields]) OR
"organization and administration"[All Fields] OR "management"[All Fields] OR
"disease management"[MeSH Terms] OR ("disease"[All Fields] AND
"management"[All Fields]) OR "disease management"[All Fields]) AND
("infant, newborn"[MeSH Terms] OR ("infant"[All Fields] AND "newborn"[All
Fields]) OR "newborn infant"[All Fields] OR "neonatal"[All Fields]) AND
("Childhood"[Journal] OR "childhood"[All Fields]) AND illness[All Fields]) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND (("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Early initiation and
exclusive breast
feeding
Early[All Fields] AND initiation[All Fields] AND ("breast feeding"[MeSH Terms]
OR ("breast"[All Fields] AND "feeding"[All Fields]) OR "breast feeding"[All
Fields] OR ("exclusive"[All Fields] AND "breast"[All Fields] AND "feeding"[All
Fields]) OR "exclusive breast feeding"[All Fields]
Tracking of low birth
weight babies
Tracking[All Fields] AND ("infant, low birth weight"[MeSH Terms] OR
("infant"[All Fields] AND "low"[All Fields] AND "birth"[All Fields] AND "weight"[All
Fields]) OR "low birth weight infant"[All Fields] OR ("low"[All Fields] AND
"birth"[All Fields] AND "weight"[All Fields]) OR "low birth weight"[All Fields])
AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR "babies"[All Fields]
Mothers’ Absolute
Affection
Programme (MAA)
Mothers'[All Fields] AND Absolute[All Fields] AND Affection[All Fields] AND
Programme[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]
Management of
Diarrheal diseases
with ORS and zinc
AND Infants AND
India
(("organization and administration"[MeSH Terms] OR ("organization"[All
Fields] AND "administration"[All Fields]) OR "organization and
administration"[All Fields] OR "management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All
Fields]) OR "disease management"[All Fields]) AND Diarrheal[All Fields] AND
("disease"[MeSH Terms] OR "disease"[All Fields] OR "diseases"[All Fields])
AND ("ORALIT"[Supplementary Concept] OR "ORALIT"[All Fields] OR
"ors"[All Fields]) AND ("zinc"[MeSH Terms] OR "zinc"[All Fields])) AND
("infant"[MeSH Terms] OR "infant"[All Fields] OR "infants"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields])
Intensified
Diarrhea Control
Fortnight AND
Infants AND India
(Intensified[All Fields] AND ("diarrhoea"[All Fields] OR "diarrhea"[MeSH
Terms] OR "diarrhea"[All Fields]) AND ("prevention and control"[Subheading]
OR ("prevention"[All Fields] AND "control"[All Fields]) OR "prevention and
control"[All Fields] OR "control"[All Fields] OR "control groups"[MeSH Terms]
OR ("control"[All Fields] AND "groups"[All Fields]) OR "control groups"[All
Fields]) AND Fortnight[All Fields]) AND ("infant"[MeSH Terms] OR "infant"[All
Fields] OR "infants"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Mothers’ Absolute
Affection
Programme (MAA)
(Mothers'[All Fields] AND Absolute[All Fields] AND Affection[All Fields] AND
Programme[All Fields]) AND MAA[All Fields] AND ("india"[MeSH Terms] OR
"india"[All Fields])
Tracking of low
birth weight babies
AND India
(Tracking[All Fields] AND ("infant, low birth weight"[MeSH Terms] OR
("infant"[All Fields] AND "low"[All Fields] AND "birth"[All Fields] AND "weight"[All
Fields]) OR "low birth weight infant"[All Fields] OR ("low"[All Fields] AND
"birth"[All Fields] AND "weight"[All Fields]) OR "low birth weight"[All Fields])
AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR "babies"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields])
Management of
Acute Respiratory
Infections AND
Infants AND India
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields]
AND "administration"[All Fields]) OR "organization and administration"[All
Fields] OR "management"[All Fields] OR "disease management"[MeSH Terms]
OR ("disease"[All Fields] AND "management"[All Fields]) OR "disease
management"[All Fields]) AND Acute[All Fields] AND ("respiratory tract
infections"[MeSH Terms] OR ("respiratory"[All Fields] AND "tract"[All Fields]
AND "infections"[All Fields]) OR "respiratory tract infections"[All Fields] OR
("respiratory"[All Fields] AND "infections"[All Fields]) OR "respiratory
infections"[All Fields])) AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR
"infants"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields])
Micronutrient
supplementation
(Vitamin A, Iron
Folic Acid) AND
Infants AND
Mortality AND
India
(("trace elements"[Pharmacological Action] OR
"micronutrients"[Pharmacological Action] OR "trace elements"[MeSH Terms]
OR ("trace"[All Fields] AND "elements"[All Fields]) OR "trace elements"[All
Fields] OR "micronutrient"[All Fields] OR "micronutrients"[MeSH Terms] OR
"micronutrients"[All Fields]) AND supplementation[All Fields]) AND (("vitamin
a"[MeSH Terms] OR "vitamin a"[All Fields]) AND ("iron"[MeSH Terms] OR
"iron"[All Fields]) AND ("folic acid"[MeSH Terms] OR ("folic"[All Fields] AND
"acid"[All Fields]) OR "folic acid"[All Fields])) AND ("infant"[MeSH Terms] OR
"infant"[All Fields] OR "infants"[All Fields]) AND ("mortality"[Subheading] OR
"mortality"[All Fields] OR "mortality"[MeSH Terms]) AND ("india"[MeSH Terms]
OR "india"[All Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Early initation and
exclusive breast
feeding AND India
(early[All Fields] AND initiation[All Fields] AND ("breast feeding"[MeSH Terms]
OR ("breast"[All Fields] AND "feeding"[All Fields]) OR "breast feeding"[All
Fields] OR ("exclusive"[All Fields] AND "breast"[All Fields] AND "feeding"[All
Fields]) OR "exclusive breast feeding"[All Fields])) AND ("india"[MeSH Terms]
OR "india"[All Fields])
Full immunization
coverage AND
Children AND India
(Full[All Fields] AND ("vaccination coverage"[MeSH Terms] OR ("vaccination"[All
Fields] AND "coverage"[All Fields]) OR "vaccination coverage"[All Fields] OR
("immunization"[All Fields] AND "coverage"[All Fields]) OR "immunization
coverage"[All Fields])) AND ("child"[MeSH Terms] OR "child"[All Fields] OR
"children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Complementary
feeding practices
AND Infants AND
India
(("infant nutritional physiological phenomena"[MeSH Terms] OR ("infant"[All
Fields] AND "nutritional"[All Fields] AND "physiological"[All Fields] AND
"phenomena"[All Fields]) OR "infant nutritional physiological phenomena"[All
Fields] OR ("complementary"[All Fields] AND "feeding"[All Fields]) OR
"complementary feeding"[All Fields]) AND practices[All Fields]) AND
("infant"[MeSH Terms] OR "infant"[All Fields] OR "infants"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Prevalence of
diarrhea in Infants
in India
(("epidemiology"[Subheading] OR "epidemiology"[All Fields] OR "prevalence"[All
Fields] OR "prevalence"[MeSH Terms]) AND ("diarrhoea"[All Fields] OR
"diarrhea"[MeSH Terms] OR "diarrhea"[All Fields]) AND ("infant"[MeSH Terms]
OR "infant"[All Fields] OR "infants"[All Fields]) AND ("india"[MeSH Terms] OR
"india"[All Fields])) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Management of
pneumonia AND
Infants AND India
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields]
AND "administration"[All Fields]) OR "organization and administration"[All Fields]
OR "management"[All Fields] OR "disease management"[MeSH Terms] OR
("disease"[All Fields] AND "management"[All Fields]) OR "disease
management"[All Fields]) AND ("pneumonia"[MeSH Terms] OR "pneumonia"[All
Fields])) AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR "infants"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Impact Indicator:
Infant Mortality Rate
in India
(("infant mortality"[MeSH Terms] OR ("infant"[All Fields] AND "mortality"[All
Fields]) OR "infant mortality"[All Fields]) AND ("J Rehabil Assist Technol
Eng"[Journal] OR "rate"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields])) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Perinatal mortality
rate AND India
"perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND "mortality"[All
Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH Terms] OR
("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All Fields] OR
("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("india"[MeSH Terms] OR
"india"[All Fields]) AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Impact of Home
based newborn care
on perinatal
mortality india
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND home[All
Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All
Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "newborn"[All
Fields]) AND care[All Fields] AND ("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All
Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All
Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields])) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Janani Suraksha
Yojana AND
Perinatal mortality
AND India
(Janani[All Fields] AND Suraksha[All Fields] AND ("Yojana"[Journal] OR "yojana"[All
Fields])) AND ("perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND
"mortality"[All Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH
Terms] OR ("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All
Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of "Janani
Shishu Suraksha
Karyakram" AND
"Perinatal Mortality"
AND India
("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND "Janani Shishu
Suraksha Karyakram"[All Fields] AND "Perinatal Mortality"[All Fields] AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Impact of
"Institutional
Delieveries" AND
=("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND
Institutional[All Fields] AND "Perinatal Mortality"[All Fields] AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"Perinatal Mortality"
AND India
Accredited Social
Health Activist AND
Perinatal Mortality
AND India
(Accredited[All Fields] AND Social[All Fields] AND ("health"[MeSH Terms] OR
"health"[All Fields]) AND Activist[All Fields]) AND ("perinatal mortality"[MeSH Terms]
OR ("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All
Fields] OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND
"death"[All Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND
"mortality"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of Navjat
Shishu Suraksha
Krayakram on
Perinatal Mortality
AND India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND Shishu[All
Fields] AND Suraksha[All Fields] AND ("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All
Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All
Fields]))) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Facility based
newborn care AND
perinatal mortality
AND India
(Facility[All Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms] OR
("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"newborn"[All Fields]) AND care[All Fields]) AND ("perinatal mortality"[MeSH Terms]
OR ("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All
Fields] OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND
"death"[All Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND
"mortality"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Essential newborn
care AND Perinatal
(Essential[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All Fields]
AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "newborn"[All Fields])
mortality rate AND
India
AND care[All Fields]) AND (("perinatal mortality"[MeSH Terms] OR ("perinatal"[All
Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields] OR "perinatal
death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All Fields]) OR
"perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields]))
AND ("J Rehabil Assist Technol Eng"[Journal] OR "rate"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]
Traditional Birth
attendants AND
Perinatal mortality in
India
("midwifery"[MeSH Terms] OR "midwifery"[All Fields] OR ("traditional"[All Fields] AND
"birth"[All Fields] AND "attendants"[All Fields]) OR "traditional birth attendants"[All
Fields]) AND (("perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND
"mortality"[All Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH
Terms] OR ("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All
Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("india"[MeSH
Terms] OR "india"[All Fields])) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Special New Born
Care Units (SNCUs)
AND Perinatal
mortality in India
(Special[All Fields] AND New[All Fields] AND ("parturition"[MeSH Terms] OR
"parturition"[All Fields] OR "born"[All Fields]) AND Care[All Fields] AND Units[All
Fields]) AND SNCUs[All Fields] AND (("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All Fields])
OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields])) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Birth preparedness
and complication
readiness AND
perinatal mortality
rate AND India
(("parturition"[MeSH Terms] OR "parturition"[All Fields] OR "birth"[All Fields]) AND
preparedness[All Fields] AND complication[All Fields] AND readiness[All Fields]) AND
(("perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND "mortality"[All
Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH Terms] OR
("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All Fields] OR
("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("J Rehabil Assist Technol
Still birth rate AND
India
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of Jannani
Suraksha
Yojana(JSY) on still
birth rate AND India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND Suraksha[All
Fields] AND ("Yojana"[Journal] OR "yojana"[All Fields])) AND JSY[All Fields] AND
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of Jannani
Shishu Suraksha
Karyakram(JSSK)
on still birth rate
AND India
Impact of Jannani Shishu Suraksha Karyakram(JSSK) on still birth rate (("Impact (Am
Coll Physicians)"[Journal] OR "impact"[All Fields]) AND Shishu[All Fields] AND
Suraksha[All Fields] AND Karyakram[All Fields]) AND JSSK[All Fields] AND
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Eng"[Journal] OR "rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields])
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Antenatal care OR
Postnatal care OR
Intranatal care AND
perinatal mortality
AND India
("prenatal care"[MeSH Terms] OR ("prenatal"[All Fields] AND "care"[All Fields]) OR
"prenatal care"[All Fields] OR ("antenatal"[All Fields] AND "care"[All Fields]) OR
"antenatal care"[All Fields]) OR ("postnatal care"[MeSH Terms] OR ("postnatal"[All
Fields] AND "care"[All Fields]) OR "postnatal care"[All Fields]) OR (Intranatal[All
Fields] AND care[All Fields]) AND ("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All Fields])
OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Antenatal care OR
Intranatal care AND
still birth rate AND
India
("prenatal care"[MeSH Terms] OR ("prenatal"[All Fields] AND "care"[All Fields]) OR
"prenatal care"[All Fields] OR ("antenatal"[All Fields] AND "care"[All Fields]) OR
"antenatal care"[All Fields]) OR (Intranatal[All Fields] AND care[All Fields]) AND
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Care during labour
and child birth AND
still birth rate AND
India
(Care[All Fields] AND ("labour"[All Fields] OR "work"[MeSH Terms] OR "work"[All
Fields] OR "labor"[All Fields] OR "labor, obstetric"[MeSH Terms] OR ("labor"[All Fields]
AND "obstetric"[All Fields]) OR "obstetric labor"[All Fields]) AND ("child"[MeSH Terms]
OR "child"[All Fields]) AND ("parturition"[MeSH Terms] OR "parturition"[All Fields] OR
"birth"[All Fields])) AND (("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All
Fields] AND "birth"[All Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist
Technol Eng"[Journal] OR "rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
India Newborn
Action Plan (INAP)
and still birth rate
(("india"[MeSH Terms] OR "india"[All Fields]) AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"newborn"[All Fields]) AND "action"[All Fields] AND Plan[All Fields]) AND
("isonitrosoacetophenone"[Supplementary Concept] OR "isonitrosoacetophenone"[All
Fields] OR "inap"[All Fields]) AND (("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields]
OR ("still"[All Fields] AND "birth"[All Fields]) OR "still birth"[All Fields]) AND "rate"[All
Fields])
Accredited Social
Health
Activitist(ASHA)
role AND still birth
rate AND India
(Accredited[All Fields] AND Social[All Fields] AND ("health"[MeSH Terms] OR
"health"[All Fields])) AND ("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All
Fields]) AND ("role"[MeSH Terms] OR "role"[All Fields]) AND (("stillbirth"[MeSH Terms]
OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All Fields]) OR "still birth"[All
Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR "rate"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Management of
Diarrheal
diseases with
ORS and zinc
AND Children
AND india
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields] AND
"administration"[All Fields]) OR "organization and administration"[All Fields] OR
"management"[All Fields] OR "disease management"[MeSH Terms] OR ("disease"[All
Fields] AND "management"[All Fields]) OR "disease management"[All Fields]) AND
Diarrheal[All Fields] AND ("disease"[MeSH Terms] OR "disease"[All Fields] OR
"diseases"[All Fields]) AND ("ORALIT"[Supplementary Concept] OR "ORALIT"[All
Fields] OR "ors"[All Fields]) AND ("zinc"[MeSH Terms] OR "zinc"[All Fields])) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Management of
Acute Respiratory
Infections AND
Children AND
India
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields] AND
"administration"[All Fields]) OR "organization and administration"[All Fields] OR
"management"[All Fields] OR "disease management"[MeSH Terms] OR ("disease"[All
Fields] AND "management"[All Fields]) OR "disease management"[All Fields]) AND
Acute[All Fields] AND ("respiratory tract infections"[MeSH Terms] OR ("respiratory"[All
Fields] AND "tract"[All Fields] AND "infections"[All Fields]) OR "respiratory tract
infections"[All Fields] OR ("respiratory"[All Fields] AND "infections"[All Fields]) OR
"respiratory infections"[All Fields])) AND (("child"[MeSH Terms] OR "child"[All Fields]
OR "children"[All Fields]) AND under[All Fields] AND 5[All Fields] AND years[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Intensified
Diarrhea Control
Fortnight AND
Children AND
India
(Intensified[All Fields] AND ("diarrhoea"[All Fields] OR "diarrhea"[MeSH Terms] OR
"diarrhea"[All Fields]) AND ("prevention and control"[Subheading] OR ("prevention"[All
Fields] AND "control"[All Fields]) OR "prevention and control"[All Fields] OR "control"[All
Fields] OR "control groups"[MeSH Terms] OR ("control"[All Fields] AND "groups"[All
Fields]) OR "control groups"[All Fields]) AND Fortnight[All Fields]) AND (("child"[MeSH
Terms] OR "child"[All Fields] OR "children"[All Fields]) AND under[All Fields] AND 5[All
Fields] AND years[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Integrated
management of
neonatal and
childhood illness
AND Children
AND India
(Integrated[All Fields] AND ("organization and administration"[MeSH Terms] OR
("organization"[All Fields] AND "administration"[All Fields]) OR "organization and
administration"[All Fields] OR "management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All Fields])
OR "disease management"[All Fields]) AND ("infant, newborn"[MeSH Terms] OR
("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"neonatal"[All Fields]) AND ("Childhood"[Journal] OR "childhood"[All Fields]) AND
illness[All Fields]) AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND (("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Micronutrient
supplementation
(Vitamin A, Iron
Folic Acid) AND
Children AND
Mortality AND
India
(("trace elements"[Pharmacological Action] OR "micronutrients"[Pharmacological Action]
OR "trace elements"[MeSH Terms] OR ("trace"[All Fields] AND "elements"[All Fields])
OR "trace elements"[All Fields] OR "micronutrient"[All Fields] OR "micronutrients"[MeSH
Terms] OR "micronutrients"[All Fields]) AND supplementation[All Fields]) AND ("vitamin
a"[MeSH Terms] OR "vitamin a"[All Fields]) OR ("folic acid"[MeSH Terms] OR ("folic"[All
Fields] AND "acid"[All Fields]) OR "folic acid"[All Fields]) AND ("child mortality"[MeSH
Terms] OR ("child"[All Fields] AND "mortality"[All Fields]) OR "child mortality"[All Fields]
OR ("children"[All Fields] AND "mortality"[All Fields]) OR "children mortality"[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Supplementation
with
micronutrients in
children AND
Children AND
India
supplementation[All Fields] AND ("micronutrients"[Pharmacological Action] OR
"micronutrients"[MeSH Terms] OR "micronutrients"[All Fields]) AND ("child"[MeSH
Terms] OR "child"[All Fields] OR "children"[All Fields])) AND ("child"[MeSH Terms] OR
"child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Universal
immunization
AND Children
AND India
((Universal[All Fields] AND ("immunisation"[All Fields] OR "vaccination"[MeSH Terms]
OR "vaccination"[All Fields] OR "immunization"[All Fields] OR "immunization"[MeSH
Terms])) AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Full immunization
coverage AND
Children AND
India
(Full[All Fields] AND ("vaccination coverage"[MeSH Terms] OR ("vaccination"[All Fields]
AND "coverage"[All Fields]) OR "vaccination coverage"[All Fields] OR ("immunization"[All
Fields] AND "coverage"[All Fields]) OR "immunization coverage"[All Fields])) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Child screening
and early
intervention
services AND
Children AND
India
(("child"[MeSH Terms] OR "child"[All Fields]) AND ("diagnosis"[Subheading] OR
"diagnosis"[All Fields] OR "screening"[All Fields] OR "mass screening"[MeSH Terms]
OR ("mass"[All Fields] AND "screening"[All Fields]) OR "mass screening"[All Fields] OR
"screening"[All Fields] OR "early detection of cancer"[MeSH Terms] OR ("early"[All
Fields] AND "detection"[All Fields] AND "cancer"[All Fields]) OR "early detection of
cancer"[All Fields]) AND ("early intervention (education)"[MeSH Terms] OR ("early"[All
Fields] AND "intervention"[All Fields] AND "(education)"[All Fields]) OR "early
intervention (education)"[All Fields] OR ("early"[All Fields] AND "intervention"[All Fields])
OR "early intervention"[All Fields]) AND services[All Fields]) AND ("child"[MeSH Terms]
OR "child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Birth defects in
children under 5
years AND
NRHM AND India
(("abnormalities"[Subheading] OR "abnormalities"[All Fields] OR ("birth"[All Fields] AND
"defects"[All Fields]) OR "birth defects"[All Fields] OR "congenital abnormalities"[MeSH
Terms] OR ("congenital"[All Fields] AND "abnormalities"[All Fields]) OR "congenital
abnormalities"[All Fields] OR ("birth"[All Fields] AND "defects"[All Fields])) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND under[All
Fields] AND 5[All Fields] AND years[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Deficiencies in
Children under 5
years AND India
(Deficiencies[All Fields] AND ("child"[MeSH Terms] OR "child"[All Fields] OR
"children"[All Fields]) AND under[All Fields] AND 5[All Fields] AND years[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
IFA
Supplementation
AND Children AND
India
(("iron"[MeSH Terms] OR "iron"[All Fields]) AND ("folic acid"[MeSH Terms] OR
("folic"[All Fields] AND "acid"[All Fields]) OR "folic acid"[All Fields]) AND
supplementation[All Fields] AND IFA[All Fields] AND Supplementation[All Fields])
AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Rashtriya bal
Swasthya
karyakram
(Rashtriya[All Fields] AND bal[All Fields] AND swasthya[All Fields] AND
karyakram[All Fields]) AND ("child"[MeSH Terms] OR "child"[All Fields] OR
"children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
National
deworming day
AND Children AND
India
(("federal government"[MeSH Terms] OR ("federal"[All Fields] AND "government"[All
Fields]) OR "federal government"[All Fields] OR "national"[All Fields]) AND
deworming[All Fields] AND day[All Fields]) AND ("child"[MeSH Terms] OR "child"[All
Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields])
AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Complementary
feeding practices
AND Children AND
India
(("infant nutritional physiological phenomena"[MeSH Terms] OR ("infant"[All Fields]
AND "nutritional"[All Fields] AND "physiological"[All Fields] AND "phenomena"[All
Fields]) OR "infant nutritional physiological phenomena"[All Fields] OR
("complementary"[All Fields] AND "feeding"[All Fields]) OR "complementary
feeding"[All Fields]) AND practices[All Fields]) AND ("child"[MeSH Terms] OR
"child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
AND "humans"[MeSH Terms])
Disease
management in
children in
NRHM AND
India
(("therapy"[Subheading] OR "therapy"[All Fields] OR ("disease"[All Fields] AND
"management"[All Fields]) OR "disease management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All Fields]))
AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
NRHM[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull
text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH
Terms])
Prevalence of
diarrhea in
under 5
children in
India
(("epidemiology"[Subheading] OR "epidemiology"[All Fields] OR "prevalence"[All
Fields] OR "prevalence"[MeSH Terms]) AND ("diarrhoea"[All Fields] OR
"diarrhea"[MeSH Terms] OR "diarrhea"[All Fields]) AND under[All Fields] AND 5[All
Fields] AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields])) AND ("2005/01/01"[PDAT] :
"2013/12/31"[PDAT])
Impact Indicator:
Under 5
Mortality Rate in
India
(Under[All Fields] AND 5[All Fields] AND ("mortality"[MeSH Terms] OR "mortality"[All
Fields] OR ("mortality"[All Fields] AND "rate"[All Fields]) OR "mortality rate"[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields])) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Disease
management in
children in NRHM
AND India
(("therapy"[Subheading] OR "therapy"[All Fields] OR ("disease"[All Fields] AND
"management"[All Fields]) OR "disease management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All
Fields])) AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields])
AND NRHM[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Nutritional
rehabilitation
centres AND
Children AND
India
(Nutritional[All Fields] AND ("rehabilitation"[Subheading] OR "rehabilitation"[All
Fields] OR "rehabilitation"[MeSH Terms]) AND centres[All Fields]) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Other variables
REPRODUCTIVE HEALTH
National Health
Mission
“National Health Mission” OR “NHM” [MeSH words] OR “National” [All Fields] AND
"Health” [All Fields] AND “Mission" [All Fields]
National Rural Health
Mission
“National Rural Health Mission” OR “NRHM” [MeSH words] OR “National” [All
Fields] AND “Rural” [All fields] AND "Health” [All Fields] AND “Mission" [All
Fields“National Rural Health Mission” OR “NRHM” [MeSH words] OR “National” [All
Fields] AND “Rural” [All fields] AND "Health” [All Fields] AND “Mission" [All Fields]
National Urban
Health Mission
“National Urban Health Mission” OR “NRHM” [MeSH words] OR “National” [All
Fields] AND “Urban” [All fields] AND "Health” [All Fields] AND “Mission" [All Fields]
Reproductive Health
Program
“Reproductive Health Program” [MeSH words] OR “Reproductive” [All Fields] AND
“Health” [All Fields] AND “Program” [All Fields] AND “Evaluation” [All Fields]
Family Planning “Family planning” [MeSH words] OR “Family” [All Fields] AND “Planning” [All
Fields] OR “Birth Control” OR “Birth” [All Fields] AND “control” [All Fields]
Contraceptive
Prevalence Rate
“Contraceptive Prevalence Rate” [MeSH words] OR “Contraceptive” [All Fields]
AND “Prevalence” [All Fields] AND “Rate” [All Fields]
Total Unmet need “Total Unmet Need” [MeSH words] OR “Total” [All Fields] AND “Unmet” [All Fields]
AND “Need” [All Fields]
Total Fertility Rate “Total Fertility Rate” [MeSH words] OR “Total” [All Fields] AND “Fertility” [All
Fields] AND “Rate” [All Fields]
Rashtriya Kishor
Swasthya Karyakram
“Rashtriya Kishor Swasthya Karyakram” [MeSH words] OR “Rashtriya” [All Fields]
AND “Kishor” [All Fields] AND “Swasthya” [All Fields] AND “Karyakram” [All Fields]
Adolescent Friendly
Health Clinics
“Adolescent Friendly Health Clinics” [MeSH words] OR “Adolescent” [All Fields]
AND “Friendly” [All Fields] AND “Health” [All Fields] AND “Clinics” [All Fields]
Adolescent
Reproductive and
Sexual Health/ ARSH
“Adolescent Reproductive and Sexual Health” [MeSH words] OR “ARSH” [MeSH
word] OR “Adolescent” [All Fields] AND “Reproductive” [All Fields] AND “Sexual”
[All Fields] AND “Health” [All Fields]
Weekly Iron and Folic
Acid
Supplementation
“Weekly Iron and Folic Acid Supplementation” [MeSH words] OR “Weekly” [All
Fields] AND “Iron” [All Fields] AND “Folic Acid” [All Fields] AND “Supplementation”
[All Fields]
Menstrual Hygiene
Scheme
“Menstrual hygiene scheme” [MeSH words] OR “Menstrual” [All Fields] AND
“Hygiene” [All Fields] AND “Scheme” [All Fields]
Keywords MeSH
"road connectivity"
AND "maternal
health" AND "India"
"road connectivity"[All Fields] AND "maternal health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"road connectivity"
AND "child health"
AND "India"
"road connectivity"[All Fields] AND "child health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"road connectivity"
AND "adolescent
health" AND "India"
"road connectivity"[All Fields] AND "adolescent health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"road connectivity"
AND "health
outcomes" AND
"India"
"road connectivity"[All Fields] AND "health outcomes"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"surfaced road" AND
"health outcomes"
AND "India"
(surfaced[All Fields] AND road[All Fields]) AND "health outcomes"[All Fields]
AND "India"[All Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"rural road
connectivity" AND
"health " AND "India"
(rural[All Fields] AND road[All Fields] AND connectivity[All Fields]) AND "health
"[All Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"rural connectivity"
AND "health
outcomes" AND India
(rural[All Fields] AND connectivity[All Fields]) AND "health outcomes"[All Fields]
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
(mobile phone use)
AND maternal health)
AND India
("cell phone use"[MeSH Terms] OR ("cell"[All Fields] AND "phone"[All Fields])
OR "cell phone use"[All Fields] OR ("mobile"[All Fields] AND "phone"[All Fields])
OR "mobile phone use"[All Fields]) AND ("maternal health"[MeSH Terms] OR
("maternal"[All Fields] AND "health"[All Fields]) OR "maternal health"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"mobile phone use"
AND "maternal
health" AND "India"
mobile[Title] AND phone[Title] AND maternal[Title] AND health[Title] AND
India[Title]
mobile connectivity
AND maternal health
AND India
(mobile[All Fields] AND connectivity[All Fields]) AND ("maternal health"[MeSH
Terms] OR ("maternal"[All Fields] AND "health"[All Fields]) OR "maternal
health"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
AND "maternal
health" AND "India"
"mobile connectivity"[All Fields] AND "maternal health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone" AND
"maternal health"
AND "India"
"mobile phone"[All Fields] AND "maternal health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
impact on "health
outcomes" AND
"India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "health outcomes"[All Fields] AND "India"[All Fields]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
impact on "maternal
health" AND "India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "maternal health"[All Fields] AND "India"[All Fields]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"telecommunication
connectivity" AND
"maternal health"
AND "India"
(("telecommunications"[MeSH Terms] OR "telecommunications"[All Fields] OR
"telecommunication"[All Fields]) AND connectivity[All Fields]) AND "maternal
health"[All Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"AAROGYAM" AND
"Maternal health"
AND "India"
"AAROGYAM"[All Fields] AND "Maternal health"[All Fields] AND "India"[All
Fields] AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]))
"mother and child
tracking system"
AND "India"
"mother and child tracking system"[All Fields] AND "India"[All Fields] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"information and
communication
technology" AND "
maternal mortality
ratio" AND "India"
"information and communication technology"[All Fields] AND "maternal mortality
ratio"[All Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"mobile connectivity"
impact on "child
health" AND "India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "child health"[All Fields] AND "India"[All Fields] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone" AND
"child health" AND
"India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "child health"[All Fields] AND "India"[All Fields] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
mobile connectivity
AND child health
AND India
(mobile[All Fields] AND connectivity[All Fields]) AND ("child health"[MeSH
Terms] OR ("child"[All Fields] AND "health"[All Fields]) OR "child health"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
AND "child health"
AND "India"
"mobile connectivity"[All Fields] AND "child health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
((mobile phone use)
AND child health)
AND India
(("cell phone use"[MeSH Terms] OR ("cell"[All Fields] AND "phone"[All Fields])
OR "cell phone use"[All Fields] OR ("mobile"[All Fields] AND "phone"[All Fields])
OR "mobile phone use"[All Fields]) AND ("child health"[MeSH Terms] OR
("child"[All Fields] AND "health"[All Fields]) OR "child health"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"mobile phone use"
AND "child health"
AND "India"
"mobile phone use"[All Fields] AND "child health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"AAROGYAM" AND
"child health" AND
"India"
"AAROGYAM"[All Fields] AND "child health"[All Fields] AND "India"[All Fields]
AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]))
"AAROGYAM" AND
"health outcomes"
AND "India"
"AAROGYAM"[All Fields] AND "health outcomes"[All Fields] AND "India"[All
Fields] AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]))
"mobile connectivity"
impact on
"adolescent health"
AND "India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "adolescent health"[All Fields] AND "India"[All Fields]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone" AND
"adolescent health"
AND "India"
"mobile phone"[All Fields] AND "adolescent health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
mobile connectivity
AND adolescent
health AND India
(mobile[All Fields] AND connectivity[All Fields]) AND ("adolescent health"[MeSH
Terms] OR ("adolescent"[All Fields] AND "health"[All Fields]) OR "adolescent
health"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
mobile phone use
AND adolescent
health AND India
("cell phone use"[MeSH Terms] OR ("cell"[All Fields] AND "phone"[All Fields])
OR "cell phone use"[All Fields] OR ("mobile"[All Fields] AND "phone"[All Fields])
OR "mobile phone use"[All Fields]) AND ("adolescent health"[MeSH Terms] OR
("adolescent"[All Fields] AND "health"[All Fields]) OR "adolescent health"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone use"
AND "adolescent
health" AND "India"
"mobile phone use"[All Fields] AND "adolescent health"[All Fields] AND
"India"[All Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
water supply AND
health outcomes
AND India
("water supply"[MeSH Terms] OR ("water"[All Fields] AND "supply"[All Fields])
OR "water supply"[All Fields]) AND (("health"[MeSH Terms] OR "health"[All
Fields]) AND outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields])
water supply impact
on health outcomes
AND India
(("water supply"[MeSH Terms] OR ("water"[All Fields] AND "supply"[All Fields])
OR "water supply"[All Fields]) AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND ("health"[MeSH Terms] OR "health"[All Fields]) AND
outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
sanitation impact on
health outcomes in
India
(("sanitation"[MeSH Terms] OR "sanitation"[All Fields]) AND ("Impact (Am Coll
Physicians)"[Journal] OR "impact"[All Fields]) AND ("health"[MeSH Terms] OR
"health"[All Fields]) AND outcomes[All Fields] AND ("india"[MeSH Terms] OR
"india"[All Fields])) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
sanitation AND
health outcomes
AND India
("sanitation"[MeSH Terms] OR "sanitation"[All Fields]) AND (("health"[MeSH
Terms] OR "health"[All Fields]) AND outcomes[All Fields]) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of toilets on
health outcomes in
India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND
("bathroom equipment"[MeSH Terms] OR ("bathroom"[All Fields] AND
"equipment"[All Fields]) OR "bathroom equipment"[All Fields] OR "toilets"[All
Fields]) AND ("health"[MeSH Terms] OR "health"[All Fields]) AND outcomes[All
Fields] AND ("india"[MeSH Terms] OR "india"[All Fields])) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
nutrition AND health
outcomes AND India
("nutritional status"[MeSH Terms] OR ("nutritional"[All Fields] AND "status"[All
Fields]) OR "nutritional status"[All Fields] OR "nutrition"[All Fields] OR "nutritional
sciences"[MeSH Terms] OR ("nutritional"[All Fields] AND "sciences"[All Fields])
OR "nutritional sciences"[All Fields]) AND (("health"[MeSH Terms] OR
"health"[All Fields]) AND outcomes[All Fields]) AND ("india"[MeSH Terms] OR
"india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
impact of nutrition on
health outcomes
AND India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND
("nutritional status"[MeSH Terms] OR ("nutritional"[All Fields] AND "status"[All
Fields]) OR "nutritional status"[All Fields] OR "nutrition"[All Fields] OR "nutritional
sciences"[MeSH Terms] OR ("nutritional"[All Fields] AND "sciences"[All Fields])
OR "nutritional sciences"[All Fields]) AND ("health"[MeSH Terms] OR "health"[All
Fields]) AND outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"sanitation" impact on
"health outcomes" in
"India" NOT animals
"sanitation"[All Fields] AND impact[All Fields] AND "health outcomes"[All Fields]
AND "India"[All Fields] NOT animals[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
ability to call
ambulance AND
impact on health
outcomes AND India
(("aptitude"[MeSH Terms] OR "aptitude"[All Fields] OR "ability"[All Fields]) AND
call[All Fields] AND ("ambulances"[MeSH Terms] OR "ambulances"[All Fields]
OR "ambulance"[All Fields])) AND (("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND ("health"[MeSH Terms] OR "health"[All Fields]) AND
outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
ANNEXURE 4. FLOW DIAGRAM OF STUDIES INCLUDED IN THE SYSTEMATIC REVIEW
4.1. MATERNAL MORTALITY RATIO
Studies identified through database
search N=2759
Studies after removal of duplicates
N= 2083
Studies selected according to titles
for abstract N= 1161
Studies selected for full text N= 280
Studies included in review N= 63
Duplicate records N= 676
Studies excluded by Titles
N =922
Studies excluded by
abstract N = 881
Studies excluded by full
text N = 217
MMR = 19
Institutional Deliveries = 44
Studies not
pooled N= 19
Studies pooled
in forest plot
N= 25
JSY = 6
NRHM = 6
ASHA = 1
ANC = 1
Referral transport= 2
ReMiND = 2
Others = 1
JSY = 14
BPCR = 2
ASHA = 3
JSSK = 1
ANC = 1
Referral transport= 2
Others = 2
Studies not
pooled
N = 19
JSY =7
ASHA = 2
NRHM = 5
Task shifting =1
BPCR = 1
JSSK = 2
Others = 1
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2 CHILD HEALTH
4.2.1 PERINATAL MORTALITY RATE
Studies identified in database search
(n=28568)
Studies after duplicate removal
(n=11688)
Full text articles assessed for
eligibility (n=289)
Final studies included (n=41)
Duplicates identified
(n=16880)
Studies excluded on the basis of
title and abstract (n=11399)
Studies excluded by full text
review (n=248)
Studies with outcome
as PNMR =15
Studies with outcome
as SBR= 20
Studies with outcome
as ENMR= 6
ENC= 3
NRHM =1
JSY= 2
Institutional deliveries =1
Secondary data
analysis=2
Cohort study=2
Cross sectional study =5
Case control study=1
Institutional delivery and
ENC=2
NRHM =1
JSY =1
Cross sectional studies=5
Case control study=2
Secondary data analysis=5
Survey =2
Prospective observational
study=4
JSY =1
Review article on NRHM =2
Secondary data analysis=3
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2.2 NEONATAL MORTALITY RATE
TE
Studies identified in the database
search N=19536
Studies excluded by titles and
invalid outcomes N=9950
Studies selected according to titles
for abstracts N=1802
Studies selected for full text review
N=280
Duplicated records N=7784
Studies excluded by
abstracts N=1522
Studies excluded by full text
review N=240
Studies included in the review N=40
Cross
sectional
studies
N=16
Outcome
NMR=8
Retrospec
tive study
N=2
Longitudin
al Cohort
study N=2
Quasi experimental
N=1
Mixed study N=1
Systematic reviews
N=1
RCT N=1
Impact of
NRHM on
NMR N=3
LBW=8
ENBC N=5
FBNC N=2
IMNCI N=1
IMNCI N=1
FBNC N =2
ENC N= 1
HBPNC N= 4
FBNC N=2
LBW N=2
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2.3. INFANT MORTALITY RATE
Studies identified in database
searching (n= 19,350)
Studies after duplicate removal (n=
7,120)
Full text articles assessed for
eligibility (n=1740)
Studies excluded on the basis of title
and abstract (n=5380)
Studies excluded by full text review
(n=1674)
Final studies included (n=66)
Duplicates identified
(n=12,230)
Studies on
Exclusive
breast
feeding
(N=26)
Studies on
Outcome
as IMR
(N=16)
Studies on
assessment
of ASHAs
under
(N=9)
Studies on
IMNCI
(N=5)
Studies on
Vitamin A
(N=1)
Studies on
Immunizati
on (N=3)
Studies on
Secondary
data
analysis
(N=6)
Cross
section
al
Study
(N=22)
Longitud
inal
Study
(N=4)
Cross
section
al Study
(N=4)
Secondary
data
analysis
(N=10)
Longitud
inal
Study
(N=2)
Cross
sectional
Study
(N=8)
Longitu
dinal
Study
(N=1)
Cross
sectional
Study
(N=1)
Longitu
dinal
Study
(N=1)
RCT
(N=1)
RCT
(N=1)
Cohort
(N=1)
Cross
section
al Study
(N=1)
Mixed
Study
(N=1)
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2.4 UNDER FIVE MORTALITY RATE
Studies after duplicate removal
n=9,725
Final studies included, n=66
Studies excluded by full text
review N=223
Studies excluded on the
basis of title and abstract.
n=9,436
Studies with
outcome as
Immunization
coverage (n=22)
Studies Focusing on
strategy NRC (n=18)
Studies with outcome
as U5MR, n=9
Other studies:
- Vitamin A supplementation (n=4), RBSK
(n=3), Outcome as ARI and Diarrhea
incidence (n=9), IMNCI (n=1)
Role of NRHM in reducing inequality (n=1)
Role of FLHW in improving child health (n=1)
Non Pool
able=3
Pooled =16
Pooled =15
Non Pool
able=3
Studies identified in the database
search N=14,569
Duplicated records
N=n=4,844
Full text articles assessed for
eligibility, n=289
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.3 TOTAL FERTILITY RATE AND CONTRACEPTIVE PREVELANCE RATE
Studies identified in the database
search N=6261
Studies excluded by titles and
invalid outcomes N=2491
Studies selected according to titles
for abstracts N=496
Studies selected for full text review
N=130
Duplicated records
N=3274
Studies excluded by
abstracts N=366
Studies excluded by full
text review N=81
Studies included in the review N=49
Cross sectional studies
N=32
Studies on secondary data
analysis N=14
Quasi experimental studies
with state specific
strategies
PRACHAR project in Bihar
SAHELI project in Kerala
N=3
Studies with CPR as
outcome N=22 (Pooled)
Evaluation/effectiveness
studies on ASHA N=4
Studies on other outcomes
like utilization rate, barriers
etc. N=6
Studies with TFR as an
outcome N=9
Studies with CPR as an
outcome N=5
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.4 ADOLESCENT REPRODUCTIVE SEXUAL HEALTH CLINICS AND WEEKLY IRON
FOLIC SUPPLIMENTATION
Studies identified in the database
search N=1062
Studies excluded by titles and
invalid outcomes N=296
Studies selected according to titles
for abstracts N=192
Studies selected for full text review
N=105
Duplicated records N=574
Studies excluded by
abstracts N=87
Studies excluded by full text
review N=55
Studies included in the review N=50
Studies on WIFS
N=12
Pooled for analysis,
N=10
Non pool able
Studies, N=3
Non pool able
Studies, N=4
RCTs, N=4
Cross sectional
N=5
Studies on ARSH
N=14
Pooled
Studies on Menstrual Hygiene
N=25
Pooled for
analysis, N=22
Non pool able
Studies, N=3
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.5 IMPACT OF OTHER VARIABLES ON MCH OUTCOMES
Studies identified through database
search 1, 07,823
Studies after removal of duplicates
N= 42,982
Studies selected according to titles
for abstract N= 7337
Studies selected for full text N= 223
Studies included in review N= 25
Duplicate records N= 64,841
Studies excluded by Titles N =35,645
Studies excluded by abstract N =
7114
Studies excluded by full text N = 198
Mobile
connectivity = 9
Road
connectivity =8
Water supply/
sanitation = 7
Self-help
group = 1
Cross-
sectional = 3
review N=
25
Case control
= 2
review N=
25
Hospital
based = 2
review N=
25
Quasi
experimental
= 1
review N=
25
Qualitative =
1
review N=
25
Cross-sectional
= 1
review N= 25
Secondary data
analysis = 1
review N= 25
Cross sectional
= 1
review N= 25
RCT = 2
Cohort study =
2
review N= 25
Secondary
data analysis
= 8
review N=
25
Secondary
data analysis
= 1
review N=
25
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.6 MCH INEQUALITIES
Studies identified through database
search 9185
Studies after removal of duplicates
N= 3823
Studies selected according to titles
for abstract N= 362
Studies selected for full text N= 84
Studies included in review N= 12
Duplicate records N= 5362
Studies excluded by Titles N =3461
Studies excluded by abstract N = 278
Studies excluded by full text N = 72
NRHM= 5
Others= 3
ANC, PNC,
SBA= 1
ASHA= 1
JSY=2
Qualitative =
2
Secondary
data
analysis= 1
Mixed
method= 1
Quasi
experimental
= 1
Pre post
study= 1
Secondary data
analysis= 1
Survey study=
1
Secondary
data analysis =
1
Secondary
data
analysis=3
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
ANNEXURE 5. RESULTS OF STUDIES INCLUDED IN SYSTEMATIC REVIEW .
5.1 MATERNAL HEALTH
5.1.1 Results of studies with MMR as an outcome (N=19)
Author &
year of
publication
Study Period/
Location
Study Design Objective/Intervention Results
After 2013
Begum R. et
al. 2014[71]
2004-06 to
2012-13,
Assam and
India
Secondary data
analysis (SRS
data)
NHM, JSY, JSSK,
MCTS, quality ante-
natal care
Assam: MMR reduction
=480 to 301 /lakh live
births (LB) [37.3%
decline], mainly due to
increased institutional
delivery due to JSY
,India: MMR=254 to 178
[30% decline]
Shah P. et al.
2014[72]
2002-03 to
2010-11,
Jhagadia block
(rural tribal
area), Gujarat
[SEWA].
Prospective
study
JSY/Chiranjeevi
Yojana/free referral
transport
services/Community
based interventions
MMR reduction = 520 -
146 / lakh LB (71.1%
decline)
Randive B. et
al. 2014[73]
2007-2009, 9
low performing
states of India
[RJ,MP,CH,BH,
JH,UP,UK,OR,
AS]
Secondary data
analysis (DLHS
3, AHS 1 and 2,
Census 2011)
JSY MMR reduction 4 times
faster in richest areas
compared to poorest,
MMR=301-178/lakh LB
[40% decline in 2003-
2013 in India],
Disadvantaged
population needs to be
targeted for cash
incentives
Ng M. et al.
2014 [74]
2005-2010,
Madhya
Pradesh
Continuous time
series for MMR(
SRS report,
Impact of JSY on MMR MMR reduction = 371 to
327/lakh LB (12%
decline),JSY supported
AHS, MP vital
statistics,
research studies
from PubMed,
google scholar)
institutional delivery: 14%
to 80%.Not associated
with decline on MMR due
to inadequate quality of
care
Mane A B et
al. 2014 [75]
2001-2012,
India
Review study ASHA MMR reduction = 301 to
100/ Lakh LB (66.6%
decline),Due to promotion
of institutional deliveries
by ASHA
Bhushan H
et al. 2015
[76]
2006-13, India Secondary data
analysis
(Training
records from 12
states)
Task shifting from
specialist to non-
specialist doctors
ANC coverage improved
by 43%, 44%, 58%
during first, second and
third trimesters. 50%
reduction in maternal
deaths
Nagarajan S.
et al. 2015
[57]
2001-05 (pre
NRHM) to
2005-11 (post
NRHM), India
Secondary data
analysis (SRS
data)
Impact of NRHM on
Maternal mortality
MMR reduction = 301 to
178/ Lakh LB (40%
decline) .0.2% increase in
MMR reduction.MMR
was already in declining
phase prior to NRHM
owing to increased
economic growth/ roads/
transportation/ private
sectors. NRHM did
provide the further
impetus to the decline by
provision of ambulance
services EMOC, JSY.
Doke PP et
al. 2016 [77]
1997–2004 to
2005-12, ( 8
years before
and 8 years
after) India
Pre NRHM, post
NRHM
implementation
study Secondary
data analysis
(SRS Data)
NRHM MMR reduction= 398 to
167 /lakh LB
Pre NRHM, MMR decline
= 36.2%
Post NRHM, MMR
decline= 34.2%(MMR
decline had already in
pace even before NRHM.
(RCH program in 1997)
Vohra K. et
al, 2015[58]
1991-2009,
India
Secondary data
analysis (SRS,
Census data,
DLHS, NFHS)
NRHM MMR reduction= 437 to
178 /lakh LB (59.3%
decline) Reduction in
birth and increased
institutional deliveries
could be the reason for
decline in MMR.
Slow reduction in MMR
despite maternal
healthcare utilization is
inequalities related to
literacy status, economic
situation, geographic
locations.E.g. ANC check
up 1st trimester( 38%
Rural, 62%
urban),Institutional
deliveries (38%
rural,71%Urban)
Ahmed SJ et
al. 2016 [78]
1997-2013,
Assam, India
Secondary data
analysis (SRS
Data)
- Assam MMR reduction =
520-257/lakh LB (50.5%
decline)
India MMR reduction=
398-178/lakh LB (55.3%
decline)
Gupta M. et
al. 2016 [61]
2002-04 to
2012-13,
Haryana
Secondary data
analysis in
Haryana(DLHS)
NRHM MMR reduction =185 to
121 /lakh LB (34.6%
decline).ANC check up
difference in rural and
urban = 8 % pre NRHM,
12.4% during NRHM,
6.8% post NRHM
Mahala U. et
al. 2017 [79]
2008-11 to
2012-15, Jaipur
Retrospective
hospital based
descriptive study
(data related to
institutional
deliveries from
medical records
of Medical
college)
JSSY (JSSK) MMR reduction= 267 to
248/lakh LB from pre to
post JSSK period (7.1%
decline)
Because of JSSK
(JSSY); Annual prenatal
check-up = 55%
increase, Annual
institutional deliveries =
37.9% increase
Gupta M. et
al. 2017 [80]
2013, Haryana Mixed method
study
(Secondary data
analysis
Qualitative
interviews/FGD/I
n-depth
interviews in
Ambala and
Mewat)
ASHA, JSY, JSSK MMR= 121/lakh live
births
MCH inequalities reduced
due to more awareness
regarding MCH services
by ASHA, free
ambulances, diet during
hospital stay. ASHA
scheme appreciated by
all participants
Khanna D. et
al. 2018 [81]
1 year,
Lucknow, UP
Case control
Cases =
maternal deaths,
Control =
Geographic
matched control
and
complication
matched control
BPCR 50% reduction in risk of
MMR when the place of
delivery was suggested
as Institution over the
home delivery. When
place of delivery decided
as institution then risk of
maternal deaths reduced
by three fifth times.
Prinja S. et
al. 2018[82]
2011-2020,
Mooratganj
Manjhanpur
blocks of
Kaushambi
Quasi-
experimental
design
ReMiND intervention
through 259 ASHAs
Resulted in 0.2%
reduction in maternal
deaths.
Siddika B. et
al. 2018 [83]
2004-06 to
2013, Assam,
India
Descriptive
study and
secondary data
analysis (Assam
Human
Development
Reports)
JSY Assam MMR reduction=
480 to 300/lakh LB
(37.5% decline) India
MMR reduction = 254 to
167/lakh LB (34.2%
decline)
- Poor living conditions,
nutritional deficiencies,
inadequate health care,
lack of information.
5.1.2. Forest Plot studies (Outcome = Institutional deliveries, n= 25)
Author & year of
publication
Study Period/Location Study Type Interventio
n
Results
Before 2013
Uttekar B.P. et al.
2007[24]
2007, Jaisalmer,
Bhilwara, Udaipur
Secondary data
analysis(For JSY
NFHS and RCH
data)
JSY 173 deliveries out of total
248 beneficiaries.
Kilaru A. et al.,
2010 [49]
2007-2009,
Ramanagara Taluka,
Karnataka
Prospective study Institutional
delivery
513 institutional
deliveries out of 642
Lim et al, 2010
[26]
2004-04 to 2007-09,
India
Secondary data
analysis(DLHS )
JSY 98932 institutional
deliveries out of 182869
Mandal D.K. et al,
2010 [27]
2007-09, West Bengal Cross sectional JSY 99 institutional deliveries
out of 256 post-partum
females
Vikram K et al.
2011 [28]
2009-10, Trans Yamuna
area of Delhi
Cross sectional
survey
JSY 333 institutional
deliveries out of 469
mothers
Sinha S. et al.
2012 [29]
2010, Chandigarh Retrospective ANC 116 institutional
deliveries out of 147 ANC
mothers
Sidney K. et al.
2012 [30]
Jan-May 2011, Ujjain,
MP
Cross sectional JSY 318 institutional
deliveries out of 418
pregnant women.
Ved R. et al. 2012
[31]
2008-09, Empowered
Action Group States(BH,
CH, OR, RJ, UK, UP,
JH, MP,)
Mixed method JSY 2759 institutional
deliveries out of 3469
post-partum females.JSY
has resulted in increase
institutional deliveries.
Reasons for home
delivery = limited access
to transport, poor quality
of services, high cost in
institution, cultural
preferences
Panja TK et al. 2012
[32]
2008, Bankura District,
West Bengal
Cross sectional JSY 236 institutional deliveries
out of 324 JSY
beneficiaries. Cash
incentive under JSY had
positive association on
institutional deliveries.
After 2013
Mukopadhyay D.K.
et al. 2013 [33]
Sep-Dec 2011, Uttar
Dinajpur, West Bengal
Cross sectional
mixed method
BPCR 164 institutional deliveries
out of 355 women
Amudhan S. et al
2013 [34]
2006-2010, Ballabgarh
(HR)
Quasi
experimental
JSY 1012 institutional deliveries
out of 1884 JSY mothers
Govil D et al. 2013
[35]
April 2010 - March 2011,
Udaipur, Banaswara, ,
Sikar, Sawai Madhopur
districts of Rajasthan
Cross-sectional JSY 353 institutional deliveries
out of 424 mothers. Out of
these 62 % in public
facilities and 21 % in private
facilities.JSY has done
phenomenal increase in
institutional deliveries and
decrease in out of pocket
expenditure.
Sidney K. et al.
2014 [36]
2012-13, Madhya Pradesh Cross-sectional JEY( Janani
Express
Yojna) State
Run Public
Private
Emergency
Transportatio
n Service
342 institutional deliveries
out of 353 women who
used JEY.
JEY usage was greater
among women from lower
socioeconomic position
Fathima F.N. et al
2015 [69]
2012, Kolar,
Chamrajanagar and Haveri
districts of Karnataka
Cross-sectional ASHA 1141 institutional deliveries
out of 1800 mothers.
Kaur H. et al. 2015
[38]
Jan-June 2014, Amritsar,
Punjab
Cross sectional JSY 141 delivered at hospital
out of 185 JSY
beneficiaries.
JSY was not rolled out
strongly in the state.
Nipte D. et al. 2015
[39]
July –September 2013,
Maharashtra
Cross sectional
survey
JSY 336 institutional deliveries
out of 374 mothers
Only 50% of mothers have
completed three ANC visits.
Kumar et al 2015
[40]
2010-11, Agra Cross-sectional JSY 171 institutional deliveries
out of 246 beneficiaries.
55% increase in ANC
registration after JSY
implementation
Strehlow M.C. at el.
2016 [41]
Feb-April 2014, India—
Andhra Pradesh, Assam,
Gujarat, Karnataka and
Meghalaya
Prospective
observational
study
free of charge
ambulance
transport
1212 institutional deliveries
out of 1411 deliveries.
Meta-analysis of studies with outcome as institutional deliveries.
Mukhopadhyay DK
et al. 2016 [43]
2012-2013, West Bengal Cross-sectional JSY 745 institutional deliveries
out of 946 JSY mothers.
Cash incentive most crucial
step influencing institutional
care.
Mukhopadhyay et
al. 2016 [42]
2011, Bankura District,
West Bengal
Cross sectional
study
BPCR 207 institutional deliveries
out of 235 women who
have delivered recently
Kumar S. et al. 2017
[44]
2008-2009, Uttar Pradesh Cross-sectional
study
ASHA 167 institutional deliveries
out of 270 women who
have delivered in last 6
months.
ASHA has helped the rural
beneficiaries in getting
continuous information
about ANC.
Seth A. et al. 2017
[45]
2014, Varanasi, Uttar
Pradesh
Mix method ASHA 3472 institutional deliveries
influenced by ASHA out of
4912 mothers.
There is positive
relationship between visit of
ASHA and utilization of
maternal health services.
Salve H. R. et al.
2017 [46]
August 2010 to March
2013, Ballabgarh, Haryana
Cross-sectional JSSK 537 institutional deliveries
out of 734 beneficiaries
Khes SP et al. 2017
[47]
June 2015-July 2016,
Chhattisgarh
Cross-sectional JSY 353 institutional deliveries
out of 384 beneficiaries
Majority of participants were
not aware about JSY
services except monetary
services.
Siddaiah A et al
2018 [48]
2015, Faridabad Mixed method JSY 119 institutional deliveries
out of 518 mothers
5.1.3 Results of studies with Institutional deliveries as an outcome, but not included in forest
plot (n=21)
Overall (I^2 = 99.69%, p = 0.00)
Govil D et al.(2013)
Limm et al(2010)
Mukhopadhyay et al.(2016)
Sidney K et al.(2014)
Mukhopadhyay DK et al.(2016)
Farah N. et al, (2015)
Ved R et al.(2012)
Vikram K et al.(2011)
Kilaru A. et al.(2010)
Siddaiah A et al.(2018)
Kumar S et al. (2017)
Sidney K et al.(2012)
Strehlow MC at el. (2016)
Khes SP et al.(2017)
Kaur H. et al.(2015)
Uttekar BP et al.(2007)
Kumar et al(2015)
Mukhopadhyay DK et al.(2013)
Mandal DK et al(2010)
Study
Amudhan S et al(2013)
Salve H et al. (2017)
Nipte D. et al.(2015)
Sinha S. et al. (2012)
Seth A et al. (2017)
Panja TK et al.(2012)
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
-.50.511.5
Interpretation of forest plot
Year of publication = 2007 to 2018
Total studies pooled = 25
Sample size = 147 - 182869 mothers
Pooled prevalence of institutional deliveries = 71% (CI : 0.64 to 0.78)
Heterogeneity = 99.69% (very high because of sample size variability
Author & year of
publication
Study Period Study Type Intervention Results
Before 2013
Nandan D. et al. 2010
[370]
2010, Delhi Descriptive
study
MAMTA Scheme 84.3 % of beneficiaries under
the scheme came to know
about the scheme through
ASHAs.
Scheme has increased
number of institutional
deliveries among the target
women in some localities,
where it is functional.
But 30% of the beneficiaries
underwent delivery at home.
Kilaru A et al. 2010 [25] 1996-1998 to
2007-2009,
Karnataka
Comparative
study
NRHM
(Institutional
deliveries
SBA home
deliveries)
45% increase in institutional
deliveries 17% decline in SBA
home deliveries
Singh SK et al. 2011
[52]
2005-2008, India Secondary
data analysis(
SRS data)
NRHM (SRS
data)
57% relative increase in
institutional deliveries.
Sandeep S. et al. 2012
[53]
2011, Haryana Cross-
sectional
descriptive
study
JSY Out of 72 JSY mothers, 39
mothers had institutional
deliveries.
Out of 76 non-JSY mothers
55 had institutional deliveries.
Gupta SK et al. 2012 [51] 2003-2005 to
2005-2007,
Jabalpur, MP
Observational
study
JSY 42.6% increase in institutional
deliveries.
Gopalan D et al. 2012
[54]
2005-09, Orissa Mixed method
design
( HMIS data,
FGDs of JSY
JSY 18.1% increase in institutional
deliveries.
Gain in institutional deliveries
is greater than those of ANC,
PNC indicating limited role of
JSY in comprehensively
beneficiaries
and ASHA)
addressing maternal care
needs.
After 2013
Randive et al. 2013 [7] 2005-2010, India Secondary
data analysis
(SRS data)
JSY Increase in institutional
births= 20% to 49%
Prinja S. et al. 2014 [55] 2011, Haryana,
3 districts=
Ambala, Hisar,
Narnaul
Secondary
data analysis
(Civil
registration
data on
institutional
deliveries)
National
ambulance
system utilization
Institutional deliveries in
Haryana rose significantly
after the introduction of NAS
service
Ambala (OR=137.4, CI=22.4-
252.4 ) Hisar (OR=215,
CI=88.5-341.3 ). No
significant increase was
observed in Narnaul (OR=4.5,
CI= -137.4 to 146.4)
Mohanan M. et al. 2014
[56]
2010, Gujarat Observational
study
Chiranjeevi
Yojanana
10.7 % point increase in
institutional deliveries.
Nagarajan S. et al. 2015
[57]
2001-05 to 2005-
11, India
Secondary
data analysis
(DLHS)
NRHM Increase in Institutional
deliveries = 39% to 84%.
Vohra K. et al. 2015 [58] 1992-2009, India Secondary
data analysis
(SRS, census
data)
NRHM 73 % increase in institutional
deliveries.
Prinja S. et al. 2015 [59] 2011–15, UP,
district
Kaushambi
RCT ReMiND Project(
MNCH services)
34% increase in coverage of
institutional deliveries.
Saksena S. R. et al.
2015 [60]
2009-2010,
Unnao district,
Uttar Pradesh
Descriptive
study
Referral transport 25% of the women were
taken to one facility, 32%
were taken to two facilities,
and 25% taken to three
facilities, while 19% were not
taken to any facility before
deaths.
Gupta M. et al. 2016 [61] 2002-04 to 2012-
13, Haryana
Secondary
data analysis
(DLHS data)
NRHM Institutional delivery rate has
been narrowed down from
48.2% to 13%.
Singh U.B., 2016 [62] 2005-6 V/s 2010-
11, Uttrakhand
Secondary
data analysis(
AHS, DLHS 3,
NFHS 3)
NRHM Increase in institutional
deliveries
15.7%
Prinja P. et al. 2017 [63] 2015, UP Pre- and post-
quasi-
experimental
ReMiND
intervention
Increase in Institutional
deliveries
30-40%.
Vellakkal S. et al. 2016
[64]
2007–08 to 2011–
12
Secondary
data analysis
(DLHS, AHS)
NRHM In the EAG states as a whole,
there was an increase of 13%
and 40% points in the uptake
of institutional delivery in
the early post-NRHM period
2007–08 (38.3%) and late
post-
NRHM period 2011–12
(65.5%)
Wagner AL.et al.
2017[65]
2007-08 and
2012-13, India
Secondary
data analysis
(DLHS)
ASHA Institutional delivery
increased = 61.6% to 82.5%
Apum A. Et al. 2017[66] 2014, Assam Cross
sectional
ANC services
Institutional
deliveries
Institutional delivery =33.3%
ANC visits (4 or more)
=50.3%
Singh SK et al. 2017 [44] 2005-13, India Secondary
data analysis
(SRS data)
JSSK and JSY Institutional deliveries
increased = 24.4 to 69.7 %.
Agarwal R. et al. 2018
[67]
2014-2015,
Haryana
Cluster
randomised
trial
Quality
management
activities
7345 deliveries =
5108 delivered in the PHCs
2237 were referred to higher
centres before childbirth
ANNEXURE 5.2. CHILD HEALTH
5.2.1 Results of studies with outcome as Perinatal Mortality Rate (N=14).
Author
Name, Year
of publication
Journal Name Study period,
Place
Type of study/
Intervention
Results
[n,(N)]
Singh S et
al,2011 [52]
Indian Pediatrics 2005-2008,
Indian
states(Rural
area)
Secondary
data analysis
(SRS)/ NRHM
Relative decline in PNMR was only
2.5% in the rural areas, relative
increase in hospital delieveries:57%
Goudar S et
al,2015
[229]
Reproductive health
journal
Jan 2010-Dec
2013,
Belgaun,Nagpu
r
Prospective
population
based
surveillance
Increase in community PMR from
60.7 to 76.7 per 1000 births in
Belgaum, from 114.1 to 400.0
deaths per 1000 births in Nagpur;
Vishwanah K
et al,2015
[231]
The international
electronic journal of
Rural and Remote
Health Research,
education, practice
and policy
Feb-July 2012,
Jawadhi Hills
Tamilnadu,
under CMC
Vellore
Case control
study
Perinatal mortality rate: 149.3/1000
births)(40 perinatal deaths) ;preterm:
16,term: 24
Mony P et
al,2015
[230]
BMJ Open Nov 2012(30
days), 10
districts of the
northern state
of Rajasthan
Hospital based
prospective
cohort study
The estimated perinatal mortality
rate was 35.8 (34 to 37) per 1000
births
Rani S et
al,2012 [232]
Indian Pediatrics May-Oct 2009,
Labor room
and postnatal
wards of a
teaching
hospital in
North India.
Prospective
cohort study.
IPPM Rate: 80/1000 live births(8%)
,significant risk factors for IPPM:
presence of obstructed labor , father
engaged in unskilled labor and
absence of urine examination during
antenatal period .
Carlo W et
al, 2018
Multicounty
study [228]
New England
Journal of Medicine
Mar 2005-Feb
2007,
Indian(Rural
communities)
Pre post study
design/
Training of
Birth
Attendants on
ENC
Perinatal mortality did not
significantly decrease after ENBC.
Siddalingapp
a H et al,
2013 [233]
Journal of Clinical
and Diagnostic
Research
2011,
Nanjangud
talluk of Mysore
district, India
Cross sectional
community
based study
PNMR: 28.93 per 1000 live births.
Asalkar MR
et al, 2013
[234]
International Journal
of Reproduction,
Contraception,
Obstetrics and
Gynaecology
Jan 2008-
December
2010
cross sectional
study
PNMR: 86/1000,preterm PNMR:
426/1000,Term: 37/1000,Post Term:
68/1000.
Singh S et
al, 2017
[371]
Indian Journal of
Community
Medicine
2005-2013
rural areas in
each of the
major states of
India
Secondary
data analysis
(SRS)
Increase in hospital deliveries:
185.7% ,relative decline in PNMR
was 30% ,most states had
significant decline in PNMR; Assam,
Haryana, and Karnataka have only a
marginal decline, but Jharkhand has
shown no decline in PNMR during
the same period
Iyengar K et
al,2012 [235]
J health popul nutr April-December
2006,
Community
based study
Compared to women with no
anaemia, women with severe
anaemia were 3.7 times more likely
to have a perinatal death while
compared to mild anaemia, they
were 2.1times more likely to have
perinatal death
Lim S et
al,2010 [26]
Lancet 2010 Secondary
data analysis
from the
nationwide
district-level
household
surveys(2002-
04,2007-09)
In matching analysis: JSY payment
was associated with a reduction of
3·7 (95% CI 2·2–5·2) perinatal
deaths per 1000 pregnancies, In the
with-versus-without comparison, the
reductions were 4·1 (2·5–5·7)
perinatal deaths per 1000
pregnancies
Gaur A et
al,2015 [127]
Journal of Evidence
based Medicine and
Healthcare
(2003–2004),
2006–
2007,2010-
2011, tertiary
care hospital,
associated with
medical college
in M.P.
retrospective
hospital based,
observational
comparative
study
Perinatal deaths have decreased
from 64.86 in 2003-04 to 51.54 in
2006-07 (p<0.05) and 31.97 in
2010-2011.
Kulkarni R et
al,2007 [237]
Indian Journal of
Community
Medicine
Rural and
urban areas in
six districts in
Maharashtra
Verbal autopsy Total number of perinatal deaths=
83 (31 stillbirths and 52 early
neonatal deaths,
Devi P et al,
2015 [128]
Journal of Evolution
of Medical and
Dental Sciences
January 2014
to January
2015, Tertiary
Care Hospital
of Andhra
Pradesh.
retrospective
study
The PMR was 15.3 per thousand
births(129)
Results of studies with outcome as Still birth Rate(n=25)
Author
,Publication year
Journal Name Study period, Place Type of
study/Interv
ention
Results
Goudar S,2015 [229] Reproductive
health journal
Jan 2010-Dec 2013,
Belgaun,Nagpur
Prospective
population
based
surveillance
Decline in SBR from 22.5 to
16.3 per 1,000 births in
Belgaum and from 29.3 to
21.1 in Nagpur
Carlo W et al,2018
[228]
New England
Journal of
Medicine
Mar 2005-Feb 2007,
Indian(Rural
communities)
Pre post
study
design/
Training of
Birth
Attendants
on ENC
There was a significant
reduction in SBR (RR
0.69,the rate of stillbirths by
delivery attendant decreased
significantly for
nurses/midwives (RR 0.50
and TBA (RR 0.63; but not
for physicians. The SBR
among home deliveries
decreased.
McClure E et
al,2015[240]
Reproductive
Health Journal
2010-13,
Belgaun,Nagpur
Prospective
observational
Nagpur: Reduction in SBR
from 33 to 25,Belgaum:
Reduction in SBR from 28.3
to 22.3
Newtonraj A et
al,2017 [243]
BMC Pregnancy
and Childbirth
July 2013-Aug 2014,
Chandigarh
Case control
study
SBR: 16/1000 births per
year, Antepartum causes:
68% ,intrapartum causes:
32%.
Kumbhare S et
al,2016 [242]
The Journal of
Obstetrics and
Gynecology of
India
Sep 2012-Aug 2013,
Department of Obstetrics
and Gynecology,Medical
College Baroda, Gujarat.
Prospective
case control
study
SBR: 87.83 per 1000 live
births(506),fresh stillbirths:
88.5 %,macerated stillbirths:
11.5 %
Bhattacharyya R et
al,2011 [241]
Journal of
Obstetrics and
Gynecology
Research
Jan 1999-Dec 2008,
Department of Obstetrics
& Gynaecology,
Burdwan Medical
College, Burdwan(WB)
retrospective
cross-
sectional
study
SBR: 33.67 per 1000
births,SBR decreased from
44.87 per 1000 total births in
1999–2003 to 24.15
per 1000 total births in
2004–2008
Altijani N et al,2018
[244]
BMJ Open 2010-2013, Nine states
in India
Secondary
analysis of
cross-
sectional data
from the
Indian Annual
Health Survey
SBR: 10 per 1000 total
Births.
Siddalingappa H et
al,2013 [233]
Journal of
Clinical and
Diagnostic
Research
2011, Nanjangud talluk
of Mysore district, India
Cross
sectional
community
based study
Still birth rate of 9.55 per
1000 total births.
Kulkarni N et al,2018
[237]
Journal of the
Turkish-German
Gynecological
Association
January 2017 to
December 2017, Tertiary
care perinatal center,
Christian Medical
College Vellore
Retrospective
data analysis
SBR:16.8 per 1000 births.
Kochar P et al,2014
[245]
BMC Pregnancy
and Childbirth
2012, all districts of
Bihar
baseline
survey
SBR: 20 per 1,000 births.
McClure E et al, 2018
[246]
BJOG 2014-15,
Belagavi,Nagpur
Prospective,
observational
study
SBR in Belgavi:
24.1,Nagpur: 20.9
Asalkar MR et
al,2013 [234]
International
Journal of
Reproduction,
Contraception,
Obstetrics and
Gynecology
2008-2010, Dept of Obs
and Gynae,rural MIMER
Medical College and Dr.
Bhausaheb Sardesai
Talegaon rural Hospital,
Talegaon Dabhade,
Pune, Maharashtra.
cross
sectional
study
SBR:
47/1000,Preterm:74.3/1000
Term:28.81/1000,Post-term:
40.5/1000
Saleem S et al,2018
[247]
BMC
Reproductive
Health,
Jan 2010-Dec 2016,
Belagavi and Nagpur
prospective,
population-
based
observational
study
cumulative SBR: 25.3/1000
births and decreased from
31.3/1000 births in 2010 to
23.8/1000 births in 2016
giving an annual decline rate
of 4.5%
Satishchandra DM et
al,2009 [248]
Indian Journal
of Pediatrics
Mar 2006 to Feb 2007,
Primary Health Centre
Community
based study,
statistically significant
(p<0.05) reduction in the
(PHC) area of
Vantamuri,
District Belgaum,
Karnataka
perinatal deaths (11 to 3)
after the training.
Mukhopadhyay P et
al,2010 [68]
J HEALTH
POPUL NUTR
June 2006–May 2007,
R.G. Kar Medical
College and Hospital in
Kolkata
cross-
sectional,
observational
5.1%(18) vs 0.9%(6)
Dandona R et al,2019
[250]
BMC Medicine January to December
2016, 1657 clusters in
Bihar state
15.4 per 1000 births ,
Antepartum and intrapartum
SBR was 5.6 and 4.5 per
1000 births , higher
proportion of births was
stillborn
(8.6%, p < 0.001) among
women (175, 0.9%) for
whom the delivery was
deferred
Dandona R et al,2017
[249]
PLOS Medicine 2014 -2015. 38 districts
of Bihar (772 rural and
245 urban clusters)
Survey Incidence of stillbirths was
21.2 per 1,000 births in
Bihar state
Gaur A et al,2015
[127]
Journal of
Evidence based
Medicine and
Healthcare
(2003–2004),2006–
2007, 2010-2011,
tertiary care hospital,
associated with medical
college in M.P.
retrospective
hospital
based,
observational
comparative
study
Stillbirths have decreased
from 4.8% in 2003-04 of
3.0% in 2006-07 (p<0.210)
and 2.5%in 2010-2011.
Malhotra S et al, 2014
[182]
Journal of
health
population
nutrition
Apr 2009-Mar 2010,
Nagaur district in
Rajasthan and
Chhatarpur
district in Madhya
Pradesh
Record review SBR of both the DHs was
around 38/1,000 births.
Devi P et al, 2015
[128]
Journal of
Evolution of
Medical and
Dental Sciences
2014-January 2015,
Tertiary Care Hospital of
Andhra Pradesh
retrospective
study
still birth rate was 11.7 per
thousand births.
Baqui AH et al, 2006
[90]
Bulletin of World
Health
Organization
, 17 rural sectors in 2
districts of Uttar Pradesh
Barabanki , Unnao
Verbal
autopsy
SBR was 31.8 deaths per
1000 births.
Mony P et al,2015
[230]
BMJ Open Nov 2012(30 days), 21
public sector health
facilities of 10 districts of
the northern state of
Rajasthan
Hospital
based
prospective
cohort study
The stillbirth rate was 26.5
per 1000 births.
Malhotra S et al, 2014
[182]
Journal of
health
population
nutrition
Apr 2009-Mar 2010,
Nagaur district in
Rajasthan and
Chhatarpur
district in Madhya
Pradesh
Record review SBR of both the DHs was
around 38/1,000 births.
Devi P et al, 2015
[128]
Journal of
Evolution of
Medical and
Dental Sciences
2014-January 2015,
Tertiary Care Hospital of
Andhra Pradesh
retrospective
study
Still birth rate was 11.7 per
thousand births.
Result of studies with ENMR as outcome (n=6).
Author
,Publication
year
Journal
Name
Study
period,
Place
Type of
study
Results
[n,(N)]
Nagarajan S
et al, 2015
[57]
Elsevier Review article Average annual rate reduction (AARR) in early
neonatal mortality rate (ENMR) in three epochs
(pre-NRHM 2002-05, early post NRHM 2006-
09, and later post NRHM 2010-13): -3.8,2.5
and 4.3
Khurmi M et
al,2015 [131]
Indian
Journal of
Child Health
Review article ENMR declined from 28 to 22 (SRS 2005,
2013) for India, indicating a point decline of 6
and percentage decline of 21%.The maximum
point decline is seen in Orissa (13points) and
minimum in Himachal Pradesh and Jharkhand
(2 and 0 point each).
Decline in ENMR rural from 2005 to 2013: 6
points (19%),urban ENMR: 5 points (31%)
Gaur A et
al,2015 [127]
Journal of
Evidence
based
Medicine and
Healthcare
tertiary care
hospital,
associated
with medical
Observational
study
Reduction in early neonatal Deaths from 99 in
2003 to 54 in 2011.
5.2.2 Overall Impact of NRHM/NHM on NMR (n=3).
Author, Year of
Publication, Area
Journal Name
Study
Period
Results
college in
M.P.
Devi P et
al,2015 [238]
Journal of
Evolution of
Medical and
Dental
Sciences
January
2014 to
January
2015,
Tertiary Care
Hospital of
Andhra
Pradesh.
retrospective
study
Early neonatal death rate3.56 per thousand
births
Baqui AH et
al,2006 [90]
Bulletin of
World Health
Organization
17 rural
sectors in 2
districts of
Uttar
Pradesh
Barabanki
,Unnao
Verbal
autopsy
ENMR 35.1/1000 live births, LNMR 13.9 per
1000 live births.
Lahariya C et
al, 2010 [129]
Indian J
Pediatr
India secondary
data analysis
from SRS
,NFHS
The mortality rates in early neonatal period
declined by 21.6% between 1990 to 2007, rate
of mortality decline is different for 2000–2003
compared to 2004–2007. rapid ARR in ENMR
during 2000-03,increase in ENMR during
2004-07
Bapat U et
al,2012 [130]
BMC
Pregnancy
and
Childbirth
48 slum
localities in
six municipal
wards of
Mumbai
verbal
autopsies
ENMR=7.6/1000 live births
Kumutha;2014,Tamil
Nadu [88]
Indian Journal of
Paediatrics
2005-2012
In 2005, national NMR was 37/1,000 & Tamil
Nadu was 26/1,000 live births.
In 2011 national NMR dropped to 31/1,000
(only six points drop from 2005). But Tamil
Nadu NMR dropped to 15/1,000 livebirths
(drop of 11 points) & significant 42%
reduction from 2005.
Nagarajan et al; 2015 [57]
Seminar in Fetal
and Neonatal
Medicine
2001-2013
NMR (per 1000 live births) declined from
37 in 2005 to 28 in 2013. NRHM has
brought MDG 4 & 5 within India’s grasp.
Khurmi et al;2015 [87]
Indian Journal of
Child Health
2005-2013
NMR declined from 37 to 28 (SRS
2005,2013) indicating a point decline of 9
and percentage decline of 24%. The
maximum point decline is seen in Orissa
and Chhattisgarh (16 and 14 points,
respectively) and minimum in Jharkhand
(2 point). The maximum percentage
decline is seen in Punjab (47%) and
minimum in Jharkhand (7%).
5.2.3. Studies with specific strategies and NMR as an outcome (n=8)
Author
,Publication
year, Area
Journal
Name
Study
period
Type of
study
Interven
tion
Results
Agarwal et al;
2007, India
[89]
Journal of
Perinatolog
y
January 2004
–August
2005
Before-and-
after
intervention
trial
Essentia
l new
born
care
30% decline in NMR during
intervention period as
compared to control period
(20.3 versus 29.3 per 1000 live
births; RR 0.69, 95%
confidence interval (CI) 0.57 to
0.85).
Baquai et al;
2008, Uttar
Pradesh [372]
Bulletin of
the World
Health
Organizatio
n
2004-2005
Quasi
experiment
al study
HBPNC
Neonates who received a
postnatal home visit within 28
days of birth had 34% lower
NMR (35.7 deaths per 1000
live births, 95% confidence
interval, CI: 29.2–42.1) than
those who received no
postnatal visit (53.8 deaths per
1000 live births, 95% CI: 48.9–
58.8),
Sen A et al;
2009, [92]
Purulia, West
Bengal
Journal of
Perinatolog
y
January 2003
to October
2005
Observation
al study
Facility
based
new
born
care
NMR reduced by 14% in 1st
year and 21% in 2nd year after
SNCU became functional.
Estimated neonatal deaths
averted were 329, which would
reduce NMR of the district from
55 to 47 in 2 years.
Baqui et
al;2009, Sylhet
district, [91]
Bangladesh
BMJ 2004-2005
Observational
Cohort study
HBPNC
NMR was 67% lower in those
who received a visit on day one
than in those who received no
visit (adjusted hazard ratio 0.33,
95% confidence interval 0.23 to
0.46; P<0.001).
Darmstadt et
al; 2010 [93]
Mirzapur,
Bangladesh
PLOS One
January2004–
December 2006
Cluster
randomised
controlled trial
HBPNC
NMR was 24.8 (95% CI: 20.7–
29.4) and 27.9 (95% CI:23.5–
32.8) in the comparison arm at
baseline and endline,
respectively, and was 25.2 (95%
CI: 21.0–30.1) and 24.0 (95% CI:
19.8–29.0) in the intervention arm
at baseline and end line,
respectively.
Bhandari et
al;2012,
[94]Faridabad,
Haryana
BMJ
January 2008
and 31 March
2010
Cluster
randomised
trial.
IMNCI
NMR beyond first 24hours
(adjusted hazard ratio 0.86, 0.79
to 0.95) were significantly lower in
intervention than in control
clusters. Adjusted hazard ratio for
NMR was 0.91(0.80to 1.03).
Tripathy et al;
2016, [95]
Rural
Jharkhnand &
Odisha
Lancet
Global
Health
September
2009–
December 2012
Cluster
randomised
controlled trial
HBPNC
NMR was 30 per 1000 livebirths in
the intervention group and 44 per
1000 livebirths in the control
group. (odds ratio [OR] 0.69, 95%
CI 0·53–0·89). 31% reduction in
neonatal mortality rate during 2
years.
Gautam et al;
2016, [96]
Jabalpur,Madh
ya Pradesh
Internation
al Journal
of
Healthcare
and
Biomedical
Research
August 2011 to
July 2012
Observational
study
Facility
based
new
born
care
NMR was reduced by 12%.
Estimated neonatal deaths
averted were 111(7%) out of 1590
admissions compared to
200(19.1%) out of 1048
admissions in previous year (p
value <0.001). Improved survival
and reduced morbidity after
establishment of SNCU.
5.2.4. Studies with essential newborn care practices as an intervention (n=6).
5.2.5 Studies with facility based newborn care as an intervention (n=4).
Author,
Publication
year , Area
Journal
Name
Study
period
Type of
study
Intervent
ion
Results
Sodani et al;
2011 [97]
CHC, Bharatpur
district,
Rajasthan
Indian
Journal of
Public
Health
September
and October
2010
Cross
sectional
study
Essential
new born
care
None of the CHCs have fully
equipped facility based
newborn care services
(including newborn corner and
newborn care stabilization
unit).
Vijayalakshmi et
al; 2014, [173]
Journal
of Neonat
al Biology
1st April
2012 to 31st
June 2012
Cross
sectional
Essential
new born
care
65% newborns were breastfed
within an hour after birth and
5.9% were pre lacteally fed.
Mothers age at marriage and
day of first bath to newborn’s
was significantly associated
(p=0.02).
Sinha et al;2014,
[99]
Mewat, Haryana
Western
Pacific
Surveillan
ce and
Response
Journal
January and
March 2013
Cross
sectional
study
Essential
new born
care
60% of mothers adopted less
than three safe practices
(wrapping newborns, delayed
bathing, cord care). 237 (74%)
mothers started breastfeeding
within the first hour, 279 (87%)
fed colostrum, and 188 (58%)
mothers exclusively breastfed
their newborn.
Kumar et al;
2016 [70]
Rajasthan, India
BMC
Pregnanc
y and
Childbirth
March 2013
to April
2014.
Quasi-
eperimental
Essential
new born
care
Safe childbirth checklist (SCC)
was used in 86 % of the
observed deliveries in
intervention facilities. Client in
intervention facility received
11.5 more SCC (95 % CI-8.5–
14.6)) best practices than client
in comparison sites (p<0.001).
Narasimha BC et
al; 2016, [100]
Internatio
nal
Journal of
Communit
y
Medicine
and
Public
Health
October
2013 to
September
2014.
Cross-
sectional
Essential
new born
care
62.5% of the mothers initiated
breast feeding within 1 hour
and colostrum was fed to 95.6%
of babies. About 137 (85.6%)
babies were immunized up to
date. 12.5% (20) were low birth
weight babies.
Gosain et al;
2017, [101]
Journal of
Tropical
Paediatric
s
February-
March 2014
Cross
sectional
study
Essential
new born
care
ENC services were largely in
the public-sector domain
(68.5% of births). SNC burden
was largely borne by the private
sector (66% of admissions).
Only 53.9% of government
facilities and 17.5% of private
facilities had a fully equipped
newborn care corner.
Author
,Publication
year,Area
Journal
Name
Study
period
Type of
study
Intervention Results
Kumaravel et
al;2015, [102]
Dharmapuri
district, Tamil
Nadu
Journal of
Evolution of
Medicine and
Dental
sciences
Jan 2011
to Dec
2014.
Descriptive-
retrospective
study
Facility
based new
born care
Increase newborn care,
survival rate (74.4%- 85%)
due to NRHM provided
manpower & equipments to
improve SNCU. Admissions
increased two folds in the
past 4 years. Referral
out(5%-1.7%), death
rate(11.6%-9.6%),
LAMA(9%-3.7%) rates
were decreased.
Sachan et al;2015,
Lucknow, Uttar
Pradesh [103]
Journal of
Neonatology
2013
to
2015
Retrospective
analytical
study
Facility
based new
born care
Score in FBNC training pre-
test was 2.80 (±0.31) which
increased to 8.25 (±0.49) in
post test. The increase from
pre-test to post test was
5.30 (±0.33) (p=0.0001).
FBNC training program by
the GOI has improved the
knowledge of the
participants significantly
which is expected to result
in decline of NMR at faster
pace.
Chauhan et
al;2016,Bihar
[104]
Indian
Journal of
Public Health
May to
June
2015
Cross
sectional
study
Facility
based new
born care
Only 22.8% of the NBCCs
were found to be fully
functional, majority (68.4%)
were partially functional,
and 9% were
nonfunctional.1/3rd of the
neonates delivered were
kept in NBCCs
Oza JR et al;2017,
Rajkot
district,Gujarat
[105]
International
Journal of
Community
Medicine &
Public Health
August
2013 to
October,
2013
Cross
sectional
study
Facility
based new
born care
All 32 (100%) NBCC were
found partially functional.
Total 68 (67.3%) of 101
respondents were trained
in NSSK. From total 68
trained health personnel, 12
(17.7%) got the score
above the cut off for
resuscitation skill.
5.2.6 Studies with IMNCI as an intervention (n=3).
5.2.7 Studies on secondary data analysis (n=5)
Author
,Publication
year,Area
Journal Name Study
period
Type of
study
Interventio
n
Results
Mohan et
al;2011,
India [108]
Journal of Healt
h, Population an
d Nutrition
2005-2009
Mixed
methods
study
IMNCI
65.5% newborns were
visited by a trained worker
within 24 hours, and 63.1%
were visited three times
within 10 days. Difference
was significant only for
care-seeking for ARI (net
difference: 17.8%; 95%
confidence interval 2.3-
33.2, p<0.026).
Taneja et
al;2015,
Faridabad,
Haryana
[107]
Journal of
Global Health
Jan 2008
Cluster–
randomized
controlled trial
IMNCI
Implementation of IMNCI
had no effect on
inequities in neonatal
mortality but reduced
inequities in post–
neonatal mortality
between wealth quintiles
Author,
Year of
Publication
Journal
Name
Study
Period
Results
Rammohan
et al;2013
[113]
Plos One
2008-
2010
80% of neonatal deaths occurred within the first week of
birth. Neonatal mortality is significantly lower when the
child’s village is closer to the district hospital (DH),
suggesting the critical importance of specialist hospital care
in the prevention of newborn deaths.
Aguayo et
al;2016[114]
BMJ Global
Health
2006-
2014
Rates of early initiation of breastfeeding increased from
24.5% in 2006to 44.6% in 2014 (i.e. a 1.8-fold increase).
Jha et al; 2017
[115]
Lancet
2000-
2015
Neonatal tetanus mortality rate fell from 1·6 per 1000
livebirths in 2000 to less than 0·1 per 1000 livebirths in 2015
. Average annual decline in mortality rates from 2000 to
2015 was 3·3% for neonates
Phukan et
al;2018
[116]
International
Breastfeeding
Journal
2011-2015
Less than 1/4
th
(21%) of children were breastfed within 1 h
of birth. Odds of neonatal deaths were increased (OR 2.93;
95% CI 1.89, 4.53) in comparison with neonates who have
breastfed within 1 h of birth.
Bora et al;2018
[117]
Plos One
2015-
2016
Estimated NMR is about 2.4 times greater than the targeted
one (estimated 29.2 against targeted 12.0 deaths per 1000
live births in SDG3).
Review Study with HBPNC by ASHAs as an intervention (n=1)
Som et
al;2017,
Odisha [106]
International
Journal of
Health Sciences
& Research
Not
mentioned
Cross
sectional
IMNCI
Trained AWW have
enhanced knowledge of
childhood illness and
their management as
compared to IMNCI
untrained counterparts
1.41(95% CI,1.07-1.73),
P<0.0001
Gogia et
al;2016 [118]
Journal of
Perinatology
2012
Intervention was associated with a reduced risk of mortality
during the neonatal period .
RR = 0.75; 95% confidence intervals (CIs) 0.61 to 0.92, P =
0.005
5.2.8 Studies included in forest plot with outcome as prevalence of low birth weight babies.
(n=10).
Author ,Publication
year,Area
Journal Name Study
period
Type of study Intervention
/Strategy
Results
Number of low
birth babies
[n,(N)]
Sharma et al; 2008,
Government Medical
College, Chandigarh
[373]
The Internet
Journal of Health
April 2007
to March
2008
Cross sectional
study
LBW 46(193)
Biswas et al;2008,
District of Puruliya,
West Bengal [134]
Rural Health
Journal
2004-05
Cross sectional
study
LBW 152(487)
Velankar et
al;2009,Sahaji
Nagar, Mumbai
[135]
Bombay Hospital
Journal
Ten months
Cross sectional
study
LBW 114(252)
Jha et
al;2009,Varanasi
district, Uttar
Pradesh [136]
Indian Journal of
Community
Health
June 2006-
May 2007
Longitudinal
Cohort study
LBW 83(298)
Agarwal et
al;2011,Tertiary care
hospital, Uttar
Pradesh [137]
Annals of
Nigerian
Medicine
Not
mentioned
Cross sectional
study
LBW 140(350)
Metgud et al;2012,
Kinaye (PHC) in
rural Karnataka,
[138]
Plos One
June 2008 to
December
2009.
Cross sectional
study
LBW 260(1138)
Choudhary et
al;2013, Banganga,
Bhopal [139]
Indian Journal of
Public Health
Not
mentioned
Longitudinal
Cohort study
LBW 105(290)
Dandekar et al;2014,
Perambalur,Tamil
Nadu [140]
Global Journal of
Medicine and
Public Health
June –
November
2013
Cross sectional
study
LBW 35(300)
Lateef et al;2015,
Era’s Lucknow
Medical College
[141]
International
Journal of
Community
Medicine and
Public Health
July 2014 to
December
2014
Cross sectional
study
LBW 105(356)
Shashikantha et
al;2016, Chiri,
International
Journal of
February to
April 2013
Cross sectional
study
LBW 102(564)
Meta-analysis of studies with outcome as prevalence of low birth weight babies.
PGIMS, Rohtak
[142]
Community
Medicine and
Public Health
Interpretation of Forest Plot
Study design: Cross sectional, longitudinal cohort study,
Year of publication: 2008 to 2016,
Total studies pooled: 10
Sample size: 193 to 1138
Pooled LBW: 28% (CI: 0.23, 0.34)
Heterogeneity: 94.91% (very high because of sample size variability)
5.2.9 Result of studies with IMR as an outcome (n=16).
Author
,Publication
year,Area
Journal Name Study
period
Type of
study
Interventi
on/
Strategy
Results
Ramani et al ;
2010 [143]
VIKALPA 1990-2008
Secondar
y data
analysis
NRHM
Average annual reduction of 1.9
% in IMR over the period 1990-
2008. Aim for annual average rate
of reduction of 6.74 per cent in
IMR during the period 2009-2015
if MDG target of IMR at 28/1,000
live births by 2015 is to be
achieved.
Shah et al ;
2011,
Aligarh district,
Uttar Pradesh
[144]
Australasian
Medical Journal
July 2005 to
June 2006
Cross
sectional
study
Infants
death in
Medical
College
Infant mortality rate was 83.0 per
thousand live births . Main causes
of death were diarrhoea,
pneumonia and malnutrition in the
post- neonatal period.
Prasad et al ;
2013 [145]
Global Health
Action
April 2005 to
March 2012
Cross
sectional
study
NRHM
In high focus states, Rural IMR fell
by 15.6 points between 2004 and
2011, as compared to 9 points in
urban areas.
Narwal et al ;
2013, [146]
International
Journal of MCH
and AIDS
2000-2009
Secondar
y data
analysis
NRHM
IMR in rural India declined from 68
to 50/1000 live births between 2000
and 2009, with AARR of 3.0% (95%
CI=2.6%-3.4%) .IMR decline with
AARR of 3% in Pre NRHM & 3.3%
in Post NRHM era.
Singariya et al ;
2013 [147]
Journal of Finance
and Economic
2005-2012
Secondar
y data
analysis
NRHM
Rural IMRs declined from 76 points
– from 124 to 48 while urban IMRs
36 points decline in the same period
(1980- 2011). Annual rate of
reduction of IMR is much higher in
the post NRHM period. It was near 2
percent in 2000 -05 and its previous
years, but after implementation
NRHM it has been accelerated to 4
percent in 2005-10 and nearly 6
percent in 2011 .
Author
,Publication
year,Area
Journal Name
Study
period
Type of
study
Interventio
n/
Strategy
Results
Prasad et al ;
2017,
Tertiary care
hospital, Surat
[148]
National Journal of
Community
Medicine
October
2016 to
November
2017.
Cross
sectional
study
Infant
deaths in
tertiary
hospital.
Total live births were 7677, 223
died within a year i.e. infant mortality
rate is 29.04
Sudhir et al ;
2017,
Tertiary
hospital,
Muzaffarpur
[149]
Journal of
Evidence-Based
Medicine and
Health Care
February
1, 2016, to
January
31, 2017.
Longitudin
al study
Infant
deaths in
tertiary
hospital.
Infant mortality was highest 71
(56.8%) in maternal age of delivery
<18 years (P<0.05). Infants on
exclusive breastfeeding had lowest
mortality 25 (20%) and infants on
formula feed had 56 (44.8%)
mortality (P=0.0001).
Rai et al, 2017,
Ballagarh, North
India [150]
BMJ 2008-2012
Cross
sectional
study
Health
and
Demograp
hic
Surveillan
ce System
IMR was 46.5/1000 live births. Care-
seeking was delayed among 50% of
neonatal deaths and 41.2% of post-
neonatal death.
Gopalkrishnan
et al, 2018 [151]
International
Journal of
Community
Medicine and
Public Health
2005-2012
Secondar
y data
analysis
NRHM
IMR 58-30/1000 live births(2005-
2012).
10 states/UT achieved, 15 states in
the range of 30-40/1000 LB .
Bills et al; 2018;
AP, Assam,
Gujarat,
Karnathaka,
Meghalaya
[152]
BMJ
February
to April
2014
Prospecti
ve
observatio
nal study
Emergenc
y medical
services
Cumulative mortality rates at 2, 7
and 42 days follow-up were 43, 53
and 62 per 1000 births . At 42 days
follow-up, preterm birth (OR 2.89,
95% CI 1.67 to 5.00) and twin
deliveries (OR 2.80, 95% CI 1.10 to
7.15) were the strongest predictors
of mortality
Studies on secondary data analysis
Author, Year of
Publication
Journal Name Study
Period
Results
Reddy et al ; 2012
[153]
WHO South-East Asia
Journal of Public Health
1990-2010
Declining trend in IMR observed during 1990-
2010 continues linearly, India’s IMR would be 42
per 1000 live births (95% CI: 38-45) by 2015
and MDG 4 target level of ‘28’ would be
achieved in 2023–2024
Sahu et al ; 2015
[154]
Indian Journal of Medical
Research
1992 to 2006
The hazard of infant mortality during 2005-2006
was 20 % less compared to period 1992-
1993..Hazard of infant mortality was highest
among births to mothers >/30 (HR=1.3) and
37% less among birth interval > 24 months.
Chowdhury et al ;
2017 [155]
BMJ
January 2008 -
March 2010.
The odds of death at 29–180 days and at 181–365
days were 1.4 (95% CI 1.3 to 1.6) and 1.7 (95%
CI: 1.4 to 2.0) higher in females compared with
males, respectively. IMR - 67.1/1000 live births
Kaur et al ; 2017
[156]
International Journal of
Community Medicine
and Public Health
1998-2014
Total fertility rate (TFR), women who had
institutional deliveries, safe deliveries and mean
children ever born are statistically significantly
associated with decline in infant mortality rate.
(p<0.01)
Ranjan et al;
2017 [157]
International Journal of
Population Studies
2004-2008
Infants born to rural women had 29% (p < 0.05)
higher risk of death compared to infants born to
urban women
Dhirar N et al;
2018 [158]
Indian Pediatrics 2005-2016
Reduction in IMR from 57 to 41/1000 live births.
Initiation of breast feeding within one hour
improved from – 23.4% to 41.6%, Exclusive
breastfeeding of the infants less than 6 months of
age improved from -46.3% to 54.9%..
5.2.10. Studies on evaluation of ASHAs under HBPNC (n=9).
Author,
Publication
year
Journal
Name
Study
period
Type of
study
Intervention/
Strategy
Results
Srivastava et al ;
2012, Thane
district of
Maharashtra [119]
Rural and
Remote Health
January
2011 to
March
2011,
Cross
sectional
study
HBPNC
71 ASHAs (48.6%) were unaware
of preventive actions to be taken for
Vitamin A. Twenty-nine (19.9%) of
the ASHAs did not feel the need for
referral for a child with diarrhoea
who is unable to drink or breast
feed.
Das et al ; 2013,
Priimary health
centers in Babina
block [120]
Indian Journal
of Paediatrics
November
2012-
February
2013
Cross
sectional
study
HBPNC
ASHA-investigator agreement on
the need to assess infants was
intermediate (kappa 0.48,
P<0.001). ASHAs did not follow
home-based newborn care formats
and skipped critical signs. Overall
ASHA-investigator agreement on
diagnosis was poor (kappa=0.23,
P=0.01)
Shashank et al ;
2013, Bijapur taluk
[121]
International
Journal of
Contemporary
June -
October,
2012.
Cross
sectional
study
HBPNC
Regarding complete cessation of
breast feeding 11(8.3%) said at 6
months, 45(34.1%) said by 1
years of age,44(33.3%) said at 2
years of age, 32(24.3%) said at 3
Research and
Review
yrs of age. 58(43.9%) of ASHA
were aware of the importance of
immunization and the adverse
events following immunization
Karol et al ; 2014,
Rajasthan [122]
International
Journal of
Humanities
and Social
Science
Not
mentioned
Cross
sectional
study
HBPNC
Average score of the ASHAs in
child health care is 86.62 %.
80.61 % of children in
immunization were motivated by
ASHAs.
Fathima et al; 2015
Karnataka [37]
Journal of
Health,
Population,
and Nutrition
February-
May
2012.
Cross
sectional
study
HBPNC
Advice on breastfeeding (83.6%)
, home-visits to see the puerperal
mother (72.4%) and
immunization at birth (84.2%)
was reported to be high.
Author, Publication
year
Journal Name
Study
period
Type of
study
Intervention/
Strategy
Results
Choudhary et al ;
2015,
Jamnagar district,
Gujarat [123]
National
Journal of
Community
Medicine
March
2012 to
Feb 2013
Cross
sectional
study
HBPNC
Four fifth of ASHA (80.93%)
knew about exclusive breast
feeding correctly and around
three fifth (60.31%) of ASHA
knew about the method of
prevention of neonatal tetanus.
Gupta M et al,
2016 , urban slum
areas, Chandigarh
[[124]
Advances in
Medical
Education
and Practice
August
2013 -
December
2014.
Longitudinal
study
HBPNC
Overall skill assessment score
improved from 0.64 to 1.76,
newborn examination skill from
0.52 to 1.63 after three rounds of
video recording. Proportion of
carrying PNC register increased
from 50% at the baseline to 86%
in the second round and 100% in
the third round
Pandit at al ; 2016;
Rural area of
Maharashtra [125]
International
Journal of
Health
April 2016
to June
2016.
Cross
sectional
study
HBPNC
Home Based Newborn Care
(5.41% of the ASHA had poor,
83.78% had average and 10.81%
had good level of knowledge
score respectively. Mean
Sciences and
Research
knowledge score of the ASHA for
the area of HBNC was 3.94±1.05
and in Breast Feeding initiative
was 2.54±0.55
Panda et al;2019
;Odisha [126]
International
Journal of
Community
Medicine and
Public Health
March -
June 2018
Cross
sectional
study
HBPNC
ASHA workers were aware
regarding the responsibilities.
64.7% in HBNC. All of them
(100%) ASHA’s helped in
immunization. 24.65% gave
advice to mothers about breast
feeding .
5.2.11 Studies under strategy IMNCI(n=5)
Author,
Publication year
Journal
Name
Study
period
Type of
study
Intervention/
Strategy
Results
Venkatachala J et al
; 2011
Panchkula district of
Haryana stat [109]
Indian
Journal of
public health
2006-2009 Cohort study IMNCI
Composite knowledge and skill
scores for Auxilliary Nurse
Midwives (ANMs) and Anganwari
workers (AWWs) together
declined significantly in the year
2009 from 74.6 to 58.0 in 8-day
training group and from 73.2 to
57.0 in 5-day training group (P <
0.001).
Biswas B et al ;
2011.West Bengal
[110]
Journal of
Tropical
Paediatrics
October
2008 to
July 2009
Cross
sectional
study
IMNCI
Appropriate management for all
associated conditions was given
in one-third (33.6%) young infants
and about one-fourth (23.9%)
older children
Bhandari et al ;
2012,Haryana
[94]
BMJ
June to
October
2006
Cluster
randomized
trial
IMNCI
IMR (adjusted hazard ratio 0.85,
95% confidence interval 0.77 to
0.94) were significantly lower in
the intervention clusters than in
control clusters.
Chishty S et al ;
2016,
Baran district of
Rajasthan [111]
International
Journal of
Current
Research
Two years
Longitudinal
study
IMNCI
Baseline scores for IMNCI skills
for assessing infants in age group
of 0-2 months was 7.23 at the
end of second visit the mean
scores in the four blocks
improved to 10.62 and further to
13.36 at the end of third visit
Thummakomma ;
2016,
Kakatiya Medical
College, Warangal
[112]
Journal of
Evidence
Based
Medicine
and
Healthcare
January
2013 to
September
2014.
Prospective
observational
study
IMNCI
Sensitivity of IMNCI criterion in
correctly identifying sick infants
of age 0-2 months is 90.02%,
specificity is 63.10%, positive
predictive value being 92.44%
and negative predictive value is
55.79%
5.2.12 Studies on Immunization(n=3) And Viamin A(n=1)
Author,
Publication
year
Journal
Name
Study
period
Type of
study
Interventio
n/Strategy
Results
Gupta et al ; 2007
[259]
Journal of
Urban Health
April to June
2006
Cross
sectional
study
Immunizati
on
Fully immunized children at the
age of 2 years were 30% in slums
as compared to 74% and 62.5% in
urban and rural areas (p<0.001),
respectively.
Prinja et al ; 2010
[356]
Bulletin of the
World Health
Organization
July 2005
and
December
2006.
Cohort
design
Immunizati
on
Proportion of children with 3
rd
DPT
dose by age of 4, 6 and 9 months
was 22%, 70% and 88%,
respectively, in the post-
intervention cohort. This was
significantly greater (P < 0.001)
than in the pre-intervention cohort,
where the proportions were 19%,
62% and 85%, respectively.
Verma et al ; 2017
[374]
Public
Health
Action
April 2013 to
March 2016
Mixed
methods
Immunization
Immunisation coverage- 100 % for
BCG vaccination in both
settlements by 2015, irrespective of
the presence of the ASHAs. For
DPT (or the pentavalent vaccine),
coverage was 100% in the
settlement with the ASHAs and
94% without ASHAs. Infant deaths
from 11-6/1000 live births(2013-
2015) in settlement with ASHAs.
Study on Vitamin A(n=1)
Mazumdar et al ;
2015 [375]
Lancet
June 24,
2010 - July
1, 2012
Randomi
zed
control
trial
Vitamin A
supplementati
on
The risk difference between the
vitamin A and placebo groups was
– 3·1 deaths per 1000 (95% CI –
6·3 to 0·1) - 322 neonates need to
be supplemented with vitamin A to
prevent one infant death in the first
6 months of life.
5.2.13 Studies included in forest plot with outcome as Exclusive Breastfeeding (n= 26)
Author, year of
publication, Area
Journal Name Study period Study
type
Interventio
n/Strategy
Results [Total
Number of
exclusive breast
feeding
babies[n,(N)]
Kishore et al; 2008
Panchkula district of
Haryana [159]
Journal of Tropical
Paediatrics
August 2007 (one
month)
Cross
sectional
Exclusive
breast
feeding
8(77)
S Sapna et al ; 2009
Urban Slum In Western
India [160]
International e-Journal
of Science, Medicine &
Education
Six months
Cross
sectional
Exclusive
breast
feeding
123(200)
K Madhu et al; 2009
Kengeri, Rural
Bangalore [161]
Indian Journal of
Community Medicine
January 2006 to
April 2006
Cross
sectional
Exclusive
breast
feeding
40(100)
Chudasama et al ;
2009,Rajkot [163]
Ojhas online journal of
Health and Allied
sciences
1st January to
19th February,
2007
Prospect
ive
cohort
Exclusive
breast
feeding
286(462)
Roy et al; 2009
Urban Slum of Kolkata
[162]
Indian Journal of
Community Medicine
Not mentioned
Cross
sectional
Exclusive
breast
feeding
34(120)
Sinhababu et al; 2010
Bankura District, West
Bengal, [164]
Journal of Health
Population and
Nutrition
June-July 2008
Cross
sectional
Exclusive
breast
feeding
369(647)
Dinesh et al ;
2012,District
Anand,Gujarat [296]
National Journal of
Community Medicine
Not mentioned
Cross
sectional
Exclusive
breast
feeding
38(75)
Bagul et al ; 2012,
Nagpur ,
Maharashtra [166]
Journal of Clinical and
Diagnostic Research
June 2011 to
December 2011
Cross
sectional
Exclusive
breast
feeding
142(384)
Radhakrishnan et al;
2012, Tamil Nadu [167]
International Journal of
Health & Allied
Sciences
March 2011–
June 2011
Cross
sectional
Exclusive
breast
feeding
99(291)
D J Naik et al; 2013
GMC, Miraj, [168]
International Journal of
Recent Trends in
Science And
Technology
September -
October 2011
Cross
sectional
Exclusive
breast
feeding
76(154)
Anwar et al ; 2013,
Varanasi district, Uttar
Pradesh [169]
Indian Journal of
Preventive and Social
Medicine
September 2011
to November
2011.
Cross
sectional
Exclusive
breast
feeding
4(97)
Joseph et al ;
2013,South India [170]
Journal of Family
Medicine and Primary
Care
November 2004
to April 2006.
Longitud
inal
study
Exclusive
breast
feeding
81(194)
Das et al ; 2014, Rural
medical college in
Eastern Indi [171]
Journal of Evolution of
Medical and Dental
Sciences
Not mentioned
Cross
sectional
Exclusive
breast
feeding
120(200)
Jain et al; 2014,Rural
Madhya Pradesh [172]
National Journal of
Community Medicine
March to Aug
2014.
Cross
sectional
Exclusive
breast
feeding
254(300)
Vijayalakshmi et al;
2014,
Rural Area of
Puducherry [173]
Journal of Community
Medicine and Health
Education
1st April 2012 to
31st March 2013
Longitud
inal
study
Exclusive
breast
feeding
98(136)
Vijayalakshmi et al;
2015 [98]
International Journal of
Health Sciences
January 2014
(one month)
Cross
sectional
Exclusive
breast
feeding
33(122)
Mishra et al; 2015
jasra block of
Allahabad district [176]
Indian Journal Child
Health
November 2011
to April 2012
Cohort
study
Exclusive
breast
feeding
45(80)
Prasad et al; 2015
Rural Community of
Pondicherry [177]
Scholars Academic
Journal of Bioscience
November and
December 2014
Cross
sectional
Exclusive
breast
feeding
249(350)
Choudhary et al; 2015,
Tertiary care center in
Bhopal [175]
International Journal of
Medical Science and
Public Health
January 2014 to
June2014
Cross
sectional
Exclusive
breast
feeding
330(1000)
Cacodkar et al;
2016,Goa [174]
International Journal of
Community Medicine
and Public Health
One year
Cross
sectional
Exclusive
breast
feeding
115(307)
Kar et al;2016,Odisha
[179]
Journal of
Epidemiological
Research
July 15th to Oct
15th 2011.
Cross
sectional
Exclusive
breast
feeding
173(360)
Jha et al ; 2016,
Warangal, Telangana
[180]
International Journal of
Community Medicine
and Public Health
September 2015
to November
2015
Cross
sectional
Exclusive
breast
feeding
120(200)
Kumar S et al ; 2018,
IGIMS, Patna, Bihar
[181]
International Journal of
Community Medicine
and Public Health
January 2017 to
June 2017
Cross
sectional
Exclusive
breast
feeding
140(400)
Meta analysis of studies with outcome as Exclusive breast feeding
Interpretation of Forest Plot
Study design: Cross sectional, Longitudinal study
Year of publication: 2008 to 2018
Total studies pooled: 26
Sample size: 61 to 1000
Pooled exclusive breastfeeding: 47% (CI: 0.39, 0.55)
Heterogeneity - 98% (very high because of sample size variability)
5.2.14 Studies with outcome as under 5 mortality rate (U5MR), N=9
Author
,Publication
year
Journal
Name
Study
period,
Place
Type of study Strategy/
Cause/Data
source
Results
Semba R. et al,
2009 [186]
The
Journal
of
Nutrition
2005-06,
India
Secondary data
analysis from
NFHS 2005-06
Vitamin A Proportion of U5 Mortality in
Vitamin A supplemented
children vs. Non
supplemented : 8.4%
vs.11.4%
Espie E et al,
2010 [183]
Journal
of
tropical
pediatrics
2008, Bihar
(Darbhanga
Distt)
Cross sectional
design
Survey U5MR: 0.53 deaths/10,000
persons/day
Global acute
malnutrition:19.4%
Kumar C et al,
2013 [185]
Journal
of Public
Health
1990-2008,
India
Secondary data
analysis
Sample
Registration
System (1990-
2008)
U5MR: Decline of 42% from
26/1000 in 1990 to 15/1000
in 2008
Average annual rate of
reduction:3.2%
Ram U et al,
2013 [115]
Lancet
Global
Health
2001-12,
India
Secondary data
analysis
National
demographic
and mortality
surveys[SRS(2
009-11),NFHS
3(2005-
06),DLHS2(200
2-
04),DLHS3(200
7-08)]
U5MR: Fell at a mean rate
of 3.7% per year between
2001-2012 , from 96/1000
live births to 57.3/1000 live
births.
Number of districts with >80
deaths/1000 live births also
reduced from 384 to 80
districts.
Farooqui H et al,
2015 [184]
PLOS
One
2010, India Modelling
based estimate
from
multicentric
hospital based
studies
Pneumonia All cause pneumonia deaths
occurred in children=0.35
million , Pneumococcal
deaths = 105 thousand (92–
119 thousand) Highest
deaths-UP, BH,MP, RJ,JH
Wang H et al,
2016 (Multi-
country study)
[187]
Lancet 2000-13,
India
Secondary
data analysis
Global burden
of
disease,injuries
,risk factor
study (GBD
2013)
Annualized rate of change
in child mortality from 2000
to 2013= -3.2 to -5.1 (-4.3)
in India
Dhirar N et al,
2018 [158]
Indian
Pediatric
s
2005-16,
India
Secondary
data analysis
Comparison of
NFHS 3 Data
with NFHS 4
U5MR: 74 to 50/1000live
births [ 48% decline]
Strategies: Increase in
intake of ORS: 26% to 50%,
Increase in immunization
coverage: 43.5% to 62%
,Reduction in prevalence of
stunting: 10%
Jha P et al,
2017 [180]
Lancet 2001-2015,
India
Secondary
data analysis
Combining the
proportion of
child death
from Million
Death survey
2001-13 with
annual US
estimates for
2000-15
Average annual decline
from 2000-15: 5.4%,Annual
decline from 2000-05: 4.5%
, Annual decline from 2005-
15: 5.9%, Decline was
faster during 2005-15.
Decline in mortality rate
from pneumonia: 63%,
Decline in diarrhea rate:
66%,Decline in measles
mortality rate: 3.3 to
0.3/1000 live births.
India avoided 1 million child
deaths.
Gothankar J. et
al, 2018 [188]
BMC
Public
Health
2015 (7
months),Ur
ban and
rural field
practice
area BVDU
in
Maharasthr
a
Cross
sectional
ARI U5MR: 3.81/1000 children
Proportionate death rate for
pneumonia: 21.42%
5.2.15 Studies included in forest plot with outcome as full immunization coverage, N=16
Author, year
of
publication
Journal Name Study period,
Place
Study
type
Intervention/
Strategy
Results
Total Number of
fully immunized
children [n,(N)]
Nath B et al,
2007 [194]
Indian journal of
medical sciences
2005(4
months),
Urban slums of
Lucknow
Coverage
survey
Immunization 244(510)
Mallika MC
et al, 2014
[193]
Journal of Evolution of
Medical and Dental
Sciences
2013-14,
Thiruvanantha
puram Distt,
Kerala
Cross
sectional
Immunization 189(210)
Devasenapa
thy N et al,
2016 [190]
BMJ Open 2014(4
months), Delhi
urban slums
Cross
sectional
Immunization 863(1849)
Gill N et al,
2016 [191]
International Journal
of Community
Medicine and Public
Health
2014(3
months),
Mankhurd
suburb,
Mumbai
Descriptiv
e study
Immunization 189(210)
Datta A et
al,
2017 [189]
Journal of Clinical and
Diagnostic Research
2013-14, Rural
field practice
area of
Agartala GMC
Cross
sectional
Immunization 304(303)
Srivastava A
et al,
2017 [195]
Indian Journal of
Forensic and
Community Medicine
2016(3months)
, Urban field
practice area
SNMC
Bagalkot,
Karnataka
Cross
sectional
Immunization 235(283)
Jain A et al,
2018 [172]
International Journal
for Scientific Research
and Development
2018(2
months), Rural
area of
Tikamgarh,MP
Descriptiv
e
research
Mission
Indradhanush
114(204)
Gothankar J
et al,2018
[188]
BMC Public Health 2015(7
months),
Urban and
rural field
practice area
BVDU in
Maharasthra
Cross
sectional
Immunization 605(639)
Kurane A et
al,
2018 [201]
International Journal
of Contemporary
Pediatrics
2015-17,
Pediatric ward
in DY Patil
hospital
Kolhapur,
Maharashtra
Hospital
based
study
Immunization 1303(2000)
Chavan G et
al, 2018
[196]
National Journal of
Community Medicine
2017,
Mahabubnagar
Distt of
Telangana
Cross
sectional
Immunization 101(122)
Mohapatra I
et al, 2018
[202]
Journal of Family
Medicine and Primary
Care
2017 (4
months),
Urban field
practice area
of KIMS
Bhubaneswar
Cross
sectional
Mission
Indradhanush
72(100)
Ganguly E
et al, 2018
[199]
INQUIRY: The Journal
of Health Care
2008-09,
Churu Distt
Rajasthan
Househol
d survey
REACH
strategy
4441(5007)
Cherian V et
al, 2019
[197]
International Journal
of Community
Medicine and Public
Health
2015-17,
Dallupura in
East Delhi
Cross
sectional
Immunization 301(350)
Joy T et al,
2019 [200]
Journal of Family
Medicine and Primary
Care
2017(3
months), Kochi
metropolitan
area of Kerala
Cross
sectional
Immunization 276(310)
Bhonsla S
et al, 2019
[203]
Indian journal of
community health
2017(12
months),Urban
and rural area
of Ambala
Cross
sectional
Immunization 349(420)
Francis M et
al, 2019
[198]
Elsevier Science
Direct
2017(2
months),Thimiri
rural block of
Distt Vellore
Cross
sectional
Mission
Indradhanush
509(606)
Other studies on immunization coverage not included in forest plot, N=6
Author
,publication
year
Journal
name
Study
period,
Place
Type of
study
Intervention/
strategy
Results
Carvalho N et
al, 2014 [6]
PLOS one 2007-08,
India(34
states and
UT)
Quasi
experimental
Effect of financial
assistance from
JSY on
immunization
(Use of DLHS 3
data)
Increase in 9.1 % points in
the proportion of fully
vaccinated children, 3-8%
point increase in coverage of
most vaccines,reduction of
3.2 % points in the
proportion of children who
had not received a single
vaccine.
Prinja S et al,
2017 [63]
Tropical
Medicine
and
International
Health
2015,
Kaushambi
Distt Uttar
Pradesh
Pre- and
post-quasi
experimental
design
ReMind(Reducing
maternal and
newborn deaths)
Full immunization increased
in the range of 30-40% from
2011 to 2015.Full
immunization in Intervention
group vs. control group(%):
Before matching
AHS 2011(n=124 vs.186) :
7.7 vs.7.1 ,CEAHH
2015(n=1418 vs.1473) : 49
vs.55.5
After matching(n=1219),
In AHS 2011= 44.40 vs.
46.50, CEAHH 2015= 47.20
vs. 55.70
Mathiarasu
A.M et al,
2017 [207]
International
Journal of
Public
health
Research
2012-13,
Kanyakumari
Distt
Tamilnadu
Cross-
sectional
Immunization Coverage of measles
vaccination (n=210):81.4%
with dropout of 18.6%.
Goel S et al,
2012 [205]
Indian Pediatrics 2009-10,
Bihar
Secondary data
analysis, comparison
of immunization
coverage before and
after launch of
Proportion of fully
immunized children in
2005-09: 19% to 49%
Muskaan Ek Abhiyaan
in Bihar with EAG
states.
Increase in BCG
Coverage from 2005-09:
52.8% to 82.3% , in
DPT-3 coverage: 36.5%
to 59.3%
Increase in OPV-3
coverage: 27.1% to
61.6% , in measles
vaccination coverage:
28.4% to 58.2%
Johri M et
al, 2016
[206]
Bull World Health
Organ
2009-13,India
(12 states)
Modelling of impact of
interventions , source
of mortality data:
million death study and
Indian household
survey
Under 5 lives saved by
measles vaccination in
12 states: 9346 (29% of
India’s Annual measles
mortality)
Lives saved by measles
vaccine with add-on
interventions=74367
Bawankule
R et al,
2017 [204]
PLOS one 2005-
2006,India
Secondary data
analysis from
Demographic Health
Survey
Coverage of measles
vaccination: 62%,
Prevalence of ARI in
measles vaccinated vs.
unvaccinated: 5.6 vs.
7.3, Measles
vaccination was
associated with a
reduction of 15% ARI
,12% diarrhoea
Meta analysis of studies on full immunization coverage
Interpretation of forest plot
Study design: Cross sectional
Year of publication: 2007 to 2019
Total studies pooled: 15
Sample size:100 to 5007
Pooled Full Immunization coverage: 77% (CI: 0.69, 0.85)
Heterogeneity:99% (very high because of sample size variability)
5.2.16 Studies with focus on Vitamin A Strategy (n=4)
Author,
Year of
Publicatio
n
Journal
Name
Study type Study
Period
Interventio
n/Strategy
Results
Semba R
et al, 2009
[186]
The
Journal
of
Nutrition
Secondary
data analysis
from NFHS 3
2005-
06,India
Vitamin A Out of total 23008
children,4459(20.2%)receive
d Vitamin A within last 6
months
Characteristics of children
who received Vitamin A vs.
who did not received
supplementation:-Severe
underweight=16.7%vs.22.1%
(p<0.0001)
-Severe wasting=6.7% vs.
7.6 %,Severe stunting
=24.6% vs. 32.2%(p<0.0001)
Agarwal S,
2013 [223]
Int J Med
Public
Health
Secondary
data analysis
from NFHS 3
2005-
06,India
Vitamin A n=20802
Only 25%(20802 of the
children in India received
vitamin A supplementation,
Rural children(71.8) and
children of educated mothers
were more likely to receive
vitamin A supplementation
than others(urban-
28.2%).one-third of the
children aged 12-23
months(61.2%) received
vitamin A supplementation
as compared with only one-
fifth of the children aged 24-
35 months(38.8%).
Kapil U et
al,
2013 [225]
Public
Health
Nutrition
Prospective
cohort study
2011-
12,Uttar
Pradesh
Vitamin A n=262
Resolution of Bitot spots
after Mega Dose Vitamin A
supplementation-
At 6 months of follow
up:51.1% (134)cured , At 1
year : 59.9%(157) cured
Aguayo V
et al
2014 [224]
Public
Health
Nutrition
Secondary
data analysis
from DLHS
2006-2011,7
states
(Bihar,Chhat
tisgarh,Jhar
khand,Madh
ya Pradesh,
Odisha,
Rajasthan,
UP)
Vitamin A Increase in the mean full
VAS coverage in seven
states from 44.7% to 67.3%
Annually decrease in
number of poor children who
did not receive two VAS
doses-40.3%
5.2.17 Studies with outcome as ARI and Diarrhoea, N=9
Author, Publication
year
Journal Name Study period Type of
study
Results
Prajapati B et al, 2011
[376]
National
Journal of
community
medicine
2008-09,
urban and
rural areas of
Ahmedabad
Cross
sectional
study
n=500
Prevalence of ARI in last 1 month :
22%, prevalence in urban area:
17.2% and in rural are: 26.8%,
It was higher in low social class:
26.56%, in Illiterate mothers:24.4%,
Overcrowded houses: 28.5%.
Goel K , 2012 [377] Journal of
Community
medicine and
Health
Education
2011-12,
Urban and
rural areas of
Meerut
Cross
sectional
study
n=450
Prevalence of ARI: 52%, mean
number of episodes of ARI -2.25 per
child per year, It was higher in severe
malnourished children: 26.49% than
less malnourished: 09.82 %.
Mathew M et al, 2013
[378]
Indian
pediatrics
2009-11,
Ernakulam
Distt Kerala
cross-
sectional
n=1827
Overall prevalence of Rotavirus
diarrhoea: 35.9%(648) ;prevalence of
rotavirus diarrhea in children of 12- 23
months : 41.9%;
24- 35 months: 46.9% and 36- 59
months:33.3% in, Death:0
Kumar G et al, 2015
[379]
Journal of
Natural
Science,
Biology and
Medicine
2013-14,
Kerala
cross-
sectional
n=509
Overall prevalence of ARI:
59.1%(301),prevalence in urban
areas: 63.7% and rural areas: 53.7%
Prevalence of ARI in 13-24 months
age group: 52.6% , in 25-60 months
age group: 59.5%.
Gupta A ,2015 et al
[380]
Journal of
Global
Infectious
Diseases
1 month,
West Bengal
cross-
sectional
n=152
Overall prevalence of
diarrhea:22.36%(34); prevalence of
diarrhea was 21.83% in completely
immunized children and 30% in
partially immunized children.
Author, Publication
year
Journal Name Study period,
Place
Type of study Results
Farooqui H et al,
2015 [184]
PLOS One 2010,India Secondary
data
anlaysis,Data
from DLHS-3
Incidence rate of severe pneumonia -
30.7/1000 children /year,
Lower incidence :Southern
state(Kerala, Tamil Nadu),North
eastern states
annual incidence of severe
pneumococcal pneumonia-4.8
episodes/1000 children
Highest in Jharkhand(7.9) ,lowest in
Manipur(1.1)
Ramani V et al,2016
[381]
Journal of
Clinical and
Diagnostic
Research
2006-07,
Karnataka
longitudinal
cohort
n=400
Overall incidence rate of ARI :
27.25%(109),Incidence of URTI and
LRTI:19.25% and 8% respectively.
Incidence of ARI in Type IV and Type
V grade malnutrition: 53.85% and
66.67% respectively.
Kumar B et al,2017
[382]
International
journal of
contemporary
medical
research
Andhra
Pradesh
Longitudinal
study
n=650
The ARI incidence: 3.33
episodes/child/year, it was declined
with increasing age , maximum in the
first year (2.66 episodes/ child/year)
,minimum in 20 -24 months (1.59
episodes/child/year) of life
Gothankar J et al,
2018 [188]
BMC Public
Health
2015(7
months),
Maharasthra
Cross
sectional
n=3569
Incidence of ARI in last one month:
0.49/child/month; in rural: 0.53,urban:
0.43;P= 0.05 [6 episodes of ARI in
one year], reported incidence of
pneumonia in last one
year:0.075/child/year
(281/3569)[Rural: 0.13(146),Urban:
0.07(135)]
N=605 ;Cases of pneumonia in Full
immunized vs. non immunized
children :64 vs 541 (p < 0.05)
Other Studies
Author,
Publication
year
Journal
Name
Study
Period
Study type Data
source/Intervention
Results
Reduction in geographical and socioeconomic inequalities post NRHM period
Gupta M et
al, 2016 [61]
PLOS
One
2002-13,
Haryana
Secondary
data
analysis
DLHS before(2002-
04),during(2007-
08),after(2012-13)
the NRHM
Implementation
The geographical
and socioeconomic
differences between
urban and rural
areas, between rich
and poor were
significantly
(p<0.05) reduced for
children with full
vaccination :10% to
3.5%, 48.3% to 14%
and who received
oral rehydration
solution(ORS) for
diarrhea:11% to -
2.2%; 41% to 5%.
Inequalities between
male and female
children were
significantly
(p<0.05) reversed
for full immunization
from 5.7% to -0.6%.
Role of Frontline workers in improving child health
Gupta M et
al, 2017 [80]
BMC
Public
Health
2002-13,
Haryana
Secondary
data
analysis
Demographic Health
Survey post(2012-
13),during(2007-
08),pre(2002-04)
NRHM
implementation
Full extent of
implementation for
immunization by
NRHM was found,
Accredited social
health activists act
as an catalyst in
acceptance of
immunization.
Vir S et al,
2014 [354]
Food
and
Nutrition
Bulletin
2011,Rural
Chhattisgarh
Quasi-
experimental
mixed
methods
Mitanin Programme Nutritional status of
children up to
35mo[Project
Group(n = 1,775) vs.
Control Group(n =
1,749)]
Severely
underweight:13.8
vs.15.6 ,Severely
wasted :11.1 vs. 15.3
Annual average
reduction rates
(AARRs) for
underweight ,
stunting and wasting
-
In 1998-2005 :1.45%
, 1.93% and 0.4%
In 2005-2011: 4.22%,
5.64% and 3.53%
5.2.18 Studies with focus on RBSK, N=3
Author, Year
of Publication
Journal
Name
Study
Period
Study Type Intervention/
Strategy
Results
Singh P et al,
2011 [383]
National
Journal of
Community
Medicine
January
2011-June
2011, Surat
Retrospectiv
e analysis
School
health
program
Total number of
patients screened
=24 children
Incidence of heart
diseases=14 children
Tiwari J et al,
2015 [227]
Internationa
l Journal of
Community
Medicine
and Public
Health
6 months
(August
2014-
Januray201
5),
Panna Distt
Madhya
Pradesh
Cross
sectional
survey
RBSK Number of children
screened for birth
defects,
deficiency,
developmental delays
and other
diseases=26977
Balat M et al,
2018 [226]
Internationa
l Journal of
Community
Medicine
and Public
Health
June -
October
2016,
Ahmedabad
Cross
sectional
study
RBSK Number of
beneficiaries under
RBSK=169
Children diagnosed
for heart
diseases=47.9%,
Number of children
operated
=53%,Children given
drug therapy=31.95%
5.2.19 Studies included in forest plot with outcome as recovered children under nutritional
rehabilitation centers, N=15
Author
,Publication year
Journal Name Study period,
Place
Type of study Intervention Results
Number of
recovered
children,[n,(N)]
Taneja G et
al,2012 [211]
Indian Journal of
Community
Medicine
2008-09, Indore
and Ujjain
division Madhya
Pradesh
Prospective
study
NRC 42(100)
Maurya M et
al,2014 [209]
Indian Pediatrics 2011(12
months),
Allahabad Uttar
Pradesh
Retrospective
analysis
NRC 110(162)
Singh K et
al,2014 [222]
Indian Pediatrics 2010-11, Uttar
Pradesh(12
NRCs)
Secondary
data analysis
NRC 286(1181)
Sanghvi J et
al,2014 [210]
ISRN Pediatrics 2011-12,
SAIMS hospital
Indore
Prospective
study
NRC 128(300)
Aprameya HS et
al ,2015 [208]
International
Journal of Health &
Allied Sciences
2013-14,
Wenlock Distt
Hospital
Mangalore
Prospective
study
NRC 38(91)
Rawat R et
al,2015 [216]
Journal of
Evolution of
Medical and Dental
Sciences
2014(6 months),
Bhopal
Observational
study
NRC 68(102)
Ningadalli S et
al,2015 [214]
International
Journal of Science
and Research
2013(10
months),
Belgaum Distt
Karnataka
longitudinal
study
NRC 24(30)
Rao B et al, 2015
[215]
Journal of
Evidence Based
Medical Healthcare
2013,
Visakhapatnam
Andhra Pradesh
Retrospective
analysis
NRC 43(63)
Tariq S et al,
2015 [212]
International
Journal of
Contemporary
Pediatrics
2014-15,
GMC Srinagar
Prospective
study
NRC 110(146)
Mathur A et al,
2016 [213]
International
Journal of
Contemporary
Pediatrics
2012-14, HRH
hospital Delhi
Not
mentioned
NRC 250(327)
Golandaj J et al,
2016 [217]
Nutrition and Food
Science
Jan -Dec 2014,
4 Distt of
Northern
Karnataka
Cross
sectional
study
NRC 94(722)
Kumar N et al,
2016 [218]
Journal of
Evolution of
Medical Dental
Sciences
2014-15,
Ananthapuramu
Andhra Pradesh
Prospective
study
NRC 103(195)
Dhanalakshmi
K.et al ,2017
[221]
International
Journal of
Contemporary
Pediatrics
2014-15,
Bangalore
Retrospective
study
NRC 599(736)
Shekhar C et al,
2018 [220]
International
Journal of
Community
Medicine and
Public Health
2013(10
months), Urban
Kurnool area
Andhra Pradesh
Cross
sectional
NRC 37(52)
Chaturvedi A et
al, 2018 [219]
Nutrition Journal 2011-12,
Jharkhand 48
MTCs
Prospective
study
Malnutrition
treatment
center
26(116)
Figure: Meta analysis of studies with outcome as recovered children under NRC
Interpretation of forest plot
Study design: Cross sectional, Prospective study, Retrospective study
Year of publication: 2012 to 2018
Total studies pooled: 15
Sample size: 30 to 1181
Pooled Recovered Children under NRC: 55 %( CI: 0.39, 0.70)
Heterogeneity: 99% (very high because of sample size variability)
5.3 REPRODUCTIVE HEALTH
5.3.1 Results of studies with TFR as an outcome (N=9)
Author, year
of publication
Study period Outcome Proportion
Mohanty et al,
2013 [384]
1991-2011
(respective
rounds of DLHS,
Census and
NSS data)
TFR
The variance of TFR in districts of India has increased from 0.87 in
1991 to 0.91 in 2001 and declined to 0.71 by 2011.
Prasad et al,
2013 [254]
2001-2011 TFR
TFR declined from 3.81 to 2.58 after the implementation of NRHM
in India
Barman,
2013 [251]
NFHS 3 report
and SRS 2007-
08
Unmet
Need,
TFR
TFR is maximum in EAG states (2.6 to 4.0).EAG states unmet need
33.1, South Indian States -27.7 and rest of Indian states 27.2, MMR
EAG states 308, South Indian states 127, Rest Indian states 149.
Mohanty et al,
2014 [253]
2000-2011 TFR TFR declined from 3.87 in 1991 to 2.66 in 2011
Sebastian et
al, 2014 [252]
2000-2010 (SRS
reports)
TFR
TFR in Bihar declined from 4.5 to 3.6 in 2011, Odisha 2.8 to 2.2 and
MP 4 to 3.1 compared to national decline from 3.2 to 2.4 in 2011.
Chhetri et al,
2016 [255]
Post
NRHM(2005-
2014)
TFR has declined from 2.6 in 2006 to 2.4 in 2011. Rural TFR has
declined from 3.1 to 2.7 and urban has declined from 2.0 to 1.9 in
this period.
Bansod et al,
2016 [256]
NFHS 4
Most of the Indian states have achieved replacement level fertility of
2.1 except Bihar-3.4, Meghalaya 3.0, Manipur 2.6 and MP 2.3. CPR
(any method) varies from 24% in Manipur to 71% in West Bengal.
CPR (modern method) 13 % in Manipur to 69% in Andhra Pradesh.
Khan et al,
2017 [257]
1991-2011
Before NRHM TFR was 3.81 and after NRHM TFR 2.58 so mean
difference is 0.6
Narwal et,
2017 [258]
2007-2015 (Pre
and post
evaluation of
NRHM)
TFR declined from 2.9 in 2005 to 2.4 in 2011. TFR declined by 10.3
% in 2001-06 compared with 14.3% in 2006-11.
5.3.2 Studies included in forest plot with outcome as CPR (n=22)
Takkar et al,
2005 [270]
2005 81 % women were practicing contraception and 73% of them were regular users.
Only 11% participants were aware of emergency contraceptive measures.
S. K.
Bhattacharya,
2006 [269]
2006 proportion of women using contraception was 45%, 41.6% was the unmet need,
major reason of high unmet need was opposition of family/husband.
Gupta et al, 2007
[259]
2007 contraceptive practices in slums were significantly low as compared to urban and
rural areas in Chandigarh (53.4% vs 73% vs 75%).
Kumar et al,
2010 [263]
2010 Contraception usage: 52%. Most common age group was 23-27 years. Mean age of
first delivery was 20 years. 62% of the non-contraceptive users were illiterate and
usage increases with increase in education. 505 have the knowledge of male
sterilization but they believe it will weaken the male. None had the correct
knowledge of emergency contraception.
Makade et al,
2012 [264]
2012 234/342 (68.42%) participants were using any one contraceptive method
Speizer et al,
2012 [265]
2012 All the districts report about 50% of modern contraaceptive use. Across all districts
higher unmet need was found in slum population.
Prateek et al,
2012 [266]
2012 Participants having knowledge of contraception 52.2%, Participants using
contraception 32.2%,
Das et al, 2012
[120]
2012 65.3 % contraceptive acceptance rate, OCP and female sterilization are most
common methods used
Lakshmi et al,
2013 [308]
2013 Awareness 95%, Acceptance 87%, Followed contraception 71%, Users 52%
Bhattacharjee et
al, 2013 [268]
2013 89.5% women had the knowledge of contracetive measures, OCP knowledge
(84%), only 35% women were using contraception. Religion, age, literacy and
number of living children were associated with contraceptive usage.
Singh et al, 2009
[273]
2009 75.3 % were contraceptive users. Religion was found to be significantly associated
with contraceptive use. Unmet need for contraception was more than 33% and
unmet need for spacing was 23.5%.
Murarkat et al,
2011 [271]
2011
249(48.63%) women were contraceptive acceptors
Mahawar et al,
2011 [274]
2011 a) 18% KAP Gap was found in total subjects. Maximum KAP Gap was found in the
19-21 year age group.
b) 98% of the subjects had the knowledge,
Mody et al, 2014
[275]
2014
65.3% women were not using any contraeption. Among the women who were
using contraception condom was the most common choice (77.8%)
Parameaswari et
al, 2014 [272]
2014
CPR was 67.1%. Unmet need 23.1
Bhutia, 2015
[276]
2015
TFR is 2.0 as compared to national 2.8, Knowledge and awareness about
contraceptive methods is 99.1 %, contraceptive usage is 50%.
Ambure et al,
2015 [277]
2015
50% women were using contraceptives. contraception was more among Hindus
and christians then muslims. Although women having full PNC were proportionally
higher in using contraceptives but staistically no association was found
Hiralal Nayak,
2016 [278]
2016
98% of women were aware of a family planning method, 64% were using any
method of contraception
Kanika et al,
2017 [279]
2017
90% clients were adequately utilizing the family planning services under NRHM
and 100% satisfaction was there.
Smith et al, 2017
[280]
2017
Awareness about contraception- 93.1%, most common purpose of using
contraception- maternal health benefits (65.5%) and birth spacing (60%),
counselling regarding postpartum contraception (24%), postpartum contraception
usage-48.3%
Trigun et al, 2017
[281]
2017
Contraceptive usage 51.1%
Singh et al,2019
[385]
2019
contraceptive usage was 19.7%
Meta Analysis of studies on CPR
Interpretation of Forest Plot
Study design: Cross sectional
Year of publication: 2007 to 2017
Total studies pooled: 22
Sample size: 50 to 17643
Pooled CPR: 54% (CI: 0.49, 0.59)
Heterogeneity - 98% (very high because of sample size variability)
5.3.3 Studies with secondary data analysis where CPR is an outcome
Author &
year of
Publication
Source of data Outcome focused Results
Prusty et al &
2014 [386]
DLHS-RCH III:2007-
08
(3 states with tribal
population:
Jharkhand, MP and
Chhattisgarh)
Contraceptive
Prevalence Rate
CPR: Jharkhand tribal 22.8, Non tribe 41.8,
Chhattisgarh: Tribal 43.5, non tribal 56.2,
MP: tribal 50.2 and non tribal 60.2
Sankariah et
al & 2015
[387]
Data from DLHS 3
and NFHS 4
Modern family
planning methods use
mCPR 47.5 (DLHS3) and 45.4 (NFHS 4)
mean difference -2.1 (95% CI -3.2,-1.1)
Cahill et al &
2018 [388]
Family planning
estimation tool
(FPET) used in 68
countries (2012-
2017)
estimates and
projections of the
modern contraceptive
prevalence rate,
unmet need for and
demand satisfied with
modern methods of
contraception
In Asian countries the m CPR growth has
been less than 1% since 2012
Unpublished
presented in
Bhopal
DLHS survey report Contraceptive use Use of Contraception is more in the age
group of 30-34, 35-39 and 40-44 i.e. 51-68%.
The contraception use was found to be very
low in the age group of 20-24 i.e. 28%
Unpublished
presented in
Bhopal
NFHS 3 - NFHS 4
survey report
Gender gap in
contraceptive use
Unmet need for family planning marginally
decreased from 14 (2005-06) to 13% (2015-
16), MCPR highest in HP (75%) and lowest in
Bihar (34%), MCPr is around 60% in 20% of
the districts. Female family planning method
usage (87.6%) and male FP method (12.6%)
5.3.4 Results of studies with ASHA as an intervention (N=4)
Author, year of
publication
Objective/Intervention Results and recommendations
Nimavat et al,
2013 [260]
To find out effects of new ASHA
incentive scheme under NRHM on
the performance of ASHA in
motivating couples to undergo
permanent sterilization method
ASHAs performance was increased; 1.13 times for
eligible couples and 1.14 times for couples having
two or less children after introduction of an
incentive, and incentive showed a significant impact
on motivation of eligible couples
Fotso et al, 2015
[262]
Engaging male CHWs to
complement the work of ASHAs
the engagement of male counterparts have
improved the performance of ASHA program
(statistically non significant), and unveils the
complementarity of male and female CHWs in
increased demand for MNCH services.
Karol, 2014 [122] Checking knowledge of ASHA
workers
ASHA's capacity is low in motivating family
planning cases for restricting high fertility in rural
areas (30.49%)
Bajpai et al, 2009
[261]
ASHA, Pregnancy Tracking system More than 90% ASHA workers interviewed
informed that they are involved in promoting
contraceptive usage and family planning measures
and all other services, go training about doses and
side effects of OCPs, 77% ASHAs help ANM and
AWW in preparation of list of eligible couples,
Tracking of married couples and pregnant women
for family planning counselling became easy.
5.4 ADOLESCENT HEALTH
5.4.1 Studies included in forest plot with outcome as prevalence of Anemia
Author, year of
publication
Study period Impact Results
Vir et al 2008 [282]
(Cross sectional)
Sept 2001 to
Dec 2006
Reduction in
anaemia
overall prevalence of anaemia reduced from 73.3%
to 25.4%
Dongre et al 2011
(Cross sectional)
[364]
March to July
2008
Reduction in
nutritional
anaemia
Among adolescent girls, the prevalence of anemia
declined significantly from 73.8% at baseline to
54.6% at endline (p < .001). The median
hemoglobin level increased from 10 to 11 g/dL.
There were significant declines in the prevalence of
moderate anemia (p = .003) and severe anemia (p
= .002)
Vani et al 2015
(Cross sectional)
[284]
Jan to Dec 2004 Prevalence of
Anaemia
78.3% adolescent girls had anaemia, only 11%girls
had the knowledge about anaemia
Shah et al 2016
(Cross sectional)
[285]
April to June
2013
Reduction in
anaemia
anaemia in girl reduced from 79.5 % to 58% and in
boys it declined from 64%to 9%.
Diwakar et al 2017
(Cross sectional)
[286]
Not mentioned Decline in
anaemia
BMI does not improved much, No severe anaemia
found
Meta-analysis of 5 cross sectional studies on WIFS
5.4.2Studies included in forest plot with outcome as mean change in Hb levels
Author, year of
publication
Study period Impact Results
Sen et al 2007
[288]
Not mentioned Change in mean Hb
levels post intervention
(IFA daily vs IFA once
weekly vs IFA twice
weekly vs No IFA
Highest change was found in IFA
daily group (1.9g/dL) followed by IFA
twice weekly group (1.6 g/dL)
Bhoite et al 2012
[287]
Not mentioned IFA once weekly +
deworming vs
Deworming only
IFA + deworming showed 17.3%
increase in Hb levels as compared
to deworming only
Joshi et al 2013
[289]
June 2011 to
October 2012
IFA daily vs IFA weekly Mean rise in Hb was almost equal
IFA daily (1.0+0.7 g/dL vs 1.0+0.8
g/dL)
Bansal et al 2016
[290]
January 2012 to
March 2013
IFA + cynocobalamin vs
IFA
Mean increase in similar in both the
groups i.e. 108.9 ± 8.91 g/l and
106.7 ± 11.2 g/l respectively
Results of RCTs on WIFS (N=4)
5. 4.3 Studies included in forest plot with outcome as awareness about AFHCs
5.4.4. Studies included in forest plot with outcome as awareness about Menstrual Hygiene
Author, year of
publication
Study period Impact Results
Prateek et al 2011 [266]
Sept 2010 to Novemeber
2010
knowledge, attitude, and
practices regarding
menstruation and
menstrual hygiene
among adolescent girls in
rural areas.
49 (20.3%) have
awareness about
menstruation before
menarche
Author, year of
publication
Study period Impact Results
Kotecha et al, 2009
[312]
not mentioned readiness to use AFCs if
available
70% participants were ready to use the clinics
Nair et al, 2011 [313] not mentioned attitude of parents and
teachers towards imparting
RSH education to
adolescents
8 (1.1%) parents and 6 teachers discussed the
sexual health related issues with adolescents
Ray et al 2012 [310]
3 months
issues and challenges of
menstruation faced by
adolescents
Presence of Pre-
menarchial Knowledge
Regarding Menstruation
80(42%)
Nair et al, 2012
[389]
not mentioned gain in knowledge about
RSH
Among girls, percentage of poor knowledge had
reduced significantly from 64.1% to 8.3% and
among boys from 37.7% to 3.5%. less than 20% of
boys (17.7% 9th and 16.5% 11th standard) and
less than 10% of girls (5.1% 9th and 1.2% 11
th
standard) knew about symptoms of STDs before
intervention. increase in knowledge was observed
after intervention
Nair et al, 2013 [314] Two years Knowledge about Menstrual
hygiene practices,
knowledge attitude and
practices of 10-20 age group
regarding RSH issues
56% adolescents know the age of menarche
Nair et al, 2013 [315] Two years Knowledge about
contraceptive measures,
ideal age of pregnancy and
other RSH indicators
92% boys had knowledge about condoms as
compared to 56% girls having knowledge about
cu-T.
Mehra et al, 2013
[319]
Jan to April
2012
knowledge and utilization of
ARSH clinics
595 (78%) were aware of ARSH clinics, 61%
adolescents visited ARSh clinics
Chauhan et al, 2015
[316]
Feb 2014-Aug
2014
awareness and utilization of
AFHCs, barriers in utilization
14.1% were aware, 38.67% out of them visited,
major reason of non untilization was
shynessamong 54.35% girls
Shah et al 2013 [298]
Jan-July 2011
awareness about
menstrual hygiene
practices
65 out of 164 were aware
of menses before its
onset, 59 subjects knew
about sanitary pads, at
baseline 90% girls were
using old cloths but at the
end of the study 68%
chose fatalin cloths as
first choice and 32%
chose sanitary pads.
Paul et al 2014 [296]
2012
knowledge, attitude and
practices during
menstruation among the
adolescent school girls
363 (72.6%) adolescent
girls were aware about
menstrualtion till its onset
in 2012 as compared to
147 (29.4%) in 2007, use
of sanitary napkins also
increased from 23.8% to
74% from 2007 to 2012
Paria et al 2014 [295]
April 2013 - September
2013
knowledge, attitude and
practices during
menstruation among the
adolescent school girls
Awareness about
menstrual hygiene- 203
(37.52 %), Use of
sanitary pads was more
in urban girls as
compared t0 rural girls
(176 vs 120), Cleaning of
genetilia was satisfactory
Gupta et al, 2015
[363]
Feb to april
2011
Knowledge about ARSH and
access to the ARSH clinics
76% were aware of balanced diet, 17% were
aware of RTI/STI, utilization of ARSh was 7.4%
only
Kamath et al, 2015
[317]
Aug2012 to Jan
2015
Knowledge about
reproductive health
Only 8 (11%) boys were aware ARSH services
Mahalakshmy et al,
2018 [318]
Not mentioned awareness and utilization of
AFHCs
50% were aware, 2-10% utilized the services
in 47% urban and 38% in
rural girls
Ramchandra et al 2016
[301]
not mentioned
impact of menstrual
hygiene program under
NRHM on knowledge
and awareness on
menstrual hygiene
among adolescents
83 (34%) participants
were aware about
menstruation and 69%
were using sanitary
napkins
Nagaraj 2016 [390]
not mentioned
awareness about
menarche, items used for
menstruation, factors
associated with school
absence during
menstruation
awareness before
menarche 91 (29.93%),
after health education
campaign awareness
about cause of
mensturation increased
from 34% to 80%, the
awareness about source
of discharge increased
from 37.5% to 50.3%.
Vijaykeerthi et al 2016
[391]
Jan to Aug 2016
awareness about
menarche, items used for
menstruation
Awareness about
menstrual hygiene-
45.7%
Dudeja et al 2016 [293]
Jan-16
Knowledge about
menstruation hygiene
119 (56.4%) were aware
about menarche before
its onset, 191 (90%) use
sanitary pads, 88% use
dustbin for disposal
Kansal et al 2016 [294]
January to June 2011
Knowledge about
menstruation hygiene
174 (29.4%) were aware
about menarche before
its onset, source of
information was sister,
183 (31%) were using
sanitary pads and 69%
were using cloths, those
who were following
hygienic practices less
no. of RTIs were there as
compared to those who
wer not following (5 vs
27)
Syed 2017 [392]
not mentioned
Knowledge about
menstruation hygiene
67.5% participants were
aware about
menstruation before
intervention as compared
to 80% postintervention,
57% of subjects stated
hat shout for help in case
of any appropriate touch.
Deshpande et al 2018
[304]
June to August 2017
Knowledge about
menstruation hygiene
only 24% girls had the
knowledge of menarche
prior to menstruation,
60% of girls used
sanitary pads
Sivakami et al 2019 [311]
2015
knowledge about
menstrual hygiene
40% girls were aware of
menstruation before its
onset and 48% were
aware at the time of 1st
period. Parents were the
major source (68%), 87%
girls reported going to
school during
menstruation, 45% of the
girls reported
concentration problems
at school during
menstruation
Chaudhary & Gupta 2019
[305]
April to July 2018
knowledge about
menstrual hygiene and
HIV
Awareness about
menstruation was more
among urban girls (159,
67.7%) as compared to
rural girls (127, 59%),
usage of sanitary pads
was more in urban areas
(132, 56.2%) than rural
area (63, 29.3%),
awareness about
subsidized sanitary pads
was 30% in urban and
13% in rural girls.
Mamilla et al 2019 [306]
not mentioned
knowledge about
menstrual hygiene
75 (60%) were ware
about menstruation,
mother was the major
source, 84% used
sanitary pads, 85 % used
dustbin for disposal of
absorbent, 47% used
soap and water for
cleaning genitals, 50%
did not know about any
contraceptive method
Studies included in forest plot with outcome as usage of sanitary napkins, n=16
Author, year of
publication
Study period Impact Results
Thakre et al 2012 [299] Jan to March 2011 awareness about
menstrual hygiene
practices
191(49.3%)used
sanitary pads, more in
urban as compared to
rural, washing of
genetalia was
satisfactory with 34% of
participants
Shah et al 2013 [298] Jan-July 2011 awareness about
menstrual hygiene
practices
65 out of 164 were
aware of menses before
its onset, 59 subjects
knew about sanitary
pads, at baseline 90%
girls were using old
cloths but at the end of
the study 68% chose
fatalin cloths as first
choice and 32% chose
sanitary pads.
Paul et al 2014 [296] 2012 knowledge, attitude and
practices during
menstruation among the
adolescent school girls
363 (72.6%) adolescent
girls were aware about
menstruation till its onset
in 2012 as compared to
147 (29.4%) in 2007,
use of sanitary napkins
also increased from
23.8% to 74% from 2007
to 2012
Paria et al 2014 [295] April 2013 - September
2013
knowledge, attitude and
practices during
menstruation among the
adolescent school girls
Awareness about
menstrual hygiene- 203
(37.52 %), Use of
sanitary pads was more
in urban girls as
compared t0 rural girls
(176 vs 120), Cleaning
of genetilia was
satisfactory in 47%
urban and 38% in rural
girls
Rana et al 2015 [297] not mentioned knowledge, attitude and
practices during
menstruation among the
adolescent school girls
156 (39%) were using
sanitary pads, 208
(54.7%) use only water
to clean genitals
Udayar et al 2016 [178] April to Sept 2015 prevalence of
unhygienic practices in
the study area
230 (78.5%) were using
sanitary pads. 108
(37%) were changing
the absorbent twice a
day, 243 (82.9%) are
using only water for
cleaning external
genitalia
Vijayshree et al 2016
[393]
1st to 15th October 2013 awareness about gender
equity, abuse, violence
60% of the subjects
were scared when they
attained menarche, 78%
subjects used sanitary
napkins, 64% dispose
the used napkin in
dustbin, 87% wash their
hands after changing the
pads
Dudeja et al [293] Jan-16 Knowledge about
menstruation hygiene
119 (56.4%) were aware
about menarche before
its onset, 191 (90%) use
sanitary pads, 88% use
dustbin for disposal
Kansal et al 2016 [294] January to June 2011 Knowledge about
menstruation hygiene
174 (29.4%) were aware
about menarche before
its onset, source of
information was sister,
183 (31%) were using
sanitary pads and 69%
were using cloths, those
who were following
hygienic practices less
no. of RTIs were there
as compared to those
who wer not following (5
vs 27)
Agarwal et al 2017 [394] Feb-16 Knowledge about
menstruation hygiene
usage of sanitary
napkins was 37 (14%),
sanitary pads and cloths
91 (36%), the frequency
of change was once in a
day 129 (51.6%)
Ramchandra et al 2016
[301]
not mentioned impact of menstrual
hygiene program under
NRHM on knowledge
and awareness on
menstrual hygiene
among adolescents
83 (34%) participants
were aware about
menstruation and 69%
were using sanitary
napkins
Jain et al 2017 [302] May-16 Knowledge about
menstruation hygiene
222 (78%) subjects used
sanitary pads during
menstruation while
washed clothes were
used by 19%, mother is
the main source of
information followed by
peer group
Krishnaleela 2018 [303] not mentioned knowledge and source
of info about
menstruation and its
perceptions and
practices
Dysmenoorhea was
present in 90% of the
participants, 55% used
sanitary napkins, 15%
were aware of frequency
of change in sanitary
napkins, only 3% were
aware about nutritional
status with menstrual
irregularities
Deshpande et al 2018
[304]
June to August 2017 Knowledge about
menstruation hygiene
only 24% girls had the
knowledge of menarche
prior to menstruation,
60% of girls used
sanitary pads
Chaudhary & Gupta
2019 [305]
April to July 2018 knowledge about
menstrual hygiene and
HIV
Awareness about
menstruation was more
among urban girls (159,
67.7%) as compared to
rural girls (127, 59%),
usage of sanitary pads
was more in urban areas
(132, 56.2%) than rural
area (63, 29.3%),
awareness about
subsidized sanitary pads
was 30% in urban and
13% in rural girls.
Mamilla 2019 [306]
not mentioned knowledge about
menstrual hygiene
75 (60%) were ware
about menstruation,
mother was the major
source, 84% used
sanitary pads, 85 %
used dustbin for
disposal of absorbent,
47% used soap and
water for cleaning
genitals, 50% did not
know about any
contraceptive method
Kumar et al 2011 Not mentioned menstrual pattern and
menstrual hygiene
practices
41.2% in residential area
and 45.5% in slum area
- aware of menarche
before its onset, girls in
residential areas use
sanitary napkins girls in
the slum areas who use
cloth.
Social restrictions 4% in
residential area and
more than 45% in slums.
Bhudagaonkar 2014
[307]
Not mentioned awareness generation
about menstrual hygiene
practices
Knowledge about
staining of clothes
increase from 48% to
85%, absorbent can
provide media for
organism growth
increase from 41% to
94% and that it may
spread infection
increase from 31% to
70%
Patel et al 2016 [308] Baseline in 2013-14 and
intervention in 2016-17
Knowledge about
menstruation hygiene,
anaemia, reproductive
and sexual health,
program awareness and
utilization
Awareness about
nutritional status
including anemia-
increased in 15-18 years
age group and
decreased in 11-14
years age group,
menstrual hygiene
practice- there is
increase in the use of
sanitary napkins in
intervention as well as
control block (4.6% and
7% respectively).
awareness about
programs- increase in
the awareness and
compliance to WIFS,
poor knowledge and
access to AFHC was
reported.
5.5 Studies on RCH Inequalities
Author Journal name Study area Study
Type
Interven
tion
Results
Gupta M et al,
2017 [5]
PLOS one Ambala and
Mewat
Districts of
Haryana
Qualitative
study
NRHM
(MCH
plans)
Geographic inequalities reduction-
Increased utilization of MCH services
like ANC, institutional deliveries and
reduction in maternal and child death
gaps in urban and rural parts.
Socioeconomic inequalities between
rich and poor decreased to some
extent because of availability of free
ambulances, medicines, and diet
during hospital stay for the poor.
However, it was reported that food
security in general would reduce this.
Gender Inequality between girls and
boys- Small size of the families and
increased educational status
reported to have led to the changes
in gender inequality; Gender
inequality was less seen in Mewat
district
Randive B, et
al 2014 [73]
ELSEVIER,
Social Science
and Medicine
9 low
performing
states: RJ,
MP, CG, BR,
JH, UP, UK,
OR and AS.
Secondar
y analysis
of data
(DLHS3)
JSY Reduced inequalities in institutional
deliveries during the JSY program,
maternal mortality decline was
slower in the poorest areas
compared to richest ones. Absolute
increase in proportion of institutional
deliveries during JSY program was
about similar across all
socioeconomic groups, differential
rate of relative increase (i.e. from
16% to 45% in poorest district
quintile vs from 40% to 69%
in richest ones).
Degree of inequality in male literacy
contribute to 30% of inequality in
institutional delivery. Relative
increase in institutional delivery=
29% increase in poorest districts also
in richest district.
Jain R et al,
2016 [320]
India Human
Development
Survey Report
India Pre post
study,
(IHDS 1
and IHDS
2)
JSY Odds of receiving full ANC among
women educated up to the high
school level during the pre-JSY
period was 3.651 times as great as
for illiterate women whereas it was
only 2.261 times as great during the
JSY period. The relative odds of
women receiving safe delivery had
significantly gone down among
women who were college graduates
from 6.371 times as great as illiterate
women during the pre-JSY period to
1.846 times during the JSY period.
The odds of full ANC declined from
1.031 per asset in IHDS-I to 1.025 in
IHDS-II. For postnatal care, the odds
declined from 1.050 per assets in
IHDS-I to non-significance in IHDS.
Likelihood of safe delivery increased
from IHDS 1 to IHDS 2 among
Muslims and forward caste Hindus.
Vellakkal S et
al, 2017 [64]
Health Policy
and Planning,
Oxford
8 EAG and 7
North-east
states
excluding
Nagaland
Quasi-
natural
experimen
t study
design
using data
from
DLHS1, 2,
3, 4 and
AHS
NRHM Wealth-related relative index for
inequalities for institutional delivery
fell from 14.5 in 1995– 99 to 11.7 in
2000–04 to 3.6 in 2007–08 to 1.3 in
2011–12 . Inequities in institutional
delivery and ANC were already
declining between the pre-NRHM
Period 1 (1995–99) and the pre-
NRHM Period 2 (2000–04), but
declined at steeper rates in the post-
NRHM periods. effects were stronger
for institutional delivery than ANC
Ali B. et al,
2018 [322]
Journal of Bio
social Science
India Secondar
y data
analysis of
NFHS 3
(2005-06)
andNFHS
4 (2015-
16), last
two
rounds
were
considere
d.
ANC,
PNC,
SBA
The usage gap of MCH services
between the poor and non-poor
remained large which was difference
of
- 4.3% (poor) and 15.3% (non
poor) for utilization of ANC.
Same for PNC
- 43% (poor) and 38% (non
poor) for SBA
This gap was higher in urban areas
in 2005–06, but more in rural areas
in 2015–16.
Poor women from SCs had higher
utilization of SBA and PNC than
women from OBCs and General
Castes in 2015–16.
Seth A. et al,
2017 [45]
International
Journal for
Equity in Health
Uttar
Pradesh
Survey
study
ASHA Women belonging to SC/ST and
OBC castes were less likely, as
compared to General Caste women,
to participate in at least 4 ANC visits.
Positive relationship between visits
by a community health worker and
likelihood of utilizing critical maternal
health services. Contact with ASHA
increased the odds of participation in
at least 4 ANC among lower wealth
women.
Gupta M. et al,
2016 [61]
PLOS One Haryana Secondar
y analysis
of DLHS
data
NRHM Geographic inequalities : Significant
(p<0.05) decline in difference of MCH
indicators between urban and rural
areas for pregnant women in urban
and rural areas –
3 ANCs from 23% to 5.4%
Full ANC from 8% to 6.8%
PNC from 2.8% to 1.5%
Full child vaccination10% to 3.5%
ORS fro diarrhoea from 11% to -
2.2%
Socioeconomic inequalities :
Significantly (p<0.05) decline in
difference of MCH indicators
between rich and poor-
TT injections in pregnant women
from 30.3% to 7%
Institutional deliveries : 48.2% to
13%
Fully immunized children from 48.3%
to 14%
ORS for diarrhoea from 41% to 5%
Although inequalities have been
increased between lowest and
highest wealth quintile groups related
to ANC pre and post NRHM ( 0.2 to
23%)
Gender inequalities : Difference of
inequalities between male and
female children was significantly
(p<0.05) reversed-
Full immunization (5.7% to -0.6%)
BCG from 1.9 to -0.9 points
Oral polio vaccine from 4% to 0%
Measles vaccine from 4.2% to 0.1%
Gupta M et al,
2017 [80]
BMC public
health
Haryana Explanato
ry
sequential
mixed
methods
study
NRHM Significant reduction in inequalities
pertaining to various MCH indicators
between poor and rich
(socioeconomic), rural and urban
(geographical), and girls and boys
(gender) across time period. But
reduction in gender based
inequalities was associated with
increase in educational status and
acceptance of small family size.
Mújica JO et
al, 2014 [323]
Bull world
health organ
BRICS
(Brazil,
Russia,
India, China,
South Africa)
Secondar
y data
analysis
MCH
inequalit
ies from
1990 to
2010
Maternal mortality- difference of 400
deaths per 1, 00,000 live births.
Infant mortality- 32.4 deaths per
1000 live births.
Child mortality- 50.8 deaths per 1000
live births
Pathak PK et
al, 2010 [324]
PLOS one UP, MH, TL NFHS
survey
data
analysis
PNC
and
SBA
Use of PNC among rural mothers in
India increased by 8 percentage
points (from 13% in 1992–1993 to
21% in 2005–2006). While it
improved by 19 % points (33% in
1992–1993 to 52% in 2005–2006)
among urban mothers during 1992–
2006. Use of
PNC remained significantly lower
among poor mothers than among
their non poor counterparts.
Gopichandra V
et al, 2012
[325]
PUBLIC
HEALTH
ETHICS
UP Review
study
(Data
adapted
from
UNFPA’s
Concurren
t
Assessme
nt of JSY)
JSY JSY beneficiaries=
Hindu = 38.8, Muslims = 23.5
SC/St = 32.5,others= 38.9
BPL= 38.1, Above BPL= 35.8
Living in huts= 33.5, living in
cemented houses= 43.1
Singh A. et al,
2012 [326]
PLOS one India
Secondar
y data
analysis
(DLHS)
PNC Mothers received check up within 48
hours- Home= 18 %, Institution =
80.8%
Newborn received check up -
Home= 18.8%, Institution = 82%
Newborn check in govt. facility -
Home = 17%, facility = 52.7%
Newborn check in private facility-
Home = 83%, institutional = 47%
Patel P et al,
2018 [321]
Reproductive
Health Matters
Purnia
district, Bihar
Qualitative
study
NRHM=
ASHA,
JSY ,
JSSK,
ANM
27% women received facilities from
ASHA. Only 5 % received PNC from
ANM. SC caste women did not
received needed care. USHA were
absents in urban slum due to caste
discrimination. Participants did not
receive JSY money and poor quality
of service was offered at PHC due to
belonging from lower caste. 16%
women discussed only being treated
at the PHC after women of higher
caste.
Kant S etal,
2016 [330]
International
Journal of
Gynecology
and Obstetrics
Haryana Observati
onal study
Delivery
huts in
rural
areas
The services successfully reached
pregnant women belonging to
disadvantaged caste groups, in
addition to those from higher castes.
There was also a significant increase
in the proportion of women attending
the huts who were illiterate over the
study period.
Saikia N. et al,
2016 [329]
Asian
Population
Studies
India Trend
analysis
Secondar
y data
analysis
SRS data
(1981-
2011)
- 1981= NMR with difference of 37
between urban and rural India.
2011= NMR with difference of 17
between urban and rural.
Bhatia M et al,
2018 [327]
SSM -
Population
Health
ELSEVIER
India Secondar
y data
analysis
- Relative change in inequalities in
infant and under five mortality over
the survey periods from NHFS-I to 3,
NHFS 3 to 4 and NHFS-1 to 4.
IMR = -30 among poorest and -38
among richest. Which was -25 and -
23 for NFHS 1 to 3 respectively?
U5MR = -39 -38 among poorest and
richest respectively during NFHS 3 to
4 and with no difference among poor
and rich during NFHS 1-NFHS 3.
The worst performing states (e.g.
Chhattisgarh, Odisha, Uttarakhand),
both in terms of high mortality and
high differentials between rich and
poor.
Motkuri V et al,
2018 [328]
Status of
Maternal and
Child Health
(MCH) in
Telangana
Telangana Secondar
y data
analysis
(SRS and
NFHS 4)
- Rural urban difference in Telangana=
11, AP= 14 India=15
Inequalities across social groups in
general and in the health dimension
are very narrow-
Rural and urban health
inequalities(maternal and child) -
2002-04 =0.478 and 2012-13= 0.750
Fertility rates low and harmonized
across social and religious groups in
the state.
Contraception rates are lower in
Muslims tribe.
IMR is high among ST and SC. Child
vaccination do not vary much with
respect to background.
ANC is low among ST women and
high among Muslims.
5.6 IMPACT OF OTHER VARIABLES ON HEALTH OUTCOMES
5.6.1 Results of studies on mobile connectivity (9 studies)
Author
and
year
Study
area
Study
Period
Study Type Intervention Results
Chib A,
2012
[332]
Udham
Sing
Nagar
District,
Uttrakha
nd
2008-
09
Qualitative
study
Mobile phone
use by
community
health workers
under NHM
scheme
(ICTH4H
model)
Improved communication flow during
emergencies. Increase in connectivity
with higher medical officers regarding
delivery and vaccination.
Balakris
hnan R.
et al
2016
[331]
Saharsa
District,
Bihar
July
2012
to
March
2015
Case control Continuum of
Care Services
(CCS)
(Maternal and
Child) by using
an mHealth
platform
Improved reporting and service
delivery.
21% more ANC visits in intervention
group in comparison to control group.
14% more cases of early breast feeding
in intervention group.
Hazra
A. et al
2018
[333]
Jhansi,
Uttar
Pradesh
April to
May,
2014
Quasi-
experimental
Voice
messages to
husbands of
pregnant
women on 5
health
behaviours ;
ANC check up,
Postnatal
check up, Early
breastfeeding,
Clean cord
care, Bathing of
baby
Improved knowledge. 39% asked their
wives and 13% asked their mothers to
follow the instructions. 80% of
husbands knew the importance of ANC,
40% knew about early initiation of
breast feeding. Uptake of one ANC,
PNC with in 7 days and delayed
bathing with odd of 1.72, 3.02 and 1.93
respectively.
Nair H.
et al,
2018
[335]
Pune,
Mahara
shtra
2015 Case control
study
Smartphone
with a track
care app.
Under 5 children with diarrhoea and
sought care ; Case= 75%, longitudinal
Control = 80%, cross-sectional control
=78%
Under 5 children with fever who sought
care; Case = 83%, longitudinal control
= 79%, cross sectional control = 79%
Under 5 children with fever and cough
who sought care; Case = 88%, cross
sectional control =84%, longitudinal
control = 89%.
No significant difference between case
and control. This could be due to
Hawthorne effect or due to repeated
study contacts.
Pai N. et
al, 2013
[336]
Low
income
area of
Mumbai
Hospital based
mixed method
study ( case
control and
qualitative
study)
Voice calls for
IFA supplement
The treatment group improved Hb by
0.43 g/dL (95% CI = -0.13 0.98 g/dL)
more than the control group. This
improvement is not statistically
significant (p=0.13).
Qualitative finding; Women offered
positive feedback regarding the voice
messages, describing them as
informative, entertaining, and a service
that they would recommend to friends.
Patel A.
et al,
2018
[337]
Nagpur 2010
to
2012
Hospital based
case control
study
Cell phone
counselling
The rates of exclusive breastfeeding
were sustained above 95% at all visits
in the cell phone group but dropped
from 81% at 6 weeks to 48.5% at 6
months in the control group.
Intervention group was 6 time more
exclusively breastfed than control
group. 13% higher rates of early
breastfeeding in intervention group.
Shah S.
et al,
2018
[338]
Bharuch
and
Narmad
a
districts
of
Gujarat
2016 Nested cross
sectional study
with a
randomized
controlled trial
ImTECHO Significantly higher knowledge and
skills of MNCH in the intervention arm
compared to the control arm with
difference of 18%. Intervention group
demonstrated better skills for
measuring temperature of new-borns
and preventing hypothermia compared
to the control group with difference of
30% and 15% respectively.
Spindler
H. et al,
2017
[339]
Bihar 2015
to
2017
Cross sectional
study
Mobile nurse
mentoring
programme
Communication with mother improved .
85 % improvement in debriefing. 77%
complicated deliveries were conducted
by nurses. Improvement in vaginal
delivery, non vigorous infant and
postpartum haemorrhage.
Modi D.
et al,
2016
[334]
Bharuch
district,
Gujarat
April-
May
2015
Cross sectional
study
ImTECHO
(Support and
supervision of
ASHA and
PHC staff)
Higher sensitivity for registration of
pregnancy, delivery and child death i.e.
97%, 99% and 100% respectively.
5.6.2 Results of studies on road connectivity (8 studies)
Author
and year
Study
area
Stud
y
Perio
d
Study
Type
Intervention Results
Bawdekar
M, 2008
[340]
Mahara
s-htra,
33
districts
2003 Secondar
y data
analysis
(DLHS-
RCH
Round II)
Road length
Female
literacy rate
Health
facilities
Toilet
facilities
Temperature
Road length and percentage female literacy had
an inverse relationship with severe malnutrition
and the association was significant at p<0·05.
Children in the households with either a personal
or public toilet facility are 11% less likely to suffer
from severe malnourishment as compared with
those with no toilet facility at all. Climate on
health facilities have insignificant association with
server malnutrition.
Ghosh A.
et al 2016
[341]
India 2016 Secondar
y data
analysis
((DLHS-
3)
Road
connectivity
Weather
Health
center
Mother
literacy
Availability
of ANM and
ASHA
Indicators of village-level general infrastructure,
like availability of electricity and all weather road
connectivity with the sub center or PHC, are
associated with both higher chances of receiving
of at least one DPT dose and higher chances of
completing the three-dose series among infants
who have received at least one dose of DPT.
36% and 46 % difference in DPT 3 and DPT 1
coverage respectively among children of mothers
educated up to 10th or higher education and
mothers without any schooling.
Lalmalsa
wmzauva
KC et al,
2009
[342]
India Secondar
y data
analysis
(NFHS 3,
India's
Year
Book,
Census
of India
2001)
Road
density
Positive correlations between surface road
density and all the indicators of utilization of
maternity services at a high 0.05 significant level
with ranges from(r=0.936) for institutional birth,
(r=0.950) for delivery assisted by health
personnel, (r=0.939) for any postnatal check-up
and (r=0.947) for postnatal check up within two
days of birth.
1. Very high surface road density areas - ANC
(36%), Institutional deliveries(70.8%), health
personnel attended delivery(77.88%) , PNC
(70.65%)
2. High density surface road areas- ANC(17.1%),
Institutional deliveries(40.94%), health persona;
attended delivery(52.11%), PNC(48.24%).
3. Medium density surface road areas-
ANC(17%), Institutional deliveries(41%), health
persona; attended delivery(48.38%),
PNC(39.08%).
4. Low density surface road areas- ANC(9.72%),
Institutional deliveries(28%), health personal;
attended delivery(36%), PNC(26.08%).
5. Very low density surface road areas-
ANC(10.2%), Institutional deliveries(41.87%),
health personal attended delivery(45.8%),
PNC(40.5%)
Kumar S.
et al,
2012
[344]
India 2013 Secondar
y data
analysis
from
DLHS 3
and
Demogra
phic
health
Surveys
Road
connectivity
and access
to health
facility
focusing on
delay 3
Distance to the nearest health facility is inversely
associated with the probability of in-facility
delivery.
With in 5 km of health facility- 42% of IFD.
With in 5 and 9 km- 32% of IFD
More than 10 Km- 26% of IFD.
Banerjee
R. et al,
2015
[345]
India Secondar
y data
analysis
(DLHS 3),
village
directory
of the
2001
Census
data
Road
connectivity/
Pradhan
Mantri Gram
Sadak
Yojana
(PMGSY)
Connecting villages with an all-weather road
increases the usage of preventive healthcare.
Women are 20% more likely to use ante-natal
care. Women rely more on female sterilization
and 12% less chances of use of withdrawal
methods. 3% more likely to enroll in government
health schemes. 30% and 25% likelihood of
having ASHA and ANM in the village
respectively.
Aggarwal
S, 2018
[300]
India Secondar
y data
analysis
(DLHS-3)
Road
connectivity
Better quality prenatal care , more likely to
receive micronutrient supplements, tetanus
shots. Full road connectivity = 4% less chances
of complications in delivery. Children are more
likely to receive vaccination except polio, reason
could be massive initiative to attain universal
polio vaccination rates.
Author Study
Location
Study
Period
Study Type Intervention Results
Sahoo
M. et al,
2017
[346]
Odisa 2014 to
2015
Descriptive
study
Supply side
barriers
The supply side barriers are; physical
barriers faced by the service providers
due to lack of proper roads and the
absence of transportation to the
interior villages. 38% respondents had
travelled 5 km distance for delivery,
15.2% of respondents had travelled
10 km, 9.4% had travelled for 15km
for delivery
Studies with road connectivity/distance as barrier, not as intervention
Barman
D. et al,
2009
[343]
Murshidabad
district of West
Bengal
2008 secondary
data
analysis
( RCH-
DLHS)
Supply side
and demand
side barriers
Supply side barriers- Distance to
travel by health workers,
Infrastructure
Demand side barriers- mother
education and awareness, use of
private or government health sector.
In comparison to illiterate mothers,
educated mother’s children were
more likely to get fully immunized.
Who used private sector were 28%
less likely to be fully immunized.
If ANM did not visit the household
during the pregnancy or after child
birth the child was 31% less likely to
be fully immunized. Better village
infrastructure score, child was more
likely to be fully immunized. If a
mother was employed her child was
found to be 33% less likely to be fully
immunized. Muslim children were
found 45 % less likely to be
completely immunized compared to
their Hindu counterparts
5.6.3 Results of studies on water supply and sanitation (7 studies)
Author
and
year
Study
area
Study
Period
Study
Type
Intervention Results
Bajpai
N. et al,
2006
[395]
Jalore
and
Chittorgar
h
districts,
Rajastha
n
April-
May
2006
Cross
sectional
NRHM
coordination
with sub
sectors like
sanitation,
Nutrition,
Safe
drinking
water.
Usage of safe water- 68% to 70% of the
households. Unsafe water practices-
30% of the household's Tap water
facility- 2% to 3%. Toilet facility at
home- none of the households. No
regular waste removal facility.
Percentage of sickness (2005)- 42% in
Jalore and 43% in Chittorgarh.
Incidence of hospitalization-
11% in Jalore but only 5% in Chittorgarh.
Institutional deliveries- 4% in Jalore and
8% in Chittorgarh district.
ANC- 3% in Jalore and 9% in Chittorgarh
received such care.
Incidence of still birth-5.3% in Jalore
and 3.3% in Chittorgarh.
Vaccination of children-In Jalore 95%
and in Chittorgarh 98% of the poor
families got their children vaccinated. This
could be due to polio erradication
program
Butala N
M. et al,
2010
[352]
Ahmadab
ad
2001-
08
Case and
control
design
used
secondary
data
(micro
insurance
provider
VIMO
Slum
Upgrading
Significant reduction in waterborne illness
from 25% to 10%. Reduction in
waterborne illness claims 32% before the
intervention to 14% after the intervention.
SEWA in
the years
2001- 2008
)
Nandi A.
et al,
2016
[349]
India Secondary
data
analysis
(DLHS-3)
Access to
piped water
and
improved
sanitation
(Intervention
1; 95%
coverage at
random,
Intervention
2; At least
95%
coverage in
each state)
Intervention 1; Diarrheal incidence
averted- 43,126, deaths averted- 68.
Intervention 2; Diarrheal incidence
averted-43352, deaths averted- 68.
Intervention could avert could avert
43,352 diarrheal episodes and 68
diarrheal deaths per 100,000 under-5
children per year, compared with the
baseline.
Ercume
n A. et
al, 2015
[348]
Hubli-
Dharwad,
Karnatak
a
Nov
2010
to Feb
2012
Matched
cohort
study
Intermittent
water supply
and
continuous
water
supply.
No significant overall association was
found between continuous versus
intermittent supply and diarrhea bloody
diarrhea or weight for age. In continuous
supply wards, 42% fewer households had
at least one reported case of typhoid
fever compared to intermittent supply
wards. No significant association between
continuous versus intermittent supply and
cholera. Lower <2-y-old mortality
associated with continuous versus
intermittent supply. (No reason listed out
because of small number of deaths).
Berende
s D et
al, 2017
[347]
Vellore,
India
2010
to
2014
Cohort
study
Household
sanitation
(toilets)
Risk of enteric infection was 9% lower in
children in households with toilets
compared to those without toilets. Risks
of bacterial and protozoal infections for
children in households with toilets were
13% and 36% lower than for children in
households without toilets. But these
relationships were not significant.
Patil S
R. et al,
2014
[351]
Dhar and
Khargone
districts,
Madhya
Pradesh
2011 Cluster
randomize
d control
trial
Total
Sanitation
Program
Diarrhea prevalence did not differ
between groups (7.4% intervention
versus 7.7% control).
Padhi B
K, et al,
2015
[350]
Odisha Population
based
prospective
cohort
study
Sanitation 58.2%)had no access to a latrine and
reported open defecation at recruitment.
About half (45.8%) of the pregnant
women living in a household with latrine
access. 32% reported rare use of the
facility. Compared to latrine access, open
defecation was associated with higher
odds of APO , preterm birth, and low
birth weight . Other factors associated
with higher odd of APO are ; Occasional
use of toilets, non availability of water in
latrines, washing of body with water from
open sources.
Other study (Self-help group)
Author and
year
Study
area
Study
Period
Study
Type
Intervention Results
Saha S. et
al, 2013
[396]
India Secondary
data
analysis
(DLHS-3)
Self Help
Groups
The presence of a SHG in a village is
associated with 19 % higher odds of
mother’s delivering in an institution. 8
% higher odds of an increase in
colostrum feeding. Presence of a
health and sanitation committee in
a village or accessibility of a
CHC/RH does not appear to
influence the outcome.
5.6.4 Impact of food availability on health outcomes (N=6)
Author
and year
Study area Study
Period
Study Type
/Intervention
Results
Singh V et
al,2017
Barabanki
and Unnao
ditrict of
Uttar
Pradesh
May-Aug
2005
quasi
experimental
randomized
longitudinal
study/
Integrated
nutririon and
health program
Impact on breastfeeding practices:
Early initiation was more frequently
reported in the intervention arm
(17.4% vs. 2.7%)In the intervention
group, 34.7% of the women reported
giving colostrum to their
babies versus 8.4% in the
comparison district (p<0.001)
Impact on complementary feeding
practices: Improvement in total
quantity of food given in the
intervention area from 12±18
months, whereas, no such increase
in the comparison district was
observed .
Passi R et
al
22
VHSNCs of
Chandigarh
January
and May
2015
cross‑section
al mix method
study
The villages showed good
performance regarding the nutritional
status of children aged 0–3 years but
performance of providing
complimentary feeding to children of
age 6–12 months was average.
Alim F et
al, 2012
16
Anganwadi
s
in 5 villages
in Aligarh,
Uttar
Pradesh
(U.P.)
January-
June, 2011
Survey based
study/ ICDS
Only76.4% of children had received
the supplementary nutrition through
ICDS and 23.6% of children did not
received supplementary nutrition.
Children who received supp
nutrition:62.7 % of children, were
having normal weight for age, 13.7%
were underweight, and 49.4% of the
children were of normal height for
their age.
Children who did not received
supplementary nutrition: majority
14.3 % of their children was
underweight, 68% children were
stunted.
Thakur J
et al, 2010
45
Anganwadi
centres
(AWCs)
in
Chandigarh
April
to August
2007
Prevalence of underweight among
under-five children remained almost
stagnant in the last one decade from
51.6% (1997) to 50.4% (2007). There
was insignificant difference (P=0.3) in
prevalence of underweight among
children registered under ICDS
program (52.1%) and those not
registered (48.4%) in 2007.
Vaid S et
al, 2005
Resham
Ghar
colony
of Jammu
city
(Jammu
and
Kashmir
State)
- Cross
sectional study
children who attended Anganwadi
centres had good health or
appearance as compared to their
counterparts, also ICDS children had
good dietary intake as compared to
the children who did not attend ICDS
centres.
Kumar A
et al,2009
field
practice
area
encompass
ing 35
Anganwadi
s
in 11
villages by
the
Community
Medicine
Department
of
Kasturba
Medical
College
situated in
July 2009 cross-sectional
study/ICDS
Assessment of the growth chart
revealed that malnourishment was
evident in 189 (32.3%)
of the children, of which 166 children
were grade I
malnourished and 23 children were
grade II malnourished.
Proportionally girls (46.2%) were
more malnourished than
boys (33.6%).
Southern
India
ANNEXURE 6: LIST OF GOOD QUALITY STUDIES INCLUDED IN THE SYSTEMATIC
REVIEW.
S. No. Author and
Year
Journal Geographic area Study design Intervention Target
Population
Sample
size
Outcome Odd ratio
controlled
Confounders
controlled
Grading
JSY
1 Lim et al, 2010 LANCET India Secondary data
analysis
JSY Pregnant
females
Institutional
deliveries
√ √ +++
2 Randive B. et
al, 2013
PLOS ONE India Secondary data
analysis
JSY pregnant
females
Institutional
births
√ +++
3 Panja TK et al,
2019
Indian Journal of Public Health West Bengal Cross sectional
community
based study
JSY pregnant
females
Institutional
deliveries
√ √ +++
4 Mukhopadhyay
DK et al,
201
Indian Journal of Public Health West Bengal Cross sectional
study
JSY JSY eligible
women
946 Institutional
deliveries
√ √ +++
5 Gopalan d et al,
2012
BMC Health Services Research Orissa Mixed method
design
JSY Pregnant
females
Institutional
deliveries
× × ++
6 Amudhan S et
al, 2013
International J of Epidemiology Ballabgarh, Haryana Quasi
experimental
study
JSY Post-natal
females
1884 Institutional
deliveries
√ √ +++
7 Sidney K et al,
2012
BMC Reproductive Health Ujjain Cross sectional
study
JSY Pregnant
females
418 Institutional
deliveries
√ √ +++
8 Ng M et al,
2014
Global Health Action Madhya Pradesh Continuous time
series
JSY Reproductive
age group
females
MMR reduction √ +++
9 Ved R et al,
2012
BMC proceeding oral presentation EAG states Survey Women of
institutional and
home delivery
Institutional
delivery
× × +
10 Randive B et al,
2014
Social Science and Medicine 9 states( RJ, MP, CG, BR, JH, UP, UK,
OR, AS)
Ecological study
with secondary
data analysis
JSY MMR reduction
and institutional
deliveries.
Inequalities in
institutional
deliveries
× × ++
11 Gaur A et
al,2015
Journal of Evidence based Medicine and
Healthcare
M.P. retrospective
hospital based,
observational
comparative
study
JSY Perinatal
mortality
× × ++
12. Carvalho N et
al, 2014
PLOS one
34 states and union territories in India
(excluding Nagaland)
Secondary data
analysis
(District Level
Household
Survey (DLHS-
3)
JSY
12–23 months
chldren
37289
Immunization
rate
√
×
++
13 Kaur et al ;
2017
International Journal of Community
Medicine and Public Health
Punjab Secondary data
analysis ( DLHS
, SRS for Punjab)
Institutional
deleveries
Postnatal
women
IMR × × +
ASHA
14 Padda et al INDIAN JOURNAL OF COMMUNITY
HEALTH
Malwa region of Punjab survey ASHA PREGNANT
women
PNMR × × ++
15 Tripathy P et
al,2016
Lancet Glob Health Five rural districts of Jharkhand and
Odisha
RCT ASHA women of
reproductive
age (15–49
years)
PNMR √ √ +++
16 Tripathy P et
al,2016
Lancet Glob Health Five rural districts of Jharkhand and
Odisha
RCT ASHA women of
reproductive
age (15–49
years)
NMR √ √ +++
17 Seth A et al.
2017
International Journal for Equity in Health Secondary data
analysis
ASHA women who
gave birth in
one year
4912 ANC and
Institutional
deliveries
√ √ +++
18 Farah N.
Fathima et al,
2015
BMC J HEALTH POPUL NUTR Karnatka Cross sectional
study
ASHA Mothers and
ASHAs
1800
mothers,
300
ASHAs
Institutional
deliveries
× × ++
19 Gupta M et al,
2017
PLOS One
Haryana Secondary data
analysis
ASHA
Immunization × × ++
20 Wagner AL et
al, 2017
Journal of public health India(21 states) Secondary data
analysis(DLHS)
ASHA 12-23 months
children
Immunization √ √ +++
21 Prinja S et al,
2017
Tropical Medicine and International Health
Community development blocks of
Kaushambi district.
pre- and post-
quasi-
experimental
design
ASHA (m-
health)
12-23 months
3201
Immunization
rate
× × ++
22 Sheila C.
Vir,2014
Food and Nutrition Bulletin
Chhattisgarh
Quasi-
experimental
mixed methods
Mitanin
programme
(Nutritional
Security
Innovation
project)
Under 3 yrs
children
3628
children
under 3
yrs of
age
Nutritional
status, AARR
× × ++
23 Gupta M et al,
2017
BMC Public Health Haryana Mixed method
study
NRHM MCH
plans: ASHA,
JSY, JSSK
MMR × × ++
24 Gupta M et al,
2016
PLOS ONE Haryana Comparative
study of DLHS
2, 3 ,4
NRHM Currently
married women
18,227 MMR × × ++
25 Gupta M et al,
2017
BMC Public Health Haryana Mixed method
study
NRHM MCH
plans: ASHA,
JSY, JSSK
IMR × × +
26 Gupta et al;
2016
PLOS One Haryana Comparative
study of DLHS
2, 3 ,4
NRHM Currently
married women
18,227 ORS, Diarrhoea
uptake in
children
× × +
27 Fathima et al;
2015
Journal of Health, Population, and Nutrition
Karnataka Cross sectional
study
ASHA ASHA 300 Knowledge
regarding CH
practices
× × +
Referral Transport
28 Prinja S et al,
2014
Indian J Med Res Haryana, 3 districts=
Ambala, Hisar, Narnaul
Secondary data
analysis
National
ambulance
system
utilization
116562 Institutional
deliveries
√ √ +++
29 Strehlow M C at
el, 2016
BMJ Open Andhra Pradesh, Assam,
Gujarat, Karnataka and Meghalaya
Prospective
observational
study
free of charge
ambulance
transport
women in third
trimester of
pregnancy
calling with a
‘pregnancy-
1684 Method of
delivery and
Death.
√ √ +++
related’
problem for free
of charge
ambulance
30 Sidney K et al,
2014
PLOS ONE MP cross-sectional
study
JEY( Janani
Express Yojna)
State Run
Public Private
Emergency
Transportation
Service
women who
delivered in
hospital
Utilization of
JEY and ASHA
role
× × ++
Quality Management
31 Agarwal R et al,
2018
BMJ Global Health Haryana cluster
randomised
trial
Quality
management
activities
Pregnant
females
approaching to
PHC
7345 Quality
management
√ √ +++
Immunization
32 Nath B et al,
2007
Indian journal of medical sciences
Urban slums of Lucknow survey
Immunization 12-23 months
Children
510
Full
Immunization
√ √ +++
33 Devasenapathy
N et al, 2016
BMJ Open
Urban poor community in the
Southeast district of Delhi, India
cross-sectional
study
Immunization 1–3.5 years
1849
children
Full
Immunization
√ √ +++
34 Gill N et al,2016
International Journal of Community
Medicine and Public Health
Mumbai
Descriptive
Immunization
1-2 years
210
Full
Immunization
√
× ++
35 Kurane A et al,
2018
International Journal of Contemporary
Pediatrics
Paediatric OPD, immunization clinics
and children admitted in Paediatric
ward in D. Y. Patil hospital, Kolhapur.
Immunization
2-5 years
2000
children
Full
Immunization
× × ++
36 Francis M et al,
2019
Vaccine, Elsevier science direct
Thimiri, a rural administrative
block comprising 67 villages in Vellore
district in Tamil Nadu
cross-sectional
household
survey
Immunization
12–23 months
606
children
Full
Immunization
√ √ +++
37 Goel S et al,
2012
Indian Paediatrics Bihar Observational
study,
Immunization 12-23 months
children
Increase in
proportion of
× × ++
Comparison of
the
immunization
coverage before
and after launch
of campaign
with other
(EAG) states in
the
corresponding
period
immunization
rate
38 Bawankule R et
al, 2017
PLOS one
India
Secondary data
analysis from
NFHS 3
Immunization
12-59 months.
27354
Occurrence of
ARI and
diarrhoea
√ √ +++
39 Prinja et al ;
2010
Bulletin of the World Health Organization
Khizrabad in the Yamunanagar district
of Haryana
Cohort design
Immunization
12-18 months 4336 Immunization
rate
× × ++
NRC
40 SINGH K et al,
2014
INDIAN PEDIATRICS
12 functional NRCs of Uttar
Pradesh.
Review of data
of all children
with SAM
NRC
6-59 months
1181
Recovery rate × × ++
41. Dhanalakshmi
K. et al, 2017
International Journal of Contemporary
Pediatrics
NRC At Vani Vilas children’s Hospital,
attached to Bangalore Medical College
and Research Institute, Bangalore,
Karnataka
retrospective
hospital based
study
NRC
1m to 59 m
736
Recovery rate × × ++
Vitamin A
42 Semba R et
al,2009
The Journal of Nutrition
29 states of India
secondary data
analysis
(NFHS)
Vitamin A Preschool
children(12-59
mo)
4459
children
Under 5
mortality,
Vitamin A
supplementation
√ √ +++
43 Agrawal S et al,
2013
Int J Med Public Health
India
Secondary data
analysis
Vitamin A
12-35 months
20,802
children
Vi t A suppl. √ √ +++
NFHS 3(2005-
2006)
44 Aguayo V et al,
2014
Public Health Nutrition
Seven Indian states
(Bihar,Chhattisgarh,Jharkhand,Madhya
Pradesh,Odisha,Rajasthan, Uttar
Pradesh)with the highest burden of
mortality in children
Analysis of VAS
programme
coverage data,
data from
India’s District
Level
Household
Survey, India’s
Office of the
Registrar
General and
Census
Commissioner
Vitamin A
under 5
children(6–59
months)
VAS Coverage
× × ++
45 Mazumdar et al
; 2015
Lancet
Randomized
control trial
Vitamin A
supplementation
Children upto 6
months of age
44 984 IMR × √ ++
ENC
46 Malhotra S et
al,2014
J HEALTH POPUL NUTR Nagaur district in Rajasthan and
Chhatarpur
district in Madhya Pradesh
Record review Essential new
born care
SBR × × ++
47 Agarwal et al;
2007, India
Journal of Perinatology
India Before-and-
after
intervention
trial
Essential new
born care
Neonates 7938 NMR × × ++
48 Sodani et al;
2011
Indian Journal of Public Health
CHC, Bharatpur district, Rajasthan
Cross sectional
study
Essential new
born care
CHC 13 ENC Practices × × ++
49 Kumar et al;
2016
BMC Pregnancy and Childbirth Rajasthan, India Quasi-
experimental
Essential new
born care
Healthcare
facilities
16 ENC × × ++
50 Gosain et al;
2017
Journal of Tropical Paediatrics
Ballabgarh, Faridabad District,
Haryana
Cross sectional
study
Essential new
born care
Healthcare
facilities
45 ENC, SNCU × × ++
51 Kumaravel
al;2015,
Journal of Evolution of Medicine and
Dental sciences
Dharmapuri district, Tamil Nadu
Descriptive-
retrospective
study
Facility based
new born care
Neonates 2350 NMR × × ++
HBPNC
52
Baquai et al;
2008
Bulletin of the World Health Organization
Uttar Pradesh Quasi
experimental
study
HBPNC
NMR × × ++
53 Sinha et al;2014
Western Pacific Surveillance and Response
Journal
Mewat, Haryana
Cross sectional
study
HBPNC Postnatal
mothers
320 Newborn care
practices
√ × +++
54 Srivastava et al
; 2012
Rural and Remote Health
Thane district of Maharashtra
Cross sectional
study
HBPNC ASHA 150 Knowledge
regarding child
health practices
× × +
55 Karol et al ;
2014
International Journal of Humanities and
Social Science
Rajasthan Cross sectional
study
HBPNC ASHA 200 Knowledge
regarding CH
practices
× × +
56 Pandit at al ;
2016
International Journal of Health Sciences
and Research
Rural area of Maharashtra
Cross sectional
study
HBPNC ASHA 37 Knowledge
regarding CH
practices
× × +
57 Panda et
al;2019
International Journal of Community
Medicine and Public Health
Odisha Cross sectional
study
HBPNC
ASHA 1218 Knowledge
regarding CH
practices
× × +
IMNCI
58 Bhandari et
al;2012
BMJ
Faridabad, Haryana Cluster
randomised
trial.
IMNCI Live births 60 702 NMR √ √ +++
59 Mohan et
al;2011,
Journal of Health, Population and Nutrition
12 districts of India
Mixed methods
study
IMNCI Training of
health workers
BF,
Immunization
√ √ +++
60 Taneja et
al;2015
Journal of Global Health
Faridabad, Haryana Cluster–
randomized
controlled trial
IMNCI Live births 30000 NMR, IMR,
newborn care
practices
× √ ++
61 Som et al;2017
International Journal of Health Sciences &
Research
Odisha
Cross sectional
IMNCI AWWs 381 AWWs
knowledge
× × +
62 Venkatachala J
et al ; 2011
Indian Journal of public health
Panchkula district of Haryana stat
Cohort study
IMNCI HCWs(ANM,
AWW)
85 Knowledge.
Skills of HCWs
× × +
63 Biswas B et al;
2011.
Journal of Tropical Paediatrics
West Bengal Cross sectional
study
IMNCI FLWs 155 Skills of FLWs × × +
64 Chowdhury et
al ; 2017
BMJ
Palwal and Faridabad distr. If Hariyana Secondary data
analysis
IMNCI Infants 60 480 IMR √ √ +++
65 Bora et al;2018
Plos One
India Secondary data
analysis
NFHS 3
IMNCI Neonates NMR × × +
66 Thummakomma
; 2016,
Journal of Evidence Based Medicine and
Healthcare
Kakatiya Medical College, Warangal
Prospective
observational
study
IMNCI Infants 500 IMR × × +
Breastfeeding
67 Phukan et
al;2018
International Breastfeeding Journal
India Secondary data
analysis
BF Postnatal
women
NMR √ √ +++
NHM
68 Narwal et al ;
2013
International Journal of MCH and AIDS
India Secondary data
analysis
NRHM IMR × × +
CPR
69 Ambure et al International Journal of Medical Science
and Public Health
Shimoga, Karnataka Cross sectional females who
had delivered in
the last–36
months
210 Prevalence of
Contraception
and its
association with
postnatal
checkups
× × +
70 Nimavat et al International Journal of Medical Science
and Public Health
Gujarat Cross sectional ASHA incentive
scheme
ASHA workers
of ten talukas
and PHCs
Permanent
sterilization
× × ++
71 Subramanian et
al
Global Health: Science and Practice Bihar Quasi-
experimental
evaluation
PRACHAR
strategies
Contraceptive
usage
√ √ +++
72 Gupta et al Journal of Urban Health: Bulletin of the
New York Academy of Medicine
Chandigarh Cross sectional women in the
age group of
15-49 years
Contraceptive
practices
× × +
73 Speizer et al Journal of Urban Health: Bulletin of the
New York Academy of Medicine
Six districts of UP Cross sectional NRHM and
Urban health
Initiative funded
by BMGF
women in the
age group of
15-49 years
17643 Contraceptive
practices
× × ++
74 Prateek et al African Health Sciences Urban health centre in South India Cross sectional Married women
in reproductive
age group (15-
49years)
180 Awareness,
practice and
reasons of
adoption and
non-adoption
46of
co47ntraception
× × +
75 Shaheen
Rahman
International Journal of Scientific Study Guwahati Cross sectional Cu-T currently
married women
260 Cu-T utilization
stateu
× × ++
76 NIRANKAR
SINGH
The Journal of Family Welfare Patiala, Punjab Cross sectional Married women
in the age
group of 15-
49years
1123 Contraception
usage
× × +
77 Chandrasekhar
et al.
Journal of Young Pharmacists Kerala Quasi
experimental
Saheli program women in age
group of 15-45
years
140 Knowledge
about family
planning, child
care and
maternal health
× × +
78 Mcdougal et al PLOS One Bihar Quasi
experimental
Ananya
program
married women
15-49 years
with 0-5 months
old child
Bseline-
7191
and
follow
up-6143
Improvement in
postpartum
contraceptive
use
√ √ +++
ARSH
79 Nair & 2013 Indian J Pediatr Kerala Cross sectional ARSH Adolescents
and young
adults (10-24
years)
4223 Knowledge
about Menstrual
hygiene
practices,
knowledge
attitude and
practices of 10-
2 age group
regarding RSH
issues
++
80 Nair & 2013 Indian J Pediatr Kerala Cross sectional ARSH Adolescents
and young
adults (10-24
years)
4220 Knowledge
about
contraceptive
measures, ideal
age of
pregnancy and
other RSH
indicators
++
81 Gupta 2015 Indian Journal of Public Health Chandigarh Cross sectional ARSH Adolescent age
group(10-19
years)
854 Knowledge
about ARSH
and access to
the ARSH
clinics
++
RBSK
82 Tiwari J et al,
2015
International Journal of Community
Medicine and Public Health
Panna Distt Madhya Pradesh
Cross sectional
survey
RBSK Children up to
18 years
26977 Early diagnosis
and screening
× × +
83 Balat M et al,
2018
International Journal of Community
Medicine and Public Health
Ahmedabad Cross sectional
survey
RBSK Children up to 3
years
169 Early diagnosis
and screening
× × +
WIFS
84 Vir 2008 SAGE Journal Food and Nutrition Bulletin UP Community
based
intervention
study
WIFS Adolescents
10-19 years
150700 Reduction in
anaemia
× × ++
85 Dongre 2011 SAGE Journal Food and Nutrition Bulletin Wardha, Maharashtra participatory
action research
IFA prophylaxis
for 100 days in
a year through
community
participation
Adolescent girls
12-19 years
249 Reduction in
nutritional
anaemia
× × ++
Menstrual Hygiene
86 Shah et al 2013 ELSEVIER Reproductive Health Matters Gujarat cross sectional Adolescents
girls
164 Awareness
about menstrual
hygiene
practices
× × +
87 Sivakami et al
2019
Journal of Global Health Maharashtra, Chhatisgarh, Tamilnadu cross sectional Adolescent girls
above 12 years
of age
2564 Knowledge
about menstrual
hygiene
× × +
Health Inequalities
88 Gupta M et al,
2017
PLOS one Ambala and Mewat Districts of
Haryana
Qualitative
study
NRHM (MCH
plans)
Program
officers,
community
representatives,
mothers, health
service
providers
72 Maternal and
child health
inequalities
× × +
89 Vellakkal S et
al, 2017
Health Policy and Planning, Oxford 8 EAG and 7 North-east states quasi-natural
experiment
study design
using data from
DLHS1, 2, 3, 4
and AHS
NRHM Married women socioeconomic
inequities in the
uptake of
institutional
delivery and
antenatal care
(ANC)
√ ++
90 Seth A. et al,
2017
International Journal for Equity in Health Uttar Pradesh Survey ASHA Women who
gave birth in
last 12 months
4912 Social inequities
and health
disparities.
√ √ +++
91 Gupta M. et al,
2016
PLOS One Haryana Secondary
analysis of
DLHS data
NRHM Currently
married women
18227 Geographical,
socioeconomic,
and gender
inequality in
MCH pre and
post NRHM
× × +
92 Gupta M et al,
2017
BMC public health Haryana Explanatory
sequential
mixed methods
study
NRHM Currently
married women
and Health
workers, health
managers
MCH
inequalities
× × +
93 Bhatia M et al,
2018
SSM - Population Health ELSEVIER India NFHS data
analysis
child health
inequalities
× × +
94 Patel P et al,
2018
Reproductive Health Matters Purnia district, Bihar Qualitative
study
NRHM= ASHA,
JSY , JSSK,
ANM
SC caste
women
18 Utilization × × +
95 Randive B, et al
2014
ELSEVIER, Social Science and Medicine Rajasthan, Madhya Pradesh,
Chhattisgarh, Bihar, Jharkhand, Uttar
Pradesh, Uttarakhand, Orissa and
Assam
Ecological
study,
secondary
analysis of data
(DLHS3)
JSY JSY
beneficiaries
Inequalities in
institutional
deliveries and
maternal
mortality
× × +
Secondary
data analysis
96 Rammohan et
al;2013
Plos One
India secondary
analysis of data
(DLHS3
NMR × √ ++
97 Jha P et al,
2017
Lancet
India Secondary data
analysis
Comparison of
NFHS 3 Data
with NFHS 4
U5MR × × +
98 Jha P et al,
2017
Lancet
India Secondary data
analysis
NMR
× × +
Comparison of
NFHS 3 Data
with NFHS 4
ANNEXURE 7. MATERNAL HEALTH INDICATORS OF WOMEN AGED 15 -49 YEARS WHO
HAD A LIVE BIRTH IN THE FIVE YEARS PRECEDING THE SURVEY.
Maternal Health Pre NHM (%) Post NHM
#
(%)
Adjusted Odds
Ratio
95%
Confidence
Interval
p-value
Adequate ANC Care 50.2 86.3 6.3 (5.837, 6.648)
<0.01*
Three ANC Check ups 52.4 55.3 1.1 (1.072, 1.177)
<0.01*
Anaemia During
Pregnancy
58.7 54.6 0.9 (0.765, 0.936)
<0.01*
100 Iron Folic Acid 15.6 18.8 1.3 (1.195, 1.318)
<0.01*
Breastfeeding within
one hour
24.5 41.8 2.2 (2.115, 2.310)
<0.01*
Tetanus Toxoid
Injection
82.6 92.7 2.7 (2.524, 2.800)
<0.01*
*Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for place of residence, maternal
age, education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health
worker density, road density, telephone-density.
Proportion of women for various maternal health indicators in 2005 and 2015.
50.2
52.4
58.7
15.6
24.5
82.6
86.3
55.3 54.6
18.8
41.8
92.7
0
10
20
30
40
50
60
70
80
90
100
Adequate
ANC Care
Three ANC
Check ups
Anemia
During
Pregnancy
100 Iron Folic
Acid
Breastfeeding
within one
hour
Tetanus
Toxoid
Injection
Percentage (%)
20052015
ANNEXURE 8. CONTRACEPTIVE METHODS CURRENTLY USED FOR FAMILY PLANNING
BY MARRIED WOMEN AGED 15 -49 YEARS.
Family Planning Pre NHM (%) Post NHM
#
(%)
Adjusted Odds
Ratio
95% Confidence
Interval
p-value
Female Sterilization 37.3 44.2 1.3 (1.293, 1.370)
<0.01*
Male Sterilization 0.1 0.2 0.2 (0.167, 0.241)
<0.01*
Condom 5.2 3.9 0.7 (0.710, 0.778)
<0.01*
Contraceptive Pills 3.1 5.3 1.7 (1.616, 1.857)
<0.01*
Inter Uterine Device 1.7 0.8 0.5 (0.444, 0.519)
<0.01*
* Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for place of residence,
maternal age, education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply,
cooking fuel, health worker density, road density, Telephone-density.
Proportion of women by contraceptive methods used for family planning in 2005 and 2015
37.3
1.0
5.2
3.1
1.7
44.2
0.2
3.9
5.3
0.8
0
10
20
30
40
50
Female
Sterilization
Male
Sterilization
CondomContraceptive
Pills
Intra Uterine
Devices
Percentage (%)
20052015
ANNEXURE 9. IMMUNIZATION OF CHILDREN AGED 12 -23 MONTHS WHO RECEIVED
SPECIFIC VACCINES AT ANY TIME BEFORE THE SURVEY.
Child Health Indicators Pre NHM (%) Post NHM
#
(%)
Adjusted
Odds Ratio
95% Confidence
Interval
p-value
BCG 78.4 90.9 2.8 (2.435, 3.125)
<0.01*
DPT1 76.3 88.6 2.5 (2.152, 2.690)
<0.01*
DPT3 55.8 77.5 2.7 (2.484, 2.985)
<0.01*
Measles 60.0 79.8 2.6 (2.391, 2.897)
<0.01*
Vitamin A1 50.8 76.8 3.3 (2.932, 3.510)
<0.01*
* Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for institutional
delivery, place of residence, maternal age, education, religion, caste, wealth index, type of housing, availability of
toilet, safe water supply, cooking fuel, health worker density, road density, telephone- density.
Percentage of children aged 12-23 months who received specific vaccines at any time before the
survey
78.4
76.3
55.8
60.0
50.8
90.9
88.6
77.5
79.8
76.8
0.0
20.0
40.0
60.0
80.0
100.0
BCG DPT1 DPT3 MeaslesVitamin A1
Percentage (%)
20052015
ANNEXURE 10. CHILD HEALTH INDICATORS OF CHILDREN UNDER 5 YEARS OF AGE IN
2 WEEKS PRECEDING THE SURVEY.
Child Health Pre NHM (%) Post NHM
#
(%)
Adjusted
Odds Ratio
95% Confidence
Interval
p-value
Diarrhoea Treatment 60.4 62.7 1.1 (0.974, 1.248) 0.122
Number of days after
Diarrhoea Treatment
1.5 1.3 0.9 (0.774, 0.889)
<0.01*
Family Size 2.5 2.2 0.9 (0.881, 0.895)
<0.01*
* Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for place of residence, maternal age,
education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density,
road density, telephone-density.
Proportion of children under age 5 years in 2005 and 2015
Proportion of children under 5 years of age in 2005 and 2015
60.462.7
0
20
40
60
80
20052015
Percentage (%)
Seek Treatment or Advice for Diarrhoea
1.5
2.5
1.3
2.2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Days after DiarrhoeaFamily Size
Mean Value
2005 2015
ANNEXURE 11: THE ITS ESTIMATES OF PRE SLOPE, POST SLOPE AND CHANGE AT
STATE AND NATIONAL LEVEL
State Pre-
Slope
Post-
Slope
Change P-
Value
LCI UCI Remark
India -1.6 -2.2 -0.7 0.058 -1.41 0.033744 Significant
Andhra
Pradesh
-1.0 -2.2 -1.2 0.068 -2.49 0.11 Significant
Assam -0.9 -2.5 -1.6 0.007 -2.72 -0.47 Significant
Bihar -1.0 -1.4 -0.4 0.472 -1.47 0.71 Non-
Significant
Delhi -0.5 -2.2 -1.7 0.122 -3.98 0.53 Non-
Significant
Gujrat -1.1 -2.3 -1.3 0.045 -2.55 -0.016 Significant
Haryana -1.0 -2.5 -1.6 0.017 -2.84 -0.30 Significant
Karnataka -1.5 -2.3 -0.8 0.328 -2.49 0.89 Non-
Significant
Kerala -0.2 -0.4 -0.2 0.633 -0.87 0.54 Non-
Significant
Madhya
Pradesh
-2.4 -2.4 -0.1 0.811 -0.80 0.64 Non-
Significant
Maharashtra -1.5 -1.4 0.1 0.745 -0.77 1.05 Non-
Significant
Orissa -2.9 -2.7 0.2 0.757 -1.29 1.74 Non-
Significant
Punjab -1.0 -2.3 -1.3 0.019 -2.44 -0.22 Significant
Rajasthan -1.3 -2.6 -1.3 0.191 -3.26 0.71 Non-
Significant
Tamil Nadu -1.6 -1.5 0.2 0.827 -1.359 1.68 Non-
Significant
Uttar
Pradesh
-1.8 -3.1 -1.2 0.021 -2.30 -0.20 Significant
West
Bengal
-1.8 -1.2 0.6 0.191 -0.35 1.60 Non-
Significant
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National Health mission:
Impact and Learnings for future
A NITI Aayog Study
Conducted by
Department of Community Medicine & School of Public Health
Postgraduate Institute of Medical Education and Research (PGIMER)
Chandigarh
2
TEAM
Technical Advisor
Dr Rajesh Kumar, Former Dean (Academics), Professor and Head
Principal Investigator
Dr Madhu Gupta, Professor of Community Medicine
Co-Investigators
Dr PVM Lakshmi, Professor of Epidemiology
Dr. Shankar Prinja, Additional Professor of Health Economics
Project Staff
Dr Ekta Sharma, Project Coordinator
Dr Ruby Nimesh, Consultant
Dr Ekta Thakur, Project Associate
Dr Aarti Goyal, Project Associate
3
ACKNOWLEDGMENTS
This study was carried out with the financial support of NITI Aayog, Government of India, and conducted
by Department of Community Medicine & School of Public Health Postgraduate Institute of Medical
Education and Research (PGIMER) Chandigarh.
We gratefully acknowledge the contributions made by the NITI Aayog officers, Dr. V.K. Paul (Member
NITI Aayog), Mr. Alok Kumar, Adviser (Health and Nutrition NITI Aayog), Dr. K. Madan Gopal (Sr.
Consultant NITI Aayog), Dr. Nina Badgyain (Consultant NITI Aayog) for showing their interest in the
study and necessary guidance throughout the study.
We also acknowledge our gratitude to the senior residents, PGIMER, Chandigarh, including Dr. Garima
Sangwan and Dr. Kirtan Raina, who rendered their help during the period of this study.
Special thanks to other research staff of PGIMER Chandigarh including Dr. Adarsh Bansal (Project
officer) for conducting a systematic review on impact of NHM strategies on reproductive and adolescent
health, Dr. Shivani Aloona (Research Officer) for conducting a systematic review on impact of NHM
strategies on neonatal and infant health, Dr. Atul Sharma (Project officer) for working on analysis and
comparison of public sector utilization for health services, out-of-pocket expenditures on hospitalization
of under-five children and delivery cases and associated catastrophic rates using NSSO 60
th
round and
71
st
round data.
4
DISCLAIMER
The Organization Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh
has received the financial assistance under the Research Scheme of NITI Aayog (RSNA-2018) to
prepare this report. While due care has been exercised to prepare the report using the data from various
sources, NITI Aayog does not confirm the authenticity of data and accuracy of the methodology to
prepare the report. NITI Aayog shall not be held responsible for findings or opinions expressed in the
document. This responsibility completely rests with the
PGIMER, Chandigarh. 5
CONTENTS
Sr.
No.
Items Page No.
Executive summary
1. Introduction 14-18
2. Objectives 18
3. Methods 19-35
4.
Results
35-59
60-84
60-63
63-70
70-84
Systematic Review
Secondary Data Analysis
Input/process Indicators
Health Output/Outcome indicators
Impact Indicators and Health Inequalities
5. Discussion 85-89
6. Conclusion 89-92
7 Recommendations 93-96
8 References 281-303
6
9. Annexures
Annexure 1:PRISMA Checklist
Annexure 2: Protocols for systematic review
Annexure 3: MeSH Strategy
Annexure 4: Flow diagram of studies included in systematic review
Annexure 5: Results of total studies included in systematic review
Annexure 6: Characteristics of good quality studies
Annexure 7: Maternal health indicators of women aged 15-49 years
who had had a live birth in the five years preceding the survey.
Annexure 8: Contraceptive methods currently used for family
planning by married women aged 15-49 years.
Annexure 9: Immunization of children aged 12-23 months who
received specific vaccines at any time before the survey.
Annexure 10: Child health indicators of children under 5 years of
age in 2 weeks preceding the survey.
Annexure 11: The Interrupted Time Series (ITS) estimates of pre
slope, post slope and change at state and national level.
97-99
100-133
134-158
159-167
168-261
262-274
275
276
277
278
279-280
7
LIST OF TABLES
Table No. Title Page No.
Table 1 Targets of National Rural Health Mission, National Health Policy
and Sustainable Development Goals
15
Table 2 Grading of studies based upon quality 23-24
Table 3 The variables selected for regression analysis 32-33
Table 4 Number of studies reviewed and included in systematic review 56
Table 5 Health indicators for women aged 15-49 years who had a live
birth in the five years preceding the survey
69
Table 6 Child health indicators of children under 5 years of age in 2005 and
2015
70
Table 7 Infant mortality rate and Neonate mortality rate (per 1000 live
births) of children born in the three years preceding the survey
78
Table 8 Health inequalities for infant mortality rate for children born in the
three years preceding the survey
81
Table 9 Health inequalities for neonate mortality rate for children born in
three years preceding the survey
84
8
LIST OF FIGURES
Figure
No.
Title Page
No.
Figure 1 Main Strategies of National Health Mission 16
Figure 2 Timeline of major strategies implemented under National Health Mission
from 2005 to 2019
23
Figure 3 Relation between thickness of arrow and strength of evidence 25
Figure 4 Flow chart showing the studies reviewed under systematic review and per
PRISMA guidelines
36
Figure 5 Forest plot of studies on institutional deliveries 38
Figure 6 Meta-analysis of studies with outcome as prevalence of low birth weight
babies
42
Figure 7 Meta-analysis of studies with outcome as Exclusive breast feeding
43
Figure 8 Meta-analysis of studies on full immunization coverage
45
Figure 9 Meta-analysis of studies with outcome as recovered children under NRC 46
Figure 10 Meta-Analysis of studies on CPR 49
Figure 11 Meta-analysis of 5 cross sectional studies on WIFS 50
Figure 12 Meta-analysis of 4 RCTs on WIFS 50
Figure 13 Meta-analysis of studies on usage of sanitary napkins
51
Figure 14 Meta-analysis of 15 studies on awareness of menstrual hygiene 52
Figure 15 Meta-analysis of 10 cross sectional studies on ARSH 53
Figure 16 Impact of NHM strategies: Evidence from literature 59
Figure 17 Allocation of funds for NRHM 60
Figure 18 Out of pocket expenditure and public health expenditure 61
Figure 19 Per capita public health expenditure 61
Figure 20 Number of Patient Beds/1000 population 62 9
Figure 21 Trend showing number of ANMs and ASHAs per 10,000 population (2005-
2019)
62
Figure 22 Trend showing doctors and nursing staff per 10,000 population in PHCs
and CHCs (2005-2018)
63
Figure 23 Utilization of public sector for outpatient care 63
Figure 24 Utilization of public sector for hospitalization 64
Figure 25 Out-of-pocket expenditure for under-five child hospitalization 65
Figure 26 Out-of-pocket expenditure on institutional deliveries 65
Figure 27 Catastrophic health expenditure on under-five child hospitalization 67
Figure 28 Catastrophic health expenditure on institutional deliveries 68
Figure 29 Health indicators for women aged 15-49 years who had a live birth in the
five years preceding the survey
68
Figure 30 Percentage of children for various child health indicators in 2005 and 2015 70
Figure 31 Trend of Maternal Mortality Ratio 1997-2017 71
Figure 32 Trend of under-five mortality rate in India, from 2005 to 2019 72
Figure 33 Trend of under-five mortality rate in Indian states, from 2008 to 2016 73
Figure 34 Trend of infant mortality rate in India, from 2005 to 2017. 73
Figure 35 Trend of infant mortality rate as per interrupted time series analysis in
India, from 2005 to 2017.
74
Figure 36 Trend of infant mortality rate in bigger states in India, from 2005 to 2017 75
Figure 37 Trend of infant mortality rate in smaller states in India, from 2005 to 2017 75
Figure 38 Trend of neonatal mortality rate in India, from 2005 to 2019.
76
Figure 39 Trend of neonatal mortality, infant mortality and under five mortality in India,
from 2007 to 2019.
77
Figure 40 Infant Mortality Rate and Neonatal Mortality Rate per 1,000 live births in
2005 and 2015.
77
Figure 41 Trend of Total Fertility Rate in India, from 2007 to 2017. 78
Figure 42 Comparison of infant mortality rate among urban and rural areas in 2005
and 2015.
79 10
Figure 43 Comparison of infant mortality rate among EAG and Non-EAG states in 2005
and 2015.
79
Figure 44 Caste wise health inequalities for infant mortality rate in 2005 and 2015 80
Figure 45 Wealth wise health inequalities for infant mortality rate in 2005 and 2015
80
Figure 46 Comparison of neonate mortality rate among urban and rural areas in 2005
and 2015.
82
Figure 47 Comparison of neonatal mortality rate among EAG and Non-EAG states in
2005 and 2015.
82
Figure 48 Caste wise health inequalities for neonate mortality rate in 2005 and 2015.
83
Figure 49 Wealth wise health inequalities for neonate mortality rate in 2005 and 2015 83
11
LIST OF ABBREVIATIONS
ANC Antenatal Care
ANM Auxiliary Nurse Midwife
ARI Acute Respiratory Infections
ARSH Adolescent Reproductive Sexual Health
AFHCs Adolescent Friendly Health Clinics
ASHA Accredited Social Health Activist
AYUSH Ayurveda Yoga Unani Siddha and Homeopathy
BCC Behaviour Change Communication
CPR Contraceptive Prevalence Rate
DLHS District Level Household Survey
ENMR Early Neonatal Mortality Rate
EBF Exclusive Breast Feeding
FBNC Facility Based Newborn Care
FLWs Frontline Health Workers
FP Family Planning
HBPNC Home based Post Neonatal Care
GDP Gross Domestic Product
ICDS Integrated Child Development Scheme
IMR Infant Mortality Rate
IMNCI Integrated Management of Neonatal and Childhood Illness
JSY Janani Suraksha Yojana
JSSK Janani Shishu Suraksha Karyakram
LBW Low Birth Weight
MCH Maternal and Child Health
MDM Mid Day Meal
MHS Menstrual Hygiene Scheme
MMR Maternal Mortality Ratio 12
MMUs Mobile Medical Units
MOs Medical Officers
MOHFW Ministry of Health and Family Welfare
NFHS National Family Health Survey
NHM National Health Mission
NSSO National Sample Survey Organization
NHP National Health Policy
NMR Neonatal Mortality Rate
NRCs Nutrition Rehabilitation Centres
NRHM National Rural Health Mission
NRHM National Urban Health Mission
OOPE Out of Pocket Expenditure
PHC Primary Health Centre
PNC Postnatal Care
PNMR Perinatal mortality Rate
SBR Still Birth Rate
SDG Sustainable Development Goals
SNCUs Sick New-born Care Units
SRS Sample Registration System
RBSK Rashtriya Bal Swasthya Karyakram
RHS Rural Health Statistics
RKSK Rashtriya Kishore Swasthya Karyakram
RMNCH+A Reproductive Maternal New-born Child and Adolescent Health
TFR Total Fertility Rate
U5MR Under Five Mortality Rate
UNICEF United Nations International Children’s Emergency Fund
VHND Village Health Nutrition Day
VHSNCs Village Health, Sanitation and Nutrition Committee 13
WHO World Health Organization
WIFS Weekly Iron Folic Supplementation 14
INTRODUCTION
The National Rural Health Mission (NRHM) was launched in 2005 by the Government of India
throughout the country, with a special focus on 18 states, to improve the accessibility, affordability and
availability of health care especially to those residing in the rural areas, poor and women. The specific
goals were reducing Maternal Mortality Ratio (MMR) to 100 per 1,00,000 births, Infant Mortality Rate
(IMR) to 30 per 1000 births, and Total Fertility Rate (TFR) to 2.1 within seven years of its implementation
i.e., by the year 2012, which were later extended to be achieved by the year 2020 under National Health
Mission. NRHM goals also included prevention and reduction of anaemia in women aged 15-49;
reducing mortality from communicable/non-communicable diseases, emerging diseases, injuries;
reducing household out-of-pocket expenditure; reducing incidence and mortality from TB by half;
reducing prevalence of Leprosy to below 1 per 10,000 population and incidence to zero in all districts;
annual malaria incidence to be less than 1/1000 population; less than 1% microfilaria prevalence in all
districts and Kala-azar elimination by 2015, less than 1 case per 10,000 in all endemic blocks. Qualitative
goals were having decentralized, community owned, inter-sectoral health delivery systems which could
address issues of water, sanitation, education, nutrition, social and gender equality. In 2013, the
government of India launched the National Health Mission (NHM) which subsumed the NRHM and
additionally launched the National Urban Health Mission (NUHM). The mission committed to raise the
government spending to health from 0.9% to 2-3% of GDP. The mission was extended in 2018 to
continue until 2020.
In 2017, the government has also brought out the National Health Policy (NHP), which aimed at
attainment of the highest possible level of health and well-being for all, at all ages, through a preventive
and promotive health care orientation in all developmental policies and universal access to good quality
health care services without anyone having to face financial hardship as a consequence [1]. The
sustainable development goals were also launched to replace the millennium development goals at the
global level during 2015 [2]. The targets of NRHM, NHP and Sustainable Development Goals (SDGs)
are listed below in the table 1 [2-4]. It was envisaged that NHM strategies will help in reaching SDGs at
the national level. 15
Table 1. Targets of National Rural Health Mission (NRHM), National Health Policy (NHP) and
Sustainable Development Goals (SDGs).
NRHM 2012 NHP targets SDG 2030
Maternal Mortality Ratio /lakh live
births
100 100 by 2020 <70
Neonatal Mortality rate
/1000 live births
- 16 by 2025 <12
Infant Mortality Rate
/1000 live births
30 28 by 2019 < 20
Under 5 Mortality Rate
/1000 live births
- 23 by 2025 <25
Total Fertility Rate 2.1 2 by 2025 -
The major NHM strategies to achieve the goals were health system strengthening by providing free
medicines and diagnostics, infrastructure development, national ambulance services, national mobile
services; human resource strengthening by providing additional Auxiliary Nurse Midwives (ANMs),
Medical Officers (MOs) etc.; flexible financing; communitization including provision of Accredited Social
Health Activists (ASHAs) in each village; improved management; implementing programs like
reproductive maternal neonatal childhood and adolescent health, communicable and non -
communicable diseases; and monitoring the progress. The main strategies and interventions of NHM
and time of launch are summarized in Figure 1 and 2. 16
Figure 1: Main strategies of National Health Mission
1
Maternal and Child Health;
2
Auxiliary Nurse Midwives;
3
Medical Officers;
4
Human Resource;
5
Accredited Social Health Activist;
6
Village
Health Nutrition Day;
7
Village Health Sanitation and Nutrition Committee;
8
Panchayat Raj Institutions;
9
District level Project Management Unit;
10
Block level Project Management Unit;
11
Financial Management Group;
12
National Health System Resource Centre;
13
State Health System
Resource Centre;
14
Family Planning;
15
Janani Suraksha Yojana;
16
Janani Shishu Suraksha Karyakram;
17
Facility Based New-born Care;
18
Sick Newborn Care Unit;
19
Nutrition Rehabilitation Centre;
20
Home based Post-natal Care;
21
Integrated Management of Neonatal and
Childhood Illness;
22
Rashtriya Bal Swasthya Karyakram;
23
Acute Respiratory Infection;
24
Weekly Iron Folic Acid Supplementation;
25
Rashtriya
Kishore Swasthya Karyakram;
26
Adolescent Friendly Health Clinics;
27
Menstrual Hygiene Scheme;
28
Indian Public Health Standard;
29
Common Review Mission;
30
Joint Review Mission.
17
Figure 2. Timeline of major strategies implemented under National Health Mission from 2005 to
2019.
As NHM has completed about 15 years (2005-2020) there is a need to review the impact of NHM on
health measures so that learnings from NHM can be utilized to further improve the outcomes for
achieving Universal Health Coverage (UHC) by 2030. Most of the earlier studies have evaluated the
effectiveness of NRHM strategies in improving the maternal and child health (MCH) outcomes, and most
of these studies were state specific. A planning commission of India evaluated the implementation of
NRHM conducted in seven states in 2011, and observed some improvements in the availability and
utilization of maternal and child health services in rural areas. However, this evaluation lacked the
comparison of the situation before the implementation of the NRHM [4]. A qualitative study by Gupta et
al (2017) in Haryana highlighted that there was increase in the demand and utilization of MCH services
after the implementation of NRHM strategies especially recruitment of accredited social health activists
at the village level in the state of Haryana [5]. Carvalho et al (2014)
and Randive et al (2013)
reported
positive impact of Janani Suraksha Yojana (JSY) on child immunization and institutional delivery rate, 18
respectively [6, 7]. A study by Prinja et al (2014) showed that the ambulance services led to increase in
institutional delivery rate [8]. Study by Gupta et al (2017) reported increase in utilization of allocated
NRHM funds for MCH strategies which correlated with improvement in health indicators. However,
implementation of NRHM was found to be partial [5]. Review of existing literature indicated that many
studies have been done on assessing the impact of NHM on health, but most of these studies had
focused on some of its components, therefore, a comprehensive evaluation was required.
This assessment was done as part of a larger study, which was proposed by NITI Ayog, to carry out
impact of NHM components in improving the health outcomes, in quantifiable terms so that lessons can
be learnt on what has worked and what has not worked with a specific focus on financing, human
resources and governance, and study the success of the NHM in achieving its said objectives while
focusing on areas of improvements and actionable recommendations in context to the framework
of Ayushman Bharat and India’s commitment for SDG Goals, UHC and Health Equity. There were
three components of the larger study including:
1. Impact of NHM on health outcomes
2. Impact of NHM on Health care spending and finances.
3. Impact of NHM on Health systems, Governance and HRH
We have focused on the first component and assessed the impact of NHM on health outcomes by
synthesizing the existing evidence and performing secondary data analysis using national level data
sources such as National Sample Survey Organization (NSSO), National Family Health Survey (NFHS),
Sample Registration System (SRS), and Rural Health Statistics (RHS).
OBJECTIVES
1. To synthesize the evidence on impact of National Health Mission on health outcomes by
conducting the systematic review.
2. To evaluate the impact of National Health Mission on health care utilization, heath outcomes
and health care inequalities by secondary data analysis.
19
METHODS
Evaluation Framework
We have considered the logic model i.e., Input-process-output-outcome-impact model for evaluation [9].
Inputs include the various NHM strategies (e.g., number of ASHAs recruited), the processes include the
implementation of strategies/activities (e.g., number of ASHA’s trained in providing reproductive and
child health care), outputs include the activities done/completed (e.g., number of pregnant women
contacted by ASHA’s in the village and counselled for institutional deliveries), outcomes include the
coverages (e.g., institutional delivery rate) and impact includes the effect on the mortality rates (e.g.,
reduction in maternal mortality ratio). The underlying principle of the logic model evaluation framework
is that unless the inputs and processes are in place you might not achieve outputs, and unless you
achieve the particular outputs you might not achieve outcomes and the resultant impact of the program.
Objective wise methodology is described below
Methodology of Objective 1
To synthesize the evidence on impact of National Health Mission on health outcomes by
conducting the systematic review.
Study design
We did systematic review to synthesize the evidence on impact of National Health Mission’s strategies
on health outcomes, as per Preferred Reporting Items for Systematic Reviews and Meta-Analysis
(PRISMA) guidelines. The PRISMA checklist is presented in Annexure 1 and protocol of the systematic
review as per the outcome variables is presented in Annexure 2.
Eligibility Criteria of studies
Publication period considered 20
Studies published between the years 2005 and 2019 were searched.
Geographical area
All states and union territories of India.
Participants
Pregnant women, antenatal women, postpartum women, neonates, infants, children up-to the
age group of 5 years , women in reproductive age group (15-49 years), eligible couples,
adolescents, ASHA workers, ANMs.
Interventions
NHM strategies considered for review included:
• Health System Strengthening: Availability of free Medicines, free Diagnostics and free diet in
the health facilities, National Ambulance services, National Mobile Medical Units (NMMUs),
Infrastructure development
• Human Resource Strengthening: Availability of Medical Officers (MOs), specialists, Auxiliary
Nurse Midwives (ANMs).
• Communitization: Accredited Social Health Activist (ASHA), Village Health Nutrition Day
(VHNDs), Village Health, Sanitation and Nutrition Committee (VHNSCs).
• Reproductive health strategies: Family planning services, newer contraceptives.
• Maternal health strategies: Janani Suraksha Yojana (JSY), Janani Shishu Suraksha Karyakram
(JSSK).
• Neonatal Health strategies: Facility Based Newborn Care (FBNC).
• Child health strategies: Immunization, Nutritional Rehabilitation Centres (NRCs), Home Based
Post Neonatal Care (HBPNC), Integrated Management of Neonatal and Childhood Illness
(IMNCI), Rashtriya Bal Swasthya Karyakram (RBSK), Acute Respiratory Infection (ARI) and
Diarrhoea control. 21
• Adolescent health strategies: Weekly Iron Folic Supplementation (WIFS), Rashtriya Kishor
Swasthya Karyakram (RKSK), Adolescent Friendly Health Clinics (AFHC), Menstrual Hygiene
Scheme (MHS)
NHM strategies NOT considered for review were:
Strategies like Communicable and Non communicable disease and monitoring progress (IPHS,
CRM, and JRM) have not been considered in this review.
Other interventions considered for review were:
• Road connectivity
• Mobile connectivity
• Water supply
• Sanitation
Comparisons
As applicable depending upon the study design.
Outcome
The outcome variables were:
Maternal Mortality Ratio (MMR)
Institutional delivery rate
Perinatal Mortality Rate (PNMR)
Neonatal Mortality Rate (NMR)
Infant Mortality Rate (IMR)
Under 5 Mortality Rate (U5MR) 22
Total fertility rate (TFR)
Contraceptive Prevalence Rate (CPR)
Full immunization coverage
Decrease in nutrition among children
Increase in Vitamin A supplementation
Early detection and treatment of childhood illnesses
Proportion of adolescents utilizing Adolescent Reproductive and Sexual Health (ARSH) services
Proportion of girls aware of menstrual hygiene and using sanitary napkins
Geographical, socioeconomic maternal health inequalities
Geographical, socioeconomic and gender child health inequalities
Study design
Studies with any study design such as randomized control trials, cluster randomized control trials, quasi
experimental, before-after studies, cohort, case control, cross sectional and qualitative studies were
included.
Information Sources
Studies were searched systematically using databases like PubMed, EMBASE, Google and Google
Scholar, and databases of agencies like Ministry of Health and Family Welfare (MoHFW), National
Health Systems Resource Centre (NHSRC), United Nations International Children’s Emergency Fund
(UNICEF), World Health Organization (WHO). Unpublished studies or grey literature, non-human
studies, studies with a focus on other countries, published in language other than English or as abstract
only were excluded in this review. 23
Search
Medical Subject Headings (MeSH) words in relevance to each strategy and outcomes were prepared
for searching potential studies. (Annexure 3). The search strategy was prepared by two researchers
independently. The cross references given in the selected articles were also searched to identify more
relevant articles. Further, hand-searching of the contents of reputed public health journals and
conference proceedings was conducted.
Study Selection
A two-stage screening process was followed based on pre-defined and explicit inclusion and exclusion
criteria:
1. First stage: Articles were included based on the title and abstract
2. Second stage: Selected Articles were further screened and included based on the full-text
Criteria for assessing the quality of the studies
The quality of eligible studies was assessed based on three criteria:
1. Indexing of journal in PubMed or Scopus.
2. Studies having sufficient sample size.
3. Confounding variables controlled in the analysis.
The studies were graded on the basis of above criteria as explained below:
Table 2. Grading of studies based upon quality.
Quality Description
(+++) Very Good Studies fulfilling all the three criteria.
(++) Good Studies fulfilling any two criteria. 24
(+) Adequate Studies fulfilling any one criteria
Data collection process
The data was extracted from the selected studies by two independent reviewers using standard data
extraction forms. The discrepancy between the two researchers was resolved by involving the third
reviewer.
Data analysis and synthesis of results
The statistical analysis approach developed by Cochrane collaborations was applied to
synthesize data [10].
The possibility of conducting a meta-analysis was kept open depending upon the
availability of studies with similar intervention and outcome and study design. The pooling of results
was undertaken after considering clinical and methodological heterogeneity using statistical
software Review Manager version 5.1 (RevMan) or STATA for meta-analysis.
Logic model was used to synthesize the evidence from good quality studies and the pathways for the
impact of the NHM strategies on health care utilization, health inequalities and maternal and child
mortality were identified. As per this framework, NRHM's interventions are the inputs leading to the
outputs, outputs in turn leads to outcomes and outcomes lead to impact of the program. The outputs are
relatively immediate effects that are expected to happen due to inputs and processes such as
improvement in availability of MCH facilities. The outcomes represent the objective of interventions such
as increase in utilization of MCH facilities and impact refers to the health indicators such as reduction in
mortality indicators. In the framework the arrows have been used for showing the relation between input,
output, outcome and impact. The thickness of the arrows indicates the strength of evidence (determined
by the quality criteria of the studies) of that intervention on the outputs as shown in Figure 3 below.
Figure 3. Relation between thickness of arrow and strength of evidence. 25
Methodology of Objective 2
To evaluate the impact of National Health Mission on health care utilization, health outcomes and
health care inequalities by secondary data analysis.
For objective 2, we did secondary data analysis and used logic model evaluation framework for
measuring the impact of NHM on health outcomes. The input, process, output, outcome and impact
indicators were obtained from available national level data sources (rural health statistics, national family
health surveys, national sample survey organization, sample registration system, census, national
health accounts etc.). These indicators were compared from the status before the year 2005 (pre NHM
period), and after the year 2015 (post NHM period). For the analysis, if the recent data was available
after the year 2015, it was accordingly used (like National Health Accounts).
Data sources
Indicators related to financing such as public health expenditure and out of pocket health expenditure
as percentage of the total health expenditure, and per capita public health expenditure were computed
using National Health Accounts (NHA) data [11]. The primary data on public and private sector utilization
and associated out-of-pocket expenditure on hospitalization and deliveries were obtained from National
Sample Survey Organization (NSSO), 60th (2004), 71st (2014) and 75
th
(2018) round data [12, 13].
NSSO conducts recall based household surveys on various topics including health, consumer
expenditure and employment.
Arrow thickness Strength of evidence
Very strong
Strong
Intermediate
Weak 26
The set of information on health system strengthening and human resources was obtained from Rural
Health Statistics (RHS) reports, year 2005 to 2018 [14, 15], ASHA updates, year 2010 to 2019 [16] and
Registers of Professional Councils [14, 15].
The status of National Health Mission’s outcome indicators (also known as dependent variables) and
predictor variables were obtained from the nationally representative demographic survey, National
Family Health Survey (NFHS), round 3 (2005-06) [17] and National Family Health Survey, round 4
(2015-16) [18]. Data was collected from:
109,041 households and 124,385 women, interviewed in NFHS round 3 [17]
628,892 households and 689,246 women, interviewed in NFHS round 4
[18]
Information on neonatal mortality rate was obtained from NFHS. Data on infant mortality rate was
obtained from NFHS and Sample Registration System (SRS) [17-19]. Latest Child Mortality Estimates
were used for child health indicators as obtained from SRS or Unicef’s mortality estimates. Data on
maternal mortality ratio was obtained from SRS year 1990 to 2016 [19].
The information on socio-demographic variables, road density, telephone density and health worker
density were collected from NFHS [17, 18], Ministry of Road transport & Highway [20, 21], Department of
Telecommunications [22], Rural Health Statistics, Registers of Professional Councils [14, 15] and ASHA
updates [16], respectively.
Input/process indicators
Financing indicators
Total health expenditure: Total health expenditure constitutes current and capital expenditures
incurred by Government and Private Sources including external funds.
Out of pocket expenditure (OOPE): Out-of-Pocket Expenditures on Healthcare (OOPE) are payments
made by an individual at the point of receiving healthcare goods and services. 27
Catastrophic health expenditure for hospitalization: Catastrophic health expenditure for
hospitalization (or delivery) is defined as the health expenditure of a household due to hospitalization
(or delivery) being above 25% of the usual household consumption expenditure over last one year from
the date of survey.
Health System strengthening and Human Resource indicators
Hospital beds: Number of government hospital beds per 1000 population.
Auxiliary Nurse Midwife (ANMs): Number of ANMs per 10,000 population in rural areas.
Accredited Social Health Activist (ASHA): Number of ASHAs per 10,000 population.
Doctors: Number of doctors (Allopathic doctors, AYUSH doctors, dental surgeons) per 10,000
population in primary health centres (PHCs) and community health centres (CHCs).
Nurses: Number of nurses per 10,000 population in PHCs and CHCs.
Health Output/Outcome indicators
Maternal Health Indicators
First Trimester Registration: First antenatal care visit during first three months of pregnancy.
Three ANC Check-ups: Women getting at least 3 Antenatal care check-ups during pregnancy.
Adequate ANC: The antenatal care was termed adequate if any four of these seven criteria were met.
1. Weighed during Pregnancy
2. Blood pressure taken during pregnancy
3. Told about complications during pregnancy
4. Told about place to go in case of complications
5. Urine sample taken during pregnancy
6. 100 IFA tablets given during pregnancy
7. Blood sample taken during pregnancy
Two Doses of Tetanus Toxoid Injection: Two doses of tetanus toxoid injection one month apart before
delivery if the woman has not previously been vaccinated. One dose of tetanus toxoid injection if the
woman had two doses of tetanus toxoid injection in the previous pregnancy within 3 years of the current
pregnancy. 28
100 Iron Folic Acid Tablets: Received 100 iron folic acid tablets during the pregnancy for the most
recent live birth.
Anaemia during Pregnancy: Woman with haemoglobin of less than 11mg/dl was considered to be
anaemic.
Institutional Delivery: Delivery in public, private, NGO / Trust hospital or health facility.
Postnatal Check-up: The woman who received a postnatal check-up.
Child Health Indicators
Breast feeding within an hour: Provision of mother's breast milk to infants within one hour of birth is
referred to as “early initiation of breastfeeding”
Exclusive Breastfeeding: Infant received only breast milk for first six months of life. This was estimated
for infants who were in the age group of 6-12 months.
Fully Immunized Children: To be called fully immunized, a child aged 12-23 months must have received
one dose of BCG vaccine, which protects against tuberculosis, three doses of DPT vaccine, which protects
against diphtheria, pertussis (whooping cough), and tetanus toxoid injection, three doses of polio vaccine
and one dose of measles vaccine. Children aged 12-23 months who received specific vaccines (BCG,
DPT1, DPT3, Measles and vitamin A1) at any time before the survey, ascertained by either vaccination
card or mother’s report.
Acute Respiratory Infection Incidence: Children under five years of age with symptoms of short, rapid
breathing which is chest-related and/or difficult breathing which is chest-related in the 2 weeks preceding
the survey.
Diarrhoea Incidence: Children under five years of age with diarrhoea at any time in the 2 weeks
preceding the survey.
Diarrhoea Treatment or Advice: Children under five years of age with diarrhoea at any time in the 2
weeks preceding the survey, for whom advice or treatment was sought.
Number of days after Treatment for Diarrhoea was sought: Days after which advice or treatment for
diarrhoea was sought for children under five years of age.
Reproductive Health Indicators
Family Size: Total number of children alive at the time of the survey who were given birth by women. 29
Contraception Rate: The currently married women aged 15-49 years who currently use any method of
contraception (female sterilization, male sterilization, condom, intra uterine devices and contraceptive
pills).
Impact Indicators
Infant Mortality Rate (IMR): Number of deaths per 1000 live births of children at ages 0 to 11 months
for three years preceding the survey.
Neonate Mortality Rate (NMR): Number of deaths per 1000 live births of children at age 0 to 1 month
for three years preceding the survey.
Maternal Mortality Ratio (MMR): Number of maternal deaths per lakh live births.
Covariates
Socio-Demographic variable: The socio demographic variables are given below:
Type of House: Houses were categorized into three groups: kuccha house, pukka house and kuccha
pukka house. If wall, roof and floor of house were pukka then house was considered as pukka, kuccha
pukka if any of two (wall, roof and floor) are pukka and if any of two (wall, roof and floor) are kuccha, house
is defined as kuccha.
Cooking Fuel: Cooking fuel used by respondents has been categorized into three categories:
LPG/electricity, kerosene and biomass.
Availability of Toilet (Sanitation): Toilet facility used by household is classified into two categories: No
toilet facility and availability of toilet facility.
Source of Drinking Water: Improved sources of drinking water include piped water, public taps,
standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, and community reverse
osmosis (RO) plants.
Religion: Religion has been categorized into four groups: Hindu, Muslim, Christian and others (Sikh, Jain,
Buddhist, Jewish, Parish etc.)
Caste: Caste of respondent has been categorized into four groups: scheduled caste (SC), scheduled tribe
(ST), other backward class (OBC) and others (general). 30
Maternal Age: Current maternal age is classified in 5-year groups: (15-19), (20-24), (25-29), (30-34), (35-
39), (40-44) and (45-49) years.
Maternal Education: This is a standardized variable providing level of education in the categories: no
education, primary, secondary and higher.
Wealth Index: The wealth index is a composite measure of a household's cumulative living standard. The
wealth index is calculated using data on a household’s ownership of selected assets, such as televisions
and bicycles; materials used for housing construction; and types of water access and sanitation facilities.
It is categorized into five groups: poorest, poorer, middle, richer and richest.
Place of Residence: Whether the respondent is a usual resident of urban or rural area.
Road Density: It is kilometres of roads for 1, 00,000 population in the particular state. It excludes roads
constructed under Jawahar Rozgar Yojana (JRY) and Pradhan Mantri Gram Sadak Yojana (PMGSY).
Telephone Density: It is number of telephone connections for every hundred individuals living within the
particular state.
Health Worker Density: Health worker density is defined as number of doctors, dental surgeons, AYUSH
practitioners, ANMs, GNMs, LHVs, pharmacist who are registered in India and health worker (male),
health assistant and ASHAs, working in government sector; per 10,000 population in the particular state.
States: The focus of this study is on less developed Empowered Action Group (EAG) states of India,
namely, Rajasthan, Bihar, Uttar Pradesh, Madhya Pradesh, Odisha, Chhattisgarh, Uttaranchal and
Jharkhand; and Non-Empowered Action Group (Non-EAG) states.
Data Analysis
The data was analyzed using Microsoft Excel (MS-Excel), Statistical Package for Social Sciences
(SPSS), version 22, R software, version 3.5.2, Review Manager, version 5.1 (RevMan), Software for
Statistics and Data (STATA), version 13.
The NSSO 60
th
round (2004) data on expenditure was inflated year wise up to 2014 using annual
Consumer Price Index from the year 2004-05 to 2014-15. The formula used for this is given below: 31
Inflated Expenditure = (((((((((((Total*1.042) *1.058) *1.063) *1.083) *1.108) *1.119) *1.088) *1.093)
*1.109) *1.063) *1.058).
The NSSO 60
th
round (2004), 71
st
round (2014) and and 75
th
round (2018) data on expenditure was
adjusted for five confounders including religion, caste, household sanitation, and household drinking
water source and wealth status of the household. The data was subjected to cleaning and consistency
check before analysis.
By using RHS 2005 to 2019 data, number of patient beds per 1000 population in pre NHM and post
NHM period were compared. Number of ANMs (per 10,000 population), number of doctors in PHCs and
CHCs (per 10,000 population) and number of ASHA workers were estimated. Health worker’s density
(per 10,000 population) was also included in the analysis.
Data files of NFHS round 3 and NFHS round 4 were screened to select the common outcome variables
related to maternal, child (under-five) and reproductive health. The selected variables from both the data
files were merged, recoded and computed to develop indicators which can be compared between pre
NHM and post NHM period. Logistic regression was done to find out the change in the dependent
variables including maternal, child and reproductive health indicators. Poisson regression was used for
family size, negative binomial regression was done for IMR, NMR and number of days after treatment
was sought for diarrhoea. The socio demographic variables, telephone density, road density and health
worker density were adjusted to see the impact of NHM. For IMR and NMR analysis, telephone density
and health worker density were not included due to ill fit in the model. The analysis was done at all India
level to study the impact of NHM on IMR and NMR. The objective of NHM was also to reduce health
inequalities across states and various groups, hence the data was also analysed across following
domains:
1. EAG states versus Non-EAG states
2. Rural area versus Urban area
3. Caste
4. Wealth Index 32
The impact of NFHS 4 was compared with NFHS 3 for various indicators after controlling effect of social
demographic variables, road, telephone and health facilities.
Control for Confounding variables
For adjusting the confounding variables, regression methods were used. The primary exposure variable/
independent variable was pre and post NHM period. The dependent variables that were studied as per
the indicator group, confounders that were adjusted and the regression method that was used, are
presented in the table 3 below.
Table 3. The variables selected for regression analysis.
Independent
Variable
Indicator
Group
Dependent Variables Regression Covariates
Pre NHM
and Post
NHM
Maternal
Health
First trimester Registration
Three ANC Check-up
Adequate ANC care
Anaemia During
Pregnancy
100 Iron folic acid
Small size of child
Breastfeeding within one
hour
Institutional Delivery
2 Tetanus Toxoid Injection
Exclusively Breastfeeding
Postnatal Check-up
Logistic
Age
Education
Place of Residence
Religion
Caste
Type of House
Sanitation
Safe Water Supply
Cooking fuel
Wealth Index
Road Density
Telephone density
Health Worker
density
Family
Planning
Female Sterilization
Male sterilization
Condom
Intra Uterine devices
Contraceptive Pills
Contraception rate
Family Size Poisson
Child Health
Acute Respiratory
Infection
Diarrhoea
Diarrhoea Treatment or
Advice
Logistic
Number of days after
which treatment was
sought for diarrhoea
Negative
Binomial 33
BCG
DPT1
DPT3
Measles
Vitamin A1
Fully Immunized
Logistic
Age
Education
Place of Residence
Religion
Caste
Type of House
Sanitation
Safe Water Supply
Cooking fuel
Wealth Index
Road Density
Telephone density
Health Worker
density
Institutional Delivery
Infant Mortality rate
Neonate Mortality Rate
Negative
Binomial
Age
Education
Place of Residence
Religion
Caste
Type of House
Sanitation
Safe Water Supply
Cooking fuel
Wealth Index
Road Density
An interrupted time series (ITS) was also done using SRS data to evaluate the impact of the NHM
implementation on mortality. The NHM was implemented in the entire country in order to improve the
coverage of various health indicators. In such a scenario, the possibility of conducting a randomized
control trial which is being considered as gold standard for evaluating the impact of an intervention was
ruled out due to the absence of control group. This difficulty was dealt by utilizing the technique of
interrupted time series (ITS). This procedure helps to compute the change in the slopes of IMR before
and after the introduction of NHM with a two-step segmented time series regression analysis. The year
wise data obtained on IMR from SRS was divided into two parts, namely pre intervention data and post
intervention data. As the advent of NHM was considered to be the year 2005, hence this was treated as
the cut-off point. However, choosing 2005 as the cut-off point is quite early to measure the impact of
NHM implementation especially on mortality indicators, as initial few years might be utilized to develop
programme strategies and to make it functional. Therefore, we have used year 2009 as the cut-off point
especially for measuring the impact on IMR. In order to evaluate the impact and comparing the time 34
trends before and after intervention, we have utilized the method of ITS along with auto regressive
integrated moving average (ARIMA) model. This methodology of segmented time-series regression
analysis works in two steps. Firstly, the time series modelling adjusts for components like non-
stationarity, seasonality (depending upon the data) and auto-correlation. Secondly, the multiple linear
regression helps to calculate the estimates for change in level and trend separately, considering the
adjusted time series as an outcome variable in the regression equation [23]. A change in level is defined
as the difference between the observed level at the first intervention time point and that predicted by the
pre-intervention time trend, and a change in trend is defined as the difference between post- and pre-
intervention slopes. Finally, a positive (negative) change in level and slope indicates an increase
(reduction) in outcome variable. As stated earlier, the outcome variables in our analysis was IMR. The
following equation summarizes this multiple linear regression approach:
??????=�+ �
1�+�
2??????ℎ??????�??????+ �
3??????��??????�????????????�??????�� (1)
As a part of this analysis, the adjusted time series of outcome variable is included in the first variable
‘Y’. The time variable ‘t’ includes the time points of observations. The phase variable is coded as 0 and
1 for pre and post-intervention period respectively. Finally, the fourth variable ‘Interaction’ takes zero
value up to year 2005, beyond which it takes up the same value as that of variable ‘t’. Now, the coefficient
�
1of time ‘t’ yields the slope of the regression line pre-intervention, �
2 represents the change in intercept
and coefficient �
3of ‘interaction’ gives the change in slope from pre- to post-intervention.
It is important to note that in order to evaluate the impact of the intervention using ITS method, the
sufficient number of observations before and after the intervention was available only in case of IMR at
the national and state level [23]. In fact, the MMR reported in the various surveys provide the data in a
span of three years which resulted in the insufficient observations for utilizing the technique of ITS.
Although, the U5MR is not reported at the intervals of three years but the data on this indicator was
available 2008 onwards constituting only 9 observations to the present date. Apart from this, this was
not available before the inception of intervention rendering this to be inappropriate for the comparison
purpose. Hence, the impact of the NHM is evaluated only considering the IMR at national and state
level. These estimates of pre slope, post slope and change at the juncture for all the states are computed 35
by applying ARIMA (1, 0, 0) while adjusting for trend, auto correlation imbibed in the data before
evaluating the estimate of change using a regression model mentioned in equation 1.
RESULTS
FINDINGS OF SYSTEMATIC REVIEW
Total 101,290 studies were identified that had reported the effect of NHM/NRHM on maternal (n=2759),
child (n=82023), adolescent (n=1062), reproductive (n=6261) health, and health inequalities (n=9185)
through systematic review as per the search strategy, as shown in Table 3. After removal of duplicates,
there were total 49,666 studies (2083 on maternal health, 40285 on child health, 2987 on reproductive
health, 488 on adolescent health and 3823 on health inequalities) that were eligible for screening. Out
of these, total 46,469 studies (1803 studies on maternal health, 37687 studies on child health, 2857
studies on reproductive health , 383 studies on adolescent health and 3739 studies on health
inequalities) were excluded based on title and abstract. The abstracts of remaining studies that had
reported the NHM/NRHM effect on maternal health (n= 280), child health (2598), reproductive health
(n=130), adolescent health (n=105) and health inequalities (n=84) were preliminarily selected for full text
review as per the inclusion criteria. On the basis of review of full length studies, total 2809 studies were
excluded as per the exclusion criteria (217 studies on maternal, 2385 on child, 81 studies on
reproductive, 54 on adolescent health and 72 on health inequalities). Therefore total 388 studies were
included in the final analysis as shown in figure 4. The results of all these studies have been explained
in annexure 5.
36
Figure 4. Flow chart showing the studies reviewed under systematic review and per PRISMA
guidelines.
As shown in above figure, out of total 388 studies; 63 studies focused on impact of NHM on maternal
health, 213 studies on child health, 51 studies on adolescent health, 41 studies on reproductive health
and 12 studies on health inequalities. The characteristics of these studies have been explained in
annexure 5.
The result of the systematic review is presented for the studies published during the period from
2005-13 (during NRHM implementation), and 2013-2019 (corresponding to NHM implementation).
Findings of studies reviewed for maternal health outcomes
Of the 65 studies identified for maternal health, 46 (25 pooled) were on institutional delivery and 19 on
maternal mortality ratio.
Institutional delivery 37
The description of the studies which were pooled and not pooled are given in Annexures 5.1.2 and
5.1.2.3 respectively. There were 25 studies [24-48] which were pooled and 21 studies which were not
pooled [7, 44, 49-67].
Systematic review of studies on maternal health published before the year 2013, found that institutional
deliveries increased after introduction of Janani Suraksha Yojana (JSY) as cash incentives under JSY
had positive association with institutional deliveries[7, 26, 31-34, 54]. But not all beneficiaries of JSY had
opted for institutional deliveries [31, 32, 34]. Also, cash incentives were not provided to all beneficiaries.
Coverage of JSY was also reported to be low during the early implementation period [32]. The reason
for this had been cited as low awareness among beneficiaries, not having the required documents to
prove the eligibility or administrative weakness in early stage of implementation [32]. It is also reported
that JSY scheme had increased the number of institutional deliveries without making effort to promote
quality antenatal care (ANC) and early detection and treatment of complications [53]. Studies published
after 2013, have shown that JSY was effective in increasing the institutional delivery rate [47, 48, 68].
Significant increase in institutional deliveries was also observed after the introduction of free referral
transport [8]. In the EAG states as a whole, there was an increase of 13%- 40% points in the uptake of
institutional delivery in during NHM period [64]. ASHA had played significant role in increasing
institutional deliveries by behaviour change and communication. There were 3 studies on ASHAs which
showed that ASHAs have also played a major role in improving maternal health by enhancing the
knowledge of pregnant women/mothers [45, 69, 70]. Positive relationship was found between visit of
ASHA and utilization of maternal health services [65].
The pooled institutional delivery rate from 25 studies [24-48] with number of pregnant women ranging
from 147 to 182869 was found to be 71.2% from the year 2007-2018 after meta-analysis done in this
study. (Figure 5). Of these 25 studies, 16 were on JSY, 3 on ASHA, 2 on birth preparedness and
complication readiness and 2 on referral transport, 1 on Janani Sishu Suraksha Karyakaram and 1 on
antenatal care. 38
Figure 5. Forest plot of studies on institutional deliveries.
Heterogeneity= 99.69% (very high because of sample size variability)
Maternal Mortality Ratio
Systematic review of 19 studies [57, 58, 61, 71-86] on maternal health found that during NHM period
there has been decline in MMR. The detailed description has been given in annexure 5.1.1. The decline
in MMR was observed in 16/19 studies. Results from 16 studies found that range of MMR reduction
varied from 7% to 71.1% during NHM period after implementation of strategies like JSY, referral
transport, institutional deliveries. On the contrary, increase in maternal deaths reported in the tertiary
care hospitals due to increase in the load of institutional delivery in three studies, indicating poor quality
of intranatal services [84-86].
Overall (I^2 = 99.69%, p = 0.00)
Govil D et al.(2013)
Limm et al(2010)
Mukhopadhyay et al.(2016)
Sidney K et al.(2014)
Mukhopadhyay DK et al.(2016)
Farah N. et al, (2015)
Ved R et al.(2012)
Vikram K et al.(2011)
Kilaru A. et al.(2010)
Siddaiah A et al.(2018)
Kumar S et al. (2017)
Sidney K et al.(2012)
Strehlow MC at el. (2016)
Khes SP et al.(2017)
Kaur H. et al.(2015)
Uttekar BP et al.(2007)
Kumar et al(2015)
Mukhopadhyay DK et al.(2013)
Mandal DK et al(2010)
Study
Amudhan S et al(2013)
Salve H et al. (2017)
Nipte D. et al.(2015)
Sinha S. et al. (2012)
Seth A et al. (2017)
Panja TK et al.(2012)
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
-.50.511.5 39
Findings of studies reviewed for child health outcomes
It is reported that NHM has been successful in reducing neonatal, infant mortality, under five mortality
and perinatal mortality rate over a period of time, through implementation of the schemes like Home
based Post Neonatal Care (HBPNC), Facility Based Newborn Care (FBNC), Sick Newborn Care Units
(SNCUs), Integrated Management of Neonatal And Childhood Illness (IMNCI), Essential Newborn Care
(ENC) training, JSY, ASHA.
Neonatal Mortality Rate
Three studies reported impact of NRHM/NHM on neonatal mortality [57, 87, 88] (Annexure 5.2.2). Eight
studies were focused upon specific strategies of NHM and neonatal mortality rate as an outcome [89-
96] (Annexure 5.2.3). Six studies were having essential newborn care practices as an intervention [70,
97-101] (Annexure 5.2.4). Four studies were based upon FBNC [102-105] (Annexure 5.2.5). IMNCI was
an intervention in eight studies [94, 106-112] (Annexure 5.2.6 and 5.2.11). Secondary data was
analysed in 5 studies [113-117] and ten studies were found with HBPNC by ASHAs as an intervention
[69, 118-126] (Annexure 5.2.7). In a recent study by Bora et al (2018), it is reported that for reaching
sustainable development goal 3 target for 2030 for the NMR and the U5MR, the estimated NMR for India
for the period 2015-16 is about 2.4 times higher, while the estimated U5MR is about double [117]. They
have done the district wise analysis and observed that only 9% districts have already reached the NMR
SDG targets (12/1000 live births), while 1/3 (177) will not be able to achieve this target. Majority of the
high districts are located in EAG states, but a few also fall in rich and advance states.
Six studies were found reporting early neonatal mortality as an outcome (annexure 5.1.1) [57, 87, 90,
127-130]. The studies published before 2013 period reported that average annual rate reduction (AARR)
in early neonatal mortality rate (ENMR) was found to be more (4.3) in post NRHM than pre NRHM period
(-3.8). Average annual rate reduction (AARR) in early neonatal mortality rate (ENMR) in three epochs
(pre-NRHM 2002-05, early post NRHM 2006-09, and later post NRHM 2010-13) was -3.8, 2.5 and 4.3
[57]. Decline in ENMR for rural areas was 6 points (19%) from 2005 to 2013, and in urban areas it was
5 points (31%). Post 2013 period, ENMR declined from 28 to 22, indicating a point decline of 6 and 40
percentage decline of 21%. The maximum point decline was seen in Orissa (13 points) and minimum in
Himachal Pradesh and Jharkhand (2 and 0 point each) [131]. The NMR declined from 37 to 28 indicating
a point decline of 9 and percentage decline of 24% [57, 88, 95, 131]. The maximum point decline was
seen in Orissa and Chhattisgarh (16 and 14 points, respectively) and minimum in Jharkhand (2 point).
The maximum percentage decline is seen in Punjab (47%) and minimum in Jharkhand (7%). National
NMR had declined from 37 (2005) to 31(2011) to 28(2013) per 1000 live births. NMR has declined in
almost all the states [131].
NMR was lower in those who received a visit by community health worker on day one by than in those
who received no visit [106, 108]. Neonatal mortality was significantly lower when the child’s village was
closer to the district hospital [106]. Neonatal tetanus mortality rate fell from 1·6 per 1000 live births in
2000 to less than 0·1 per 1000 live births in 2015 [132]. Average annual decline in mortality rates from
2000 to 2015 was 3·3% for neonates. ASHA had played a significant role in improving the neonatal
health through home based preventive and curative neonatal care, prioritizing and addressing neonatal
and maternal problems, and community mobilization efforts to increase the utilization of neonatal health
care services [95, 106, 108, 118]. There was reduction in neonatal mortality through participatory
meetings of ASHA with women’s groups as NMR was 30 per 1000 live-births in the intervention group
and 44 per 1000 live-births in the control group [95]. Home visits by community health workers were
associated with a reduced risk of mortality during the neonatal period. HBPNC by ASHA was found to
be an effective strategy as due to this 74% mothers started breastfeeding within the first hour, 87% fed
colostrum, and 58% mothers exclusively breastfed their newborn. Significant increase in trend of unsafe
newborn care practices (bathing baby before 48 hours, unclean cord) with regards to early bathing and
cord care with fewer visits by ASHA was found. Regarding Facility based new born care (FBNC), it
was found that there has been improvement in newborn care and survival rate (74.4%- 85%) due to
provision of manpower & equipment’s in SNCU during NHM implementation period. Only 22.8% of the
newborn care corners (NBCCs) were found to be fully functional, majority (68.4%) were partially
functional, and 9% were non-functional [102]. As per evidence form Jabalpur, MP, NMR was reduced
by 12% after provision of SNCU. Estimated neonatal deaths averted were 111(7%) out of 1590 41
admissions compared to 200(19.1%) out of 1048 admissions in previous year (p value <0.001).
Improved survival and reduced morbidity after establishment SNCUs was reported [96]. Referral out
(5%-1.7%), death rate (11.6%-9.6%), LAMA (9%-3.7%) rates were decreased after SNCU was
functional [92, 96, 102-105]. Also it was found in one study that all the health personnel were not fully
trained in Navjat Shishu Suraksha Karyakram (NSSK) [105]. Regarding Essential New Born Care
(ENBC) it was found that in the year 2011, none of the CHCs have fully equipped facility based newborn
care services (including newborn corner and newborn care stabilization unit [97], but studies published
after 2013 period showed that, safe childbirth checklist (SCC) were used in 86% of the observed
deliveries in intervention facilities in a study conducted in Rajasthan [70]. 65% newborns were breastfed
within an hour after birth and 5.9% were prelacteal fed [100]. Trained anganwadi workers had enhanced
the knowledge of childhood illness and their management as compared to IMNCI untrained counterparts
[108]. However, implementation of IMNCI had no effect on inequities in neonatal mortality [94].
The metanalysis, done as part of this study, of the pooled studies published between 2008 to 2016 found
the prevalence of low birth babies (10 studies pooled) to be 28%, and exclusive breast feeding (26
studies pooled) to be 47%, indicating that prevalence of low birth weight babies did not reduce and
exclusive breast feeding did not improve much after implementation of the neonatal health strategies
[133-142]. (Annexure 5.2.8).
42
Figure 6: Meta analysis of studies with outcome as prevalence of low birth weight babies
Infant Mortality Rate
There were sixteen studies which reported IMR as an outcome [143-158] (Annexure 5.2.9). As per
Khurmi et al study (2015), annual rate of reduction of IMR was nearly 2 percent in 2000-05 and its
previous years, but after implementation NRHM it has been accelerated to 4 percent in 2005-10 and
nearly 6 percent in 2011 [143-147]. IMR declined from 58 to 40 (for India indicating a point decline of 18
and a percentage decline of 31%. The maximum point decline was seen in Orissa (24 points) and
minimum in Mizoram (increased by 15 points) [131]. The maximum percentage decline was seen in
Tamil Nadu (43%) and minimum in Mizoram (increased by 75%).
Study published before the year 2013 showed that, 48.6% ASHAs were unaware of preventive actions
to be taken for Vitamin A and 20% of the ASHAs did not feel the need for referral for a child with diarrhoea
who is unable to drink or breast feed. Also ASHA-investigator agreement on the need to assess infants
was found to be intermediate. ASHAs had played a major role for improving knowledge of mothers 43
regarding infant care and creating awareness about exclusive breast feeding [69, 119-122]. There has
been improvement in rate of exclusive breastfeeding as the pooled prevalence of exclusive breast
feeding was found to be 47% from the year 2008-18.
Figure 7: Meta analysis of studies with outcome as Exclusive breast feeding
There were 26 studies which reported exclusive breastfeeding as an outcome [98, 159-181] (Annexure
5.2.13). Post 2013 publication period, it was found that average score of the ASHAs in child health care
was 87%, around 81% of children in immunization were motivated by ASHAs and 80.93% knew about
exclusive breast feeding correctly. Also 5.41% of the ASHA had poor, 83.78% had average and 10.81%
had good level of knowledge score regarding HBPNC respectively [125]. It was also found that, all of 44
the ASHA’s helped in immunization and 24.65% gave advice to mothers about breast feeding [126]. So
overall, it was observed that that during the early implementation of the ASHA’s scheme, her knowledge
related to vitamin A supplementation, early diagnosis and prompt referral of children suffering with
diarrhea/pneumonia was poor, and gradually with further trainings her knowledge and skills were
improved especially related to immunization but it needs to be further improved for home based post
natal care and exclusive breast feeding.
Role of IMNCI
Fourteen studies were found focused upon Integrated Management of Neonatal and Childhood Illness
(IMNCI) [70, 89, 94, 97, 101, 106-110, 112, 117, 155, 182]. The existing evidence indicated that IMNCI
implementation could reduce the infant mortality rate in an experimental setting (adjusted hazard ratio
of IMR 0.85, 95% confidence interval 0.77 to 0.94, were significantly lower in the intervention clusters of
IMNCI than in control clusters) as per Bhandari et al study (2012) [94]; and improved the skills of the
health care workers in implementation settings as per Thummakomma et al (2016) and Chishty et al
study (2016) [106, 111]. Sensitivity of IMNCI criterion in correctly identifying sick infants of age 0-2
months was 90.02%, specificity was 63.10%, positive predictive value being 92.44% and negative
predictive value is 55.79% as per Thummakomma et al (2016) study [106].
Under 5 Mortality Rate
Nine studies reported under 5 mortality rate [115, 158, 180, 183-188] (Annexures 5.2.15). NHM’s child
health strategies like NRCs, immunization, management of ARI and diarrhoea has played a significant
role in reducing Under Five Mortality Rate (U5MR). U5MR fell at a mean rate of 3.7% per year between
2001-2012, from 96/1000 live births to 57.3/1000 live births. The number of districts with >80
deaths/1000 live births also reduced from 384 to 80 districts in the same period [115]. Average annual
decline in U5MR from 2000-15 was 5.4%, annual decline from 2000-05 was 4.5%, and annual decline
from 2005-15 was 5.9%. Decline in mortality rate from pneumonia was found to be 63%, decline in 45
diarrhea rate was 66% and decline in measles mortality rate was 3.3 to 0.3/1000 live births [132].
Proportion of Under 5 Mortality in Vitamin A supplemented children vs. non supplemented was 8.4%
vs.11.4% [186].
Studies on immunization coverage (annexure 5.2.15) found that strategies under NRHM such as Mission
Indradhanush, financial assistance from JSY had played a significant role in improving vaccination
coverage [6, 63, 188-207]. Meta analysis of 16 studies found the pooled immunization coverage among
children to be 77% from the year 20014-19 (Figure 8). The improved vaccination coverage was also
found to be associated with decrease in ARI and diarrhea in children as the incidence was less in
immunized children than non-immunized children [189, 192-195].
Figure 8: Meta analysis of studies on full immunization coverage
46
Studies on National Rehabilitation Centers (NRCs) showed that NRCs were good initiative under NHM
as percentage of pooled recovered children under NRCs was 77% as per metaanalysis of the studies
from the year 2012-18 (Figure 9) [208-222].
Figure 9: Meta analysis of studies with outcome as recovered children under NRC
Studies published after the year 2013 showed that , only 25% of the children in India received vitamin A
supplementation (VAS), rural children (72%) and children of educated mothers were more likely to
receive vitamin A supplementation than others (urban- 28.2%). There was an Increase in the mean full
VAS coverage in seven states from 44.7% to 67.3%. Also there was 40.3% annual decrease in the
number of poor children who did not receive two VAS doses [186, 223-225] (Annexure 5.2.16).
Other child health strategies like rashtriya bal swasthaya karyakaram (RBSK) has also played an
important role in screening, early diagnosis and management of severe illnesses like heart disease, birth 47
defects [226, 227]. However, its impact on reduction on under 5 child mortality is not documented in the
existing literature.
Perinatal mortality
Fourteen studies reported perinatal mortality rate as an outcome [26, 52, 127, 228-238]. The studies
have been described in annexure 5.2.1. Singh S et al (2017), has reported that in rural areas of India,
hospital deliveries have increased during 2005–2013 from 24.4% to 69.7% and PNMR has declined
from 40 to 28 per 1000 births. At the national level, in the rural areas, relative increase in hospital
deliveries was 185.7% and relative decline in PNMR was 30% and it was significantly correlated. At the
state level, there was significant correlation between the rise in hospital delivery rate and decline in
PNMR (r 0.4, p 0.04) [52]. There is further evidence that have shown that increase in institutional delivery
rate had reduced the perinatal mortality rate [declined from 41.3 to 34.6 (p=0.008) deaths per 1,000
births in Belgaum and from 47.4 to 40.8 (p=0.09) in Nagpur) and still births (declined from 22.5 to 16.3
per 1,000 births in Belgaum and from 29.3 to 21.1 in Nagpur (both p=0.002)] in southern and central
India, respectively [239]. Earlier it was reported that implementation of JSY had impact on reducing
perinatal mortality due to increase in institutional deliveries, antenatal check-up, and referral of the
women. The studies published before 2013 showed that, JSY payment was associated with a reduction
of 3·7 perinatal deaths per 1000 pregnancies due to increase in institutional deliveries, antenatal check-
up, and referral of the women [26]. There is also evidence that essential newborn care trainings for
those involved in conducting deliveries (medical officers, nurses, ANMs, informal birth attendants) had
reduced the perinatal mortality rate from 52 per 1000 to 36 per 1000, and hence considered effective in
reducing the PMR [231].
Still birth rate
There was a total of 25 studies which reported still birth rate as an outcome [68, 90, 127, 128, 182, 228-
230, 233, 234, 237, 240-250]. The studies have been described in annexure 5.2.1. The studies that used
the data between 2005-13 showed that the range of Still Birth Rate (SBR) was between 33.7 to 47 per 48
1000 births. [228, 229, 237, 238, 240, 244]. Essential Newborn care training was found to be associated
with reduction in SBR from 23 to 15.9 per 1000 live births [228].
Evidence from the studies published after 2013 showed that, the range of SBR was between 15.4 to
26.5 per 1000 births [246, 247, 249]. Annual decline rate of SBR was found to be 4.5% (from 31.3 to
23.8 per thousand live births) from the year 2010 to 2016 in one of the study [247]. State specific results
are on still births especially from Bihar are obtained from Dandona et al study, (2017, 2019) [131, 249].
Incidence of stillbirths was 21.2 per 1,000 births in Bihar state in the year 2014-15 and it declined to 15.4
per 1000 births in 2016, higher proportion of births was stillborn among those women for whom the
delivery was deferred. [249]. It was also found that in rural communities of India, there was a significant
reduction in SBR from 23 to 15.7 per 1000 births and the rate of stillbirths by delivery attendant
decreased significantly for nurses/midwives but not for physicians [250].
Findings of studies reviewed for reproductive health outcomes
Studies published after the year 2013 found that TFR has been declined after the implementation of
NRHM due to increase in the contraceptive prevalence rate (CPR), and increase in literacy rates [251-
258] (Annexure 5.3.1). This is close to the target of achieving at least 60% CPR to attain the goal of total
fertility rate of 2. The prevalence of contraceptive usage was found to be less among tribal population
[259]. The knowledge about contraception was found to be high among males and females, but
acceptance was poor among males. The tracking of eligible couples and motivating them for using
contraception for spacing as well as delay in first pregnancy was an effective strategy implemented by
ASHA. ASHAs performance was increased upto 1.13 times for eligible couples and 1.14 times for
couples having two or less children after introduction of an incentive. From April 1, 2013, a new scheme
was introduced in “ASHA INCENTIVE SCHEME” for promoting family planning—permanent sterilization.
It is an incentive of Rs. 1,000 given to an ASHA who motivates and promotes couples having two or less
than two children to undergo permanent sterilization [260]. Incentive based performance showed a
significant impact on motivation of eligible couples for using contraceptive methods by ASHAs. It was 49
also found that the engagement of male counterparts have improved the performance of ASHA program
(statistically non-significant) which unveils the complementarity of male and female CHWs in increased
demand for MNCH services [122, 260-262]. ASHA's capacity was found to be low in motivating family
planning cases for restricting high fertility in rural areas (30.49%). Meta-analysis of 22 studies [236, 259,
263-281]found the pooled CPR to be 54% from the year 2007-17 (Figure 10). (Annexure 5.3.2)
Figure 10: Meta-Analysis of studies on CPR
Result of studies reviewed for adolescent health outcomes
There has also been improvement in adolescent health indicators due to NRHM strategies such as
Weekly Iron and Folic Acid Supplementation (WIFS), Adolescent Reproductive and Sexual Health
(ARSH) and Menstrual Hygiene Scheme (MHS). WIFS program is a good initiative and compliance was
also found to be satisfactory [282-290] Annexures 5.4.1 - 5.4.3). Studies published before the year 2013
showed significant decline in anemia due to WIFS revealing that IFA daily is an effective strategy of
reducing the anemia in adolescents [92, 287]. Studies published after 2013 showed less knowledge 50
about anemia among adolescent girls [291]. It was also found that reduction of anemia was more among
adolescent boys as compared to adolescent girls. The compliance to the WIFS program was 85.8%
[292]. Pooled prevalence of anemia among adolescents was found to be 43% from the year 2008-17
(Figure 11). Also meta-analysis of 4 RCTs found 2% pooled reduction in anemia from the year 2009-16
(Figure 12).
Figure 11: Meta-analysis of 5 cross sectional studies on WIFS
Figure 12: Meta analysis of 4 RCTs on WIFS
51
Studies published before 2013 had shown poor knowledge about menstruation. It was also found that
the usage of sanitary pads was more in urban as compared to rural areas. However studies published
after 2013 found that in post NRHM period usages of sanitary napkins had been increased. And the
pooled prevalence of usage of sanitary napkins was found to be 58% from the year 2012-19, after meta-
analysis (Figure 13) [178, 293-308]. Also the girls were less aware of government providing sanitary
napkins on subsidized rates [72, 298, 309-311].
Figure 13: Meta-analysis of studies on usage of sanitary napkins
NRHM has also raised the awareness about menstrual hygiene among adolescents. However, the
knowledge about menarche was more among urban girls as compared to the girls living in a slum.
Meta analysis of 15 studies found the pooled awareness of menstrual hygiene to be 43 % from the
year 2011-19 (Figure 14).
Overall (I^2 = 98.96%, p = 0.00)
Mamilla 2019
Study
Jain et al 2017
Chaudhary & Gupta 2019
Rana et al 2015
Kansal et al 2016
Deshpande et al 2018
Agarwal et al 2017
Vijayshree et al 2016
Udayar et al 2016
Dudeja et al 2016
Krishnaleela 2018
Paria et al 2014
Paul et al 2014
Shah et al 2013
Thakre et al 2012
Ramchandra et al 2016
0.58 (0.46, 0.70)
0.84 (0.77, 0.89)
ES (95% CI)
0.79 (0.74, 0.83)
0.43 (0.39, 0.48)
0.39 (0.34, 0.44)
0.28 (0.25, 0.32)
0.60 (0.50, 0.69)
0.15 (0.11, 0.20)
0.78 (0.72, 0.83)
0.78 (0.73, 0.83)
0.91 (0.86, 0.94)
0.55 (0.48, 0.62)
0.55 (0.51, 0.59)
0.74 (0.70, 0.78)
0.32 (0.26, 0.40)
0.49 (0.44, 0.54)
0.69 (0.65, 0.73)
100.00
6.21
Weight
6.27
6.27
6.27
%
6.30
6.07
6.28
6.26
6.27
6.29
6.20
6.28
6.29
6.19
6.26
6.29
0.58 (0.46, 0.70)
0.84 (0.77, 0.89)
ES (95% CI)
0.79 (0.74, 0.83)
0.43 (0.39, 0.48)
0.39 (0.34, 0.44)
0.28 (0.25, 0.32)
0.60 (0.50, 0.69)
0.15 (0.11, 0.20)
0.78 (0.72, 0.83)
0.78 (0.73, 0.83)
0.91 (0.86, 0.94)
0.55 (0.48, 0.62)
0.55 (0.51, 0.59)
0.74 (0.70, 0.78)
0.32 (0.26, 0.40)
0.49 (0.44, 0.54)
0.69 (0.65, 0.73)
100.00
6.21
Weight
6.27
6.27
6.27
%
6.30
6.07
6.28
6.26
6.27
6.29
6.20
6.28
6.29
6.19
6.26
6.29
-.50.511.5 52
Figure 14: Meta analysis of 15 studies on awareness of menstrual hygiene
ARSH program was found to be a good initiative under NHM and the pooled awareness of Adolescent
Friendly Health Clinics (AFHCs) was found to be 49% from the year 2009-18, after doing meta-analysis
of 10 studies (Figure 15) [312-319] (Annexure 5.4.4).
Overall (I^2 = 98.44%, p = 0.00)
Chaudhary & Gupta 2019
Paul et al 2014
Nagaraj 2016
Ramchandra et al 2016
Ray et al 2012
Dudeja et al
Shah et al 2013
Mamilla 2019
Study
Syed 2017
Vijaykeerthi et al 2016
Paria et al 2014
Sivakami et al 2019
Kansal et al 2016
Prateek et al 2011
Deshpande et al 2018
0.43 (0.34, 0.52)
0.64 (0.59, 0.68)
0.73 (0.69, 0.76)
0.30 (0.25, 0.35)
0.15 (0.12, 0.18)
0.42 (0.35, 0.49)
0.56 (0.50, 0.63)
0.40 (0.32, 0.47)
0.60 (0.51, 0.68)
ES (95% CI)
0.67 (0.60, 0.74)
0.46 (0.40, 0.51)
0.38 (0.34, 0.42)
0.40 (0.38, 0.42)
0.27 (0.24, 0.30)
0.20 (0.16, 0.26)
0.24 (0.17, 0.33)
100.00
6.74
6.76
6.70
6.80
6.58
6.60
6.54
6.45
Weight
6.60
6.69
6.76
6.83
6.78
%
6.70
6.47
0.43 (0.34, 0.52)
0.64 (0.59, 0.68)
0.73 (0.69, 0.76)
0.30 (0.25, 0.35)
0.15 (0.12, 0.18)
0.42 (0.35, 0.49)
0.56 (0.50, 0.63)
0.40 (0.32, 0.47)
0.60 (0.51, 0.68)
ES (95% CI)
0.67 (0.60, 0.74)
0.46 (0.40, 0.51)
0.38 (0.34, 0.42)
0.40 (0.38, 0.42)
0.27 (0.24, 0.30)
0.20 (0.16, 0.26)
0.24 (0.17, 0.33)
100.00
6.74
6.76
6.70
6.80
6.58
6.60
6.54
6.45
Weight
6.60
6.69
6.76
6.83
6.78
%
6.70
6.47
-.50.511.5 53
Figure 15: Meta-analysis of 10 cross sectional studies on ARSH
Result of studies reviewed for health inequalities
Studies published after the year 2013 period showed that, the inequalities related to institutional delivery
among rich and poor declined at steeper rate in post NRHM time period due to JSY and free ambulance
services [5, 45, 61, 64, 73, 80, 320-330] (Annexure 5.5). Secondary data analysis of the DLHS data
(round 1, 2, 3 and 4) by Vellakkal S et al (2017), have shown that socioeconomic inequalities for
institutional deliveries and ANCs have been reduced in the EAG and NE states. In the EAG states as a
whole, the uptake of ANC for the lowest, middle and highest wealth tertiles decreased by 5.3%(=-0.
053; P<0.001), 8.0% (=-0.080; P <0.001) and 15.1% (=-0.151; P<0.001), respectively. In the NE
states, there was no significant effects for the uptake of ANC for the lowest and middle wealth tertiles,
but negative effects for the highest wealth tertiles (=-0.131; P <0.001). However, in the late post- NRHM
period 2011–12, there was considerable improvement in the uptake of ANC, particularly for the lowest
socioeconomic tertiles. Effects were stronger for institutional delivery than antenatal care [64]. 54
ASHA had played a role in increasing the utilization of MCH services among poor women [45]. Utilization
of MCH services such as ANC among Scheduled Caste (SC), Scheduled Tribe (ST) women was less in
comparison to Muslims women. Contraception rate was still low among ST and Muslims [328]. Women
belonging to SC/ST and Other Backward Class (OBC) were less likely, as compared to General Caste
women, to participate in at least 4 ANC visits [45]. Positive relationship between visits by a community
health worker and likelihood of utilizing critical maternal health services was seen. However, significant
social inequalities still exist in association of community health worker visits [45].
As per Gupta et al study (2016) in Haryana, the geographical and socioeconomic differences between
urban and rural areas, and between rich and poor were significantly (p<0.05) reduced for pregnant
women who had an institutional delivery. (geographical difference declining from 22% to 7.6%;
socioeconomic from 48.2% to 13%), post-natal care within 2 weeks of delivery (2.8% to 1.5%; 30.3%to
7%); and for children with full vaccination (10% to 3.5%, 48.3% to 14%) and who received oral
rehydration solution (ORS) for diarrhea (11% to -2.2%; 41% to 5%). Inequalities between male and
female children were significantly (p<0.05) reversed for full immunization (5.7% to -0.6%) and BCG
immunization (1.9 to -0.9 points), and a significant (p<0.05) decrease was observed for oral polio vaccine
(4.0% to 0%) and measles vaccine (4.2% to 0.1%) [61].
In a qualitative study by Gupta et al, (2017), it was reported than an improvement in overall health
infrastructure through an increased availability of accredited social health activists, free ambulance
services, and free treatment facilities in rural areas was observed, which had increased the demand and
utilization of MCH services, especially for those related to institutional delivery, even by the poor families.
Service providers felt that acute shortage of human resources was a major health system level barrier. 55
Overall program managers, service providers and community representatives believed that NHM had a
role in improving MCH outcomes and in
reduction of geographical and socioeconomic inequalities, through improvement in accessibility,
availability and affordability of the MCH services in the rural areas and for the poor. Any reduction in
gender-based inequalities, however, was linked to the adoption of small family sizes and an increase in
educational levels [5].
Result of studies reviewed for other interventions like road and mobile connectivity
There were total 1, 07,823 studies that had reported the effect of interventions other than NRHM such
as road connectivity, mobile connectivity, water supply and sanitation on MCH outcomes. After removal
of duplicates, there were total 42,982 studies that were eligible for screening. Out of these, 223 studies
were selected after excluding the studies based on title and on abstract and 198 studies were excluded
based on exclusion criteria. Therefore, total 25 studies were included in the final analysis. Out of these
25 studies, only 18 studies were identified as good quality studies [261, 300, 331-352] (annexures 5.6.1
– 5.6.2).
Systematic review on variables other than NHM such as road connectivity, mobile connectivity, water
supply and sanitation found that mobile connectivity in form of health messages or as a tool to talk with
higher health officers had increased the knowledge and awareness related to maternal and child health
among people and front line health workers, which led to increase in early initiation of breastfeeding and
ANC utilization [333, 335, 339]. There was increase in health reporting services. It was also found that
women offered positive feedback regarding the voice messages as they described them as informative,
entertaining, and a service that they would recommend to friends. Surface road connectivity was also
found to be having positive impact on utilization of ANC and PNC services. Due to decrease in distance,
there had been increase in the chances of institutional deliveries as well as increase in immunization
among children and pregnant mothers. Pradhan Mantri Gram Sadak Yojna had also increased the
connectivity of villages with health facilities. This had also improved the chances of availability of health
care worker and ambulance services at village level [353]. Total sanitation program and NRHM in 56
coordination with other departments had increased the safe water supply which had reduced the water
borne illness and enteric infections [347, 348].
Pathways leading to reduction in Maternal and child mortality
Pathways leading to reduction in Maternal and child mortality
We have also tried to reason out how the NHM schemes might have led to the reduction in MCH mortality
and improved the MCH outcomes using good quality studies identified in the final step of the systematic
review. So, based upon the duplication, inclusion, exclusion and quality criteria a total 92 studies i.e. on
maternal health (n=18), child health (n=49), adolescent health (n=7), reproductive health (n=10), health
inequalities (n=7) were identified to construct pathways to understand the impact of NHM on health
outcomes as per logic model. (Table 4).
Table 4. Number of studies reviewed and included for construction of pathways leading to MCH
outcomes.
Strategies Studies
Reviewed
Studies Included Quality Studies
Maternal health 2759 63
Institutional delivery=44
MMR
1
=19
18
Institutional delivery=14
MMR=4
Child health 82023
NMR
2
= 19536
IMR
3
= 19,350
U5MR
4
=14,569
PNMR
5
= 28,568
213
NMR = 40
IMR=66
U5MR= 66
PNMR=41
49
NMR= 13
IMR= 15
U5MR=16
PNMR= 5
Adolescent health 1062 51
WIFS
6
=12
ARSH
7
=14
MHS
8
=25
7
ARSH=3
WIFS=2
MHS= 2
Reproductive health 6261 49
CPR
9
=27
TFR
10
=9
Utilization
rate/barriers=13
10
CPR=10
TFR=0
Health inequalities 9185 12 8
Total 101290 388 92
57
1
Maternal Mortality Ratio;
2
Neonatal Mortality Rate;
3
Infant Mortality Rate;
4
Under 5 Mortality Rate;
5
Perinatal Mortality Rate;
6
Weekly Iron
Folic Acid Supplementation;
7
Adolescent Reproductive Sexual Health;
8
Menstrual Hygiene Scheme;
9
Contraceptive Prevalence Rate;
10
Total
Fertility Rate
Pathways to understand the impact of NHM on health outcomes as per logic model is shown in Figure
16. The inputs (n=89) which included NHM strategies like communitization, RMNCHA+, health system
strengthening, human resources strengthening and social determinants of the health such as income,
education, female literacy, occupation, road connectivity, mobile users, caste and area. Processes (n=4)
include the implementation of these activities like number of ASHA’s trained in providing reproductive
and child health care, provision of incentives for institutional delivery and free treatment, outputs (n=4)
include the activities done/completed like number of pregnant women contacted by ASHA’s in the village
and counselled for institutional deliveries, increase in availability, affordability and accessibility of MCH
facilities in rural areas, outcomes include the coverages such as increase in institutional delivery rate,
increase in utilization of MCH facilities in rural areas and impact (n=80) includes the effect on the
mortality rates like reduction in maternal mortality rate, infant mortality rate, in MCH geographical,
socioeconomic and gender based inequalities.
The evidence for accredited health activists is denoted by thick arrow, which shows that ASHA had
played a significant role in improving MCH outcomes by behaviour change and communication [69].
Both ASHA [5, 45, 63, 65, 69, 95, 354, 355] and maternal health intervention such as JSY[7, 26, 30-34,
54, 73, 74, 127] were (denoted by thick arrow) were found to be very effective in increasing the
institutional delivery rate among pregnant women as compared to village health nutrition day (denoted
as dotted arrow) [80]. Due to behaviour change communication and motivation, the pregnant women
were empowered with adequate knowledge regarding the health sector plans of NRHM (free ambulance
services, free hospital deliveries, free treatment, and financial incentives for hospital deliveries) which
enabled them to take decisions regarding institutional delivery [5]. As a result, the community was
mobilized to use the MCH facilities in rural areas [5]. These factors, along with other NRHM interventions
Janani Shishu Suraksha Karyakram (JSSK) [80], child health interventions such as facility based
newborn care (FBNC) [70, 89, 97, 101, 182], Integrated Management of Neonatal and Childhood
Illness(IMNCI) [70, 89, 94, 97, 101, 106-110, 112, 117, 155, 182] home based postnatal care [90, 99, 58
119, 122, 125, 126], immunization coverage [190, 191, 194, 198, 201, 204, 205, 356], the availability of
health facilities and doctors in rural areas and the free ambulance service [36, 41, 55], free medicines
further improved the accessibility and affordability of MCH services and benefitted poor pregnant women
and children whereas mobile medical units (MMUs) were perceived to be less effective in improving the
accessibility of health services in rural areas as denoted by dotted arrow [80]. There is weak evidence
for reproductive health strategies such as family planning in improving maternal health outcomes
(denoted by dotted arrow) [259, 260, 265, 266, 273, 277, 357-360]. The diagram also shows that the
increase in institutional delivery rate was mainly due to ASHA and JSY (denoted by thick arrow). Also
due to community mobilization (denoted by thick arrow) there was increase in utilization of MCH facilities
in rural areas which led to improvement in antenatal and postnatal care [45]. The increased utilization
of MCH facilities and other factors like increase in accessibility of MCH facilities in rural areas [5], led to
improvement in child health indicators such as early diagnosis and treatment of children, reduction in
ARI, diarrhoea burden [61, 204] and malnutrition [221, 222] whereas there is weak evidence for other
child health interventions such as RBSK [226, 227] and RKSK in provision of early diagnosis as well as
treatment of childhood illnesses. There is weak evidence for adolescent health interventions like WIFS
(denoted by dotted arrow) in reduction of anaemia among adolescents [282, 298, 311, 361-364]. Though
NRHM interventions had improved the utilization of MCH services, there is weak evidence for provision
of equal child health care facilities for girls and boys (denoted by dotted arrow) [5]. All these inputs and
outputs had implications on improving MCH outcomes, on declining mortality rates and on bridging the
socioeconomic, geographical and gender based MCH inequalities [5, 61, 63, 64, 73, 80, 321, 327, 361].
59
Figure 16. Impact of NHM Strategies: Evidence from Literature.
60
FINDINGS FROM SECONDARY DATA ANALYSIS
INPUT/PROCESS INDICATORS
Allocation of funds for NHM
The fund allocated to NRHM in the year 2005-06 was Rs 6788 crore and it increased to Rs 30,130 crore
in the year 2018-19 under NHM. (Figure 17). The allocated fund had increased every year, however,
allocation of fund had been declined by 0.7% (17,310 crore to 17,188 crore) in the financial year 2011-
12 to 2012-13 and by 2% (30,802 crore to 30,130 crore) in the year 2017-18 to 2018-19 [88, 365]. The
trend of inflation adjusted budget have shown that budget allocation increased from 2005-06 to 2008-
09, and declined in the year 2009-10 and 2011-12. After that there was an increased allocation up to
the year 2017-18, which later declined in the year 2018-19.
Figure 17. Allocation of funds under NHM.
Data source: India Expenditure Budget, Volume 2, Ministry of Health and Family Welfare; Union Budget, Government of
India.
Public and out of pocket health Expenditure and Per Capita Public Health Spending
6788
8207
9947
1205012070
15258
13310
17188
18206
18609
19122
22198
30802
30130
0
5000
10000
15000
20000
25000
30000
35000
Rupees
Budget (In crores) Budget (Inflation Adjusted) 61
Out of the total health expenditure, the percentage of the public health expenditure had increased from
24% to 32% from the year 2004 to 2016. In the same period, the percentage of out of pocket health
expenditure had declined from 68% to 59 %. (Figure 18).
Figure 18. Out of pocket health expenditure and public health expenditure.
Data source: National Health Account year 2004 to 2016.
The per capita public health expenditure had increased from Rs 579 in 2004 to Rs 1418 in 2016. (Figure
19).
Figure 19. Per capita public health expenditure.
Data source: National Health Account year 2004 to 2016; Indian National Rupee; per capita public health expenditure in
different years inflated to 2016 value.
Health system strengthening and human resources
68 66 64 63 65
62 61
59
24
26 27 27 27
30
31
32
0
10
20
30
40
50
60
70
80
2004 2006 2008 2010 2012 2014 2015 2016
% of total health
expenditure
OOP health expenditurePublic health expenditure
579
1151
1321
1418
0
200
400
600
800
1000
1200
1400
1600
2004 2006 2008 2010 2012 2014 2015 2016
Per capita public health expenditure
Linear (Per capita public health expenditure)
INR 62
Number of government hospital beds per 1000 population in rural and urban areas (including CHCs) in
India increased from 0.4 in 2005 to 0.6 in 2015. (Figure 20).
Figure 20. Number of Patient Beds/1000 population.
Data source: Rural Health Statistics year 2005-2015.
Number of ASHA workers per 10,000 population increased from 1.31 in 2005 to 7.40 in 2019. The
number of ANMs per 10,000 population increased from 1.22 in 2005 to 1.69 in 2018. (Figure 21).
Figure 21. Trend showing number of ANMs and ASHAs per 10,000 population (2005-19).
Data source: ANMs data obtained from Rural Health Statistics year 2005-2018; ASHAs data obtained from ASHA updates
2005-2019.
The number of nursing staff increased from 0.26 in 2005 to 0.65 in 2018, in PHCs and CHCs per 10,000
population. Number of doctors in PHCs and CHCs per 10,000 population also increased from 0.22 in 2005
to 0.24 in 2017. (Figure 22).
0.4
0.6
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
20052015
Per 1000 Population
20052015
0.00
2.00
4.00
6.00
8.00
200520062007200820092010201120122013201420152016201720182019
PER 10,000
POPULATION
ANM ASHA 63
Figure 22. Trend showing doctors and nursing staff per 10,000 population in PHCs and CHCs
(2005-2018).
Data source: Rural Health Statistics year 2005 to 2018.
HEALTH OUTPUT/OUTCOME INDICATORS
Utilization of public sector for outpatient care
The utilization of public sector facilities for outpatient care services was higher in rural areas than urban
areas, with an increase in utilization in both rural and urban settings over the years. The rate of increase,
between years 2004 and 2014, was higher in rural areas (6.7%) in comparison to the urban areas (2.6%).
However, between 2014 and 2018, the rate of change in urban areas (5.7%) surpassed the increase in
rural areas (4.4%). This increase in public sector utilization was observed equally among both males
(10.1%) and females (9.6%), but in the initial years, the increase was higher among females (6%) as
compared to males (4%). (Figure 23).
Figure 23. Utilization of public sector for outpatient care.
Data source: NSSO round 60
th
(2004), round 71
th
(2014), round 75
th
(2018)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
20052006200720082009201020112012201320142015201620172018
Doctors Nurses
Per 10,000
population
21.2
18.1 19.8 20.8
27.9
20.7
23.7
26.2
32.5
26.2
29.9 30.4
0
20
40
60
80
100
Rural Urban Male Female
Public Sector Utilization (%)
200420142018 64
Utilization of public sector for hospitalization
A higher utilization rate of public sector facilities for hospitalization was observed in rural areas in 2014
as compared to 2004 (increase of 7%), while the same declined by 3.5% in urban areas during this
period. Between 2014 and 2018 however, whereas these utilization rates declined in rural areas by
around 5%, the rates in urban areas remained almost the same. Overall, utilization of public sector was
always higher in rural areas as compared to urban settings. A similar pattern was observed in the rates
of utilization among females and males. While the rates of utilization among females declined by 4% in
the later years, following an initial surge of 7% between 2004 and 2014, utilization by males declined by
almost 4% between 2004 and 2014, followed by an increase of the same amount between 2014 and
2018. (Figure 24).
Figure 24. Utilization of public sector for hospitalization.
Data source: NSSO round 60th (2004), round 71th (2014), round 75
th
(2018)
Out-of-pocket expenditure for under-five child hospitalization
It was found that while the expenses at public health sector facilities for under five child hospitalization
were lowered by Rs. 2741 in 2014 when compared to 2004, these increased by Rs. 1264 between 2014
and 2018. Expenses at private health facilities increased by around Rs. 5000 between 2004 to 2014 but
only by Rs. 1500, between 2014 and 2018. (Figure 25).
43.8
39.140.5
43
50.3
35.536.9
50
45.7
35.3
40.9
46.1
0
20
40
60
80
100
Rural UrbanMaleFemale
Public Sector Utilization (%)
200420142018 65
Figure 25. Out-of-pocket expenditure for under-five child hospitalization.
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; Indian National Rupee.
Out-of-pocket expenditure on institutional deliveries
The mean expenditure on institutional deliveries at public sector facilities increased marginally (by Rs.
55) in 2004-2014 period, expenses at private health facilities increased by around Rs 7000 in this period.
No increase in mean expenditure on deliveries in 2014-18 period was observed at public sector facilities,
however deliveries in private sector facilities had to spend an additional Rs. 8000 on an average.. (Figure
26).
Figure 26. Out-of-pocket expenditure on institutional deliveries.
6104
12024
3363
17192
4627
18510
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
Public Sector FacilitesPrivate Sector Facilites
INR
200420142018
2714
11198
2769
18521
2767
26476
0
5000
10000
15000
20000
25000
30000
Public Sector Facilites Private Sector Facilites
INR
200420142018 66
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; Indian National Rupee.
Catastrophic health expenditure on under-five child hospitalization
Catastrophic health expenditure due to hospitalizations at public health facilities reduced from 24.2% in
2004 to 14.5% in 2014, and further to 9.6% in 2018, whereas it stayed almost the same (around 40%)
between 2004-2018 at private health facilities (Figure 27).
Figure 27. Catastrophic health expenditure on under-five child hospitalization.
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; catastrophic health expenditure is > 25% of the
total household consumption expenditure.
Catastrophic health expenditure on institutional deliveries
The public sector has also successfully managed the financial risk to households due to catastrophic
health expenditure on delivery between 2004-18, which increased substantially from 32% to 74% at
private sector facilities in the same period (Figure 28).
24.2
40.3
14.5
42.8
9.6
39.5
0
5
10
15
20
25
30
35
40
45
Public Sector FacilitesPrivate Sector Facilites
Percentage (%)
200420142018 67
Figure 28. Catastrophic health expenditure on institutional deliveries.
Data source: NSSO data round 60
th
(2004, round 71
th
(2014), round 75
th
(2018); 2004 and 2014 data values Inflated for 2018
using annual Consumer Price Index from year 2004-05 to 2017-18, 2018 values adjusted for confounders: Religion, Social
class, HH sanitation, HH drinking water source, Wealth status of household; catastrophic health expenditure is > 25% of the
total household consumption expenditure.
Maternal Health Indicators
There was significant increase in the proportion of first trimester registration from 57.3% to 67.4%, in
institutional delivery rate from 41.6% to 87.7% and proportion of women who received post-natal check-
up from 42.4% to 72.3% from the year, 2005 to 2015. However, there was decline in contraception rate
(from 56.3% to 52.9%) in the same period. (Figure 29).
Figure 29. Health indicators for women aged 15-49 years who had a live birth in the five years
preceding the survey.
Data source: NFHS data round 3 and 4; adjusted percentage of NFHS 4 for place of residence, maternal age, education,
religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density, road
density, telephone-density.
8.2
32.8
8.1
61.8
7.5
74.1
0
10
20
30
40
50
60
70
80
Public Sector FacilitesPrivate Sector Facilites
Percentage (%)
200420142018
57.3
41.642.4
56.3
67.4
87.7
72.3
52.9
0
20
40
60
80
100
First trimester
registration
Institutional deliveryPost natal check upContraception rate
Percentage (%)
2005 2015 68
The odds of getting registered in first trimester of pregnancy was two times higher in post NHM period
as compared to pre NHM period after adjusting for the effect of confounders. Similarly, the odds of
having institutional delivery and postnatal check-ups was 11.5 and 3.5 times higher in post NHM period
as compared to pre NHM period, respectively. However, the odds of contraception rate was lower in
post NHM period as compared to pre NHM period after adjusting for the effect of confounders. (Table
5).
Table 5. Health indicators for women aged 15-49 years who had a live birth in the five years
preceding the survey.
Health Indicators
Adjusted Odds
Ratio
95% Confidence
Interval
p-value
First trimester Registration 2.0 (1.896,2.082) <0.01*
Institutional Delivery 11.5 (10.855,12.142)
<0.01*
Postnatal Check-ups 3.5 (3.377, 3.688)
<0.01*
Contraception Rate 0.9 (0.851, 0.895)
<0.01*
Data source: NFHS data round 3 and 4; *significant; adjusted for place of residence, maternal age, education, religion, caste,
wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density, road density, telephone-
density.
Child Health Indicators
The adjusted proportions of children exclusive breastfed and fully immunized in post-NHM period increased
as compared to pre-NHM period and adjusted proportions of children suffering from acute respiratory
infection decreased in post NHM period. However, the proportion of children suffering from diarrhoea
remained same before and after NHM period. (Figure 30).
Figure 30. Percentage of children for various child health indicators in 2005 and 2015. 69
Data source: NFHS data round 3 and 4; adjusted percentage of NFHS4 for institutional delivery, place of residence, maternal age,
education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density,
road density, telephone- density.
The odds of exclusive breastfeeding was 2 times in post NHM period as compared to pre NHM period,
after adjusting for confounders. Likewise, the odds of being fully immunized was 1.8 times higher in post
NHM period as compared to pre NHM period. (Table 6).
Table 6. Child health indicators of children under 5 years of age in 2005 and 2015.
Child Health Adjusted Odds Ratio
95% Confidence
Interval
p-value
Exclusive Breastfeeding 2.1 (1.756, 2.509) <0.01*
Fully Immunized 1.8 (1.618, 1.910) <0.01*
Acute Respiratory Infection (ARI) 0.5 (0.417, 0.491) <0.01*
Diarrhoea 1.0 (0.961,1.068) 0.633
Data source: NFHS data round 3 and 4; *significant; adjusted for institutional delivery, place of residence, maternal age,
education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density,
road density, telephone- density.
IMPACT INDICATORS
Maternal Mortality Ratio
The national MMR declined from 254 in the year 2004-06, to 167 in the year 2011-13, to 122 in the year
2015-17. Empowered Action Group (EAG) states and Assam also witnessed a decline from 246 to 175
in the same time period. It was also declined for South states total and other states total from 93 to 72
and 115 to 90 respectively. (Figure 31). Maternal mortality ratio declined by 52% from 2004-06 to 2015-
5.9
43.7
5.4
9.0
11.6
57.7
2.5
9.1
0
10
20
30
40
50
60
70
Exclusive BreastfeedingFully Immunized ARIDiarrhea
Percentage (%)
2005 2015 70
17, with 34.3% decline till 2011-13 and 26.9% decline during 2011-13 to 2015-17. Rate of decline per
year was 12.7 points during 2004-06 to 2011-13 and 11.3 points post 2011-13.
Figure 31. Trend of Maternal Mortality Ratio 1997-2017.
Source: SRS data
Child Health Outcomes
Under five mortality rate
Under five mortality rate declined from 78 to 37 per thousand live births from 2005 to 2019 (Unicef’s
child mortality estimates). [Figure 32]. Overall there is 52.6% reduction in U5MR from 2005 to 2019, with
33.3% during NRHM period (2005-12) and 28.8% during NHM period (2013-2019). Rate of decline per
year was 3.7 points before and 2.5 points after the year 2013.
398
167
122
0
100
200
300
400
500
600
1997-981999-012001-032004-062007-092010-122011-132014-162015-17
INDIA EAG And Assam Total South States Total Other Total
Rate of decline 12.7
points per year
Rate of decline 11.3
points per year 71
Figure 32. Trend of under five mortality rate in India, from 2005 to 2019.
Source: Unicef’s Child Mortality estimates; SRS data
Among the states, maximum reduction was seen in Assam, where U5MR had declined from 88 to 75
per thousand live births by 2012 to 52 per 1000 live births by 2016, as per SRS data. Rate of decline
per year increased from 2.6 points during 2008-12 to 5.25 points after the year 2013 in Assam. Minimum
reduction was seen in the state of Kerala which varied from 14 to 11 in the same time period, as it
already had very low U5MR. States where rate of decline increased per year after the year 2013 were
Gujarat (2.4 to 3 points), HP (1.4 to 3.5 points), Jammu and Kashmir (2.4 to 3.5), Jharkhand (3.0 to 3.75)
and West Bengal (0.8 to 2 points). In Orissa, pace of decline was also high at 4.0 points per year, which
remained the same after the year 2013. Similarly, in Madhya Pradesh pace of decline remained the
same (3.8 to 3.5 points). States where the pace of decline of U5MR reduced after the year 2013, included
Punjab, Rajasthan, Tamil Nadu, Haryana, Bihar, Andhra Pardesh, Chattisgarh, Karnataka. (Figure 33).
78
52
37
0
10
20
30
40
50
60
70
80
90
200520062007200820092010201120122013201420152016201720182019
U5MR
Rate of decline 3.7 points
per year
Rate of decline 2.5 points
per year 72
Figure 33. Trend of under five mortality rate in Indian states, from 2008 to 2016.
Source: SRS data
Infant Mortality rate
The infant mortality rate had declined from 58 per 1000 live births to 40 per thousand live births during
2005-13 (NRHM period) and to 33 per 1000 live births during 2013-17 (NHM period). [Figure 34].
Figure 34. Trend of infant mortality rate in India, from 2005 to 2017.
Source: SRS data
The interrupted time series analysis from the Sample Registration System (SRS) data had shown that
the rate of decline in IMR was 2.42 infant deaths per 1000 live births per annum before 2013 and it
accelerated to 2.10 infant deaths per 1000 live births per annum after the year 2013-17. (Figure 35).
69
64
59
55 52 49
45 43
34
88
87
83
78 75 73
66
62
52
14 14 15 13 13 12 13 13 11
0
50
100
200820092010201120122013201420152016
India Assam Orissa
Punjab Rajasthan Tamil Nadu
Haryana Kerala Uttar Pradesh
Bihar
58
40
33
0
10
20
30
40
50
60
70
2005200620072008200920102011201220132014201520162017
Rate of decline 2.6
points per year
Rate of decline 1.8
points per year 73
Figure 35. Trend of infant mortality rate as per interrupted time series analysis in India, from 2005
to 2017.
Data source: Sample Registration System; Interrupted Time series analysis; Year 1: 2005, Year 9: 2013, Year
13: 2017
The rate of decline for IMR was found to be sharper in post intervention period almost in every state
except a few, as per SRS data. Among the set of bigger states, the maximum reduction was seen in the
state of Orissa, where IMR had reduced from 51 to 41 infant deaths per 1000 live births from the year
2013-17. The minimum reduction was demonstrated by the state of Kerala which varied from 12 to 10
in the same time period. The trends of IMR for the set of smaller states/ UTs of the country had bit
different picture from the bigger and country level estimates. From the year 2013 to 2017, Arunachal
Pradesh and Manipur had witnessed an increase in IMR from 32 to 36 and from 10 to 11 per 1000 live
births, respectively. Among Union Territories (UTs), Andaman & Nikobar and Puducherry had shown
maximum decline in IMR from 24 to 16 and 17 to 10 respectively in the same time period. (Figure 36
and 37).
74
Figure 36. Trend of infant mortality rate in bigger states in India, from 2005 to 2017.
Source: SRS
data
Figure 37. Trend of infant mortality rate in smaller states in India, from 2005 to 2017.
Source: SRS data
0
10
20
30
40
50
60
70
80
2005200620072008200920102011201220132014201520162017
IMR trend in bigger states
India Assam Bihar Gujarat
Haryana Karnataka Kerala Madhya Pradesh
Odisha Punjab Rajasthan Tamil Nadu
Telangana Uttar Pradesh West Bengal
0
10
20
30
40
50
60
70
200520062007200820092010201120122013201520162017
IndiaArunachal Pradesh ManipurTripura
Andaman &Nicobar Chandigarh Daman &Diu Puducherry 75
Neonatal Mortality
Overall the neonatal mortality reduced from 38 per thousand live births to 22 per thousand live births,
with a percentage decline of 42.1% from 2005 to 2019, as per Unicef’s Child mortality estimates. The
rate of decline per year was 1.4 points from 2005 to 2013 and 1.0 from 2013 to 2019. (Figure 38).
Figure 38. Trend of neonatal mortality rate in India, from 2005 to 2019.
Source: Unicef’s Child Mortality estimates; SRS data
While the under-five mortality rate reduced from 78 to 37 (52.6% decline), infant mortality rate from 58
to 33 (43.1% decline), neonatal mortality rate reduced from 38 to 22 per thousand live births (42.1%
decline). The percentage decline was 26.3%, 31% and 33.3% during NHM period (2005-13), and 21.4%,
17.5% and 28.8% during NHM period for under-five mortality rate, infant mortality rate and neonatal
mortality rate, respectively.
Figure 39. Trend of neonatal mortality, infant mortality and under five mortality in India, from
2007 to 2019.
38
28
22
0
5
10
15
20
25
30
35
40
200520062007200820092010201120122013201420152016201720182019
Rate of decline 1.4
points per year
Rate of decline 1.0
points per year 76
Source:
Unicef’s Child Mortality estimates, SRS data
The analysis of NFHS 3 and NFHS 4 data showed that the infant mortality rate and neonatal mortality rate
had reduced significantly in post NHM period as compared to pre NHM period. Rate of decline was 0.9
points per year for IMR and it was 0.4 points per year for NMR. (Figure 40).
Figure 40. Infant Mortality Rate and Neonatal Mortality Rate per 1,000 live births in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index, type
of housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
The adjusted infant mortality rate as well as neonatal mortality rate in post-NHM period had been
reduced as compared to pre-NHM period. The risk of infant death was significantly lower in post NHM
period as compared to pre NHM period (RR=0.8). [p<0.01]. Similarly, the risk of neonate death was
38
28
22
78
52
37
58
40
33
0
10
20
30
40
50
60
70
80
90
200520062007200820092010201120122013201420152016201720182019
NMR U5MR IMR
45.1
31.6
36.1
27.0
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Mortality Rate / 1,000 Live
Births
20052015
Rate of decline 0.9 points per year Rate of decline 0.4 points per year
Infant Mortality Rate Neonatal MortalityRate 77
significantly lower in post NHM period as compared to pre NHM period after adjusting for confounders
(RR=0.9). (Table 7).
Table 7. Infant mortality rate and Neonate mortality rate (per 1000 live births) of children born in
the three years preceding the survey.
Adjusted Risk Ratio 95% Confidence Interval p-value
Infant Mortality Rate 0.8 (0.749,0.857)
<0.01*
Neonate Mortality Rate 0.9 (0.789, 0.925)
<0.01*
Data source: NFHS data round 3 and 4; *significant; adjusted for maternal age, education, religion, caste, wealth index, type of
housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Total Fertility Rate
Total fertility rate has declined from 2.82 to 2.24 from 2007 to 2017. The percentage decline was 20.6%
in this period, with 15.6% decline till 2013 and 5.9% decline after 2013. (Figure 41).
Figure 41. Trend of Total Fertility Rate in India, from 2007 to 2017.
Source: SRS data
Impact of NHM on health inequalities
Geographical inequalities in IMR
IMR declined in both urban and rural areas from 2005 to 2015. The extent of decline was slightly higher
in rural (9.0 points) as compared to urban areas (8.6 points). The inequalities in IMR in the urban and rural
2.82
2.38
2.24
0
0.5
1
1.5
2
2.5
3
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
TFR 78
areas declined from 15.9 points in 2005 to 15.5 points in 2015 after adjustment for confounders. (Figure
42).
Figure 42. Comparison of infant mortality rate among urban and rural areas in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS 4 for maternal age, education, religion, caste, wealth
Index, type of housing, availability of toilet, safe water supply, cooking fuel, road density.
The extent of decline in IMR was almost similar in EAG (12.1 points) and non EAG states (12.3 points)
from 2005 to 2015. Inequalities in IMR between EAG and Non-EAG states increased from 14.9 points in
2005 to 15.1 points in 2015 after adjustment for confounders. (Figure 43).
Figure 43. Comparison of infant mortality rate among EAG and Non-EAG states in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index,
type of housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Socioeconomic inequalities in IMR
Caste wise inequalities
34.0
25.4
49.9
40.9
0
10
20
30
40
50
60
20052015
IMR/1,000 Live
Births
Urban
Rural
52.7
40.6
37.8
25.5
0
10
20
30
40
50
60
20052015
IMR/1,000 Live Births
EAG
Non EAG 79
The Infant mortality rate reduced in all the castes, reduction being the higher among scheduled tribes (ST)
by 12 points from 2005 to 2015. Caste wise inequalities in IMR between schedule caste (SC) and general
category reduced from 11.9 points in 2005 to 10.0 points in 2015. (Figure 44).
Figure 44. Caste wise health inequalities for infant mortality rate in 2005 and 2015.
Data source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, wealth index, type of
housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Income wise inequalities
Infant mortality rate reduced in all the quintile groups, reduction being the highest in the poorer quintile
(12.5 points) and the least in richer quintile (4.3 points) from 2005 to 2015. The inequality in IMR between
the poorest and richest quintile group reduced from 29.3 points to 28.4 points from 2005 to 2015. (Figure
45).
Figure 45. Wealth wise health inequalities for infant mortality rate in 2005 and 2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, type of housing, availability
of toilet, place of residence, safe water supply, cooking fuel, road density.
50.8
38.8
45.9
36.0
47.7
40.9
38.9
28.8
0
10
20
30
40
50
60
20052015
IMR/1,000 Live Births
ST
SC
OBC
Others
55.5
47.155.9
43.4
46.9
37.6
35.2
30.9
26.3
18.7
0
10
20
30
40
50
60
20052015
IMR/1,000 Live Births
Poorest
Poorer
Middle
Richer
Richest 80
The infant mortality rate had reduced significantly in post NHM as compared to pre NHM period. The
adjusted risk was significantly less for urban area as well as for rural area in post NHM as compared to
pre NHM period. (p<0.01). Likewise, the adjusted risk was less for EAG states as well as for Non-EAG
states in post NHM period as compared to pre NHM period. (p<0.01). [Table 8].
Table 8. Health Inequalities of infant mortality rate (per 1000 live births) for children born in the
three years preceding the survey.
Infant Mortality Rate
Adjusted
Risk Ratio
95% Confidence
Interval
p-value
Place of Residence
Urban 0.8 (0.640, 0.867)
<0.01*
Rural 0.8 (0.761, 0.883)
<0.01*
States
EAG States 0.8 (0.710, 0.837)
<0.01*
Non-EAG States 0.7 (0.600, 0.759)
<0.01*
Caste
Schedule Caste 0.8 (0.683, 0.901)
<0.01*
Schedule Tribe 0.8 (0.624, 0.933)
<0.01*
Other Backward Class 0.9 (0.775, 0.949)
<0.01*
Others 0.8 (0.639, 0.855)
<0.01*
Wealth Index
Poorest 0.9 (0.757, 0.953)
<0.01*
Poorer 0.8 (0.680, 0.888)
<0.01*
Middle
0.8 (0.686, 0.937)
<0.01*
Richer
0.9 (0.726, 1.060
0.176
Richest
0.7 (0.512, 0.889)
<0.01*
*Significant; Source: NFHS data round 3 and 4; adjusted for maternal age, education, religion, type of housing, availability of
toilet, safe water supply, cooking fuel, road density.
Geographical inequalities in NMR
NMR declined in both urban and rural areas from 2005 to 2015. The extent of decline in NMR was higher
in urban (5.5 points) as compared to rural areas (4.2 points) from 2005 to 2015. The inequalities in NMR
in the urban and rural areas increased from 10.7 points in 2005 to 12 points in 2015 after adjustment for
confounders. (Figure 46).
81
Figure 46. Comparison of neonate mortality rate among urban and rural areas in 2005 and 2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index, type of
housing, availability of toilet, safe water supply, cooking fuel, road density.
Neonatal mortality rate reduced with higher reduction in Non-EAG states (8.1 points) as compared to EAG
states (6.0 points) from 2005 to 2015. Inequalities in NMR between EAG and Non-EAG states increased
from 7.8 points in 2005 to 9.9 points in 2015 after adjustment for confounders. (Figure 47).
Figure 47. Comparison of neonatal mortality rate among EAG and Non-EAG states in 2005 and
2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, wealth index, type of
housing, availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Socioeconomic inequalities in IMR
Caste wise inequalities
24.2
18.7
34.9
30.7
0
10
20
30
40
50
20052015
NMR/1,000 Live Births
Urban
Rural
35.8
29.8
28.0
19.9
0
10
20
30
40
50
20052015
NMR/1,000 Live Births
EAG
Non EAG 82
NMR reduced in all the castes, reduction being the least in other backward caste (OBC) (2.9 points) and
the highest in other caste (7.1 points) category, from 2005 to 2015. (Figure 30). Caste wise inequalities in
NMR between schedule tribe (ST) and general category remained almost same in 2005 (9.7 points) and
2015 (10 points). (Figure 48).
Figure 48. Caste wise health inequalities for neonate mortality rate in 2005 and 2015.
Source: NFHS data round 3 and 4; adjusted rate of NFHS4. for maternal age, education, religion, wealth index, type of housing,
availability of toilet, place of residence, safe water supply, cooking fuel, road density.
Income wise inequalities in NMR
NMR reduced in all the quintile groups, reduction being poorest quintile was 4.5 points and poorer quintile
was 6.2 points from 2005 to 2015. However, the inequality in NMR between the poorest and richest quintile
group increased from 19.5 points to 22 points from 2005 to 2015. (Figure 49).
Figure 49. Wealth wise health inequalities for neonate mortality rate in 2005 and 2015.
37.2
30.4
29.6
25.7
33.0
30.1
27.5
20.4
0
5
10
15
20
25
30
35
40
45
50
20052015
NMR/1,000 Live Births
ST
SC
OBC
Others
38.9
34.439.1
32.9
31.8
29.1
25.5
25.5
19.4
12.4
0
5
10
15
20
25
30
35
40
45
20052015
NMR/1,000 Live Births
Poorest
Poorer
Middle
Richer
Richest 83
Source: NFHS data round 3 and 4; adjusted rate of NFHS4 for maternal age, education, religion, caste, type of housing, availability
of toilet, place of residence, safe water supply, cooking fuel, road density.
Neonatal mortality rate reduced significantly in post NHM period as compared to pre NHM period. The risk
was significantly less for urban area (RR=0.7) as well as for rural area (RR=0.9) in post NHM as compared
to pre NHM period. (p<0.01). Similarly, the risk was significantly less for EAG states (RR=0.8) as well as
for Non-EAG states (RR=0.7) in post NHM period as compared to pre NHM period. (Table 9).
Table 9. Health inequalities for neonate mortality rate (per 1000 live births) for children born in
three years preceding the survey.
Neonate Mortality Rate
Adjusted Risk
Ratio
95% Confidence
Interval
p-value
Place of Residence
Urban 0.7 (0.645, 0.922)
<0.01*
Rural 0.9 (0.806, 0.962)
<0.01*
States
EAG States 0.8 (0.754, 0.918)
<0.01*
Non-EAG States 0.7 (0.620, 0.817)
<0.01*
Caste
Schedule Caste 0.9 (0.737, 1.023)
0.092
Schedule Tribe 0.8 (0.635, 1.053) 0.119
Other Backward Class 0.9 (0.809, 1.029) 0.134
Others 0.7 (0.626,0.877) <0.01*
Wealth Index
Poorest 0.9 (0.772, 1.014) 0.080
Poorer 0.8 (0.717, 0.989) 0.036*
Middle
0.9 (0.760, 1.102) 0.349
Richer
1.0 (0.798, 1.247) 0.982
Richest
0.7 (0.498, 0.819) <0.01*
*Significant; Source: NFHS data round 3 and 4; adjusted for maternal age, education, religion, type of housing, availability of
toilet, safe water supply, cooking fuel, road density.
84
DISCUSSION
The results of this study have shown that there has been increase in utilization of public health services
and reduction in OOPE and for MCH services post NRHM implementation period. There is improvement
in availability and accessibility of health facilities after NRHM implementation. The human resources as
well as infrastructure has also been strengthened in post NRHM period. MCH coverage indicators have
shown improvement and overall mortality statistics (MMR and IMR) has registered a significant decline
after NRHM implementation.
In this study, we have used logic model evaluation framework to evaluate the impact of National Health
Mission on health care utilization, heath care inequalities and health outcomes by conducting a
systematic review and secondary data analysis. The logic model is helpful in showing the
interrelationship among different components such as between program input and activities and desired
outcomes. It also helps in understanding the complex mechanisms of whole interventions that how they
work. The simplicity of logic model is one of its strength as well as weakness. However due to its
simplicity it may also omits the details for clarity of the representation [366].
Earlier studies have used the logical model evaluation framework for assessing the effectiveness of
interventions and showed the interrelationship among different components [61, 80, 367, 368]. By
applying this approach to explain the results of this study, it was found that there has been considerable
increase in inputs and processes that provides the link in improving the output in terms of improved
MCH coverage indicators and ultimately outcomes and impact in terms of reduction in MCH inequalities
and mortality. There is no ‘control’ population for establishing the cause and effect relationship, therefore
the assessment of effect of interventions by measuring the inputs, processes, outputs, outcomes, and
impact over a longer time horizon is considered as a best available option [61].
The results of present study shows that out of the total health expenditure, the percentage of the public
health expenditure had increased from 24% to 32% from the year 2004 to 2016. In the same period, the
percentage of out of pocket health expenditure had declined from 63% to 59%. Also the per capita public
health expenditure had increased from Rs 579 in 2004 to Rs 1418 in 2016. Our results also revealed 85
that expenses at public sector facilities were lower in 2014 when compared to 2004 and the mean
expenditure on deliveries at public sector facilities increased marginally (by Rs. 129) in 2004-2014
period, whereas the expenses at private health facilities increased by around Rs 7000 in this period.
The catastrophic health expenditure due to deliveries at private health facilities, increased significantly
in this period. Also the catastrophic health expenditure due to hospitalization and institutional deliveries
for the household presented a marginal decline from 2004 to 2014. These findings are indicative of the
success of NRHM’s policies and programs in reducing out of pocket expenditures for institutional
delivery in public sector facilities. Increased public health spending in the post-NRHM period and
introduction of strategies such as the JSY and JSSK has contributed positively toward reducing out of
pocket expenditures [6, 57, 102, 369].
The results of present study also shows that there is improvement in availability and accessibility and of
health facilities after NRHM implementation. The human resources as well as health infrastructure has
also been strengthened in post NRHM period. Our results from logistic regression analysis found that in
post NRHM period there has been increase in number of ANMs, medical officers as well as increase in
number of beds in rural and urban areas hospitals. The evidence which was synthesized from previous
literature also validated these findings and concluded that post NRHM period there has been
strengthening of health system due to improvement in health facilities, availability of ASHA, ANMs,
Nurses and MOs, availability of free medicines and diet and free ambulance services [5]. Based on the
achievements of NHM since 2005, it has been a guiding framework for strengthening the Indian health
system [57]. The output indicators like first trimester registration, institutional delivery and post-natal
check-up also increased significantly post NRHM period. The evidence showed that the NRHM
interventions such as cash incentives for hospital deliveries (Janani Suraksha Yojna) [7, 26, 30-34, 54,
73, 74, 127], free diagnostics, treatment and diet (Janani Shishu Suraksha Karyakram) [80], and
appointment of Accredited Social Health Activists (ASHAs) [5, 45, 63, 65, 69, 95, 354, 355] led to
improvement in antenatal care, institutional delivery rate and postnatal care. We also found that various
child health indicators like exclusive breastfeeding and full immunization coverage improved significantly
in post NRHM period whereas acute respiratory infections reduced significantly to 2.5% from 2005 to 86
2015. The child health strategies of NHM/NRHM like IMNCI, immunization, micronutrient
supplementation along with early diagnosis and treatment by RBSK improved the affordability,
accessibility of health services which improved the child health indicators [70, 89, 94, 97, 101, 106-110,
112, 117, 155, 182, 190, 191, 194, 198, 201, 204, 205, 226, 227, 356].
Regarding the impact indicators, it was found that neonatal and infant mortality rate reduced significantly
in post NHM as compared to pre NHM period. Both NMR and IMR reduced significantly from 31.6 to 27
neonatal deaths per 1000 live births and 45.1 to 36.1 infant deaths per 1000 live births from 2005 to
2015, respectively .The results from interrupted time series also found that NHM had contributed to
reduce the infant mortality rate at the national level. The IMR reduced at the rate of 2.2% per year in
comparison to the 1.6 % on yearly basis in pre NRHM period. The various maternal and child health
interventions by NHM had succeeded well in declining maternal as well as child mortality rate.
Manifestations of impact of NHM can be observed in declining trends of infant, child and maternal
mortality indicators [4, 26, 34, 57].
Additionally, the logic regression analysis also looked at the health inequalities and found that in the
post NRHM period there has been reduction socioeconomic and geographic inequalities for IMR. The
infant mortality rate reduced with similar rate of reduction in urban and rural areas, among various caste
categories, the wealth quintiles, and EAG and non-EAG states. Neonatal mortality rate reduced with
highest rate of reduction in non-EAG states as compared to EAG states. However, the inequalities in
NMR did not reduce across socioeconomic and geographic gradients post NHM period. It was also
evident from the literature that some of the indicators are even better in rural areas as compared to
urban area like receiving ORS for diarrhoea, and immunization among female children during the NRHM
time period [80]. Inequalities related to institutional delivery among rich and poor also declined at steeper
rate in post NRHM time period [64]. MCH inequalities reduced due to more awareness regarding MCH
services by ASHA, free ambulances and diet during hospital stay [5].
We also found from the evidence that interventions other than NRHM such as road connectivity, mobile
connectivity and water sanitation had positive impact on health care utilization and has increased the 87
chances of full vaccination, maternal health services utilization. However, the secondary data used for
analysis in this study was adjusted for confounders like place of residence, maternal age, education,
religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health
worker density, road density, and telephone-density. Therefore it is unlikely that other interventions like
road connectivity, mobile connectivity, water sanitation and health were much effective in improving
MCH outcomes.
Strength and limitations of the study
The strength of this study is its integrated approach and holistic review of NRHM interventions related
to maternal and child health. To the best of our knowledge, this was the first kind of study to evaluate
the impact of NHM on health care utilization, inequalities and outcomes all together by using a logic
model evaluation framework at national level. We did the holistic review of impact of NRHM interventions
on health outcomes as well as the impact of interventions other than NRHM such as impact of road
connectivity, mobile connectivity, water supply and sanitation on MCH outcomes at national level. Also
our study has given due consideration to both pre and post intervention duration to have precise
comparisons. The estimates of slope for pre, post and change at the juncture are robust and precise in
comparison to the simple percentage decline over the years. The findings from the current study can be
generalized, as we did the analysis for assessing the impact of NRHM on health outcomes post NRHM
period at national level.
Our study has few limitations. Meta-analysis was not possible for each intervention due to heterogeneity
of studies, hence formal narrative synthesis was done. For trend analysis, the appropriate number of
data points remains the issue to limit the present analysis with respect to IMR only. In the absence of
suitable control, we could not use the randomized control trials design which are considered to be the
gold standards for the evaluation of intervention based studies. Also the inter-state comparison was not
done due to variation in socio demographic and developmental characteristics of a particular state. The
magnitude of the slope is valid only with respect to the previous period of the same state.
Public Health implications of the study 88
The results of this study have important public health implications as it was found that the public health
system can improve access, affordability, and effectiveness of health care delivery especially among
rural population, poor, women and children. The results of this study have shown that due to NRHM
schemes there has been significant improvement in MCH outcomes, therefore these schemes should
be further continued with special focus on poor women and children of rural areas. The schemes aiming
at improving child health such as RBSK and on adolescent health such as WIFS, MHS needs to be
strengthened. However, the investments in NRHM had been far below the requirements i.e.1.2% of GDP
for investing in health where goal was to increase it up to 2-3%.The further investments are likely to
strengthen HR, institutions and supplies leading to universal health coverage for treatment, prevention
and promotion and to attain NHP goals by 2025. However achievement of universal health coverage
requires the more rigorous planning, stringent enforcement of laws, consistent monitoring, optimum
health service delivery and innovative technologies. Hence, it can be stated that NRHM has played a
role through influencing health system in terms of improving MCH outcomes and reducing the MCH
inequalities. Therefore it is recommended that NHM should be continued with doubling of resources.
CONCLUSIONS
Evidence from the systematic review
Among maternal health care strategies, JSY strategy had a strong evidence in providing
financial incentives and promoting institutional delivery and reducing perinatal mortality.
JSSK had a role in providing free diagnostics there by increasing the affordability.
However, because of increase in the number of institutional deliveries the mortality in the
institutes reported to have increase in the tertiary care hospitals indicating poor quality
of intranatal and newborn care services.
Among the communitization component of NHM, ASHA scheme had a strong evidence
of reducing maternal mortality and perinatal mortality, through the pathway of contacting
the pregnant women at the household level in the villages, behavior change
communication, empowering and mobilizing them to the health facilities mainly for 89
institutional deliveries. VHND and VHNSC had weak evidence in bringing these health
outcomes.
Among child health strategies, FBNC, HBPNC, IMNCI and immunization had a strong
evidence in increasing the availability, affordability and accessibility of child health
services especially for the rural and poor community. RBSK and micronutrient
supplements had a weak evidence in improving the child health outcomes
Adolescent health strategies including WIFS, MHS, RKSK, AFHS had weak evidence in
improving the reproductive, maternal and child health outcomes.
Strategies under health system strengthening including increased infrastructure, free
drugs and medicines, free referral services, increased human resources (MOs,
specialists, ANMs) had a strong evidence in improving the availability affordability and
accessibility of MCH services, leading to community mobilization to use public facilities
leading to increase in the utilization of MCH services leading to early diagnosis and
treatment of child hood illnesses, improved antenatal and postnatal care leading
ultimately to improved MCH outcomes.
Evidence for use mobile medical units was weak in improving the MCH outcomes.
Evidence from secondary data analysis
Maternal mortality ratio (MMR) declined by 52%, from 257 per lakh live births in 2004-06
to 122 per lakh live births, in 2015-17. Nearly, 34.3% decline in MMR occurred during
NRHM period (2004-06 to 2011-13) and 26.9% decline during NHM period (2011-13 to
2015-17). Rate of decline per year was 12.7 points during 2004-06 to 2011-13, and it
was 11.3 points post 2011-13.
Under five mortality rate (U5MR) declined from 78 to 37 per thousand live births from
2005 to 2019, as per Unicef’s child mortality estimates. Overall, there is 52.6% reduction
in U5MR from 2005 to 2019, with 33.3% during NRHM period (2005-12) and 28.8% 90
during NHM period (2013-2019). Rate of decline per year was 3.7 points before and 2.5
points after the year 2013.
Rate of decline in U5MR per year increased from 2.6 points during 2008-12 to 5.25 points
after the year 2013, in Assam. Minimum reduction was seen in the state of Kerala which
varied from 14 to 11 in the same time period, as it already had very low U5MR. States
where rate of decline increased per year after the year 2013 were Gujarat (2.4 to 3
points), HP (1.4 to 3.5 points), Jammu and Kashmir (2.4 to 3.5), Jharkhand (3.0 to 3.75)
and West Bengal (0.8 to 2 points).
The infant mortality rate (IMR) had declined from 58 per 1000 live births to 40 per
thousand live births during 2005-13 (NRHM period) and to 33 per 1000 live births during
2013-17 (NHM period). The interrupted time series analysis have shown that the rate of
decline in IMR was 2.42 infant deaths per 1000 live births per annum before 2013, and
it accelerated to 2.10 infant deaths per 1000 live births per annum after the year 2013-
17. There was lot of interstate variability in IMR.
Overall the neonatal mortality reduced from 38 per thousand live births to 22 per
thousand live births, with a percentage decline of 42.1% from 2005 to 2019, as per
Unicef’s Child mortality estimates. The rate of decline per year was 1.4 points from 2005
to 2013 and 1.0 from 2013 to 2019.
Overall, the rate of decline per year for NMR was slower than the rate of decline in IMR
and U5MR.
The percentage decline was less for NMR (42.1%) as compared with IMR (43.1%) and
U5MR (52.6%), from 2005-19. However, the percentage decline for NMR (21.4%) was
higher as compared with IMR (17.5%) during NHM period (2013-17). This could be
attributed to better implementation of facility based new born care including sick new
born care units as evidenced from systematic review. 91
Total fertility rate has declined from 2.82 to 2.24 from 2007 to 2017. The percentage
decline was 20.6% in this period, with 15.6% decline till 2013 and 5.9% decline after
2013.
NHM has led to the improvement in the MCH outcomes. Also post NRHM period there
has been increase in the human resources and infrastructure and due to increase in
affordability, accessibility there is better access of MCH services.
There has been reduction in out of pocket expenditure (OOPE) for MCH and MCH
indicators have shown improvement which has led to reduction in IMR, NMR and MMR.
However, human resources and infrastructure are still half of the requirement. Also MCH
practices and utilization of services are still not optimum. Despite reduction in
expenditure, OOPE is still high.
Though the mortality indicators for maternal and child health have been declined, the
IMR, NMR and MMR is still high. The NHM has worked in both supply and demand side
components of public health system. Despite, the evidences on improved status of public
health system and decline in the targeted health indicators, the goal of equitable,
affordable and quality health care is still not fully achieved.
92
RECOMMENDATIONS
Maternal Health strategies
It is recommended to strengthen the implementation of successful schemes like ASHA,
Janani Suraksha Yojana, Janani Shishu Suraksha Karyakram, which have shown to be
associated with improvement in maternal health indicators. More focus should be given
for JSY implementation as there was high variability in implementation of JSY from state
to state. Also there was low coverage of JSY due to the inadequate funds for JSY and
delayed payments which should be taken into consideration. Increase in the hospital
based maternal mortality indicated poor quality of intranatal maternal care services.
Hence, there is need to focus on providing quality maternal health care services
especially during intranatal period. Laqshay strategy might have led to improvement in
the intranatal health care practices, which need to be evaluated in the near future.
Child health strategies
All facility based newborn care centers including NBCC, NBSU and SNCU should be
strengthened, and monitored by experts regularly to check the equipment status and
ensure that health personnel are following standard guidelines. Training regarding NSSK
should be provided to all the health personnel involved in newborn care. Health care
personnel in the delivery points should be sensitized or reoriented time to time regarding
various knowledge and skill for newborn care. It was found that there is an increased risk
of stillbirths in deferred and referred deliveries in addition to demographic and clinical
risk factors for ante-partum and intrapartum stillbirths which highlight the aspects of
health care that need attention in addition to improving skills of health providers to reduce
stillbirths. In case of referrals, partnership with private sector for improved quality of care
in referrals should be encouraged. It is also recommended to further strengthen the
implementation of immunization services, home based post-natal check-ups, integerated 93
management of childhood and neonatal illnesses, Nutritional Rehabilitation Centers, as
these were evidenced to have strong association with improving the child health
outcomes. Strategies like micronutrient supplementation, RBSK need to be further
evaluated for their effectiveness in improving the child health outcomes.
Reproductive Health strategies
The reproductive health indicators had definitely improved after inception of ASHA
worker in rural community. There is also an urgent need for such a change in urban area
for proper coverage of urban population. There is a need to take corrective measure on
tribal population as well as for EAG states as the prevalence of contraceptive usage was
found to be less among tribal population.
Adolescent Health strategies
Adolescent health strategies after merging with school health program can have better
performance so as to involve teachers, also to educate the children as well as
adolescents and counsel them according to their needs. Training should be given to
mothers as well as the teachers about menstrual hygiene as they are the primary source
of information. ARSH strategy needs to be advertised more effectively specially the focus
should be on RTI/STI and not only on HIV. NRHM has raised the awareness about
menstrual hygiene among adolescents but there is less awareness of government
scheme of distribution of sanitary napkins on subsidized rates. It can be advertised more
effectively by strengthening the IEC activities such as regular awareness campaigns,
community based awareness activities.
Communitization
Periodical refresher training and continuous capacity-building to improve knowledge and
skills of ASHAs should be conducted for the ASHA workers. ANMs and ASHAs should
also be employed to track the nutritional status of every child after their discharge from 94
the NRC and also for community based follow up and appropriate feedback to the
mothers. Also training of community health workers to address potential biases in quality
and quantity of their house visits based on socioeconomic, class and caste is
recommended so that inequalities can be reduced. The incentives can be increased for
ASHAs to mobilize the people of ST, SC and other minor communities. Microteaching
using video recording is an effective technique for improving home-based postnatal care
skills of the health care workers and a feasible option for supportive supervision. This
supervisory tool has public health implications in terms of scaling it up in routine program
settings to improve maternal and newborn survival. Greater coverage of ante-partum,
intrapartum and early postnatal health interventions in combination with promotion of
health care seeking behavior and links between communities and health facilities in
areas with lesser use of health care services should be enhanced.
Health system strengthening
It is recommended to strengthen the implementation of successful schemes like free
ambulance service, free medicine and diagnostic facilities, increased human resource
especially doctors and nurses as these have been evidenced to be associated with
improvement in maternal and child health outcomes. The schemes like medical mobile
units need to be reviewed again for their impact and utility, as these were found to be
weakly associated with improvement in MCH indicators. Resources spent upon this
strategy can be diverted to more effective strategies like free ambulance services. It is
also recommended to increase percentage of state budget on health to 8%, increase the
per capita public health expenditure in health from INR 1418 to INR 3000, increase the
number of beds in government hospitals & CHCs from 0.6 to at least 1 per 1000
population, increase the number of doctors, nurses and ANMs per 10,000 population in 95
government health facilities as per IPHS, and to establish one Arogya Kendra per 1000
population with one full time Health Promoter/Community Health Worker.
96
ANNEXURES
ANNEXURE 1. PRISMA CHECKLIST.
Section/topic # Checklist item
Page No.
TITLE
Title 1 Identify the report as a systematic review, meta-analysis, or
both.
N/A
ABSTRACT
Structured
summary
2 Provide a structured summary including, as applicable:
background; objectives; data sources; study eligibility
criteria, participants, and interventions; study appraisal and
synthesis methods; results; limitations; conclusions and
implications of key findings; systematic review registration
number.
N/A
INTRODUCTION
Rationale 3 Describe the rationale for the review in the context of what is
already known.
7
Objectives 4 Provide an explicit statement of questions being addressed
with reference to participants, interventions, comparisons,
outcomes, and study design (PICOS).
8
METHODS
Protocol and
registration
5 Indicate if a review protocol exists, if and where it can be
accessed (e.g., Web address), and, if available, provide
registration information including registration number.
annexure 2
Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-
up) and report characteristics (e.g., years considered,
language, publication status) used as criteria for eligibility,
giving rationale.
9-12
Information
sources
7 Describe all information sources (e.g., databases with dates
of coverage, contact with study authors to identify additional
studies) in the search and date last searched.
12-13
Search 8 Present full electronic search strategy for at least one
database, including any limits used, such that it could be
repeated.
13 and annexure
3
Study selection 9 State the process for selecting studies (i.e., screening,
eligibility, included in systematic review, and, if applicable,
included in the meta-analysis).
13 97
Section/topic # Checklist item
Page No.
Data collection
process
10 Describe method of data extraction from reports (e.g.,
piloted forms, independently, in duplicate) and any
processes for obtaining and confirming data from
investigators.
14
Data items 11 List and define all variables for which data were sought
(e.g., PICOS, funding sources) and any assumptions and
simplifications made.
11-12
Risk of bias in
individual
studies
12 Describe methods used for assessing risk of bias of
individual studies (including specification of whether this
was done at the study or outcome level), and how this
information is to be used in any data synthesis.
N/A
Summary
measures
13 State the principal summary measures (e.g., risk ratio,
difference in means).
N/A
Synthesis of
results
14 Describe the methods of handling data and combining
results of studies, if done, including measures of
consistency (e.g., I
2
) for each meta-analysis.
14 and Annexure
4
Risk of bias
across studies
15 Specify any assessment of risk of bias that may affect the
cumulative evidence (e.g., publication bias, selective
reporting within studies).
N/A
Additional
analyses
16 Describe methods of additional analyses (e.g., sensitivity or
subgroup analyses, meta-regression), if done, indicating
which were pre-specified.
N/A
RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility,
and included in the review, with reasons for exclusions at
each stage, ideally with a flow diagram.
13
Study
characteristics
18 For each study, present characteristics for which data were
extracted (e.g., study size, PICOS, follow-up period) and
provide the citations.
27-28 and
annexure 4
Risk of bias
within studies
19 Present data on risk of bias of each study and, if available,
any outcome level assessment (see item 12).
N/A
Results of
individual
studies
20 For all outcomes considered (benefits or harms), present,
for each study: (a) simple summary data for each
intervention group (b) effect estimates and confidence
intervals, ideally with a forest plot.
Annexure 4and 5
Synthesis of
results
21 Present results of each meta-analysis done, including
confidence intervals and measures of consistency.
Annexure 4 (N/A) 98
Section/topic # Checklist item
Page No.
Risk of bias
across studies
22 Present results of any assessment of risk of bias across
studies (see Item 15).
N/A
Additional
analysis
23 Give results of additional analyses, if done (e.g., sensitivity
or subgroup analyses, meta-regression -see Item 16).
N/A
DISCUSSION
Summary of
evidence
24 Summarize the main findings including the strength of
evidence for each main outcome; consider their relevance to
key groups (e.g., healthcare providers, users, and policy
makers).
53-58
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of
bias), and at review-level (e.g., incomplete retrieval of
identified research, reporting bias).
56-57
Conclusions 26 Provide a general interpretation of the results in the context
of other evidence, and implications for future research.
58
FUNDING
Funding 27 Describe sources of funding for the systematic review and
other support (e.g., supply of data); role of funders for the
systematic review.
N/A
99
ANNEXURE 2. PROTOCOLS FOR SYSTEMATIC REVIEW
The review protocols were registered with an open-access electronic database-PROSPERO
(International prospective register of systematic reviews). The protocol details are given below:
2.1. Impact of National Health Mission on Maternal Mortality Ratio of India: A systematic review
Review Question
Do National Health Mission strategies had any impact on maternal mortality ratio of India?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE
databases and Google Scholar. MeSH terms will be used to search the references and the reference
lists of all identified articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
maternal mortality ratio will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on maternal mortality
ratio.
Participants/population
Pregnant/antenatal, postpartum women.
Intervention(s), Exposure(s)
The exposure refers to any strategy of National Health Mission (NHM) India focussing on maternal
mortality ratio (MMR) of India. The main aim of NHM interventions such as Accredited Social Health
Activist (ASHA), Janani Suraksha Yojana (JSY), Janani Shishu Suraksha Karyakaram (JSSK), referral
transport is to promote institutional deliveries for reducing maternal mortality ratio. These might be in the
form of counselling, advertising, communitization, incentive or any other method of promoting 100
institutional deliveries such as collaborating with nongovernmental organizations, private sectors and
public sector undertakings through public private partnerships or reaching out to rural and poor and
other marginalized populations.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcome for this review is: Decrease in maternal mortality ratio.
Secondary outcome(s)
The secondary outcome for this review is: Increase in rate of institutional deliveries.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion.
3. Methods: Including the study design, study duration, sequence generation, allocation
concealment, and blinding.
4. Participants: Number and socio-demographics.
5. Interventions: Total groups or arms, and intervention details.
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection).
7. Results: Number of participants allocated in each group, sample size, missing data, summary
data, effect size estimates, and subgroup analysis (if applicable).
8. Other: Sources of funding.
9. Key conclusions.
10. Limitations.
11. Comments by the review authors.
12. Implications/Recommendations.
Two reviewers will extract the data independently and discuss with the other reviewers in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment 101
For this review, quality assessment would be conducted primarily for included studies focussing primarily
on maternal mortality ratio. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing impact of each strategy of NHM on maternal mortality ratio.
Meta-analysis will be conducted depending on availability of eligible studies. Minimum 5 studies will be
pooled and the results will be interpreted by using summary measures like risk ratio (in case of RCTs)
or percentages (in case of cross-sectional studies). The research findings will be aggregated to examine
the effectiveness of the interventions in focus under National Health Mission. The different interventions
will be pooled separately and the results will be described for each intervention. The results of those
studies which primarily focused upon maternal mortality ratio without referring to any particular
intervention will not be pooled for meta-analysis and will be narrated in the results. Finally,
recommendations will be made according to results obtained after extracting the results from each
eligible study. Subgroup analysis will be conducted as per the nature of the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Maternal
Mortality Ratio, Institutional Deliveries, Institutional Delivery Rate.
102
2.2. Impact of National Health Mission on Perinatal mortality rate of India: A Systematic Review
Registration ID: CRD42020147992
Review Question
In India, what is the impact of National Health Mission strategies on perinatal mortality rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
perinatal mortality rate will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on perinatal mortality
rate in India.
Participants
Neonates, antenatal/pregnant women, post-natal women.
Intervention(s), Exposure(s)
The exposure refers to any strategy focusing on improving perinatal health under the various strategies
implemented under National Health Mission, India. These interventions might be in the form of
counselling, advertising or any other method of improving neonatal health (such as collaborating with
nongovernmental organizations, private sectors and public sector undertakings) through public private
partnerships or reaching out to rural and poor and other marginalized populations.
Comparator(s)/control 103
Not applicable
Primary outcome(s)
The primary outcome for this review is: Perinatal mortality rate
Secondary outcome(s)
The secondary outcomes include: Stillbirth rate, Early Neonatal mortality rate.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion.
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding.
4. Participants: Number and socio-demographics.
5. Interventions: Total groups or arms, and intervention details.
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection).
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable).
8. Other: Sources of funding.
9. Key conclusions.
10. Limitations.
11. Comments by the review authors.
12. Implications/Recommendations. 104
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on perinatal mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on perinatal mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focused upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission strategies,
perinatal mortality rate.
105
2.3. Impact of National Health Mission on neonatal mortality rate of India: A Systematic Review
Review Question
In India, what is the impact of newborn health strategies under National Health Mission on neonatal
mortality rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
neonatal mortality rate will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on neonatal mortality in
India.
Participants
Neonates, antenatal/pregnant women, post-natal women.
Intervention(s), Exposure(s)
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on neonatal mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case 106
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focussed upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcome for this review is: Neonatal mortality rate
Secondary outcome(s)
The secondary outcomes include:
Breast feeding practices
Newborn care practices
Prevalence of LBW
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details 107
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on neonatal mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on neonatal mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focussed upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after 108
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Child health
strategies, Neonatal mortality rate.
2.4. Impact of National Health Mission on infant mortality rate of India: A Systematic Review
Review Question
In India, what is the impact of child health strategies under National Health Mission on infant mortality
rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
infant mortality rate will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on infant mortality in
India.
Participants
Women in reproductive age group (15-49 years)/eligible couples, Newborns, Infants, ASHA workers,
ANMs, Anganwadi workers, Service providers.
109
Intervention(s), Exposure(s)
The exposure refers to any strategy focusing on improving infant health under the Child Health
Programme implemented under National Health Mission, India. These interventions might be in the form
of counselling, advertising or any other method of improving infant health (such as collaborating with
nongovernmental organizations, private sectors and public sector undertakings) through public private
partnerships or reaching out to rural and poor and other marginalized populations.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcome for this review is: Infant mortality rate
Secondary outcome(s)
The secondary outcomes include:
Prevalence of exclusive breast feeding
Increased knowledge of ASHAs in HBPNC
Increase in immunization coverage
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details 110
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on infant mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on infant mortality rate.
The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies
will be pooled and the results will be interpreted by using summary measures like risk ratio (in the case
of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focused upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after 111
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Child health
strategies, Infant mortality rate.
112
2.5 Impact of National Health Mission on under 5 child mortality rate of India: A Systematic
Review
Review Question
In India, what is the impact of child health strategies under National Health Mission on under 5 child
mortality rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE.
Relevant articles and reports will be searched in Google and Google Scholar. Appropriate search
strategy would be used for conducting search in databases. In addition, the reference lists of all identified
articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies on
mortality rate in children under 5 years will be included for review. In addition grey literature will be hand
searched and evidence including reports from government and non-governmental agencies and reports
from international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission strategies on child mortality in
India.
Participants
Children up-to the age group of 5 years.
Intervention(s), Exposure(s)
The exposure refers to any strategy focusing on improving child health under the Child Health
Programme implemented under National Health Mission, India. These interventions might be in the form
of counselling, advertising or any other method of improving child health (such as collaborating with
nongovernmental organizations, private sectors and public sector undertakings) through public private
partnerships or reaching out to rural and poor and other marginalized populations.
Comparator(s)/control 113
Not applicable
Primary outcome(s)
The primary outcome for this review is:
Under 5 child mortality rate
Secondary outcome(s)
The secondary outcomes include:
Increase in immunization coverage
Decrease in malnutrition
Increase in Vitamin A supplementation
Incidence of pneumonia and diarrhoea
Early detection and treatment of diseases
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection) 114
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on child mortality in India. However, systematic data extraction would be conducted for all relevant
sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on under five mortality
rate. The meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5
studies will be pooled and the results will be interpreted by using summary measures like risk ratio (in
the case of RCTs) or percentages (in the case of cross-sectional studies) depending upon the study
findings. The research findings will be aggregated to examine the effectiveness of the interventions in
focus under the National Health Mission. The different interventions will be pooled separately and the
results will be described for each intervention. The results of those studies which primarily focused upon
neonatal mortality rate without referring to any particular intervention will not be pooled for meta-analysis
and will be narrated in the results. Finally, recommendations will be made according to results obtained
after extracting the results from each eligible study. Subgroup analysis will be conducted as per the
nature of the data obtained.
Subject index terms 115
National Rural Health Mission, National Urban Health Mission, National Health Mission, Child health
strategies, U 5 child mortality rate.
2.6. Impact of National Health Mission on total fertility rate of India: A systematic review
Review Question
In India,
1. Do the family planning program under National Health Mission had any impact on total fertility
rate?
2. Do the family planning program under National Health Mission had any impact on contraceptive
prevalence rate?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE and
CINAHL. The reference lists of all identified articles on interventions will be checked to identify relevant
studies. In addition, citations tracking of prominent researchers working in the field of family planning
will be conducted to identify relevant articles. Further, hand-searching of the contents of reputed
obstetric/public health journals and conference proceedings will also be conducted. Relevant articles
and reports will be searched in Google, Google Scholar, and in databases of agencies such as UNICEF
and WHO.
Types of studies to be included
Both quantitative and qualitative studies focussing upon impact of NHM strategies on family planning or
contraceptive usage will be included for review. In addition grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on family planning and contraceptive prevalence in India.
Participants
Women in reproductive age group (15-49 years)/ eligible couples.
Intervention(s), Exposure(s) 116
The exposure refers to any strategy focusing on birth control under the reproductive health program
implemented by the Ministry of Health and Family Welfare, India. These interventions might be in the
form of counselling, advertising, communitization or any other method of promoting family planning
methods (such as collaborating with nongovernmental organizations, private sectors and public sector
undertakings through public private partnerships or reaching out to rural and poor and other marginalized
populations.
Comparator(s)/control
Not applicable
Primary outcome(s)
The primary outcomes for this review are:
Total fertility rate
Contraceptive prevalence rate
Secondary outcome(s)
The secondary outcomes include:
Total unmet need
Gaps in strategies for family planning under National Health Mission.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details 117
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing
primarily on total fertility rate in India. However, systematic data extraction would be conducted for all
relevant sources. For this review, quality assessment would be conducted primarily on total fertility
rate and contraceptive prevalence rate in India. However, systematic data extraction would be
conducted for all relevant sources. The Cochrane risk of bias tool will be used to assess the internal
validity. The quality assessment will be done by two reviewers and any disagreement between
reviewers judgement will be resolved by the third reviewer. Depending upon the study design the risk
of bias will be assessed. In randomized control trials the clarity in description of randomization,
allocation concealment and blinding will be assessed. The study will be assessed critically on the
basis of methodology followed in the study. The studies will be segregated in terms of low, moderate
and high risk of bias. The studies with minimal risk of bias will be pooled for meta-analysis.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of each strategy of NHM on total fertility rate. The
meta-analysis will be conducted depending on the availability of eligible studies. Minimum 5 studies will
be pooled and the results will be interpreted by using summary measures like risk ratio (in the case of 118
RCTs) or percentages (in the case of cross-sectional studies) depending upon the study findings. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The different interventions will be pooled separately and the results will be
described for each intervention. The results of those studies which primarily focused upon neonatal
mortality rate without referring to any particular intervention will not be pooled for meta-analysis and will
be narrated in the results. Finally, recommendations will be made according to results obtained after
extracting the results from each eligible study. Subgroup analysis will be conducted as per the nature of
the data obtained.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g. urban and
rural settings, education status) on outcomes such as contraceptive prevalence rate will be summarized
by relevant measures (e.g., rate ratios).
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Total Fertility
Rate, Family Planning, Contraceptive Prevalence Rate.
119
2.7 Level of awareness and utilization of Adolescent Reproductive and Sexual Health Services
clinics in India: A systematic review
Review Question
In India,
1) What is the level of awareness and utilization of adolescent reproductive and sexual health
service clinics in India?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE. The
reference lists of all identified articles on interventions will be checked to identify relevant studies. In
addition, citations tracking of prominent researchers working in the field of adolescent health will be
conducted to identify relevant articles. Further, hand-searching of the contents of reputed public health
journals and conference proceedings will also be conducted. Relevant articles and reports will be
searched in Google, Google Scholar, and in databases of agencies such as WHO.
Types of studies to be included
Both quantitative and qualitative studies focusing upon awareness of adolescent reproductive and
sexual health service (ARSH) clinics implemented as a strategy under national health mission (NHM)
for providing information regarding sex, stages of development, RTI/STI or menstrual hygiene to the
adolescent age group will be included for review. In addition, grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies will also be included.
Condition or domain being used
This systematic review focuses on level of awareness and utilization of adolescent reproductive and
sexual health service clinics in India.
Intervention(s), Exposure(s)
The exposure refers to the awareness and utilization of ARSH services under NHM implemented by the
Ministry of Health and Family Welfare, India by adolescents for any purpose related to their health. The
purpose may be for procuring sanitary napkins or asking for any guidance from counsellors.
Comparator(s)/control 120
In case a randomized control study or a quasi-experimental study has been conducted the controls will
include those adolescents which will not be given the above stated intervention.
Primary outcome(s)
The primary outcomes for this review are:
Awareness and utilization of adolescent reproductive and sexual health service clinics
Secondary outcome(s)
Nil
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA/STROBE guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding (if applicable)
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations 121
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing
primarily on awareness of ARSH clinics among adolescents in India. However, systematic data
extraction would be conducted for all relevant sources. The Cochrane risk of bias tool will be used to
assess the internal validity. The quality assessment will be done by two reviewers and any
disagreement between reviewers judgement will be resolved by the third reviewer. Depending upon
the study design the risk of bias will be assessed. In randomized control trials the clarity in description
of randomization, allocation concealment and blinding will be assessed. The study will be assessed
critically on the basis of methodology followed in the study. The studies will be segregated in terms
of low, moderate and high risk of bias. The studies with minimal risk of bias will be pooled for meta-
analysis.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. A formal
narrative synthesis will be done showing the impact of ARSH clinics on awareness and utilization by
adolescents in India. A meta-analysis will be conducted depending on the availability of eligible studies.
Minimum 5 studies will be pooled and the results will be interpreted by using summary measures like
risk ratio (in the case of RCTs) or percentages (in the case of cross-sectional studies). The research
findings will be aggregated to examine the effectiveness of the interventions in focus under the
National Health Mission. The results of those studies which primarily focused upon the ARSH strategy
will be pooled for meta-analysis. Finally, recommendations will be made according to results obtained
after extracting the results from each eligible study. Subgroup analysis will be conducted as per the
nature of the data obtained.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g. Urban
and rural settings, education status) on outcomes such as utilization of ARSH clinics will be summarized
by relevant measures (e.g. proportions). 122
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, adolescent
reproductive and sexual health (ARSH), Adolescent health, Anaemia
2.8 Level of awareness and utilization of Menstrual Hygiene Scheme in India: A systematic review
Registration ID: CRD42020148116
Review Question
In India,
1) What is the level of awareness regarding menstrual hygiene among adolescents in India?
2) What is the utilization rate of sanitary napkins among adolescents in India?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE. The
reference lists of all identified articles on interventions will be checked to identify relevant studies. In
addition, citations tracking of prominent researchers working in the field of adolescent health will be
conducted to identify relevant articles. Further, hand-searching of the contents of reputed public health
journals and conference proceedings will also be conducted. Relevant articles and reports will be
searched in Google, Google Scholar, and in databases of agencies such as WHO.
Types of studies to be included
Both quantitative and qualitative studies focusing upon awareness of menstrual hygiene or utilization
rate of sanitary napkins among adolescent age group published after the launch of national rural health
mission (NRHM) will be included for review. In addition, grey literature will be hand searched and
evidence including reports from government and non-governmental agencies and reports from
international agencies like UNICEF will also be included.
Condition or domain being used
This systematic review focuses on level of awareness regarding menstrual hygiene and utilization rate
of sanitary napkins among adolescents in India.
Intervention(s), Exposure(s)
The exposure refers to the awareness generation regarding menstrual hygiene that may be through
information education and communication by organizing camps in schools or in residential areas. In 123
case of cross-sectional studies assessment of the knowledge and awareness about menstrual hygiene
program being implemented under NHM by the Ministry of Health and Family Welfare, India will be done.
Apart from this the usage of sanitary napkins will be assessed as these are provided at subsidized rates
under menstrual hygiene scheme.
Comparator(s)/control
In case a randomized control study or a quasi-experimental study has been conducted the controls will
include those adolescents which will not be given the above stated intervention.
Primary outcome(s)
The primary outcomes for this review are:
Awareness about menstrual hygiene
Utilization rate of sanitary napkins among adolescents
Secondary outcome(s)
Nil
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA/STROBE guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding (if applicable)
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection) 124
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implication recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on awareness generation regarding menstrual hygiene or utilization of sanitary napkins among
adolescents in India. However, systematic data extraction would be conducted for all relevant sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g., urban
and rural settings, education status) on outcomes such as utilization of sanitary napkins will be
summarized by relevant measures (e.g. proportions).
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Menstrual
Hygiene, Menstrual Hygiene Scheme, Adolescent health.
125
2.9 Impact of weekly iron and folic acid supplementation on prevalence of anaemia among
adolescents in India: A systematic review
Review Question
In India,
1) Does the Weekly Iron and Folic acid supplementation program under National Health Mission
had any impact on reducing anaemia in adolescents?
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE. The
reference lists of all identified articles on interventions will be checked to identify relevant studies. In
addition, citations tracking of prominent researchers working in the field of adolescent health will be
conducted to identify relevant articles. Further, hand-searching of the contents of reputed public health
journals and conference proceedings will also be conducted. Relevant articles and reports will be
searched in Google, Google Scholar, and in databases of agencies such as UNICEF and WHO.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of weekly supplementation of iron and
folic acid (WIFS) program implemented as a strategy under national health mission (NHM) on
prevalence of anemia among adolescents in India will be included for review. In addition, grey literature
will be hand searched and evidence including reports from government and non-governmental agencies
and reports from international agencies will also be included.
Condition or domain being used
This systematic review focuses on prevalence of anaemia among adolescents after the launch of WIFS
program in India.
Intervention(s), Exposure(s)
The exposure refers to the intake of iron and folic acid supplementation in any dose under the WIFS
program under NHM implemented by the Ministry of Health and Family Welfare, India. These
interventions might be in the form of tablets or syrups provided to the adolescents by public sector
undertakings or nongovernmental organizations, private sectors or through public private partnerships.
Comparator(s)/control 126
In case a randomized control study or a quasi-experimental study has been conducted the controls will
include those adolescents which will not be given the above stated intervention.
Primary outcome(s)
The primary outcome for this review is:
Prevalence of anaemia
Secondary outcome(s)
The secondary outcomes include:
Improvement in body mass index
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA/STROBE guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation concealment,
and blinding (if applicable)
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary data,
effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions 127
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
The two reviewers will extract the data independently and discuss with the third reviewer in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing primarily
on prevalence of anaemia among adolescents after the implementation of WIFS program in India.
However, systematic data extraction would be conducted for all relevant sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data.
The research findings will be aggregated to examine the effectiveness of the interventions in focus under
WIFS program.
Analysis of subgroups or subsets
We will conduct appropriate analysis as per the nature of data. Differences in subgroups (e.g., urban
and rural settings, education status) on outcomes such as prevalence of anaemia will be summarized
by relevant measures (e.g., rate ratios, mean difference).
Subject index terms
National Rural Health Mission, National Urban Health Mission, National Health Mission, Weekly Iron and
Folic Acid Supplementation (WIFS), Adolescent health, Anaemia.
128
2.10. Impact of Road Connectivity, Mobile Connectivity and Others Variables on Health
Outcomes in India: A Systematic Review
Review Question
In India,
1) Do Road Connectivity, Mobile Connectivity and other variables such as water supply, sanitation and
nutrition, had any impact on health outcomes?
Methods
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE
databases and Google Scholar. MeSH terms will be used to search the references and the reference
lists of all identified articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of variables such as road connectivity
and mobile connectivity on health outcomes will be included for review. In addition grey literature will be
hand searched and evidence including reports from government and non-governmental agencies and
reports from international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of variables such as road connectivity and mobile connectivity
on health outcomes.
Participants/population
Pregnant/antenatal, postpartum females, health workers, children, adolescents.
Intervention(s), Exposure(s)
The exposure refers to any variables focusing on health outcomes. These variables might be any social
or infrastructural, impacting health outcomes.
Comparator(s)/control
Not applicable
Primary outcome(s) 129
The primary outcome for this review is: Impact on health outcomes.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation
concealment, and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary
data, effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
Two reviewer will extract the data independently and discuss with the other reviewers in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focussing on
impact of road and mobile connectivity on health outcomes. However, systematic data extraction would
be conducted for all relevant sources.
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data
The research findings will be aggregated to examine the effectiveness of the road and mobile
connectivity and other variables in focus of health outcomes.
Subject index terms 130
Road connectivity, mobile connectivity, water supply, nutrition, health outcomes.
2.11. Impact of National Health Mission on maternal and child health inequalities in India: A
Systematic Review
Review Question
What is the impact of National Health Mission on maternal and child health inequalities in India?
Methods
Searches
Studies published between the years 2005 and 2018 will be identified using the PubMed, EMBASE
databases and Google Scholar. MeSH terms will be used to search the references and the reference
lists of all identified articles on interventions will be checked to identify relevant studies.
Types of studies to be included
Both quantitative and qualitative studies focusing upon impact of National Health Mission strategies
on health inequalities (maternal and child health) will be included for review. In addition grey
literature will be hand searched and evidence including reports from government and non-
governmental agencies and reports from international agencies will also be included.
Condition or domain being used
This systematic review focuses on impact of National Health Mission on maternal and child health
inequalities.
Participants/population
Mothers, pregnant females, postpartum females, children
Intervention(s), Exposure(s)
The exposure refers to any strategy of National Health Mission India focusing on maternal and child
health inequalities. These interventions might be in the form of counselling, advertising,
communitization, incentive or any other method of promoting maternal and child health such as
collaborating with nongovernmental organizations, private sectors and public sector undertakings 131
through public private partnerships or reaching out to rural and poor and other marginalised
population.
Comparator(s)/control
Not applicable
Primary outcome(s)
Impact on maternal and child health inequalities after launch of National Health Mission in India.
Data extraction
After identifying eligible studies, data will be extracted using a structured form by two reviewers using
PRISMA guidelines. The form will contain:
1. Source: Citation and other contact details.
2. Eligibility: Including the reasons for inclusion
3. Methods: Including the study design, study duration, sequence generation, allocation
concealment, and blinding
4. Participants: Number and socio-demographics
5. Interventions: Total groups or arms, and intervention details
6. Outcomes: Outcomes measurement, outcomes definition, scales used if any (with time points of
collection)
7. Results: Number of participants allocated in each group, sample size, missing data, summary
data, effect size estimates, and subgroup analysis (if applicable)
8. Other: Sources of funding
9. Key conclusions
10. Limitations
11. Comments by the review authors
12. Implications/Recommendations
Two reviewer will extract the data independently and discuss with the other reviewers in case of any
disagreement. Reviewers will enter relevant information into Review Manager 5.1 or STATA for meta-
analysis using a structured data extraction form.
Risk of bias (quality) assessment
For this review, quality assessment would be conducted primarily for included studies focusing
primarily on maternal and child health inequalities. However, systematic data extraction would be
conducted for all relevant sources. 132
Strategy for data synthesis
Aggregate data will be used to synthesize results depending on the quality of the mined data. The
research findings will be aggregated to examine the effectiveness of the interventions in focus under
National Health Mission.
Subject index terms
Health inequalities, maternal health inequalities, child health inequalities, National Rural Health
Mission, National Urban Health Mission, National Health Mission, Janani Suraksha Yojana,
Accredited Social Health Activist, Janani Shishu Surakhsha Karyakram, referral transport.
ANNEXURE 3. MeSH STRATEGY.
Maternal Health
Keywords
MeSH
Maternal mortality
ratio AND India
(("maternal mortality"[MeSH Terms] OR ("maternal"[All Fields] AND
"mortality"[All Fields]) OR "maternal mortality"[All Fields]) AND ("Ratio
(Oxf)"[Journal] OR "ratio"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"National Health
Mission" impact on
"Maternal mortality
ratio" AND "India"
"National Health Mission"[All Fields] AND ("Impact (Am Coll
Physicians)"[Journal] OR "impact"[All Fields]) AND "Maternal mortality ratio"[All
Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Birth preparedness
and complication
readiness AND
maternal mortality
ratio AND India
(("parturition"[MeSH Terms] OR "parturition"[All Fields] OR "birth"[All Fields])
AND preparedness[All Fields] AND complication[All Fields] AND readiness[All
Fields]) AND (("maternal mortality"[MeSH Terms] OR ("maternal"[All Fields]
AND "mortality"[All Fields]) OR "maternal mortality"[All Fields]) AND ("Ratio
(Oxf)"[Journal] OR "ratio"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Janani Suraksha
Yojana
"Janani Suraksha Yojana"[All Fields] AND "India"[All Fields]
Janani Shishu
Suraksha Karyakram
“Janani Shishu Suraksha Karyakram"[All Fields] AND "India"[All Fields])
Antenatal care OR
Postnatal care OR
Intranatal care AND
("prenatal care"[MeSH Terms] OR ("prenatal"[All Fields] AND "care"[All Fields])
OR "prenatal care"[All Fields] OR ("antenatal"[All Fields] AND "care"[All
Fields]) OR "antenatal care"[All Fields]) OR ("postnatal care"[MeSH Terms] OR
("postnatal"[All Fields] AND "care"[All Fields]) OR "postnatal care"[All Fields])
Maternal mortality
ratio AND India
OR (Intranatal[All Fields] AND care[All Fields]) AND (("maternal
mortality"[MeSH Terms] OR ("maternal"[All Fields] AND "mortality"[All Fields])
OR "maternal mortality"[All Fields]) AND ("Ratio (Oxf)"[Journal] OR "ratio"[All
Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"free ambulance"
AND "maternal
mortality ratio" AND
"India"
"free ambulance"[All Fields] AND "maternal mortality ratio"[All Fields] AND
"India"[All Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
(ASHA role) AND
Maternal mortality
(("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All Fields]) AND
("role"[MeSH Terms] OR "role"[All Fields])) AND ("maternal mortality"[MeSH
Terms] OR ("maternal"[All Fields] AND "mortality"[All Fields]) OR "maternal
mortality"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
((ASHA worker) AND
Maternal health) AND
India
((("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All Fields]) AND
("occupational groups"[MeSH Terms] OR ("occupational"[All Fields] AND
"groups"[All Fields]) OR "occupational groups"[All Fields] OR "worker"[All
Fields])) AND ("maternal health"[MeSH Terms] OR ("maternal"[All Fields] AND
"health"[All Fields]) OR "maternal health"[All Fields])) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
((ASHA) AND
maternal mortality
ratio) AND India
(("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All Fields]) AND
(("maternal mortality"[MeSH Terms] OR ("maternal"[All Fields] AND
"mortality"[All Fields]) OR "maternal mortality"[All Fields]) AND ("Ratio
(Oxf)"[Journal] OR "ratio"[All Fields]))) AND ("india"[MeSH Terms] OR
"india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
referral transport
AND maternal
mortality AND India
((("referral and consultation"[MeSH Terms] OR ("referral"[All Fields] AND
"consultation"[All Fields]) OR "referral and consultation"[All Fields] OR
"referral"[All Fields]) AND ("biological transport"[MeSH Terms] OR
("biological"[All Fields] AND "transport"[All Fields]) OR "biological transport"[All
Fields] OR "transport"[All Fields])) AND ("maternal mortality"[MeSH Terms] OR
("maternal"[All Fields] AND "mortality"[All Fields]) OR "maternal mortality"[All
Fields])) AND ("india"[MeSH Terms OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"Prahdhan Mantri
Matritva Vandana
Yojana" AND
"maternal mortality
ratio" AND "India"
(mantri[All Fields] AND matritva[All Fields] AND vandana[All Fields] AND
("Yojana"[Journal] OR "yojana"[All Fields])) AND "maternal mortality ratio"[All
Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"Prahdhan Mantri
Surakshit Matritva
Abhiyan" AND
"maternal mortality
ratio" AND "India"
(Mantri[All Fields] AND Surakshit[All Fields] AND Matritva[All Fields] AND
Abhiyan[All Fields]) AND "maternal mortality ratio"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"Prahdhan Mantri
Matritva Sahyog
Yojna" AND
"maternal mortality
ratio" AND "India"
(Mantri[All Fields] AND Matritva[All Fields] AND Sahyog[All Fields] AND
Yojna[All Fields]) AND "maternal mortality ratio"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
NEWBORN AND CHILD HEALTH
Neonatal Mortality
rate (NMR)
"Infant mortality"[MeSH Terms] OR ("infant"[All Fields] AND "mortality"[All
Fields]) OR "infant mortality"[All Fields] OR ("neonatal"[All Fields] AND
"mortality"[All Fields]) OR "neonatal mortality"[All Fields]
Facility based
newborn care
(FBNC)
Facility[All Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All
Fields] OR "newborn"[All Fields]) AND care[All Fields]
Essential newborn
care
Essential[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All
Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"newborn"[All Fields]) AND care[All Fields]
Special New Born
Care Units (SNCUs)
Special[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All Fields]
AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "newborn"[All
Fields]) AND care[All Fields] AND unit[All Fields]
New Born Baby
Corners (NBCCs)
New[All Fields] AND ("parturition"[MeSH Terms] OR "parturition"[All Fields] OR
"born"[All Fields]) AND ("infant, newborn"[MeSH Terms] OR ("infant"[All Fields]
AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "baby"[All Fields]
OR "infant"[MeSH Terms] OR "infant"[All Fields]) AND corners[All Fields]) OR
"NBCC"[All Fields]
Breast feeding
practices
Breast feeding practices"[All Fields] AND "India"[MeSH Terms]
Navjat Shishu
Shuraksha
Karyakaram (NSSK)
Navjat[All Fields] AND shishu [All Fields] AND suraksha [All Fields] AND
karyakram [All Fields]) OR NSSK[All Fields]
Home based
newborn care by
ASHA (HBNC)
Home [All Fields] AND BASED[All Fields] AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All
Fields] OR "newborn"[All Fields]) AND CARE[All Fields] AND ("ASHA"[Journal]
OR "ASHA Suppl"[Journal] OR "asha"[All Fields]
Infant and Young
Child Feeding
Practices AND
India
Infant[Title] AND Young[Title] AND Child[Title] AND Feeding[Title] AND
Practices[Title] AND india[Title]
Home based
newborn care by
ASHA AND India
(Home[All Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All
Fields] OR "newborn"[All Fields]) AND care[All Fields] AND ("ASHA"[Journal]
OR "ASHA Suppl"[Journal] OR "asha"[All Fields])) AND ("india"[MeSH Terms]
OR "india"[All Fields])
Integrated
management of
neonatal and
childhood illness
AND Children AND
India
(Integrated[All Fields] AND ("organization and administration"[MeSH Terms]
OR ("organization"[All Fields] AND "administration"[All Fields]) OR
"organization and administration"[All Fields] OR "management"[All Fields] OR
"disease management"[MeSH Terms] OR ("disease"[All Fields] AND
"management"[All Fields]) OR "disease management"[All Fields]) AND
("infant, newborn"[MeSH Terms] OR ("infant"[All Fields] AND "newborn"[All
Fields]) OR "newborn infant"[All Fields] OR "neonatal"[All Fields]) AND
("Childhood"[Journal] OR "childhood"[All Fields]) AND illness[All Fields]) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND (("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Early initiation and
exclusive breast
feeding
Early[All Fields] AND initiation[All Fields] AND ("breast feeding"[MeSH Terms]
OR ("breast"[All Fields] AND "feeding"[All Fields]) OR "breast feeding"[All
Fields] OR ("exclusive"[All Fields] AND "breast"[All Fields] AND "feeding"[All
Fields]) OR "exclusive breast feeding"[All Fields]
Tracking of low birth
weight babies
Tracking[All Fields] AND ("infant, low birth weight"[MeSH Terms] OR
("infant"[All Fields] AND "low"[All Fields] AND "birth"[All Fields] AND "weight"[All
Fields]) OR "low birth weight infant"[All Fields] OR ("low"[All Fields] AND
"birth"[All Fields] AND "weight"[All Fields]) OR "low birth weight"[All Fields])
AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR "babies"[All Fields]
Mothers’ Absolute
Affection
Programme (MAA)
Mothers'[All Fields] AND Absolute[All Fields] AND Affection[All Fields] AND
Programme[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]
Management of
Diarrheal diseases
with ORS and zinc
AND Infants AND
India
(("organization and administration"[MeSH Terms] OR ("organization"[All
Fields] AND "administration"[All Fields]) OR "organization and
administration"[All Fields] OR "management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All
Fields]) OR "disease management"[All Fields]) AND Diarrheal[All Fields] AND
("disease"[MeSH Terms] OR "disease"[All Fields] OR "diseases"[All Fields])
AND ("ORALIT"[Supplementary Concept] OR "ORALIT"[All Fields] OR
"ors"[All Fields]) AND ("zinc"[MeSH Terms] OR "zinc"[All Fields])) AND
("infant"[MeSH Terms] OR "infant"[All Fields] OR "infants"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields])
Intensified
Diarrhea Control
Fortnight AND
Infants AND India
(Intensified[All Fields] AND ("diarrhoea"[All Fields] OR "diarrhea"[MeSH
Terms] OR "diarrhea"[All Fields]) AND ("prevention and control"[Subheading]
OR ("prevention"[All Fields] AND "control"[All Fields]) OR "prevention and
control"[All Fields] OR "control"[All Fields] OR "control groups"[MeSH Terms]
OR ("control"[All Fields] AND "groups"[All Fields]) OR "control groups"[All
Fields]) AND Fortnight[All Fields]) AND ("infant"[MeSH Terms] OR "infant"[All
Fields] OR "infants"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Mothers’ Absolute
Affection
Programme (MAA)
(Mothers'[All Fields] AND Absolute[All Fields] AND Affection[All Fields] AND
Programme[All Fields]) AND MAA[All Fields] AND ("india"[MeSH Terms] OR
"india"[All Fields])
Tracking of low
birth weight babies
AND India
(Tracking[All Fields] AND ("infant, low birth weight"[MeSH Terms] OR
("infant"[All Fields] AND "low"[All Fields] AND "birth"[All Fields] AND "weight"[All
Fields]) OR "low birth weight infant"[All Fields] OR ("low"[All Fields] AND
"birth"[All Fields] AND "weight"[All Fields]) OR "low birth weight"[All Fields])
AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR "babies"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields])
Management of
Acute Respiratory
Infections AND
Infants AND India
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields]
AND "administration"[All Fields]) OR "organization and administration"[All
Fields] OR "management"[All Fields] OR "disease management"[MeSH Terms]
OR ("disease"[All Fields] AND "management"[All Fields]) OR "disease
management"[All Fields]) AND Acute[All Fields] AND ("respiratory tract
infections"[MeSH Terms] OR ("respiratory"[All Fields] AND "tract"[All Fields]
AND "infections"[All Fields]) OR "respiratory tract infections"[All Fields] OR
("respiratory"[All Fields] AND "infections"[All Fields]) OR "respiratory
infections"[All Fields])) AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR
"infants"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields])
Micronutrient
supplementation
(Vitamin A, Iron
Folic Acid) AND
Infants AND
Mortality AND
India
(("trace elements"[Pharmacological Action] OR
"micronutrients"[Pharmacological Action] OR "trace elements"[MeSH Terms]
OR ("trace"[All Fields] AND "elements"[All Fields]) OR "trace elements"[All
Fields] OR "micronutrient"[All Fields] OR "micronutrients"[MeSH Terms] OR
"micronutrients"[All Fields]) AND supplementation[All Fields]) AND (("vitamin
a"[MeSH Terms] OR "vitamin a"[All Fields]) AND ("iron"[MeSH Terms] OR
"iron"[All Fields]) AND ("folic acid"[MeSH Terms] OR ("folic"[All Fields] AND
"acid"[All Fields]) OR "folic acid"[All Fields])) AND ("infant"[MeSH Terms] OR
"infant"[All Fields] OR "infants"[All Fields]) AND ("mortality"[Subheading] OR
"mortality"[All Fields] OR "mortality"[MeSH Terms]) AND ("india"[MeSH Terms]
OR "india"[All Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Early initation and
exclusive breast
feeding AND India
(early[All Fields] AND initiation[All Fields] AND ("breast feeding"[MeSH Terms]
OR ("breast"[All Fields] AND "feeding"[All Fields]) OR "breast feeding"[All
Fields] OR ("exclusive"[All Fields] AND "breast"[All Fields] AND "feeding"[All
Fields]) OR "exclusive breast feeding"[All Fields])) AND ("india"[MeSH Terms]
OR "india"[All Fields])
Full immunization
coverage AND
Children AND India
(Full[All Fields] AND ("vaccination coverage"[MeSH Terms] OR ("vaccination"[All
Fields] AND "coverage"[All Fields]) OR "vaccination coverage"[All Fields] OR
("immunization"[All Fields] AND "coverage"[All Fields]) OR "immunization
coverage"[All Fields])) AND ("child"[MeSH Terms] OR "child"[All Fields] OR
"children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Complementary
feeding practices
AND Infants AND
India
(("infant nutritional physiological phenomena"[MeSH Terms] OR ("infant"[All
Fields] AND "nutritional"[All Fields] AND "physiological"[All Fields] AND
"phenomena"[All Fields]) OR "infant nutritional physiological phenomena"[All
Fields] OR ("complementary"[All Fields] AND "feeding"[All Fields]) OR
"complementary feeding"[All Fields]) AND practices[All Fields]) AND
("infant"[MeSH Terms] OR "infant"[All Fields] OR "infants"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Prevalence of
diarrhea in Infants
in India
(("epidemiology"[Subheading] OR "epidemiology"[All Fields] OR "prevalence"[All
Fields] OR "prevalence"[MeSH Terms]) AND ("diarrhoea"[All Fields] OR
"diarrhea"[MeSH Terms] OR "diarrhea"[All Fields]) AND ("infant"[MeSH Terms]
OR "infant"[All Fields] OR "infants"[All Fields]) AND ("india"[MeSH Terms] OR
"india"[All Fields])) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Management of
pneumonia AND
Infants AND India
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields]
AND "administration"[All Fields]) OR "organization and administration"[All Fields]
OR "management"[All Fields] OR "disease management"[MeSH Terms] OR
("disease"[All Fields] AND "management"[All Fields]) OR "disease
management"[All Fields]) AND ("pneumonia"[MeSH Terms] OR "pneumonia"[All
Fields])) AND ("infant"[MeSH Terms] OR "infant"[All Fields] OR "infants"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Impact Indicator:
Infant Mortality Rate
in India
(("infant mortality"[MeSH Terms] OR ("infant"[All Fields] AND "mortality"[All
Fields]) OR "infant mortality"[All Fields]) AND ("J Rehabil Assist Technol
Eng"[Journal] OR "rate"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields])) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Perinatal mortality
rate AND India
"perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND "mortality"[All
Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH Terms] OR
("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All Fields] OR
("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("india"[MeSH Terms] OR
"india"[All Fields]) AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Impact of Home
based newborn care
on perinatal
mortality india
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND home[All
Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All
Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "newborn"[All
Fields]) AND care[All Fields] AND ("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All
Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All
Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields])) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Janani Suraksha
Yojana AND
Perinatal mortality
AND India
(Janani[All Fields] AND Suraksha[All Fields] AND ("Yojana"[Journal] OR "yojana"[All
Fields])) AND ("perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND
"mortality"[All Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH
Terms] OR ("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All
Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of "Janani
Shishu Suraksha
Karyakram" AND
"Perinatal Mortality"
AND India
("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND "Janani Shishu
Suraksha Karyakram"[All Fields] AND "Perinatal Mortality"[All Fields] AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Impact of
"Institutional
Delieveries" AND
=("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND
Institutional[All Fields] AND "Perinatal Mortality"[All Fields] AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"Perinatal Mortality"
AND India
Accredited Social
Health Activist AND
Perinatal Mortality
AND India
(Accredited[All Fields] AND Social[All Fields] AND ("health"[MeSH Terms] OR
"health"[All Fields]) AND Activist[All Fields]) AND ("perinatal mortality"[MeSH Terms]
OR ("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All
Fields] OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND
"death"[All Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND
"mortality"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of Navjat
Shishu Suraksha
Krayakram on
Perinatal Mortality
AND India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND Shishu[All
Fields] AND Suraksha[All Fields] AND ("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All
Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All
Fields]))) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Facility based
newborn care AND
perinatal mortality
AND India
(Facility[All Fields] AND based[All Fields] AND ("infant, newborn"[MeSH Terms] OR
("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"newborn"[All Fields]) AND care[All Fields]) AND ("perinatal mortality"[MeSH Terms]
OR ("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All
Fields] OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND
"death"[All Fields]) OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND
"mortality"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Essential newborn
care AND Perinatal
(Essential[All Fields] AND ("infant, newborn"[MeSH Terms] OR ("infant"[All Fields]
AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR "newborn"[All Fields])
mortality rate AND
India
AND care[All Fields]) AND (("perinatal mortality"[MeSH Terms] OR ("perinatal"[All
Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields] OR "perinatal
death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All Fields]) OR
"perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields]))
AND ("J Rehabil Assist Technol Eng"[Journal] OR "rate"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]
Traditional Birth
attendants AND
Perinatal mortality in
India
("midwifery"[MeSH Terms] OR "midwifery"[All Fields] OR ("traditional"[All Fields] AND
"birth"[All Fields] AND "attendants"[All Fields]) OR "traditional birth attendants"[All
Fields]) AND (("perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND
"mortality"[All Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH
Terms] OR ("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All
Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("india"[MeSH
Terms] OR "india"[All Fields])) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Special New Born
Care Units (SNCUs)
AND Perinatal
mortality in India
(Special[All Fields] AND New[All Fields] AND ("parturition"[MeSH Terms] OR
"parturition"[All Fields] OR "born"[All Fields]) AND Care[All Fields] AND Units[All
Fields]) AND SNCUs[All Fields] AND (("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All Fields])
OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields])) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Birth preparedness
and complication
readiness AND
perinatal mortality
rate AND India
(("parturition"[MeSH Terms] OR "parturition"[All Fields] OR "birth"[All Fields]) AND
preparedness[All Fields] AND complication[All Fields] AND readiness[All Fields]) AND
(("perinatal mortality"[MeSH Terms] OR ("perinatal"[All Fields] AND "mortality"[All
Fields]) OR "perinatal mortality"[All Fields] OR "perinatal death"[MeSH Terms] OR
("perinatal"[All Fields] AND "death"[All Fields]) OR "perinatal death"[All Fields] OR
("perinatal"[All Fields] AND "mortality"[All Fields])) AND ("J Rehabil Assist Technol
Still birth rate AND
India
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of Jannani
Suraksha
Yojana(JSY) on still
birth rate AND India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND Suraksha[All
Fields] AND ("Yojana"[Journal] OR "yojana"[All Fields])) AND JSY[All Fields] AND
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of Jannani
Shishu Suraksha
Karyakram(JSSK)
on still birth rate
AND India
Impact of Jannani Shishu Suraksha Karyakram(JSSK) on still birth rate (("Impact (Am
Coll Physicians)"[Journal] OR "impact"[All Fields]) AND Shishu[All Fields] AND
Suraksha[All Fields] AND Karyakram[All Fields]) AND JSSK[All Fields] AND
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Eng"[Journal] OR "rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields])
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Antenatal care OR
Postnatal care OR
Intranatal care AND
perinatal mortality
AND India
("prenatal care"[MeSH Terms] OR ("prenatal"[All Fields] AND "care"[All Fields]) OR
"prenatal care"[All Fields] OR ("antenatal"[All Fields] AND "care"[All Fields]) OR
"antenatal care"[All Fields]) OR ("postnatal care"[MeSH Terms] OR ("postnatal"[All
Fields] AND "care"[All Fields]) OR "postnatal care"[All Fields]) OR (Intranatal[All
Fields] AND care[All Fields]) AND ("perinatal mortality"[MeSH Terms] OR
("perinatal"[All Fields] AND "mortality"[All Fields]) OR "perinatal mortality"[All Fields]
OR "perinatal death"[MeSH Terms] OR ("perinatal"[All Fields] AND "death"[All Fields])
OR "perinatal death"[All Fields] OR ("perinatal"[All Fields] AND "mortality"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Antenatal care OR
Intranatal care AND
still birth rate AND
India
("prenatal care"[MeSH Terms] OR ("prenatal"[All Fields] AND "care"[All Fields]) OR
"prenatal care"[All Fields] OR ("antenatal"[All Fields] AND "care"[All Fields]) OR
"antenatal care"[All Fields]) OR (Intranatal[All Fields] AND care[All Fields]) AND
(("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All
Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR
"rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Care during labour
and child birth AND
still birth rate AND
India
(Care[All Fields] AND ("labour"[All Fields] OR "work"[MeSH Terms] OR "work"[All
Fields] OR "labor"[All Fields] OR "labor, obstetric"[MeSH Terms] OR ("labor"[All Fields]
AND "obstetric"[All Fields]) OR "obstetric labor"[All Fields]) AND ("child"[MeSH Terms]
OR "child"[All Fields]) AND ("parturition"[MeSH Terms] OR "parturition"[All Fields] OR
"birth"[All Fields])) AND (("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields] OR ("still"[All
Fields] AND "birth"[All Fields]) OR "still birth"[All Fields]) AND ("J Rehabil Assist
Technol Eng"[Journal] OR "rate"[All Fields])) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
India Newborn
Action Plan (INAP)
and still birth rate
(("india"[MeSH Terms] OR "india"[All Fields]) AND ("infant, newborn"[MeSH Terms]
OR ("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"newborn"[All Fields]) AND "action"[All Fields] AND Plan[All Fields]) AND
("isonitrosoacetophenone"[Supplementary Concept] OR "isonitrosoacetophenone"[All
Fields] OR "inap"[All Fields]) AND (("stillbirth"[MeSH Terms] OR "stillbirth"[All Fields]
OR ("still"[All Fields] AND "birth"[All Fields]) OR "still birth"[All Fields]) AND "rate"[All
Fields])
Accredited Social
Health
Activitist(ASHA)
role AND still birth
rate AND India
(Accredited[All Fields] AND Social[All Fields] AND ("health"[MeSH Terms] OR
"health"[All Fields])) AND ("ASHA"[Journal] OR "ASHA Suppl"[Journal] OR "asha"[All
Fields]) AND ("role"[MeSH Terms] OR "role"[All Fields]) AND (("stillbirth"[MeSH Terms]
OR "stillbirth"[All Fields] OR ("still"[All Fields] AND "birth"[All Fields]) OR "still birth"[All
Fields]) AND ("J Rehabil Assist Technol Eng"[Journal] OR "rate"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Management of
Diarrheal
diseases with
ORS and zinc
AND Children
AND india
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields] AND
"administration"[All Fields]) OR "organization and administration"[All Fields] OR
"management"[All Fields] OR "disease management"[MeSH Terms] OR ("disease"[All
Fields] AND "management"[All Fields]) OR "disease management"[All Fields]) AND
Diarrheal[All Fields] AND ("disease"[MeSH Terms] OR "disease"[All Fields] OR
"diseases"[All Fields]) AND ("ORALIT"[Supplementary Concept] OR "ORALIT"[All
Fields] OR "ors"[All Fields]) AND ("zinc"[MeSH Terms] OR "zinc"[All Fields])) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Management of
Acute Respiratory
Infections AND
Children AND
India
(("organization and administration"[MeSH Terms] OR ("organization"[All Fields] AND
"administration"[All Fields]) OR "organization and administration"[All Fields] OR
"management"[All Fields] OR "disease management"[MeSH Terms] OR ("disease"[All
Fields] AND "management"[All Fields]) OR "disease management"[All Fields]) AND
Acute[All Fields] AND ("respiratory tract infections"[MeSH Terms] OR ("respiratory"[All
Fields] AND "tract"[All Fields] AND "infections"[All Fields]) OR "respiratory tract
infections"[All Fields] OR ("respiratory"[All Fields] AND "infections"[All Fields]) OR
"respiratory infections"[All Fields])) AND (("child"[MeSH Terms] OR "child"[All Fields]
OR "children"[All Fields]) AND under[All Fields] AND 5[All Fields] AND years[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
Intensified
Diarrhea Control
Fortnight AND
Children AND
India
(Intensified[All Fields] AND ("diarrhoea"[All Fields] OR "diarrhea"[MeSH Terms] OR
"diarrhea"[All Fields]) AND ("prevention and control"[Subheading] OR ("prevention"[All
Fields] AND "control"[All Fields]) OR "prevention and control"[All Fields] OR "control"[All
Fields] OR "control groups"[MeSH Terms] OR ("control"[All Fields] AND "groups"[All
Fields]) OR "control groups"[All Fields]) AND Fortnight[All Fields]) AND (("child"[MeSH
Terms] OR "child"[All Fields] OR "children"[All Fields]) AND under[All Fields] AND 5[All
Fields] AND years[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Integrated
management of
neonatal and
childhood illness
AND Children
AND India
(Integrated[All Fields] AND ("organization and administration"[MeSH Terms] OR
("organization"[All Fields] AND "administration"[All Fields]) OR "organization and
administration"[All Fields] OR "management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All Fields])
OR "disease management"[All Fields]) AND ("infant, newborn"[MeSH Terms] OR
("infant"[All Fields] AND "newborn"[All Fields]) OR "newborn infant"[All Fields] OR
"neonatal"[All Fields]) AND ("Childhood"[Journal] OR "childhood"[All Fields]) AND
illness[All Fields]) AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND (("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Micronutrient
supplementation
(Vitamin A, Iron
Folic Acid) AND
Children AND
Mortality AND
India
(("trace elements"[Pharmacological Action] OR "micronutrients"[Pharmacological Action]
OR "trace elements"[MeSH Terms] OR ("trace"[All Fields] AND "elements"[All Fields])
OR "trace elements"[All Fields] OR "micronutrient"[All Fields] OR "micronutrients"[MeSH
Terms] OR "micronutrients"[All Fields]) AND supplementation[All Fields]) AND ("vitamin
a"[MeSH Terms] OR "vitamin a"[All Fields]) OR ("folic acid"[MeSH Terms] OR ("folic"[All
Fields] AND "acid"[All Fields]) OR "folic acid"[All Fields]) AND ("child mortality"[MeSH
Terms] OR ("child"[All Fields] AND "mortality"[All Fields]) OR "child mortality"[All Fields]
OR ("children"[All Fields] AND "mortality"[All Fields]) OR "children mortality"[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Supplementation
with
micronutrients in
children AND
Children AND
India
supplementation[All Fields] AND ("micronutrients"[Pharmacological Action] OR
"micronutrients"[MeSH Terms] OR "micronutrients"[All Fields]) AND ("child"[MeSH
Terms] OR "child"[All Fields] OR "children"[All Fields])) AND ("child"[MeSH Terms] OR
"child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Universal
immunization
AND Children
AND India
((Universal[All Fields] AND ("immunisation"[All Fields] OR "vaccination"[MeSH Terms]
OR "vaccination"[All Fields] OR "immunization"[All Fields] OR "immunization"[MeSH
Terms])) AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Full immunization
coverage AND
Children AND
India
(Full[All Fields] AND ("vaccination coverage"[MeSH Terms] OR ("vaccination"[All Fields]
AND "coverage"[All Fields]) OR "vaccination coverage"[All Fields] OR ("immunization"[All
Fields] AND "coverage"[All Fields]) OR "immunization coverage"[All Fields])) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Child screening
and early
intervention
services AND
Children AND
India
(("child"[MeSH Terms] OR "child"[All Fields]) AND ("diagnosis"[Subheading] OR
"diagnosis"[All Fields] OR "screening"[All Fields] OR "mass screening"[MeSH Terms]
OR ("mass"[All Fields] AND "screening"[All Fields]) OR "mass screening"[All Fields] OR
"screening"[All Fields] OR "early detection of cancer"[MeSH Terms] OR ("early"[All
Fields] AND "detection"[All Fields] AND "cancer"[All Fields]) OR "early detection of
cancer"[All Fields]) AND ("early intervention (education)"[MeSH Terms] OR ("early"[All
Fields] AND "intervention"[All Fields] AND "(education)"[All Fields]) OR "early
intervention (education)"[All Fields] OR ("early"[All Fields] AND "intervention"[All Fields])
OR "early intervention"[All Fields]) AND services[All Fields]) AND ("child"[MeSH Terms]
OR "child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Birth defects in
children under 5
years AND
NRHM AND India
(("abnormalities"[Subheading] OR "abnormalities"[All Fields] OR ("birth"[All Fields] AND
"defects"[All Fields]) OR "birth defects"[All Fields] OR "congenital abnormalities"[MeSH
Terms] OR ("congenital"[All Fields] AND "abnormalities"[All Fields]) OR "congenital
abnormalities"[All Fields] OR ("birth"[All Fields] AND "defects"[All Fields])) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND under[All
Fields] AND 5[All Fields] AND years[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Deficiencies in
Children under 5
years AND India
(Deficiencies[All Fields] AND ("child"[MeSH Terms] OR "child"[All Fields] OR
"children"[All Fields]) AND under[All Fields] AND 5[All Fields] AND years[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
IFA
Supplementation
AND Children AND
India
(("iron"[MeSH Terms] OR "iron"[All Fields]) AND ("folic acid"[MeSH Terms] OR
("folic"[All Fields] AND "acid"[All Fields]) OR "folic acid"[All Fields]) AND
supplementation[All Fields] AND IFA[All Fields] AND Supplementation[All Fields])
AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Rashtriya bal
Swasthya
karyakram
(Rashtriya[All Fields] AND bal[All Fields] AND swasthya[All Fields] AND
karyakram[All Fields]) AND ("child"[MeSH Terms] OR "child"[All Fields] OR
"children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
National
deworming day
AND Children AND
India
(("federal government"[MeSH Terms] OR ("federal"[All Fields] AND "government"[All
Fields]) OR "federal government"[All Fields] OR "national"[All Fields]) AND
deworming[All Fields] AND day[All Fields]) AND ("child"[MeSH Terms] OR "child"[All
Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields])
AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Complementary
feeding practices
AND Children AND
India
(("infant nutritional physiological phenomena"[MeSH Terms] OR ("infant"[All Fields]
AND "nutritional"[All Fields] AND "physiological"[All Fields] AND "phenomena"[All
Fields]) OR "infant nutritional physiological phenomena"[All Fields] OR
("complementary"[All Fields] AND "feeding"[All Fields]) OR "complementary
feeding"[All Fields]) AND practices[All Fields]) AND ("child"[MeSH Terms] OR
"child"[All Fields] OR "children"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
AND "humans"[MeSH Terms])
Disease
management in
children in
NRHM AND
India
(("therapy"[Subheading] OR "therapy"[All Fields] OR ("disease"[All Fields] AND
"management"[All Fields]) OR "disease management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All Fields]))
AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
NRHM[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull
text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH
Terms])
Prevalence of
diarrhea in
under 5
children in
India
(("epidemiology"[Subheading] OR "epidemiology"[All Fields] OR "prevalence"[All
Fields] OR "prevalence"[MeSH Terms]) AND ("diarrhoea"[All Fields] OR
"diarrhea"[MeSH Terms] OR "diarrhea"[All Fields]) AND under[All Fields] AND 5[All
Fields] AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields])) AND ("2005/01/01"[PDAT] :
"2013/12/31"[PDAT])
Impact Indicator:
Under 5
Mortality Rate in
India
(Under[All Fields] AND 5[All Fields] AND ("mortality"[MeSH Terms] OR "mortality"[All
Fields] OR ("mortality"[All Fields] AND "rate"[All Fields]) OR "mortality rate"[All Fields])
AND ("india"[MeSH Terms] OR "india"[All Fields])) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Disease
management in
children in NRHM
AND India
(("therapy"[Subheading] OR "therapy"[All Fields] OR ("disease"[All Fields] AND
"management"[All Fields]) OR "disease management"[All Fields] OR "disease
management"[MeSH Terms] OR ("disease"[All Fields] AND "management"[All
Fields])) AND ("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields])
AND NRHM[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("loattrfull text"[sb] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND
"humans"[MeSH Terms])
Nutritional
rehabilitation
centres AND
Children AND
India
(Nutritional[All Fields] AND ("rehabilitation"[Subheading] OR "rehabilitation"[All
Fields] OR "rehabilitation"[MeSH Terms]) AND centres[All Fields]) AND
("child"[MeSH Terms] OR "child"[All Fields] OR "children"[All Fields]) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("loattrfull text"[sb] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT]) AND "humans"[MeSH Terms])
Other variables
REPRODUCTIVE HEALTH
National Health
Mission
“National Health Mission” OR “NHM” [MeSH words] OR “National” [All Fields] AND
"Health” [All Fields] AND “Mission" [All Fields]
National Rural Health
Mission
“National Rural Health Mission” OR “NRHM” [MeSH words] OR “National” [All
Fields] AND “Rural” [All fields] AND "Health” [All Fields] AND “Mission" [All
Fields“National Rural Health Mission” OR “NRHM” [MeSH words] OR “National” [All
Fields] AND “Rural” [All fields] AND "Health” [All Fields] AND “Mission" [All Fields]
National Urban
Health Mission
“National Urban Health Mission” OR “NRHM” [MeSH words] OR “National” [All
Fields] AND “Urban” [All fields] AND "Health” [All Fields] AND “Mission" [All Fields]
Reproductive Health
Program
“Reproductive Health Program” [MeSH words] OR “Reproductive” [All Fields] AND
“Health” [All Fields] AND “Program” [All Fields] AND “Evaluation” [All Fields]
Family Planning “Family planning” [MeSH words] OR “Family” [All Fields] AND “Planning” [All
Fields] OR “Birth Control” OR “Birth” [All Fields] AND “control” [All Fields]
Contraceptive
Prevalence Rate
“Contraceptive Prevalence Rate” [MeSH words] OR “Contraceptive” [All Fields]
AND “Prevalence” [All Fields] AND “Rate” [All Fields]
Total Unmet need “Total Unmet Need” [MeSH words] OR “Total” [All Fields] AND “Unmet” [All Fields]
AND “Need” [All Fields]
Total Fertility Rate “Total Fertility Rate” [MeSH words] OR “Total” [All Fields] AND “Fertility” [All
Fields] AND “Rate” [All Fields]
Rashtriya Kishor
Swasthya Karyakram
“Rashtriya Kishor Swasthya Karyakram” [MeSH words] OR “Rashtriya” [All Fields]
AND “Kishor” [All Fields] AND “Swasthya” [All Fields] AND “Karyakram” [All Fields]
Adolescent Friendly
Health Clinics
“Adolescent Friendly Health Clinics” [MeSH words] OR “Adolescent” [All Fields]
AND “Friendly” [All Fields] AND “Health” [All Fields] AND “Clinics” [All Fields]
Adolescent
Reproductive and
Sexual Health/ ARSH
“Adolescent Reproductive and Sexual Health” [MeSH words] OR “ARSH” [MeSH
word] OR “Adolescent” [All Fields] AND “Reproductive” [All Fields] AND “Sexual”
[All Fields] AND “Health” [All Fields]
Weekly Iron and Folic
Acid
Supplementation
“Weekly Iron and Folic Acid Supplementation” [MeSH words] OR “Weekly” [All
Fields] AND “Iron” [All Fields] AND “Folic Acid” [All Fields] AND “Supplementation”
[All Fields]
Menstrual Hygiene
Scheme
“Menstrual hygiene scheme” [MeSH words] OR “Menstrual” [All Fields] AND
“Hygiene” [All Fields] AND “Scheme” [All Fields]
Keywords MeSH
"road connectivity"
AND "maternal
health" AND "India"
"road connectivity"[All Fields] AND "maternal health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"road connectivity"
AND "child health"
AND "India"
"road connectivity"[All Fields] AND "child health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"road connectivity"
AND "adolescent
health" AND "India"
"road connectivity"[All Fields] AND "adolescent health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"road connectivity"
AND "health
outcomes" AND
"India"
"road connectivity"[All Fields] AND "health outcomes"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"surfaced road" AND
"health outcomes"
AND "India"
(surfaced[All Fields] AND road[All Fields]) AND "health outcomes"[All Fields]
AND "India"[All Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"rural road
connectivity" AND
"health " AND "India"
(rural[All Fields] AND road[All Fields] AND connectivity[All Fields]) AND "health
"[All Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"rural connectivity"
AND "health
outcomes" AND India
(rural[All Fields] AND connectivity[All Fields]) AND "health outcomes"[All Fields]
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
(mobile phone use)
AND maternal health)
AND India
("cell phone use"[MeSH Terms] OR ("cell"[All Fields] AND "phone"[All Fields])
OR "cell phone use"[All Fields] OR ("mobile"[All Fields] AND "phone"[All Fields])
OR "mobile phone use"[All Fields]) AND ("maternal health"[MeSH Terms] OR
("maternal"[All Fields] AND "health"[All Fields]) OR "maternal health"[All Fields]))
AND ("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"mobile phone use"
AND "maternal
health" AND "India"
mobile[Title] AND phone[Title] AND maternal[Title] AND health[Title] AND
India[Title]
mobile connectivity
AND maternal health
AND India
(mobile[All Fields] AND connectivity[All Fields]) AND ("maternal health"[MeSH
Terms] OR ("maternal"[All Fields] AND "health"[All Fields]) OR "maternal
health"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
AND "maternal
health" AND "India"
"mobile connectivity"[All Fields] AND "maternal health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone" AND
"maternal health"
AND "India"
"mobile phone"[All Fields] AND "maternal health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
impact on "health
outcomes" AND
"India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "health outcomes"[All Fields] AND "India"[All Fields]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
impact on "maternal
health" AND "India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "maternal health"[All Fields] AND "India"[All Fields]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"telecommunication
connectivity" AND
"maternal health"
AND "India"
(("telecommunications"[MeSH Terms] OR "telecommunications"[All Fields] OR
"telecommunication"[All Fields]) AND connectivity[All Fields]) AND "maternal
health"[All Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"AAROGYAM" AND
"Maternal health"
AND "India"
"AAROGYAM"[All Fields] AND "Maternal health"[All Fields] AND "India"[All
Fields] AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]))
"mother and child
tracking system"
AND "India"
"mother and child tracking system"[All Fields] AND "India"[All Fields] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"information and
communication
technology" AND "
maternal mortality
ratio" AND "India"
"information and communication technology"[All Fields] AND "maternal mortality
ratio"[All Fields] AND "India"[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"mobile connectivity"
impact on "child
health" AND "India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "child health"[All Fields] AND "India"[All Fields] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone" AND
"child health" AND
"India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "child health"[All Fields] AND "India"[All Fields] AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
mobile connectivity
AND child health
AND India
(mobile[All Fields] AND connectivity[All Fields]) AND ("child health"[MeSH
Terms] OR ("child"[All Fields] AND "health"[All Fields]) OR "child health"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile connectivity"
AND "child health"
AND "India"
"mobile connectivity"[All Fields] AND "child health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
((mobile phone use)
AND child health)
AND India
(("cell phone use"[MeSH Terms] OR ("cell"[All Fields] AND "phone"[All Fields])
OR "cell phone use"[All Fields] OR ("mobile"[All Fields] AND "phone"[All Fields])
OR "mobile phone use"[All Fields]) AND ("child health"[MeSH Terms] OR
("child"[All Fields] AND "health"[All Fields]) OR "child health"[All Fields])) AND
("india"[MeSH Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
"mobile phone use"
AND "child health"
AND "India"
"mobile phone use"[All Fields] AND "child health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"AAROGYAM" AND
"child health" AND
"India"
"AAROGYAM"[All Fields] AND "child health"[All Fields] AND "India"[All Fields]
AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]))
"AAROGYAM" AND
"health outcomes"
AND "India"
"AAROGYAM"[All Fields] AND "health outcomes"[All Fields] AND "India"[All
Fields] AND (("2005/01/01"[PDAT] : "2018/12/31"[PDAT]))
"mobile connectivity"
impact on
"adolescent health"
AND "India"
"mobile connectivity"[All Fields] AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND "adolescent health"[All Fields] AND "India"[All Fields]
AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone" AND
"adolescent health"
AND "India"
"mobile phone"[All Fields] AND "adolescent health"[All Fields] AND "India"[All
Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
mobile connectivity
AND adolescent
health AND India
(mobile[All Fields] AND connectivity[All Fields]) AND ("adolescent health"[MeSH
Terms] OR ("adolescent"[All Fields] AND "health"[All Fields]) OR "adolescent
health"[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
mobile phone use
AND adolescent
health AND India
("cell phone use"[MeSH Terms] OR ("cell"[All Fields] AND "phone"[All Fields])
OR "cell phone use"[All Fields] OR ("mobile"[All Fields] AND "phone"[All Fields])
OR "mobile phone use"[All Fields]) AND ("adolescent health"[MeSH Terms] OR
("adolescent"[All Fields] AND "health"[All Fields]) OR "adolescent health"[All
Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"mobile phone use"
AND "adolescent
health" AND "India"
"mobile phone use"[All Fields] AND "adolescent health"[All Fields] AND
"India"[All Fields] AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
water supply AND
health outcomes
AND India
("water supply"[MeSH Terms] OR ("water"[All Fields] AND "supply"[All Fields])
OR "water supply"[All Fields]) AND (("health"[MeSH Terms] OR "health"[All
Fields]) AND outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields])
water supply impact
on health outcomes
AND India
(("water supply"[MeSH Terms] OR ("water"[All Fields] AND "supply"[All Fields])
OR "water supply"[All Fields]) AND ("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND ("health"[MeSH Terms] OR "health"[All Fields]) AND
outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
sanitation impact on
health outcomes in
India
(("sanitation"[MeSH Terms] OR "sanitation"[All Fields]) AND ("Impact (Am Coll
Physicians)"[Journal] OR "impact"[All Fields]) AND ("health"[MeSH Terms] OR
"health"[All Fields]) AND outcomes[All Fields] AND ("india"[MeSH Terms] OR
"india"[All Fields])) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
sanitation AND
health outcomes
AND India
("sanitation"[MeSH Terms] OR "sanitation"[All Fields]) AND (("health"[MeSH
Terms] OR "health"[All Fields]) AND outcomes[All Fields]) AND ("india"[MeSH
Terms] OR "india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
Impact of toilets on
health outcomes in
India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND
("bathroom equipment"[MeSH Terms] OR ("bathroom"[All Fields] AND
"equipment"[All Fields]) OR "bathroom equipment"[All Fields] OR "toilets"[All
Fields]) AND ("health"[MeSH Terms] OR "health"[All Fields]) AND outcomes[All
Fields] AND ("india"[MeSH Terms] OR "india"[All Fields])) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
nutrition AND health
outcomes AND India
("nutritional status"[MeSH Terms] OR ("nutritional"[All Fields] AND "status"[All
Fields]) OR "nutritional status"[All Fields] OR "nutrition"[All Fields] OR "nutritional
sciences"[MeSH Terms] OR ("nutritional"[All Fields] AND "sciences"[All Fields])
OR "nutritional sciences"[All Fields]) AND (("health"[MeSH Terms] OR
"health"[All Fields]) AND outcomes[All Fields]) AND ("india"[MeSH Terms] OR
"india"[All Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
impact of nutrition on
health outcomes
AND India
(("Impact (Am Coll Physicians)"[Journal] OR "impact"[All Fields]) AND
("nutritional status"[MeSH Terms] OR ("nutritional"[All Fields] AND "status"[All
Fields]) OR "nutritional status"[All Fields] OR "nutrition"[All Fields] OR "nutritional
sciences"[MeSH Terms] OR ("nutritional"[All Fields] AND "sciences"[All Fields])
OR "nutritional sciences"[All Fields]) AND ("health"[MeSH Terms] OR "health"[All
Fields]) AND outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All
Fields]) AND ("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
"sanitation" impact on
"health outcomes" in
"India" NOT animals
"sanitation"[All Fields] AND impact[All Fields] AND "health outcomes"[All Fields]
AND "India"[All Fields] NOT animals[All Fields] AND ("2005/01/01"[PDAT] :
"2018/12/31"[PDAT])
ability to call
ambulance AND
impact on health
outcomes AND India
(("aptitude"[MeSH Terms] OR "aptitude"[All Fields] OR "ability"[All Fields]) AND
call[All Fields] AND ("ambulances"[MeSH Terms] OR "ambulances"[All Fields]
OR "ambulance"[All Fields])) AND (("Impact (Am Coll Physicians)"[Journal] OR
"impact"[All Fields]) AND ("health"[MeSH Terms] OR "health"[All Fields]) AND
outcomes[All Fields]) AND ("india"[MeSH Terms] OR "india"[All Fields]) AND
("2005/01/01"[PDAT] : "2018/12/31"[PDAT])
ANNEXURE 4. FLOW DIAGRAM OF STUDIES INCLUDED IN THE SYSTEMATIC REVIEW
4.1. MATERNAL MORTALITY RATIO
Studies identified through database
search N=2759
Studies after removal of duplicates
N= 2083
Studies selected according to titles
for abstract N= 1161
Studies selected for full text N= 280
Studies included in review N= 63
Duplicate records N= 676
Studies excluded by Titles
N =922
Studies excluded by
abstract N = 881
Studies excluded by full
text N = 217
MMR = 19
Institutional Deliveries = 44
Studies not
pooled N= 19
Studies pooled
in forest plot
N= 25
JSY = 6
NRHM = 6
ASHA = 1
ANC = 1
Referral transport= 2
ReMiND = 2
Others = 1
JSY = 14
BPCR = 2
ASHA = 3
JSSK = 1
ANC = 1
Referral transport= 2
Others = 2
Studies not
pooled
N = 19
JSY =7
ASHA = 2
NRHM = 5
Task shifting =1
BPCR = 1
JSSK = 2
Others = 1
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2 CHILD HEALTH
4.2.1 PERINATAL MORTALITY RATE
Studies identified in database search
(n=28568)
Studies after duplicate removal
(n=11688)
Full text articles assessed for
eligibility (n=289)
Final studies included (n=41)
Duplicates identified
(n=16880)
Studies excluded on the basis of
title and abstract (n=11399)
Studies excluded by full text
review (n=248)
Studies with outcome
as PNMR =15
Studies with outcome
as SBR= 20
Studies with outcome
as ENMR= 6
ENC= 3
NRHM =1
JSY= 2
Institutional deliveries =1
Secondary data
analysis=2
Cohort study=2
Cross sectional study =5
Case control study=1
Institutional delivery and
ENC=2
NRHM =1
JSY =1
Cross sectional studies=5
Case control study=2
Secondary data analysis=5
Survey =2
Prospective observational
study=4
JSY =1
Review article on NRHM =2
Secondary data analysis=3
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2.2 NEONATAL MORTALITY RATE
TE
Studies identified in the database
search N=19536
Studies excluded by titles and
invalid outcomes N=9950
Studies selected according to titles
for abstracts N=1802
Studies selected for full text review
N=280
Duplicated records N=7784
Studies excluded by
abstracts N=1522
Studies excluded by full text
review N=240
Studies included in the review N=40
Cross
sectional
studies
N=16
Outcome
NMR=8
Retrospec
tive study
N=2
Longitudin
al Cohort
study N=2
Quasi experimental
N=1
Mixed study N=1
Systematic reviews
N=1
RCT N=1
Impact of
NRHM on
NMR N=3
LBW=8
ENBC N=5
FBNC N=2
IMNCI N=1
IMNCI N=1
FBNC N =2
ENC N= 1
HBPNC N= 4
FBNC N=2
LBW N=2
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2.3. INFANT MORTALITY RATE
Studies identified in database
searching (n= 19,350)
Studies after duplicate removal (n=
7,120)
Full text articles assessed for
eligibility (n=1740)
Studies excluded on the basis of title
and abstract (n=5380)
Studies excluded by full text review
(n=1674)
Final studies included (n=66)
Duplicates identified
(n=12,230)
Studies on
Exclusive
breast
feeding
(N=26)
Studies on
Outcome
as IMR
(N=16)
Studies on
assessment
of ASHAs
under
(N=9)
Studies on
IMNCI
(N=5)
Studies on
Vitamin A
(N=1)
Studies on
Immunizati
on (N=3)
Studies on
Secondary
data
analysis
(N=6)
Cross
section
al
Study
(N=22)
Longitud
inal
Study
(N=4)
Cross
section
al Study
(N=4)
Secondary
data
analysis
(N=10)
Longitud
inal
Study
(N=2)
Cross
sectional
Study
(N=8)
Longitu
dinal
Study
(N=1)
Cross
sectional
Study
(N=1)
Longitu
dinal
Study
(N=1)
RCT
(N=1)
RCT
(N=1)
Cohort
(N=1)
Cross
section
al Study
(N=1)
Mixed
Study
(N=1)
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.2.4 UNDER FIVE MORTALITY RATE
Studies after duplicate removal
n=9,725
Final studies included, n=66
Studies excluded by full text
review N=223
Studies excluded on the
basis of title and abstract.
n=9,436
Studies with
outcome as
Immunization
coverage (n=22)
Studies Focusing on
strategy NRC (n=18)
Studies with outcome
as U5MR, n=9
Other studies:
- Vitamin A supplementation (n=4), RBSK
(n=3), Outcome as ARI and Diarrhea
incidence (n=9), IMNCI (n=1)
Role of NRHM in reducing inequality (n=1)
Role of FLHW in improving child health (n=1)
Non Pool
able=3
Pooled =16
Pooled =15
Non Pool
able=3
Studies identified in the database
search N=14,569
Duplicated records
N=n=4,844
Full text articles assessed for
eligibility, n=289
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.3 TOTAL FERTILITY RATE AND CONTRACEPTIVE PREVELANCE RATE
Studies identified in the database
search N=6261
Studies excluded by titles and
invalid outcomes N=2491
Studies selected according to titles
for abstracts N=496
Studies selected for full text review
N=130
Duplicated records
N=3274
Studies excluded by
abstracts N=366
Studies excluded by full
text review N=81
Studies included in the review N=49
Cross sectional studies
N=32
Studies on secondary data
analysis N=14
Quasi experimental studies
with state specific
strategies
PRACHAR project in Bihar
SAHELI project in Kerala
N=3
Studies with CPR as
outcome N=22 (Pooled)
Evaluation/effectiveness
studies on ASHA N=4
Studies on other outcomes
like utilization rate, barriers
etc. N=6
Studies with TFR as an
outcome N=9
Studies with CPR as an
outcome N=5
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.4 ADOLESCENT REPRODUCTIVE SEXUAL HEALTH CLINICS AND WEEKLY IRON
FOLIC SUPPLIMENTATION
Studies identified in the database
search N=1062
Studies excluded by titles and
invalid outcomes N=296
Studies selected according to titles
for abstracts N=192
Studies selected for full text review
N=105
Duplicated records N=574
Studies excluded by
abstracts N=87
Studies excluded by full text
review N=55
Studies included in the review N=50
Studies on WIFS
N=12
Pooled for analysis,
N=10
Non pool able
Studies, N=3
Non pool able
Studies, N=4
RCTs, N=4
Cross sectional
N=5
Studies on ARSH
N=14
Pooled
Studies on Menstrual Hygiene
N=25
Pooled for
analysis, N=22
Non pool able
Studies, N=3
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.5 IMPACT OF OTHER VARIABLES ON MCH OUTCOMES
Studies identified through database
search 1, 07,823
Studies after removal of duplicates
N= 42,982
Studies selected according to titles
for abstract N= 7337
Studies selected for full text N= 223
Studies included in review N= 25
Duplicate records N= 64,841
Studies excluded by Titles N =35,645
Studies excluded by abstract N =
7114
Studies excluded by full text N = 198
Mobile
connectivity = 9
Road
connectivity =8
Water supply/
sanitation = 7
Self-help
group = 1
Cross-
sectional = 3
review N=
25
Case control
= 2
review N=
25
Hospital
based = 2
review N=
25
Quasi
experimental
= 1
review N=
25
Qualitative =
1
review N=
25
Cross-sectional
= 1
review N= 25
Secondary data
analysis = 1
review N= 25
Cross sectional
= 1
review N= 25
RCT = 2
Cohort study =
2
review N= 25
Secondary
data analysis
= 8
review N=
25
Secondary
data analysis
= 1
review N=
25
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
4.6 MCH INEQUALITIES
Studies identified through database
search 9185
Studies after removal of duplicates
N= 3823
Studies selected according to titles
for abstract N= 362
Studies selected for full text N= 84
Studies included in review N= 12
Duplicate records N= 5362
Studies excluded by Titles N =3461
Studies excluded by abstract N = 278
Studies excluded by full text N = 72
NRHM= 5
Others= 3
ANC, PNC,
SBA= 1
ASHA= 1
JSY=2
Qualitative =
2
Secondary
data
analysis= 1
Mixed
method= 1
Quasi
experimental
= 1
Pre post
study= 1
Secondary data
analysis= 1
Survey study=
1
Secondary
data analysis =
1
Secondary
data
analysis=3
Identification
Identification
Screening
Screening
Eligibility
Eligibility
Inclusion
Inclusion
n
ANNEXURE 5. RESULTS OF STUDIES INCLUDED IN SYSTEMATIC REVIEW .
5.1 MATERNAL HEALTH
5.1.1 Results of studies with MMR as an outcome (N=19)
Author &
year of
publication
Study Period/
Location
Study Design Objective/Intervention Results
After 2013
Begum R. et
al. 2014[71]
2004-06 to
2012-13,
Assam and
India
Secondary data
analysis (SRS
data)
NHM, JSY, JSSK,
MCTS, quality ante-
natal care
Assam: MMR reduction
=480 to 301 /lakh live
births (LB) [37.3%
decline], mainly due to
increased institutional
delivery due to JSY
,India: MMR=254 to 178
[30% decline]
Shah P. et al.
2014[72]
2002-03 to
2010-11,
Jhagadia block
(rural tribal
area), Gujarat
[SEWA].
Prospective
study
JSY/Chiranjeevi
Yojana/free referral
transport
services/Community
based interventions
MMR reduction = 520 -
146 / lakh LB (71.1%
decline)
Randive B. et
al. 2014[73]
2007-2009, 9
low performing
states of India
[RJ,MP,CH,BH,
JH,UP,UK,OR,
AS]
Secondary data
analysis (DLHS
3, AHS 1 and 2,
Census 2011)
JSY MMR reduction 4 times
faster in richest areas
compared to poorest,
MMR=301-178/lakh LB
[40% decline in 2003-
2013 in India],
Disadvantaged
population needs to be
targeted for cash
incentives
Ng M. et al.
2014 [74]
2005-2010,
Madhya
Pradesh
Continuous time
series for MMR(
SRS report,
Impact of JSY on MMR MMR reduction = 371 to
327/lakh LB (12%
decline),JSY supported
AHS, MP vital
statistics,
research studies
from PubMed,
google scholar)
institutional delivery: 14%
to 80%.Not associated
with decline on MMR due
to inadequate quality of
care
Mane A B et
al. 2014 [75]
2001-2012,
India
Review study ASHA MMR reduction = 301 to
100/ Lakh LB (66.6%
decline),Due to promotion
of institutional deliveries
by ASHA
Bhushan H
et al. 2015
[76]
2006-13, India Secondary data
analysis
(Training
records from 12
states)
Task shifting from
specialist to non-
specialist doctors
ANC coverage improved
by 43%, 44%, 58%
during first, second and
third trimesters. 50%
reduction in maternal
deaths
Nagarajan S.
et al. 2015
[57]
2001-05 (pre
NRHM) to
2005-11 (post
NRHM), India
Secondary data
analysis (SRS
data)
Impact of NRHM on
Maternal mortality
MMR reduction = 301 to
178/ Lakh LB (40%
decline) .0.2% increase in
MMR reduction.MMR
was already in declining
phase prior to NRHM
owing to increased
economic growth/ roads/
transportation/ private
sectors. NRHM did
provide the further
impetus to the decline by
provision of ambulance
services EMOC, JSY.
Doke PP et
al. 2016 [77]
1997–2004 to
2005-12, ( 8
years before
and 8 years
after) India
Pre NRHM, post
NRHM
implementation
study Secondary
data analysis
(SRS Data)
NRHM MMR reduction= 398 to
167 /lakh LB
Pre NRHM, MMR decline
= 36.2%
Post NRHM, MMR
decline= 34.2%(MMR
decline had already in
pace even before NRHM.
(RCH program in 1997)
Vohra K. et
al, 2015[58]
1991-2009,
India
Secondary data
analysis (SRS,
Census data,
DLHS, NFHS)
NRHM MMR reduction= 437 to
178 /lakh LB (59.3%
decline) Reduction in
birth and increased
institutional deliveries
could be the reason for
decline in MMR.
Slow reduction in MMR
despite maternal
healthcare utilization is
inequalities related to
literacy status, economic
situation, geographic
locations.E.g. ANC check
up 1st trimester( 38%
Rural, 62%
urban),Institutional
deliveries (38%
rural,71%Urban)
Ahmed SJ et
al. 2016 [78]
1997-2013,
Assam, India
Secondary data
analysis (SRS
Data)
- Assam MMR reduction =
520-257/lakh LB (50.5%
decline)
India MMR reduction=
398-178/lakh LB (55.3%
decline)
Gupta M. et
al. 2016 [61]
2002-04 to
2012-13,
Haryana
Secondary data
analysis in
Haryana(DLHS)
NRHM MMR reduction =185 to
121 /lakh LB (34.6%
decline).ANC check up
difference in rural and
urban = 8 % pre NRHM,
12.4% during NRHM,
6.8% post NRHM
Mahala U. et
al. 2017 [79]
2008-11 to
2012-15, Jaipur
Retrospective
hospital based
descriptive study
(data related to
institutional
deliveries from
medical records
of Medical
college)
JSSY (JSSK) MMR reduction= 267 to
248/lakh LB from pre to
post JSSK period (7.1%
decline)
Because of JSSK
(JSSY); Annual prenatal
check-up = 55%
increase, Annual
institutional deliveries =
37.9% increase
Gupta M. et
al. 2017 [80]
2013, Haryana Mixed method
study
(Secondary data
analysis
Qualitative
interviews/FGD/I
n-depth
interviews in
Ambala and
Mewat)
ASHA, JSY, JSSK MMR= 121/lakh live
births
MCH inequalities reduced
due to more awareness
regarding MCH services
by ASHA, free
ambulances, diet during
hospital stay. ASHA
scheme appreciated by
all participants
Khanna D. et
al. 2018 [81]
1 year,
Lucknow, UP
Case control
Cases =
maternal deaths,
Control =
Geographic
matched control
and
complication
matched control
BPCR 50% reduction in risk of
MMR when the place of
delivery was suggested
as Institution over the
home delivery. When
place of delivery decided
as institution then risk of
maternal deaths reduced
by three fifth times.
Prinja S. et
al. 2018[82]
2011-2020,
Mooratganj
Manjhanpur
blocks of
Kaushambi
Quasi-
experimental
design
ReMiND intervention
through 259 ASHAs
Resulted in 0.2%
reduction in maternal
deaths.
Siddika B. et
al. 2018 [83]
2004-06 to
2013, Assam,
India
Descriptive
study and
secondary data
analysis (Assam
Human
Development
Reports)
JSY Assam MMR reduction=
480 to 300/lakh LB
(37.5% decline) India
MMR reduction = 254 to
167/lakh LB (34.2%
decline)
- Poor living conditions,
nutritional deficiencies,
inadequate health care,
lack of information.
5.1.2. Forest Plot studies (Outcome = Institutional deliveries, n= 25)
Author & year of
publication
Study Period/Location Study Type Interventio
n
Results
Before 2013
Uttekar B.P. et al.
2007[24]
2007, Jaisalmer,
Bhilwara, Udaipur
Secondary data
analysis(For JSY
NFHS and RCH
data)
JSY 173 deliveries out of total
248 beneficiaries.
Kilaru A. et al.,
2010 [49]
2007-2009,
Ramanagara Taluka,
Karnataka
Prospective study Institutional
delivery
513 institutional
deliveries out of 642
Lim et al, 2010
[26]
2004-04 to 2007-09,
India
Secondary data
analysis(DLHS )
JSY 98932 institutional
deliveries out of 182869
Mandal D.K. et al,
2010 [27]
2007-09, West Bengal Cross sectional JSY 99 institutional deliveries
out of 256 post-partum
females
Vikram K et al.
2011 [28]
2009-10, Trans Yamuna
area of Delhi
Cross sectional
survey
JSY 333 institutional
deliveries out of 469
mothers
Sinha S. et al.
2012 [29]
2010, Chandigarh Retrospective ANC 116 institutional
deliveries out of 147 ANC
mothers
Sidney K. et al.
2012 [30]
Jan-May 2011, Ujjain,
MP
Cross sectional JSY 318 institutional
deliveries out of 418
pregnant women.
Ved R. et al. 2012
[31]
2008-09, Empowered
Action Group States(BH,
CH, OR, RJ, UK, UP,
JH, MP,)
Mixed method JSY 2759 institutional
deliveries out of 3469
post-partum females.JSY
has resulted in increase
institutional deliveries.
Reasons for home
delivery = limited access
to transport, poor quality
of services, high cost in
institution, cultural
preferences
Panja TK et al. 2012
[32]
2008, Bankura District,
West Bengal
Cross sectional JSY 236 institutional deliveries
out of 324 JSY
beneficiaries. Cash
incentive under JSY had
positive association on
institutional deliveries.
After 2013
Mukopadhyay D.K.
et al. 2013 [33]
Sep-Dec 2011, Uttar
Dinajpur, West Bengal
Cross sectional
mixed method
BPCR 164 institutional deliveries
out of 355 women
Amudhan S. et al
2013 [34]
2006-2010, Ballabgarh
(HR)
Quasi
experimental
JSY 1012 institutional deliveries
out of 1884 JSY mothers
Govil D et al. 2013
[35]
April 2010 - March 2011,
Udaipur, Banaswara, ,
Sikar, Sawai Madhopur
districts of Rajasthan
Cross-sectional JSY 353 institutional deliveries
out of 424 mothers. Out of
these 62 % in public
facilities and 21 % in private
facilities.JSY has done
phenomenal increase in
institutional deliveries and
decrease in out of pocket
expenditure.
Sidney K. et al.
2014 [36]
2012-13, Madhya Pradesh Cross-sectional JEY( Janani
Express
Yojna) State
Run Public
Private
Emergency
Transportatio
n Service
342 institutional deliveries
out of 353 women who
used JEY.
JEY usage was greater
among women from lower
socioeconomic position
Fathima F.N. et al
2015 [69]
2012, Kolar,
Chamrajanagar and Haveri
districts of Karnataka
Cross-sectional ASHA 1141 institutional deliveries
out of 1800 mothers.
Kaur H. et al. 2015
[38]
Jan-June 2014, Amritsar,
Punjab
Cross sectional JSY 141 delivered at hospital
out of 185 JSY
beneficiaries.
JSY was not rolled out
strongly in the state.
Nipte D. et al. 2015
[39]
July –September 2013,
Maharashtra
Cross sectional
survey
JSY 336 institutional deliveries
out of 374 mothers
Only 50% of mothers have
completed three ANC visits.
Kumar et al 2015
[40]
2010-11, Agra Cross-sectional JSY 171 institutional deliveries
out of 246 beneficiaries.
55% increase in ANC
registration after JSY
implementation
Strehlow M.C. at el.
2016 [41]
Feb-April 2014, India—
Andhra Pradesh, Assam,
Gujarat, Karnataka and
Meghalaya
Prospective
observational
study
free of charge
ambulance
transport
1212 institutional deliveries
out of 1411 deliveries.
Meta-analysis of studies with outcome as institutional deliveries.
Mukhopadhyay DK
et al. 2016 [43]
2012-2013, West Bengal Cross-sectional JSY 745 institutional deliveries
out of 946 JSY mothers.
Cash incentive most crucial
step influencing institutional
care.
Mukhopadhyay et
al. 2016 [42]
2011, Bankura District,
West Bengal
Cross sectional
study
BPCR 207 institutional deliveries
out of 235 women who
have delivered recently
Kumar S. et al. 2017
[44]
2008-2009, Uttar Pradesh Cross-sectional
study
ASHA 167 institutional deliveries
out of 270 women who
have delivered in last 6
months.
ASHA has helped the rural
beneficiaries in getting
continuous information
about ANC.
Seth A. et al. 2017
[45]
2014, Varanasi, Uttar
Pradesh
Mix method ASHA 3472 institutional deliveries
influenced by ASHA out of
4912 mothers.
There is positive
relationship between visit of
ASHA and utilization of
maternal health services.
Salve H. R. et al.
2017 [46]
August 2010 to March
2013, Ballabgarh, Haryana
Cross-sectional JSSK 537 institutional deliveries
out of 734 beneficiaries
Khes SP et al. 2017
[47]
June 2015-July 2016,
Chhattisgarh
Cross-sectional JSY 353 institutional deliveries
out of 384 beneficiaries
Majority of participants were
not aware about JSY
services except monetary
services.
Siddaiah A et al
2018 [48]
2015, Faridabad Mixed method JSY 119 institutional deliveries
out of 518 mothers
5.1.3 Results of studies with Institutional deliveries as an outcome, but not included in forest
plot (n=21)
Overall (I^2 = 99.69%, p = 0.00)
Govil D et al.(2013)
Limm et al(2010)
Mukhopadhyay et al.(2016)
Sidney K et al.(2014)
Mukhopadhyay DK et al.(2016)
Farah N. et al, (2015)
Ved R et al.(2012)
Vikram K et al.(2011)
Kilaru A. et al.(2010)
Siddaiah A et al.(2018)
Kumar S et al. (2017)
Sidney K et al.(2012)
Strehlow MC at el. (2016)
Khes SP et al.(2017)
Kaur H. et al.(2015)
Uttekar BP et al.(2007)
Kumar et al(2015)
Mukhopadhyay DK et al.(2013)
Mandal DK et al(2010)
Study
Amudhan S et al(2013)
Salve H et al. (2017)
Nipte D. et al.(2015)
Sinha S. et al. (2012)
Seth A et al. (2017)
Panja TK et al.(2012)
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
0.71 (0.64, 0.78)
0.83 (0.79, 0.87)
0.54 (0.54, 0.54)
0.88 (0.83, 0.92)
0.97 (0.95, 0.98)
0.79 (0.76, 0.81)
0.63 (0.61, 0.66)
0.80 (0.78, 0.81)
0.71 (0.67, 0.75)
0.80 (0.77, 0.83)
0.23 (0.20, 0.27)
0.62 (0.56, 0.67)
0.76 (0.72, 0.80)
0.86 (0.84, 0.88)
0.92 (0.89, 0.94)
0.76 (0.70, 0.82)
0.70 (0.64, 0.75)
0.70 (0.63, 0.75)
0.46 (0.41, 0.51)
0.39 (0.33, 0.45)
ES (95% CI)
0.54 (0.51, 0.56)
0.73 (0.70, 0.76)
0.90 (0.86, 0.93)
0.79 (0.72, 0.85)
0.71 (0.69, 0.72)
0.73 (0.68, 0.77)
100.00
4.01
4.05
4.00
4.04
4.03
4.04
4.05
4.00
4.02
%
4.01
3.95
4.00
4.04
4.03
3.93
3.95
3.95
3.97
3.94
Weight
4.04
4.02
4.02
3.92
4.05
3.98
-.50.511.5
Interpretation of forest plot
Year of publication = 2007 to 2018
Total studies pooled = 25
Sample size = 147 - 182869 mothers
Pooled prevalence of institutional deliveries = 71% (CI : 0.64 to 0.78)
Heterogeneity = 99.69% (very high because of sample size variability
Author & year of
publication
Study Period Study Type Intervention Results
Before 2013
Nandan D. et al. 2010
[370]
2010, Delhi Descriptive
study
MAMTA Scheme 84.3 % of beneficiaries under
the scheme came to know
about the scheme through
ASHAs.
Scheme has increased
number of institutional
deliveries among the target
women in some localities,
where it is functional.
But 30% of the beneficiaries
underwent delivery at home.
Kilaru A et al. 2010 [25] 1996-1998 to
2007-2009,
Karnataka
Comparative
study
NRHM
(Institutional
deliveries
SBA home
deliveries)
45% increase in institutional
deliveries 17% decline in SBA
home deliveries
Singh SK et al. 2011
[52]
2005-2008, India Secondary
data analysis(
SRS data)
NRHM (SRS
data)
57% relative increase in
institutional deliveries.
Sandeep S. et al. 2012
[53]
2011, Haryana Cross-
sectional
descriptive
study
JSY Out of 72 JSY mothers, 39
mothers had institutional
deliveries.
Out of 76 non-JSY mothers
55 had institutional deliveries.
Gupta SK et al. 2012 [51] 2003-2005 to
2005-2007,
Jabalpur, MP
Observational
study
JSY 42.6% increase in institutional
deliveries.
Gopalan D et al. 2012
[54]
2005-09, Orissa Mixed method
design
( HMIS data,
FGDs of JSY
JSY 18.1% increase in institutional
deliveries.
Gain in institutional deliveries
is greater than those of ANC,
PNC indicating limited role of
JSY in comprehensively
beneficiaries
and ASHA)
addressing maternal care
needs.
After 2013
Randive et al. 2013 [7] 2005-2010, India Secondary
data analysis
(SRS data)
JSY Increase in institutional
births= 20% to 49%
Prinja S. et al. 2014 [55] 2011, Haryana,
3 districts=
Ambala, Hisar,
Narnaul
Secondary
data analysis
(Civil
registration
data on
institutional
deliveries)
National
ambulance
system utilization
Institutional deliveries in
Haryana rose significantly
after the introduction of NAS
service
Ambala (OR=137.4, CI=22.4-
252.4 ) Hisar (OR=215,
CI=88.5-341.3 ). No
significant increase was
observed in Narnaul (OR=4.5,
CI= -137.4 to 146.4)
Mohanan M. et al. 2014
[56]
2010, Gujarat Observational
study
Chiranjeevi
Yojanana
10.7 % point increase in
institutional deliveries.
Nagarajan S. et al. 2015
[57]
2001-05 to 2005-
11, India
Secondary
data analysis
(DLHS)
NRHM Increase in Institutional
deliveries = 39% to 84%.
Vohra K. et al. 2015 [58] 1992-2009, India Secondary
data analysis
(SRS, census
data)
NRHM 73 % increase in institutional
deliveries.
Prinja S. et al. 2015 [59] 2011–15, UP,
district
Kaushambi
RCT ReMiND Project(
MNCH services)
34% increase in coverage of
institutional deliveries.
Saksena S. R. et al.
2015 [60]
2009-2010,
Unnao district,
Uttar Pradesh
Descriptive
study
Referral transport 25% of the women were
taken to one facility, 32%
were taken to two facilities,
and 25% taken to three
facilities, while 19% were not
taken to any facility before
deaths.
Gupta M. et al. 2016 [61] 2002-04 to 2012-
13, Haryana
Secondary
data analysis
(DLHS data)
NRHM Institutional delivery rate has
been narrowed down from
48.2% to 13%.
Singh U.B., 2016 [62] 2005-6 V/s 2010-
11, Uttrakhand
Secondary
data analysis(
AHS, DLHS 3,
NFHS 3)
NRHM Increase in institutional
deliveries
15.7%
Prinja P. et al. 2017 [63] 2015, UP Pre- and post-
quasi-
experimental
ReMiND
intervention
Increase in Institutional
deliveries
30-40%.
Vellakkal S. et al. 2016
[64]
2007–08 to 2011–
12
Secondary
data analysis
(DLHS, AHS)
NRHM In the EAG states as a whole,
there was an increase of 13%
and 40% points in the uptake
of institutional delivery in
the early post-NRHM period
2007–08 (38.3%) and late
post-
NRHM period 2011–12
(65.5%)
Wagner AL.et al.
2017[65]
2007-08 and
2012-13, India
Secondary
data analysis
(DLHS)
ASHA Institutional delivery
increased = 61.6% to 82.5%
Apum A. Et al. 2017[66] 2014, Assam Cross
sectional
ANC services
Institutional
deliveries
Institutional delivery =33.3%
ANC visits (4 or more)
=50.3%
Singh SK et al. 2017 [44] 2005-13, India Secondary
data analysis
(SRS data)
JSSK and JSY Institutional deliveries
increased = 24.4 to 69.7 %.
Agarwal R. et al. 2018
[67]
2014-2015,
Haryana
Cluster
randomised
trial
Quality
management
activities
7345 deliveries =
5108 delivered in the PHCs
2237 were referred to higher
centres before childbirth
ANNEXURE 5.2. CHILD HEALTH
5.2.1 Results of studies with outcome as Perinatal Mortality Rate (N=14).
Author
Name, Year
of publication
Journal Name Study period,
Place
Type of study/
Intervention
Results
[n,(N)]
Singh S et
al,2011 [52]
Indian Pediatrics 2005-2008,
Indian
states(Rural
area)
Secondary
data analysis
(SRS)/ NRHM
Relative decline in PNMR was only
2.5% in the rural areas, relative
increase in hospital delieveries:57%
Goudar S et
al,2015
[229]
Reproductive health
journal
Jan 2010-Dec
2013,
Belgaun,Nagpu
r
Prospective
population
based
surveillance
Increase in community PMR from
60.7 to 76.7 per 1000 births in
Belgaum, from 114.1 to 400.0
deaths per 1000 births in Nagpur;
Vishwanah K
et al,2015
[231]
The international
electronic journal of
Rural and Remote
Health Research,
education, practice
and policy
Feb-July 2012,
Jawadhi Hills
Tamilnadu,
under CMC
Vellore
Case control
study
Perinatal mortality rate: 149.3/1000
births)(40 perinatal deaths) ;preterm:
16,term: 24
Mony P et
al,2015
[230]
BMJ Open Nov 2012(30
days), 10
districts of the
northern state
of Rajasthan
Hospital based
prospective
cohort study
The estimated perinatal mortality
rate was 35.8 (34 to 37) per 1000
births
Rani S et
al,2012 [232]
Indian Pediatrics May-Oct 2009,
Labor room
and postnatal
wards of a
teaching
hospital in
North India.
Prospective
cohort study.
IPPM Rate: 80/1000 live births(8%)
,significant risk factors for IPPM:
presence of obstructed labor , father
engaged in unskilled labor and
absence of urine examination during
antenatal period .
Carlo W et
al, 2018
Multicounty
study [228]
New England
Journal of Medicine
Mar 2005-Feb
2007,
Indian(Rural
communities)
Pre post study
design/
Training of
Birth
Attendants on
ENC
Perinatal mortality did not
significantly decrease after ENBC.
Siddalingapp
a H et al,
2013 [233]
Journal of Clinical
and Diagnostic
Research
2011,
Nanjangud
talluk of Mysore
district, India
Cross sectional
community
based study
PNMR: 28.93 per 1000 live births.
Asalkar MR
et al, 2013
[234]
International Journal
of Reproduction,
Contraception,
Obstetrics and
Gynaecology
Jan 2008-
December
2010
cross sectional
study
PNMR: 86/1000,preterm PNMR:
426/1000,Term: 37/1000,Post Term:
68/1000.
Singh S et
al, 2017
[371]
Indian Journal of
Community
Medicine
2005-2013
rural areas in
each of the
major states of
India
Secondary
data analysis
(SRS)
Increase in hospital deliveries:
185.7% ,relative decline in PNMR
was 30% ,most states had
significant decline in PNMR; Assam,
Haryana, and Karnataka have only a
marginal decline, but Jharkhand has
shown no decline in PNMR during
the same period
Iyengar K et
al,2012 [235]
J health popul nutr April-December
2006,
Community
based study
Compared to women with no
anaemia, women with severe
anaemia were 3.7 times more likely
to have a perinatal death while
compared to mild anaemia, they
were 2.1times more likely to have
perinatal death
Lim S et
al,2010 [26]
Lancet 2010 Secondary
data analysis
from the
nationwide
district-level
household
surveys(2002-
04,2007-09)
In matching analysis: JSY payment
was associated with a reduction of
3·7 (95% CI 2·2–5·2) perinatal
deaths per 1000 pregnancies, In the
with-versus-without comparison, the
reductions were 4·1 (2·5–5·7)
perinatal deaths per 1000
pregnancies
Gaur A et
al,2015 [127]
Journal of Evidence
based Medicine and
Healthcare
(2003–2004),
2006–
2007,2010-
2011, tertiary
care hospital,
associated with
medical college
in M.P.
retrospective
hospital based,
observational
comparative
study
Perinatal deaths have decreased
from 64.86 in 2003-04 to 51.54 in
2006-07 (p<0.05) and 31.97 in
2010-2011.
Kulkarni R et
al,2007 [237]
Indian Journal of
Community
Medicine
Rural and
urban areas in
six districts in
Maharashtra
Verbal autopsy Total number of perinatal deaths=
83 (31 stillbirths and 52 early
neonatal deaths,
Devi P et al,
2015 [128]
Journal of Evolution
of Medical and
Dental Sciences
January 2014
to January
2015, Tertiary
Care Hospital
of Andhra
Pradesh.
retrospective
study
The PMR was 15.3 per thousand
births(129)
Results of studies with outcome as Still birth Rate(n=25)
Author
,Publication year
Journal Name Study period, Place Type of
study/Interv
ention
Results
Goudar S,2015 [229] Reproductive
health journal
Jan 2010-Dec 2013,
Belgaun,Nagpur
Prospective
population
based
surveillance
Decline in SBR from 22.5 to
16.3 per 1,000 births in
Belgaum and from 29.3 to
21.1 in Nagpur
Carlo W et al,2018
[228]
New England
Journal of
Medicine
Mar 2005-Feb 2007,
Indian(Rural
communities)
Pre post
study
design/
Training of
Birth
Attendants
on ENC
There was a significant
reduction in SBR (RR
0.69,the rate of stillbirths by
delivery attendant decreased
significantly for
nurses/midwives (RR 0.50
and TBA (RR 0.63; but not
for physicians. The SBR
among home deliveries
decreased.
McClure E et
al,2015[240]
Reproductive
Health Journal
2010-13,
Belgaun,Nagpur
Prospective
observational
Nagpur: Reduction in SBR
from 33 to 25,Belgaum:
Reduction in SBR from 28.3
to 22.3
Newtonraj A et
al,2017 [243]
BMC Pregnancy
and Childbirth
July 2013-Aug 2014,
Chandigarh
Case control
study
SBR: 16/1000 births per
year, Antepartum causes:
68% ,intrapartum causes:
32%.
Kumbhare S et
al,2016 [242]
The Journal of
Obstetrics and
Gynecology of
India
Sep 2012-Aug 2013,
Department of Obstetrics
and Gynecology,Medical
College Baroda, Gujarat.
Prospective
case control
study
SBR: 87.83 per 1000 live
births(506),fresh stillbirths:
88.5 %,macerated stillbirths:
11.5 %
Bhattacharyya R et
al,2011 [241]
Journal of
Obstetrics and
Gynecology
Research
Jan 1999-Dec 2008,
Department of Obstetrics
& Gynaecology,
Burdwan Medical
College, Burdwan(WB)
retrospective
cross-
sectional
study
SBR: 33.67 per 1000
births,SBR decreased from
44.87 per 1000 total births in
1999–2003 to 24.15
per 1000 total births in
2004–2008
Altijani N et al,2018
[244]
BMJ Open 2010-2013, Nine states
in India
Secondary
analysis of
cross-
sectional data
from the
Indian Annual
Health Survey
SBR: 10 per 1000 total
Births.
Siddalingappa H et
al,2013 [233]
Journal of
Clinical and
Diagnostic
Research
2011, Nanjangud talluk
of Mysore district, India
Cross
sectional
community
based study
Still birth rate of 9.55 per
1000 total births.
Kulkarni N et al,2018
[237]
Journal of the
Turkish-German
Gynecological
Association
January 2017 to
December 2017, Tertiary
care perinatal center,
Christian Medical
College Vellore
Retrospective
data analysis
SBR:16.8 per 1000 births.
Kochar P et al,2014
[245]
BMC Pregnancy
and Childbirth
2012, all districts of
Bihar
baseline
survey
SBR: 20 per 1,000 births.
McClure E et al, 2018
[246]
BJOG 2014-15,
Belagavi,Nagpur
Prospective,
observational
study
SBR in Belgavi:
24.1,Nagpur: 20.9
Asalkar MR et
al,2013 [234]
International
Journal of
Reproduction,
Contraception,
Obstetrics and
Gynecology
2008-2010, Dept of Obs
and Gynae,rural MIMER
Medical College and Dr.
Bhausaheb Sardesai
Talegaon rural Hospital,
Talegaon Dabhade,
Pune, Maharashtra.
cross
sectional
study
SBR:
47/1000,Preterm:74.3/1000
Term:28.81/1000,Post-term:
40.5/1000
Saleem S et al,2018
[247]
BMC
Reproductive
Health,
Jan 2010-Dec 2016,
Belagavi and Nagpur
prospective,
population-
based
observational
study
cumulative SBR: 25.3/1000
births and decreased from
31.3/1000 births in 2010 to
23.8/1000 births in 2016
giving an annual decline rate
of 4.5%
Satishchandra DM et
al,2009 [248]
Indian Journal
of Pediatrics
Mar 2006 to Feb 2007,
Primary Health Centre
Community
based study,
statistically significant
(p<0.05) reduction in the
(PHC) area of
Vantamuri,
District Belgaum,
Karnataka
perinatal deaths (11 to 3)
after the training.
Mukhopadhyay P et
al,2010 [68]
J HEALTH
POPUL NUTR
June 2006–May 2007,
R.G. Kar Medical
College and Hospital in
Kolkata
cross-
sectional,
observational
5.1%(18) vs 0.9%(6)
Dandona R et al,2019
[250]
BMC Medicine January to December
2016, 1657 clusters in
Bihar state
15.4 per 1000 births ,
Antepartum and intrapartum
SBR was 5.6 and 4.5 per
1000 births , higher
proportion of births was
stillborn
(8.6%, p < 0.001) among
women (175, 0.9%) for
whom the delivery was
deferred
Dandona R et al,2017
[249]
PLOS Medicine 2014 -2015. 38 districts
of Bihar (772 rural and
245 urban clusters)
Survey Incidence of stillbirths was
21.2 per 1,000 births in
Bihar state
Gaur A et al,2015
[127]
Journal of
Evidence based
Medicine and
Healthcare
(2003–2004),2006–
2007, 2010-2011,
tertiary care hospital,
associated with medical
college in M.P.
retrospective
hospital
based,
observational
comparative
study
Stillbirths have decreased
from 4.8% in 2003-04 of
3.0% in 2006-07 (p<0.210)
and 2.5%in 2010-2011.
Malhotra S et al, 2014
[182]
Journal of
health
population
nutrition
Apr 2009-Mar 2010,
Nagaur district in
Rajasthan and
Chhatarpur
district in Madhya
Pradesh
Record review SBR of both the DHs was
around 38/1,000 births.
Devi P et al, 2015
[128]
Journal of
Evolution of
Medical and
Dental Sciences
2014-January 2015,
Tertiary Care Hospital of
Andhra Pradesh
retrospective
study
still birth rate was 11.7 per
thousand births.
Baqui AH et al, 2006
[90]
Bulletin of World
Health
Organization
, 17 rural sectors in 2
districts of Uttar Pradesh
Barabanki , Unnao
Verbal
autopsy
SBR was 31.8 deaths per
1000 births.
Mony P et al,2015
[230]
BMJ Open Nov 2012(30 days), 21
public sector health
facilities of 10 districts of
the northern state of
Rajasthan
Hospital
based
prospective
cohort study
The stillbirth rate was 26.5
per 1000 births.
Malhotra S et al, 2014
[182]
Journal of
health
population
nutrition
Apr 2009-Mar 2010,
Nagaur district in
Rajasthan and
Chhatarpur
district in Madhya
Pradesh
Record review SBR of both the DHs was
around 38/1,000 births.
Devi P et al, 2015
[128]
Journal of
Evolution of
Medical and
Dental Sciences
2014-January 2015,
Tertiary Care Hospital of
Andhra Pradesh
retrospective
study
Still birth rate was 11.7 per
thousand births.
Result of studies with ENMR as outcome (n=6).
Author
,Publication
year
Journal
Name
Study
period,
Place
Type of
study
Results
[n,(N)]
Nagarajan S
et al, 2015
[57]
Elsevier Review article Average annual rate reduction (AARR) in early
neonatal mortality rate (ENMR) in three epochs
(pre-NRHM 2002-05, early post NRHM 2006-
09, and later post NRHM 2010-13): -3.8,2.5
and 4.3
Khurmi M et
al,2015 [131]
Indian
Journal of
Child Health
Review article ENMR declined from 28 to 22 (SRS 2005,
2013) for India, indicating a point decline of 6
and percentage decline of 21%.The maximum
point decline is seen in Orissa (13points) and
minimum in Himachal Pradesh and Jharkhand
(2 and 0 point each).
Decline in ENMR rural from 2005 to 2013: 6
points (19%),urban ENMR: 5 points (31%)
Gaur A et
al,2015 [127]
Journal of
Evidence
based
Medicine and
Healthcare
tertiary care
hospital,
associated
with medical
Observational
study
Reduction in early neonatal Deaths from 99 in
2003 to 54 in 2011.
5.2.2 Overall Impact of NRHM/NHM on NMR (n=3).
Author, Year of
Publication, Area
Journal Name
Study
Period
Results
college in
M.P.
Devi P et
al,2015 [238]
Journal of
Evolution of
Medical and
Dental
Sciences
January
2014 to
January
2015,
Tertiary Care
Hospital of
Andhra
Pradesh.
retrospective
study
Early neonatal death rate3.56 per thousand
births
Baqui AH et
al,2006 [90]
Bulletin of
World Health
Organization
17 rural
sectors in 2
districts of
Uttar
Pradesh
Barabanki
,Unnao
Verbal
autopsy
ENMR 35.1/1000 live births, LNMR 13.9 per
1000 live births.
Lahariya C et
al, 2010 [129]
Indian J
Pediatr
India secondary
data analysis
from SRS
,NFHS
The mortality rates in early neonatal period
declined by 21.6% between 1990 to 2007, rate
of mortality decline is different for 2000–2003
compared to 2004–2007. rapid ARR in ENMR
during 2000-03,increase in ENMR during
2004-07
Bapat U et
al,2012 [130]
BMC
Pregnancy
and
Childbirth
48 slum
localities in
six municipal
wards of
Mumbai
verbal
autopsies
ENMR=7.6/1000 live births
Kumutha;2014,Tamil
Nadu [88]
Indian Journal of
Paediatrics
2005-2012
In 2005, national NMR was 37/1,000 & Tamil
Nadu was 26/1,000 live births.
In 2011 national NMR dropped to 31/1,000
(only six points drop from 2005). But Tamil
Nadu NMR dropped to 15/1,000 livebirths
(drop of 11 points) & significant 42%
reduction from 2005.
Nagarajan et al; 2015 [57]
Seminar in Fetal
and Neonatal
Medicine
2001-2013
NMR (per 1000 live births) declined from
37 in 2005 to 28 in 2013. NRHM has
brought MDG 4 & 5 within India’s grasp.
Khurmi et al;2015 [87]
Indian Journal of
Child Health
2005-2013
NMR declined from 37 to 28 (SRS
2005,2013) indicating a point decline of 9
and percentage decline of 24%. The
maximum point decline is seen in Orissa
and Chhattisgarh (16 and 14 points,
respectively) and minimum in Jharkhand
(2 point). The maximum percentage
decline is seen in Punjab (47%) and
minimum in Jharkhand (7%).
5.2.3. Studies with specific strategies and NMR as an outcome (n=8)
Author
,Publication
year, Area
Journal
Name
Study
period
Type of
study
Interven
tion
Results
Agarwal et al;
2007, India
[89]
Journal of
Perinatolog
y
January 2004
–August
2005
Before-and-
after
intervention
trial
Essentia
l new
born
care
30% decline in NMR during
intervention period as
compared to control period
(20.3 versus 29.3 per 1000 live
births; RR 0.69, 95%
confidence interval (CI) 0.57 to
0.85).
Baquai et al;
2008, Uttar
Pradesh [372]
Bulletin of
the World
Health
Organizatio
n
2004-2005
Quasi
experiment
al study
HBPNC
Neonates who received a
postnatal home visit within 28
days of birth had 34% lower
NMR (35.7 deaths per 1000
live births, 95% confidence
interval, CI: 29.2–42.1) than
those who received no
postnatal visit (53.8 deaths per
1000 live births, 95% CI: 48.9–
58.8),
Sen A et al;
2009, [92]
Purulia, West
Bengal
Journal of
Perinatolog
y
January 2003
to October
2005
Observation
al study
Facility
based
new
born
care
NMR reduced by 14% in 1st
year and 21% in 2nd year after
SNCU became functional.
Estimated neonatal deaths
averted were 329, which would
reduce NMR of the district from
55 to 47 in 2 years.
Baqui et
al;2009, Sylhet
district, [91]
Bangladesh
BMJ 2004-2005
Observational
Cohort study
HBPNC
NMR was 67% lower in those
who received a visit on day one
than in those who received no
visit (adjusted hazard ratio 0.33,
95% confidence interval 0.23 to
0.46; P<0.001).
Darmstadt et
al; 2010 [93]
Mirzapur,
Bangladesh
PLOS One
January2004–
December 2006
Cluster
randomised
controlled trial
HBPNC
NMR was 24.8 (95% CI: 20.7–
29.4) and 27.9 (95% CI:23.5–
32.8) in the comparison arm at
baseline and endline,
respectively, and was 25.2 (95%
CI: 21.0–30.1) and 24.0 (95% CI:
19.8–29.0) in the intervention arm
at baseline and end line,
respectively.
Bhandari et
al;2012,
[94]Faridabad,
Haryana
BMJ
January 2008
and 31 March
2010
Cluster
randomised
trial.
IMNCI
NMR beyond first 24hours
(adjusted hazard ratio 0.86, 0.79
to 0.95) were significantly lower in
intervention than in control
clusters. Adjusted hazard ratio for
NMR was 0.91(0.80to 1.03).
Tripathy et al;
2016, [95]
Rural
Jharkhnand &
Odisha
Lancet
Global
Health
September
2009–
December 2012
Cluster
randomised
controlled trial
HBPNC
NMR was 30 per 1000 livebirths in
the intervention group and 44 per
1000 livebirths in the control
group. (odds ratio [OR] 0.69, 95%
CI 0·53–0·89). 31% reduction in
neonatal mortality rate during 2
years.
Gautam et al;
2016, [96]
Jabalpur,Madh
ya Pradesh
Internation
al Journal
of
Healthcare
and
Biomedical
Research
August 2011 to
July 2012
Observational
study
Facility
based
new
born
care
NMR was reduced by 12%.
Estimated neonatal deaths
averted were 111(7%) out of 1590
admissions compared to
200(19.1%) out of 1048
admissions in previous year (p
value <0.001). Improved survival
and reduced morbidity after
establishment of SNCU.
5.2.4. Studies with essential newborn care practices as an intervention (n=6).
5.2.5 Studies with facility based newborn care as an intervention (n=4).
Author,
Publication
year , Area
Journal
Name
Study
period
Type of
study
Intervent
ion
Results
Sodani et al;
2011 [97]
CHC, Bharatpur
district,
Rajasthan
Indian
Journal of
Public
Health
September
and October
2010
Cross
sectional
study
Essential
new born
care
None of the CHCs have fully
equipped facility based
newborn care services
(including newborn corner and
newborn care stabilization
unit).
Vijayalakshmi et
al; 2014, [173]
Journal
of Neonat
al Biology
1st April
2012 to 31st
June 2012
Cross
sectional
Essential
new born
care
65% newborns were breastfed
within an hour after birth and
5.9% were pre lacteally fed.
Mothers age at marriage and
day of first bath to newborn’s
was significantly associated
(p=0.02).
Sinha et al;2014,
[99]
Mewat, Haryana
Western
Pacific
Surveillan
ce and
Response
Journal
January and
March 2013
Cross
sectional
study
Essential
new born
care
60% of mothers adopted less
than three safe practices
(wrapping newborns, delayed
bathing, cord care). 237 (74%)
mothers started breastfeeding
within the first hour, 279 (87%)
fed colostrum, and 188 (58%)
mothers exclusively breastfed
their newborn.
Kumar et al;
2016 [70]
Rajasthan, India
BMC
Pregnanc
y and
Childbirth
March 2013
to April
2014.
Quasi-
eperimental
Essential
new born
care
Safe childbirth checklist (SCC)
was used in 86 % of the
observed deliveries in
intervention facilities. Client in
intervention facility received
11.5 more SCC (95 % CI-8.5–
14.6)) best practices than client
in comparison sites (p<0.001).
Narasimha BC et
al; 2016, [100]
Internatio
nal
Journal of
Communit
y
Medicine
and
Public
Health
October
2013 to
September
2014.
Cross-
sectional
Essential
new born
care
62.5% of the mothers initiated
breast feeding within 1 hour
and colostrum was fed to 95.6%
of babies. About 137 (85.6%)
babies were immunized up to
date. 12.5% (20) were low birth
weight babies.
Gosain et al;
2017, [101]
Journal of
Tropical
Paediatric
s
February-
March 2014
Cross
sectional
study
Essential
new born
care
ENC services were largely in
the public-sector domain
(68.5% of births). SNC burden
was largely borne by the private
sector (66% of admissions).
Only 53.9% of government
facilities and 17.5% of private
facilities had a fully equipped
newborn care corner.
Author
,Publication
year,Area
Journal
Name
Study
period
Type of
study
Intervention Results
Kumaravel et
al;2015, [102]
Dharmapuri
district, Tamil
Nadu
Journal of
Evolution of
Medicine and
Dental
sciences
Jan 2011
to Dec
2014.
Descriptive-
retrospective
study
Facility
based new
born care
Increase newborn care,
survival rate (74.4%- 85%)
due to NRHM provided
manpower & equipments to
improve SNCU. Admissions
increased two folds in the
past 4 years. Referral
out(5%-1.7%), death
rate(11.6%-9.6%),
LAMA(9%-3.7%) rates
were decreased.
Sachan et al;2015,
Lucknow, Uttar
Pradesh [103]
Journal of
Neonatology
2013
to
2015
Retrospective
analytical
study
Facility
based new
born care
Score in FBNC training pre-
test was 2.80 (±0.31) which
increased to 8.25 (±0.49) in
post test. The increase from
pre-test to post test was
5.30 (±0.33) (p=0.0001).
FBNC training program by
the GOI has improved the
knowledge of the
participants significantly
which is expected to result
in decline of NMR at faster
pace.
Chauhan et
al;2016,Bihar
[104]
Indian
Journal of
Public Health
May to
June
2015
Cross
sectional
study
Facility
based new
born care
Only 22.8% of the NBCCs
were found to be fully
functional, majority (68.4%)
were partially functional,
and 9% were
nonfunctional.1/3rd of the
neonates delivered were
kept in NBCCs
Oza JR et al;2017,
Rajkot
district,Gujarat
[105]
International
Journal of
Community
Medicine &
Public Health
August
2013 to
October,
2013
Cross
sectional
study
Facility
based new
born care
All 32 (100%) NBCC were
found partially functional.
Total 68 (67.3%) of 101
respondents were trained
in NSSK. From total 68
trained health personnel, 12
(17.7%) got the score
above the cut off for
resuscitation skill.
5.2.6 Studies with IMNCI as an intervention (n=3).
5.2.7 Studies on secondary data analysis (n=5)
Author
,Publication
year,Area
Journal Name Study
period
Type of
study
Interventio
n
Results
Mohan et
al;2011,
India [108]
Journal of Healt
h, Population an
d Nutrition
2005-2009
Mixed
methods
study
IMNCI
65.5% newborns were
visited by a trained worker
within 24 hours, and 63.1%
were visited three times
within 10 days. Difference
was significant only for
care-seeking for ARI (net
difference: 17.8%; 95%
confidence interval 2.3-
33.2, p<0.026).
Taneja et
al;2015,
Faridabad,
Haryana
[107]
Journal of
Global Health
Jan 2008
Cluster–
randomized
controlled trial
IMNCI
Implementation of IMNCI
had no effect on
inequities in neonatal
mortality but reduced
inequities in post–
neonatal mortality
between wealth quintiles
Author,
Year of
Publication
Journal
Name
Study
Period
Results
Rammohan
et al;2013
[113]
Plos One
2008-
2010
80% of neonatal deaths occurred within the first week of
birth. Neonatal mortality is significantly lower when the
child’s village is closer to the district hospital (DH),
suggesting the critical importance of specialist hospital care
in the prevention of newborn deaths.
Aguayo et
al;2016[114]
BMJ Global
Health
2006-
2014
Rates of early initiation of breastfeeding increased from
24.5% in 2006to 44.6% in 2014 (i.e. a 1.8-fold increase).
Jha et al; 2017
[115]
Lancet
2000-
2015
Neonatal tetanus mortality rate fell from 1·6 per 1000
livebirths in 2000 to less than 0·1 per 1000 livebirths in 2015
. Average annual decline in mortality rates from 2000 to
2015 was 3·3% for neonates
Phukan et
al;2018
[116]
International
Breastfeeding
Journal
2011-2015
Less than 1/4
th
(21%) of children were breastfed within 1 h
of birth. Odds of neonatal deaths were increased (OR 2.93;
95% CI 1.89, 4.53) in comparison with neonates who have
breastfed within 1 h of birth.
Bora et al;2018
[117]
Plos One
2015-
2016
Estimated NMR is about 2.4 times greater than the targeted
one (estimated 29.2 against targeted 12.0 deaths per 1000
live births in SDG3).
Review Study with HBPNC by ASHAs as an intervention (n=1)
Som et
al;2017,
Odisha [106]
International
Journal of
Health Sciences
& Research
Not
mentioned
Cross
sectional
IMNCI
Trained AWW have
enhanced knowledge of
childhood illness and
their management as
compared to IMNCI
untrained counterparts
1.41(95% CI,1.07-1.73),
P<0.0001
Gogia et
al;2016 [118]
Journal of
Perinatology
2012
Intervention was associated with a reduced risk of mortality
during the neonatal period .
RR = 0.75; 95% confidence intervals (CIs) 0.61 to 0.92, P =
0.005
5.2.8 Studies included in forest plot with outcome as prevalence of low birth weight babies.
(n=10).
Author ,Publication
year,Area
Journal Name Study
period
Type of study Intervention
/Strategy
Results
Number of low
birth babies
[n,(N)]
Sharma et al; 2008,
Government Medical
College, Chandigarh
[373]
The Internet
Journal of Health
April 2007
to March
2008
Cross sectional
study
LBW 46(193)
Biswas et al;2008,
District of Puruliya,
West Bengal [134]
Rural Health
Journal
2004-05
Cross sectional
study
LBW 152(487)
Velankar et
al;2009,Sahaji
Nagar, Mumbai
[135]
Bombay Hospital
Journal
Ten months
Cross sectional
study
LBW 114(252)
Jha et
al;2009,Varanasi
district, Uttar
Pradesh [136]
Indian Journal of
Community
Health
June 2006-
May 2007
Longitudinal
Cohort study
LBW 83(298)
Agarwal et
al;2011,Tertiary care
hospital, Uttar
Pradesh [137]
Annals of
Nigerian
Medicine
Not
mentioned
Cross sectional
study
LBW 140(350)
Metgud et al;2012,
Kinaye (PHC) in
rural Karnataka,
[138]
Plos One
June 2008 to
December
2009.
Cross sectional
study
LBW 260(1138)
Choudhary et
al;2013, Banganga,
Bhopal [139]
Indian Journal of
Public Health
Not
mentioned
Longitudinal
Cohort study
LBW 105(290)
Dandekar et al;2014,
Perambalur,Tamil
Nadu [140]
Global Journal of
Medicine and
Public Health
June –
November
2013
Cross sectional
study
LBW 35(300)
Lateef et al;2015,
Era’s Lucknow
Medical College
[141]
International
Journal of
Community
Medicine and
Public Health
July 2014 to
December
2014
Cross sectional
study
LBW 105(356)
Shashikantha et
al;2016, Chiri,
International
Journal of
February to
April 2013
Cross sectional
study
LBW 102(564)
Meta-analysis of studies with outcome as prevalence of low birth weight babies.
PGIMS, Rohtak
[142]
Community
Medicine and
Public Health
Interpretation of Forest Plot
Study design: Cross sectional, longitudinal cohort study,
Year of publication: 2008 to 2016,
Total studies pooled: 10
Sample size: 193 to 1138
Pooled LBW: 28% (CI: 0.23, 0.34)
Heterogeneity: 94.91% (very high because of sample size variability)
5.2.9 Result of studies with IMR as an outcome (n=16).
Author
,Publication
year,Area
Journal Name Study
period
Type of
study
Interventi
on/
Strategy
Results
Ramani et al ;
2010 [143]
VIKALPA 1990-2008
Secondar
y data
analysis
NRHM
Average annual reduction of 1.9
% in IMR over the period 1990-
2008. Aim for annual average rate
of reduction of 6.74 per cent in
IMR during the period 2009-2015
if MDG target of IMR at 28/1,000
live births by 2015 is to be
achieved.
Shah et al ;
2011,
Aligarh district,
Uttar Pradesh
[144]
Australasian
Medical Journal
July 2005 to
June 2006
Cross
sectional
study
Infants
death in
Medical
College
Infant mortality rate was 83.0 per
thousand live births . Main causes
of death were diarrhoea,
pneumonia and malnutrition in the
post- neonatal period.
Prasad et al ;
2013 [145]
Global Health
Action
April 2005 to
March 2012
Cross
sectional
study
NRHM
In high focus states, Rural IMR fell
by 15.6 points between 2004 and
2011, as compared to 9 points in
urban areas.
Narwal et al ;
2013, [146]
International
Journal of MCH
and AIDS
2000-2009
Secondar
y data
analysis
NRHM
IMR in rural India declined from 68
to 50/1000 live births between 2000
and 2009, with AARR of 3.0% (95%
CI=2.6%-3.4%) .IMR decline with
AARR of 3% in Pre NRHM & 3.3%
in Post NRHM era.
Singariya et al ;
2013 [147]
Journal of Finance
and Economic
2005-2012
Secondar
y data
analysis
NRHM
Rural IMRs declined from 76 points
– from 124 to 48 while urban IMRs
36 points decline in the same period
(1980- 2011). Annual rate of
reduction of IMR is much higher in
the post NRHM period. It was near 2
percent in 2000 -05 and its previous
years, but after implementation
NRHM it has been accelerated to 4
percent in 2005-10 and nearly 6
percent in 2011 .
Author
,Publication
year,Area
Journal Name
Study
period
Type of
study
Interventio
n/
Strategy
Results
Prasad et al ;
2017,
Tertiary care
hospital, Surat
[148]
National Journal of
Community
Medicine
October
2016 to
November
2017.
Cross
sectional
study
Infant
deaths in
tertiary
hospital.
Total live births were 7677, 223
died within a year i.e. infant mortality
rate is 29.04
Sudhir et al ;
2017,
Tertiary
hospital,
Muzaffarpur
[149]
Journal of
Evidence-Based
Medicine and
Health Care
February
1, 2016, to
January
31, 2017.
Longitudin
al study
Infant
deaths in
tertiary
hospital.
Infant mortality was highest 71
(56.8%) in maternal age of delivery
<18 years (P<0.05). Infants on
exclusive breastfeeding had lowest
mortality 25 (20%) and infants on
formula feed had 56 (44.8%)
mortality (P=0.0001).
Rai et al, 2017,
Ballagarh, North
India [150]
BMJ 2008-2012
Cross
sectional
study
Health
and
Demograp
hic
Surveillan
ce System
IMR was 46.5/1000 live births. Care-
seeking was delayed among 50% of
neonatal deaths and 41.2% of post-
neonatal death.
Gopalkrishnan
et al, 2018 [151]
International
Journal of
Community
Medicine and
Public Health
2005-2012
Secondar
y data
analysis
NRHM
IMR 58-30/1000 live births(2005-
2012).
10 states/UT achieved, 15 states in
the range of 30-40/1000 LB .
Bills et al; 2018;
AP, Assam,
Gujarat,
Karnathaka,
Meghalaya
[152]
BMJ
February
to April
2014
Prospecti
ve
observatio
nal study
Emergenc
y medical
services
Cumulative mortality rates at 2, 7
and 42 days follow-up were 43, 53
and 62 per 1000 births . At 42 days
follow-up, preterm birth (OR 2.89,
95% CI 1.67 to 5.00) and twin
deliveries (OR 2.80, 95% CI 1.10 to
7.15) were the strongest predictors
of mortality
Studies on secondary data analysis
Author, Year of
Publication
Journal Name Study
Period
Results
Reddy et al ; 2012
[153]
WHO South-East Asia
Journal of Public Health
1990-2010
Declining trend in IMR observed during 1990-
2010 continues linearly, India’s IMR would be 42
per 1000 live births (95% CI: 38-45) by 2015
and MDG 4 target level of ‘28’ would be
achieved in 2023–2024
Sahu et al ; 2015
[154]
Indian Journal of Medical
Research
1992 to 2006
The hazard of infant mortality during 2005-2006
was 20 % less compared to period 1992-
1993..Hazard of infant mortality was highest
among births to mothers >/30 (HR=1.3) and
37% less among birth interval > 24 months.
Chowdhury et al ;
2017 [155]
BMJ
January 2008 -
March 2010.
The odds of death at 29–180 days and at 181–365
days were 1.4 (95% CI 1.3 to 1.6) and 1.7 (95%
CI: 1.4 to 2.0) higher in females compared with
males, respectively. IMR - 67.1/1000 live births
Kaur et al ; 2017
[156]
International Journal of
Community Medicine
and Public Health
1998-2014
Total fertility rate (TFR), women who had
institutional deliveries, safe deliveries and mean
children ever born are statistically significantly
associated with decline in infant mortality rate.
(p<0.01)
Ranjan et al;
2017 [157]
International Journal of
Population Studies
2004-2008
Infants born to rural women had 29% (p < 0.05)
higher risk of death compared to infants born to
urban women
Dhirar N et al;
2018 [158]
Indian Pediatrics 2005-2016
Reduction in IMR from 57 to 41/1000 live births.
Initiation of breast feeding within one hour
improved from – 23.4% to 41.6%, Exclusive
breastfeeding of the infants less than 6 months of
age improved from -46.3% to 54.9%..
5.2.10. Studies on evaluation of ASHAs under HBPNC (n=9).
Author,
Publication
year
Journal
Name
Study
period
Type of
study
Intervention/
Strategy
Results
Srivastava et al ;
2012, Thane
district of
Maharashtra [119]
Rural and
Remote Health
January
2011 to
March
2011,
Cross
sectional
study
HBPNC
71 ASHAs (48.6%) were unaware
of preventive actions to be taken for
Vitamin A. Twenty-nine (19.9%) of
the ASHAs did not feel the need for
referral for a child with diarrhoea
who is unable to drink or breast
feed.
Das et al ; 2013,
Priimary health
centers in Babina
block [120]
Indian Journal
of Paediatrics
November
2012-
February
2013
Cross
sectional
study
HBPNC
ASHA-investigator agreement on
the need to assess infants was
intermediate (kappa 0.48,
P<0.001). ASHAs did not follow
home-based newborn care formats
and skipped critical signs. Overall
ASHA-investigator agreement on
diagnosis was poor (kappa=0.23,
P=0.01)
Shashank et al ;
2013, Bijapur taluk
[121]
International
Journal of
Contemporary
June -
October,
2012.
Cross
sectional
study
HBPNC
Regarding complete cessation of
breast feeding 11(8.3%) said at 6
months, 45(34.1%) said by 1
years of age,44(33.3%) said at 2
years of age, 32(24.3%) said at 3
Research and
Review
yrs of age. 58(43.9%) of ASHA
were aware of the importance of
immunization and the adverse
events following immunization
Karol et al ; 2014,
Rajasthan [122]
International
Journal of
Humanities
and Social
Science
Not
mentioned
Cross
sectional
study
HBPNC
Average score of the ASHAs in
child health care is 86.62 %.
80.61 % of children in
immunization were motivated by
ASHAs.
Fathima et al; 2015
Karnataka [37]
Journal of
Health,
Population,
and Nutrition
February-
May
2012.
Cross
sectional
study
HBPNC
Advice on breastfeeding (83.6%)
, home-visits to see the puerperal
mother (72.4%) and
immunization at birth (84.2%)
was reported to be high.
Author, Publication
year
Journal Name
Study
period
Type of
study
Intervention/
Strategy
Results
Choudhary et al ;
2015,
Jamnagar district,
Gujarat [123]
National
Journal of
Community
Medicine
March
2012 to
Feb 2013
Cross
sectional
study
HBPNC
Four fifth of ASHA (80.93%)
knew about exclusive breast
feeding correctly and around
three fifth (60.31%) of ASHA
knew about the method of
prevention of neonatal tetanus.
Gupta M et al,
2016 , urban slum
areas, Chandigarh
[[124]
Advances in
Medical
Education
and Practice
August
2013 -
December
2014.
Longitudinal
study
HBPNC
Overall skill assessment score
improved from 0.64 to 1.76,
newborn examination skill from
0.52 to 1.63 after three rounds of
video recording. Proportion of
carrying PNC register increased
from 50% at the baseline to 86%
in the second round and 100% in
the third round
Pandit at al ; 2016;
Rural area of
Maharashtra [125]
International
Journal of
Health
April 2016
to June
2016.
Cross
sectional
study
HBPNC
Home Based Newborn Care
(5.41% of the ASHA had poor,
83.78% had average and 10.81%
had good level of knowledge
score respectively. Mean
Sciences and
Research
knowledge score of the ASHA for
the area of HBNC was 3.94±1.05
and in Breast Feeding initiative
was 2.54±0.55
Panda et al;2019
;Odisha [126]
International
Journal of
Community
Medicine and
Public Health
March -
June 2018
Cross
sectional
study
HBPNC
ASHA workers were aware
regarding the responsibilities.
64.7% in HBNC. All of them
(100%) ASHA’s helped in
immunization. 24.65% gave
advice to mothers about breast
feeding .
5.2.11 Studies under strategy IMNCI(n=5)
Author,
Publication year
Journal
Name
Study
period
Type of
study
Intervention/
Strategy
Results
Venkatachala J et al
; 2011
Panchkula district of
Haryana stat [109]
Indian
Journal of
public health
2006-2009 Cohort study IMNCI
Composite knowledge and skill
scores for Auxilliary Nurse
Midwives (ANMs) and Anganwari
workers (AWWs) together
declined significantly in the year
2009 from 74.6 to 58.0 in 8-day
training group and from 73.2 to
57.0 in 5-day training group (P <
0.001).
Biswas B et al ;
2011.West Bengal
[110]
Journal of
Tropical
Paediatrics
October
2008 to
July 2009
Cross
sectional
study
IMNCI
Appropriate management for all
associated conditions was given
in one-third (33.6%) young infants
and about one-fourth (23.9%)
older children
Bhandari et al ;
2012,Haryana
[94]
BMJ
June to
October
2006
Cluster
randomized
trial
IMNCI
IMR (adjusted hazard ratio 0.85,
95% confidence interval 0.77 to
0.94) were significantly lower in
the intervention clusters than in
control clusters.
Chishty S et al ;
2016,
Baran district of
Rajasthan [111]
International
Journal of
Current
Research
Two years
Longitudinal
study
IMNCI
Baseline scores for IMNCI skills
for assessing infants in age group
of 0-2 months was 7.23 at the
end of second visit the mean
scores in the four blocks
improved to 10.62 and further to
13.36 at the end of third visit
Thummakomma ;
2016,
Kakatiya Medical
College, Warangal
[112]
Journal of
Evidence
Based
Medicine
and
Healthcare
January
2013 to
September
2014.
Prospective
observational
study
IMNCI
Sensitivity of IMNCI criterion in
correctly identifying sick infants
of age 0-2 months is 90.02%,
specificity is 63.10%, positive
predictive value being 92.44%
and negative predictive value is
55.79%
5.2.12 Studies on Immunization(n=3) And Viamin A(n=1)
Author,
Publication
year
Journal
Name
Study
period
Type of
study
Interventio
n/Strategy
Results
Gupta et al ; 2007
[259]
Journal of
Urban Health
April to June
2006
Cross
sectional
study
Immunizati
on
Fully immunized children at the
age of 2 years were 30% in slums
as compared to 74% and 62.5% in
urban and rural areas (p<0.001),
respectively.
Prinja et al ; 2010
[356]
Bulletin of the
World Health
Organization
July 2005
and
December
2006.
Cohort
design
Immunizati
on
Proportion of children with 3
rd
DPT
dose by age of 4, 6 and 9 months
was 22%, 70% and 88%,
respectively, in the post-
intervention cohort. This was
significantly greater (P < 0.001)
than in the pre-intervention cohort,
where the proportions were 19%,
62% and 85%, respectively.
Verma et al ; 2017
[374]
Public
Health
Action
April 2013 to
March 2016
Mixed
methods
Immunization
Immunisation coverage- 100 % for
BCG vaccination in both
settlements by 2015, irrespective of
the presence of the ASHAs. For
DPT (or the pentavalent vaccine),
coverage was 100% in the
settlement with the ASHAs and
94% without ASHAs. Infant deaths
from 11-6/1000 live births(2013-
2015) in settlement with ASHAs.
Study on Vitamin A(n=1)
Mazumdar et al ;
2015 [375]
Lancet
June 24,
2010 - July
1, 2012
Randomi
zed
control
trial
Vitamin A
supplementati
on
The risk difference between the
vitamin A and placebo groups was
– 3·1 deaths per 1000 (95% CI –
6·3 to 0·1) - 322 neonates need to
be supplemented with vitamin A to
prevent one infant death in the first
6 months of life.
5.2.13 Studies included in forest plot with outcome as Exclusive Breastfeeding (n= 26)
Author, year of
publication, Area
Journal Name Study period Study
type
Interventio
n/Strategy
Results [Total
Number of
exclusive breast
feeding
babies[n,(N)]
Kishore et al; 2008
Panchkula district of
Haryana [159]
Journal of Tropical
Paediatrics
August 2007 (one
month)
Cross
sectional
Exclusive
breast
feeding
8(77)
S Sapna et al ; 2009
Urban Slum In Western
India [160]
International e-Journal
of Science, Medicine &
Education
Six months
Cross
sectional
Exclusive
breast
feeding
123(200)
K Madhu et al; 2009
Kengeri, Rural
Bangalore [161]
Indian Journal of
Community Medicine
January 2006 to
April 2006
Cross
sectional
Exclusive
breast
feeding
40(100)
Chudasama et al ;
2009,Rajkot [163]
Ojhas online journal of
Health and Allied
sciences
1st January to
19th February,
2007
Prospect
ive
cohort
Exclusive
breast
feeding
286(462)
Roy et al; 2009
Urban Slum of Kolkata
[162]
Indian Journal of
Community Medicine
Not mentioned
Cross
sectional
Exclusive
breast
feeding
34(120)
Sinhababu et al; 2010
Bankura District, West
Bengal, [164]
Journal of Health
Population and
Nutrition
June-July 2008
Cross
sectional
Exclusive
breast
feeding
369(647)
Dinesh et al ;
2012,District
Anand,Gujarat [296]
National Journal of
Community Medicine
Not mentioned
Cross
sectional
Exclusive
breast
feeding
38(75)
Bagul et al ; 2012,
Nagpur ,
Maharashtra [166]
Journal of Clinical and
Diagnostic Research
June 2011 to
December 2011
Cross
sectional
Exclusive
breast
feeding
142(384)
Radhakrishnan et al;
2012, Tamil Nadu [167]
International Journal of
Health & Allied
Sciences
March 2011–
June 2011
Cross
sectional
Exclusive
breast
feeding
99(291)
D J Naik et al; 2013
GMC, Miraj, [168]
International Journal of
Recent Trends in
Science And
Technology
September -
October 2011
Cross
sectional
Exclusive
breast
feeding
76(154)
Anwar et al ; 2013,
Varanasi district, Uttar
Pradesh [169]
Indian Journal of
Preventive and Social
Medicine
September 2011
to November
2011.
Cross
sectional
Exclusive
breast
feeding
4(97)
Joseph et al ;
2013,South India [170]
Journal of Family
Medicine and Primary
Care
November 2004
to April 2006.
Longitud
inal
study
Exclusive
breast
feeding
81(194)
Das et al ; 2014, Rural
medical college in
Eastern Indi [171]
Journal of Evolution of
Medical and Dental
Sciences
Not mentioned
Cross
sectional
Exclusive
breast
feeding
120(200)
Jain et al; 2014,Rural
Madhya Pradesh [172]
National Journal of
Community Medicine
March to Aug
2014.
Cross
sectional
Exclusive
breast
feeding
254(300)
Vijayalakshmi et al;
2014,
Rural Area of
Puducherry [173]
Journal of Community
Medicine and Health
Education
1st April 2012 to
31st March 2013
Longitud
inal
study
Exclusive
breast
feeding
98(136)
Vijayalakshmi et al;
2015 [98]
International Journal of
Health Sciences
January 2014
(one month)
Cross
sectional
Exclusive
breast
feeding
33(122)
Mishra et al; 2015
jasra block of
Allahabad district [176]
Indian Journal Child
Health
November 2011
to April 2012
Cohort
study
Exclusive
breast
feeding
45(80)
Prasad et al; 2015
Rural Community of
Pondicherry [177]
Scholars Academic
Journal of Bioscience
November and
December 2014
Cross
sectional
Exclusive
breast
feeding
249(350)
Choudhary et al; 2015,
Tertiary care center in
Bhopal [175]
International Journal of
Medical Science and
Public Health
January 2014 to
June2014
Cross
sectional
Exclusive
breast
feeding
330(1000)
Cacodkar et al;
2016,Goa [174]
International Journal of
Community Medicine
and Public Health
One year
Cross
sectional
Exclusive
breast
feeding
115(307)
Kar et al;2016,Odisha
[179]
Journal of
Epidemiological
Research
July 15th to Oct
15th 2011.
Cross
sectional
Exclusive
breast
feeding
173(360)
Jha et al ; 2016,
Warangal, Telangana
[180]
International Journal of
Community Medicine
and Public Health
September 2015
to November
2015
Cross
sectional
Exclusive
breast
feeding
120(200)
Kumar S et al ; 2018,
IGIMS, Patna, Bihar
[181]
International Journal of
Community Medicine
and Public Health
January 2017 to
June 2017
Cross
sectional
Exclusive
breast
feeding
140(400)
Meta analysis of studies with outcome as Exclusive breast feeding
Interpretation of Forest Plot
Study design: Cross sectional, Longitudinal study
Year of publication: 2008 to 2018
Total studies pooled: 26
Sample size: 61 to 1000
Pooled exclusive breastfeeding: 47% (CI: 0.39, 0.55)
Heterogeneity - 98% (very high because of sample size variability)
5.2.14 Studies with outcome as under 5 mortality rate (U5MR), N=9
Author
,Publication
year
Journal
Name
Study
period,
Place
Type of study Strategy/
Cause/Data
source
Results
Semba R. et al,
2009 [186]
The
Journal
of
Nutrition
2005-06,
India
Secondary data
analysis from
NFHS 2005-06
Vitamin A Proportion of U5 Mortality in
Vitamin A supplemented
children vs. Non
supplemented : 8.4%
vs.11.4%
Espie E et al,
2010 [183]
Journal
of
tropical
pediatrics
2008, Bihar
(Darbhanga
Distt)
Cross sectional
design
Survey U5MR: 0.53 deaths/10,000
persons/day
Global acute
malnutrition:19.4%
Kumar C et al,
2013 [185]
Journal
of Public
Health
1990-2008,
India
Secondary data
analysis
Sample
Registration
System (1990-
2008)
U5MR: Decline of 42% from
26/1000 in 1990 to 15/1000
in 2008
Average annual rate of
reduction:3.2%
Ram U et al,
2013 [115]
Lancet
Global
Health
2001-12,
India
Secondary data
analysis
National
demographic
and mortality
surveys[SRS(2
009-11),NFHS
3(2005-
06),DLHS2(200
2-
04),DLHS3(200
7-08)]
U5MR: Fell at a mean rate
of 3.7% per year between
2001-2012 , from 96/1000
live births to 57.3/1000 live
births.
Number of districts with >80
deaths/1000 live births also
reduced from 384 to 80
districts.
Farooqui H et al,
2015 [184]
PLOS
One
2010, India Modelling
based estimate
from
multicentric
hospital based
studies
Pneumonia All cause pneumonia deaths
occurred in children=0.35
million , Pneumococcal
deaths = 105 thousand (92–
119 thousand) Highest
deaths-UP, BH,MP, RJ,JH
Wang H et al,
2016 (Multi-
country study)
[187]
Lancet 2000-13,
India
Secondary
data analysis
Global burden
of
disease,injuries
,risk factor
study (GBD
2013)
Annualized rate of change
in child mortality from 2000
to 2013= -3.2 to -5.1 (-4.3)
in India
Dhirar N et al,
2018 [158]
Indian
Pediatric
s
2005-16,
India
Secondary
data analysis
Comparison of
NFHS 3 Data
with NFHS 4
U5MR: 74 to 50/1000live
births [ 48% decline]
Strategies: Increase in
intake of ORS: 26% to 50%,
Increase in immunization
coverage: 43.5% to 62%
,Reduction in prevalence of
stunting: 10%
Jha P et al,
2017 [180]
Lancet 2001-2015,
India
Secondary
data analysis
Combining the
proportion of
child death
from Million
Death survey
2001-13 with
annual US
estimates for
2000-15
Average annual decline
from 2000-15: 5.4%,Annual
decline from 2000-05: 4.5%
, Annual decline from 2005-
15: 5.9%, Decline was
faster during 2005-15.
Decline in mortality rate
from pneumonia: 63%,
Decline in diarrhea rate:
66%,Decline in measles
mortality rate: 3.3 to
0.3/1000 live births.
India avoided 1 million child
deaths.
Gothankar J. et
al, 2018 [188]
BMC
Public
Health
2015 (7
months),Ur
ban and
rural field
practice
area BVDU
in
Maharasthr
a
Cross
sectional
ARI U5MR: 3.81/1000 children
Proportionate death rate for
pneumonia: 21.42%
5.2.15 Studies included in forest plot with outcome as full immunization coverage, N=16
Author, year
of
publication
Journal Name Study period,
Place
Study
type
Intervention/
Strategy
Results
Total Number of
fully immunized
children [n,(N)]
Nath B et al,
2007 [194]
Indian journal of
medical sciences
2005(4
months),
Urban slums of
Lucknow
Coverage
survey
Immunization 244(510)
Mallika MC
et al, 2014
[193]
Journal of Evolution of
Medical and Dental
Sciences
2013-14,
Thiruvanantha
puram Distt,
Kerala
Cross
sectional
Immunization 189(210)
Devasenapa
thy N et al,
2016 [190]
BMJ Open 2014(4
months), Delhi
urban slums
Cross
sectional
Immunization 863(1849)
Gill N et al,
2016 [191]
International Journal
of Community
Medicine and Public
Health
2014(3
months),
Mankhurd
suburb,
Mumbai
Descriptiv
e study
Immunization 189(210)
Datta A et
al,
2017 [189]
Journal of Clinical and
Diagnostic Research
2013-14, Rural
field practice
area of
Agartala GMC
Cross
sectional
Immunization 304(303)
Srivastava A
et al,
2017 [195]
Indian Journal of
Forensic and
Community Medicine
2016(3months)
, Urban field
practice area
SNMC
Bagalkot,
Karnataka
Cross
sectional
Immunization 235(283)
Jain A et al,
2018 [172]
International Journal
for Scientific Research
and Development
2018(2
months), Rural
area of
Tikamgarh,MP
Descriptiv
e
research
Mission
Indradhanush
114(204)
Gothankar J
et al,2018
[188]
BMC Public Health 2015(7
months),
Urban and
rural field
practice area
BVDU in
Maharasthra
Cross
sectional
Immunization 605(639)
Kurane A et
al,
2018 [201]
International Journal
of Contemporary
Pediatrics
2015-17,
Pediatric ward
in DY Patil
hospital
Kolhapur,
Maharashtra
Hospital
based
study
Immunization 1303(2000)
Chavan G et
al, 2018
[196]
National Journal of
Community Medicine
2017,
Mahabubnagar
Distt of
Telangana
Cross
sectional
Immunization 101(122)
Mohapatra I
et al, 2018
[202]
Journal of Family
Medicine and Primary
Care
2017 (4
months),
Urban field
practice area
of KIMS
Bhubaneswar
Cross
sectional
Mission
Indradhanush
72(100)
Ganguly E
et al, 2018
[199]
INQUIRY: The Journal
of Health Care
2008-09,
Churu Distt
Rajasthan
Househol
d survey
REACH
strategy
4441(5007)
Cherian V et
al, 2019
[197]
International Journal
of Community
Medicine and Public
Health
2015-17,
Dallupura in
East Delhi
Cross
sectional
Immunization 301(350)
Joy T et al,
2019 [200]
Journal of Family
Medicine and Primary
Care
2017(3
months), Kochi
metropolitan
area of Kerala
Cross
sectional
Immunization 276(310)
Bhonsla S
et al, 2019
[203]
Indian journal of
community health
2017(12
months),Urban
and rural area
of Ambala
Cross
sectional
Immunization 349(420)
Francis M et
al, 2019
[198]
Elsevier Science
Direct
2017(2
months),Thimiri
rural block of
Distt Vellore
Cross
sectional
Mission
Indradhanush
509(606)
Other studies on immunization coverage not included in forest plot, N=6
Author
,publication
year
Journal
name
Study
period,
Place
Type of
study
Intervention/
strategy
Results
Carvalho N et
al, 2014 [6]
PLOS one 2007-08,
India(34
states and
UT)
Quasi
experimental
Effect of financial
assistance from
JSY on
immunization
(Use of DLHS 3
data)
Increase in 9.1 % points in
the proportion of fully
vaccinated children, 3-8%
point increase in coverage of
most vaccines,reduction of
3.2 % points in the
proportion of children who
had not received a single
vaccine.
Prinja S et al,
2017 [63]
Tropical
Medicine
and
International
Health
2015,
Kaushambi
Distt Uttar
Pradesh
Pre- and
post-quasi
experimental
design
ReMind(Reducing
maternal and
newborn deaths)
Full immunization increased
in the range of 30-40% from
2011 to 2015.Full
immunization in Intervention
group vs. control group(%):
Before matching
AHS 2011(n=124 vs.186) :
7.7 vs.7.1 ,CEAHH
2015(n=1418 vs.1473) : 49
vs.55.5
After matching(n=1219),
In AHS 2011= 44.40 vs.
46.50, CEAHH 2015= 47.20
vs. 55.70
Mathiarasu
A.M et al,
2017 [207]
International
Journal of
Public
health
Research
2012-13,
Kanyakumari
Distt
Tamilnadu
Cross-
sectional
Immunization Coverage of measles
vaccination (n=210):81.4%
with dropout of 18.6%.
Goel S et al,
2012 [205]
Indian Pediatrics 2009-10,
Bihar
Secondary data
analysis, comparison
of immunization
coverage before and
after launch of
Proportion of fully
immunized children in
2005-09: 19% to 49%
Muskaan Ek Abhiyaan
in Bihar with EAG
states.
Increase in BCG
Coverage from 2005-09:
52.8% to 82.3% , in
DPT-3 coverage: 36.5%
to 59.3%
Increase in OPV-3
coverage: 27.1% to
61.6% , in measles
vaccination coverage:
28.4% to 58.2%
Johri M et
al, 2016
[206]
Bull World Health
Organ
2009-13,India
(12 states)
Modelling of impact of
interventions , source
of mortality data:
million death study and
Indian household
survey
Under 5 lives saved by
measles vaccination in
12 states: 9346 (29% of
India’s Annual measles
mortality)
Lives saved by measles
vaccine with add-on
interventions=74367
Bawankule
R et al,
2017 [204]
PLOS one 2005-
2006,India
Secondary data
analysis from
Demographic Health
Survey
Coverage of measles
vaccination: 62%,
Prevalence of ARI in
measles vaccinated vs.
unvaccinated: 5.6 vs.
7.3, Measles
vaccination was
associated with a
reduction of 15% ARI
,12% diarrhoea
Meta analysis of studies on full immunization coverage
Interpretation of forest plot
Study design: Cross sectional
Year of publication: 2007 to 2019
Total studies pooled: 15
Sample size:100 to 5007
Pooled Full Immunization coverage: 77% (CI: 0.69, 0.85)
Heterogeneity:99% (very high because of sample size variability)
5.2.16 Studies with focus on Vitamin A Strategy (n=4)
Author,
Year of
Publicatio
n
Journal
Name
Study type Study
Period
Interventio
n/Strategy
Results
Semba R
et al, 2009
[186]
The
Journal
of
Nutrition
Secondary
data analysis
from NFHS 3
2005-
06,India
Vitamin A Out of total 23008
children,4459(20.2%)receive
d Vitamin A within last 6
months
Characteristics of children
who received Vitamin A vs.
who did not received
supplementation:-Severe
underweight=16.7%vs.22.1%
(p<0.0001)
-Severe wasting=6.7% vs.
7.6 %,Severe stunting
=24.6% vs. 32.2%(p<0.0001)
Agarwal S,
2013 [223]
Int J Med
Public
Health
Secondary
data analysis
from NFHS 3
2005-
06,India
Vitamin A n=20802
Only 25%(20802 of the
children in India received
vitamin A supplementation,
Rural children(71.8) and
children of educated mothers
were more likely to receive
vitamin A supplementation
than others(urban-
28.2%).one-third of the
children aged 12-23
months(61.2%) received
vitamin A supplementation
as compared with only one-
fifth of the children aged 24-
35 months(38.8%).
Kapil U et
al,
2013 [225]
Public
Health
Nutrition
Prospective
cohort study
2011-
12,Uttar
Pradesh
Vitamin A n=262
Resolution of Bitot spots
after Mega Dose Vitamin A
supplementation-
At 6 months of follow
up:51.1% (134)cured , At 1
year : 59.9%(157) cured
Aguayo V
et al
2014 [224]
Public
Health
Nutrition
Secondary
data analysis
from DLHS
2006-2011,7
states
(Bihar,Chhat
tisgarh,Jhar
khand,Madh
ya Pradesh,
Odisha,
Rajasthan,
UP)
Vitamin A Increase in the mean full
VAS coverage in seven
states from 44.7% to 67.3%
Annually decrease in
number of poor children who
did not receive two VAS
doses-40.3%
5.2.17 Studies with outcome as ARI and Diarrhoea, N=9
Author, Publication
year
Journal Name Study period Type of
study
Results
Prajapati B et al, 2011
[376]
National
Journal of
community
medicine
2008-09,
urban and
rural areas of
Ahmedabad
Cross
sectional
study
n=500
Prevalence of ARI in last 1 month :
22%, prevalence in urban area:
17.2% and in rural are: 26.8%,
It was higher in low social class:
26.56%, in Illiterate mothers:24.4%,
Overcrowded houses: 28.5%.
Goel K , 2012 [377] Journal of
Community
medicine and
Health
Education
2011-12,
Urban and
rural areas of
Meerut
Cross
sectional
study
n=450
Prevalence of ARI: 52%, mean
number of episodes of ARI -2.25 per
child per year, It was higher in severe
malnourished children: 26.49% than
less malnourished: 09.82 %.
Mathew M et al, 2013
[378]
Indian
pediatrics
2009-11,
Ernakulam
Distt Kerala
cross-
sectional
n=1827
Overall prevalence of Rotavirus
diarrhoea: 35.9%(648) ;prevalence of
rotavirus diarrhea in children of 12- 23
months : 41.9%;
24- 35 months: 46.9% and 36- 59
months:33.3% in, Death:0
Kumar G et al, 2015
[379]
Journal of
Natural
Science,
Biology and
Medicine
2013-14,
Kerala
cross-
sectional
n=509
Overall prevalence of ARI:
59.1%(301),prevalence in urban
areas: 63.7% and rural areas: 53.7%
Prevalence of ARI in 13-24 months
age group: 52.6% , in 25-60 months
age group: 59.5%.
Gupta A ,2015 et al
[380]
Journal of
Global
Infectious
Diseases
1 month,
West Bengal
cross-
sectional
n=152
Overall prevalence of
diarrhea:22.36%(34); prevalence of
diarrhea was 21.83% in completely
immunized children and 30% in
partially immunized children.
Author, Publication
year
Journal Name Study period,
Place
Type of study Results
Farooqui H et al,
2015 [184]
PLOS One 2010,India Secondary
data
anlaysis,Data
from DLHS-3
Incidence rate of severe pneumonia -
30.7/1000 children /year,
Lower incidence :Southern
state(Kerala, Tamil Nadu),North
eastern states
annual incidence of severe
pneumococcal pneumonia-4.8
episodes/1000 children
Highest in Jharkhand(7.9) ,lowest in
Manipur(1.1)
Ramani V et al,2016
[381]
Journal of
Clinical and
Diagnostic
Research
2006-07,
Karnataka
longitudinal
cohort
n=400
Overall incidence rate of ARI :
27.25%(109),Incidence of URTI and
LRTI:19.25% and 8% respectively.
Incidence of ARI in Type IV and Type
V grade malnutrition: 53.85% and
66.67% respectively.
Kumar B et al,2017
[382]
International
journal of
contemporary
medical
research
Andhra
Pradesh
Longitudinal
study
n=650
The ARI incidence: 3.33
episodes/child/year, it was declined
with increasing age , maximum in the
first year (2.66 episodes/ child/year)
,minimum in 20 -24 months (1.59
episodes/child/year) of life
Gothankar J et al,
2018 [188]
BMC Public
Health
2015(7
months),
Maharasthra
Cross
sectional
n=3569
Incidence of ARI in last one month:
0.49/child/month; in rural: 0.53,urban:
0.43;P= 0.05 [6 episodes of ARI in
one year], reported incidence of
pneumonia in last one
year:0.075/child/year
(281/3569)[Rural: 0.13(146),Urban:
0.07(135)]
N=605 ;Cases of pneumonia in Full
immunized vs. non immunized
children :64 vs 541 (p < 0.05)
Other Studies
Author,
Publication
year
Journal
Name
Study
Period
Study type Data
source/Intervention
Results
Reduction in geographical and socioeconomic inequalities post NRHM period
Gupta M et
al, 2016 [61]
PLOS
One
2002-13,
Haryana
Secondary
data
analysis
DLHS before(2002-
04),during(2007-
08),after(2012-13)
the NRHM
Implementation
The geographical
and socioeconomic
differences between
urban and rural
areas, between rich
and poor were
significantly
(p<0.05) reduced for
children with full
vaccination :10% to
3.5%, 48.3% to 14%
and who received
oral rehydration
solution(ORS) for
diarrhea:11% to -
2.2%; 41% to 5%.
Inequalities between
male and female
children were
significantly
(p<0.05) reversed
for full immunization
from 5.7% to -0.6%.
Role of Frontline workers in improving child health
Gupta M et
al, 2017 [80]
BMC
Public
Health
2002-13,
Haryana
Secondary
data
analysis
Demographic Health
Survey post(2012-
13),during(2007-
08),pre(2002-04)
NRHM
implementation
Full extent of
implementation for
immunization by
NRHM was found,
Accredited social
health activists act
as an catalyst in
acceptance of
immunization.
Vir S et al,
2014 [354]
Food
and
Nutrition
Bulletin
2011,Rural
Chhattisgarh
Quasi-
experimental
mixed
methods
Mitanin Programme Nutritional status of
children up to
35mo[Project
Group(n = 1,775) vs.
Control Group(n =
1,749)]
Severely
underweight:13.8
vs.15.6 ,Severely
wasted :11.1 vs. 15.3
Annual average
reduction rates
(AARRs) for
underweight ,
stunting and wasting
-
In 1998-2005 :1.45%
, 1.93% and 0.4%
In 2005-2011: 4.22%,
5.64% and 3.53%
5.2.18 Studies with focus on RBSK, N=3
Author, Year
of Publication
Journal
Name
Study
Period
Study Type Intervention/
Strategy
Results
Singh P et al,
2011 [383]
National
Journal of
Community
Medicine
January
2011-June
2011, Surat
Retrospectiv
e analysis
School
health
program
Total number of
patients screened
=24 children
Incidence of heart
diseases=14 children
Tiwari J et al,
2015 [227]
Internationa
l Journal of
Community
Medicine
and Public
Health
6 months
(August
2014-
Januray201
5),
Panna Distt
Madhya
Pradesh
Cross
sectional
survey
RBSK Number of children
screened for birth
defects,
deficiency,
developmental delays
and other
diseases=26977
Balat M et al,
2018 [226]
Internationa
l Journal of
Community
Medicine
and Public
Health
June -
October
2016,
Ahmedabad
Cross
sectional
study
RBSK Number of
beneficiaries under
RBSK=169
Children diagnosed
for heart
diseases=47.9%,
Number of children
operated
=53%,Children given
drug therapy=31.95%
5.2.19 Studies included in forest plot with outcome as recovered children under nutritional
rehabilitation centers, N=15
Author
,Publication year
Journal Name Study period,
Place
Type of study Intervention Results
Number of
recovered
children,[n,(N)]
Taneja G et
al,2012 [211]
Indian Journal of
Community
Medicine
2008-09, Indore
and Ujjain
division Madhya
Pradesh
Prospective
study
NRC 42(100)
Maurya M et
al,2014 [209]
Indian Pediatrics 2011(12
months),
Allahabad Uttar
Pradesh
Retrospective
analysis
NRC 110(162)
Singh K et
al,2014 [222]
Indian Pediatrics 2010-11, Uttar
Pradesh(12
NRCs)
Secondary
data analysis
NRC 286(1181)
Sanghvi J et
al,2014 [210]
ISRN Pediatrics 2011-12,
SAIMS hospital
Indore
Prospective
study
NRC 128(300)
Aprameya HS et
al ,2015 [208]
International
Journal of Health &
Allied Sciences
2013-14,
Wenlock Distt
Hospital
Mangalore
Prospective
study
NRC 38(91)
Rawat R et
al,2015 [216]
Journal of
Evolution of
Medical and Dental
Sciences
2014(6 months),
Bhopal
Observational
study
NRC 68(102)
Ningadalli S et
al,2015 [214]
International
Journal of Science
and Research
2013(10
months),
Belgaum Distt
Karnataka
longitudinal
study
NRC 24(30)
Rao B et al, 2015
[215]
Journal of
Evidence Based
Medical Healthcare
2013,
Visakhapatnam
Andhra Pradesh
Retrospective
analysis
NRC 43(63)
Tariq S et al,
2015 [212]
International
Journal of
Contemporary
Pediatrics
2014-15,
GMC Srinagar
Prospective
study
NRC 110(146)
Mathur A et al,
2016 [213]
International
Journal of
Contemporary
Pediatrics
2012-14, HRH
hospital Delhi
Not
mentioned
NRC 250(327)
Golandaj J et al,
2016 [217]
Nutrition and Food
Science
Jan -Dec 2014,
4 Distt of
Northern
Karnataka
Cross
sectional
study
NRC 94(722)
Kumar N et al,
2016 [218]
Journal of
Evolution of
Medical Dental
Sciences
2014-15,
Ananthapuramu
Andhra Pradesh
Prospective
study
NRC 103(195)
Dhanalakshmi
K.et al ,2017
[221]
International
Journal of
Contemporary
Pediatrics
2014-15,
Bangalore
Retrospective
study
NRC 599(736)
Shekhar C et al,
2018 [220]
International
Journal of
Community
Medicine and
Public Health
2013(10
months), Urban
Kurnool area
Andhra Pradesh
Cross
sectional
NRC 37(52)
Chaturvedi A et
al, 2018 [219]
Nutrition Journal 2011-12,
Jharkhand 48
MTCs
Prospective
study
Malnutrition
treatment
center
26(116)
Figure: Meta analysis of studies with outcome as recovered children under NRC
Interpretation of forest plot
Study design: Cross sectional, Prospective study, Retrospective study
Year of publication: 2012 to 2018
Total studies pooled: 15
Sample size: 30 to 1181
Pooled Recovered Children under NRC: 55 %( CI: 0.39, 0.70)
Heterogeneity: 99% (very high because of sample size variability)
5.3 REPRODUCTIVE HEALTH
5.3.1 Results of studies with TFR as an outcome (N=9)
Author, year
of publication
Study period Outcome Proportion
Mohanty et al,
2013 [384]
1991-2011
(respective
rounds of DLHS,
Census and
NSS data)
TFR
The variance of TFR in districts of India has increased from 0.87 in
1991 to 0.91 in 2001 and declined to 0.71 by 2011.
Prasad et al,
2013 [254]
2001-2011 TFR
TFR declined from 3.81 to 2.58 after the implementation of NRHM
in India
Barman,
2013 [251]
NFHS 3 report
and SRS 2007-
08
Unmet
Need,
TFR
TFR is maximum in EAG states (2.6 to 4.0).EAG states unmet need
33.1, South Indian States -27.7 and rest of Indian states 27.2, MMR
EAG states 308, South Indian states 127, Rest Indian states 149.
Mohanty et al,
2014 [253]
2000-2011 TFR TFR declined from 3.87 in 1991 to 2.66 in 2011
Sebastian et
al, 2014 [252]
2000-2010 (SRS
reports)
TFR
TFR in Bihar declined from 4.5 to 3.6 in 2011, Odisha 2.8 to 2.2 and
MP 4 to 3.1 compared to national decline from 3.2 to 2.4 in 2011.
Chhetri et al,
2016 [255]
Post
NRHM(2005-
2014)
TFR has declined from 2.6 in 2006 to 2.4 in 2011. Rural TFR has
declined from 3.1 to 2.7 and urban has declined from 2.0 to 1.9 in
this period.
Bansod et al,
2016 [256]
NFHS 4
Most of the Indian states have achieved replacement level fertility of
2.1 except Bihar-3.4, Meghalaya 3.0, Manipur 2.6 and MP 2.3. CPR
(any method) varies from 24% in Manipur to 71% in West Bengal.
CPR (modern method) 13 % in Manipur to 69% in Andhra Pradesh.
Khan et al,
2017 [257]
1991-2011
Before NRHM TFR was 3.81 and after NRHM TFR 2.58 so mean
difference is 0.6
Narwal et,
2017 [258]
2007-2015 (Pre
and post
evaluation of
NRHM)
TFR declined from 2.9 in 2005 to 2.4 in 2011. TFR declined by 10.3
% in 2001-06 compared with 14.3% in 2006-11.
5.3.2 Studies included in forest plot with outcome as CPR (n=22)
Takkar et al,
2005 [270]
2005 81 % women were practicing contraception and 73% of them were regular users.
Only 11% participants were aware of emergency contraceptive measures.
S. K.
Bhattacharya,
2006 [269]
2006 proportion of women using contraception was 45%, 41.6% was the unmet need,
major reason of high unmet need was opposition of family/husband.
Gupta et al, 2007
[259]
2007 contraceptive practices in slums were significantly low as compared to urban and
rural areas in Chandigarh (53.4% vs 73% vs 75%).
Kumar et al,
2010 [263]
2010 Contraception usage: 52%. Most common age group was 23-27 years. Mean age of
first delivery was 20 years. 62% of the non-contraceptive users were illiterate and
usage increases with increase in education. 505 have the knowledge of male
sterilization but they believe it will weaken the male. None had the correct
knowledge of emergency contraception.
Makade et al,
2012 [264]
2012 234/342 (68.42%) participants were using any one contraceptive method
Speizer et al,
2012 [265]
2012 All the districts report about 50% of modern contraaceptive use. Across all districts
higher unmet need was found in slum population.
Prateek et al,
2012 [266]
2012 Participants having knowledge of contraception 52.2%, Participants using
contraception 32.2%,
Das et al, 2012
[120]
2012 65.3 % contraceptive acceptance rate, OCP and female sterilization are most
common methods used
Lakshmi et al,
2013 [308]
2013 Awareness 95%, Acceptance 87%, Followed contraception 71%, Users 52%
Bhattacharjee et
al, 2013 [268]
2013 89.5% women had the knowledge of contracetive measures, OCP knowledge
(84%), only 35% women were using contraception. Religion, age, literacy and
number of living children were associated with contraceptive usage.
Singh et al, 2009
[273]
2009 75.3 % were contraceptive users. Religion was found to be significantly associated
with contraceptive use. Unmet need for contraception was more than 33% and
unmet need for spacing was 23.5%.
Murarkat et al,
2011 [271]
2011
249(48.63%) women were contraceptive acceptors
Mahawar et al,
2011 [274]
2011 a) 18% KAP Gap was found in total subjects. Maximum KAP Gap was found in the
19-21 year age group.
b) 98% of the subjects had the knowledge,
Mody et al, 2014
[275]
2014
65.3% women were not using any contraeption. Among the women who were
using contraception condom was the most common choice (77.8%)
Parameaswari et
al, 2014 [272]
2014
CPR was 67.1%. Unmet need 23.1
Bhutia, 2015
[276]
2015
TFR is 2.0 as compared to national 2.8, Knowledge and awareness about
contraceptive methods is 99.1 %, contraceptive usage is 50%.
Ambure et al,
2015 [277]
2015
50% women were using contraceptives. contraception was more among Hindus
and christians then muslims. Although women having full PNC were proportionally
higher in using contraceptives but staistically no association was found
Hiralal Nayak,
2016 [278]
2016
98% of women were aware of a family planning method, 64% were using any
method of contraception
Kanika et al,
2017 [279]
2017
90% clients were adequately utilizing the family planning services under NRHM
and 100% satisfaction was there.
Smith et al, 2017
[280]
2017
Awareness about contraception- 93.1%, most common purpose of using
contraception- maternal health benefits (65.5%) and birth spacing (60%),
counselling regarding postpartum contraception (24%), postpartum contraception
usage-48.3%
Trigun et al, 2017
[281]
2017
Contraceptive usage 51.1%
Singh et al,2019
[385]
2019
contraceptive usage was 19.7%
Meta Analysis of studies on CPR
Interpretation of Forest Plot
Study design: Cross sectional
Year of publication: 2007 to 2017
Total studies pooled: 22
Sample size: 50 to 17643
Pooled CPR: 54% (CI: 0.49, 0.59)
Heterogeneity - 98% (very high because of sample size variability)
5.3.3 Studies with secondary data analysis where CPR is an outcome
Author &
year of
Publication
Source of data Outcome focused Results
Prusty et al &
2014 [386]
DLHS-RCH III:2007-
08
(3 states with tribal
population:
Jharkhand, MP and
Chhattisgarh)
Contraceptive
Prevalence Rate
CPR: Jharkhand tribal 22.8, Non tribe 41.8,
Chhattisgarh: Tribal 43.5, non tribal 56.2,
MP: tribal 50.2 and non tribal 60.2
Sankariah et
al & 2015
[387]
Data from DLHS 3
and NFHS 4
Modern family
planning methods use
mCPR 47.5 (DLHS3) and 45.4 (NFHS 4)
mean difference -2.1 (95% CI -3.2,-1.1)
Cahill et al &
2018 [388]
Family planning
estimation tool
(FPET) used in 68
countries (2012-
2017)
estimates and
projections of the
modern contraceptive
prevalence rate,
unmet need for and
demand satisfied with
modern methods of
contraception
In Asian countries the m CPR growth has
been less than 1% since 2012
Unpublished
presented in
Bhopal
DLHS survey report Contraceptive use Use of Contraception is more in the age
group of 30-34, 35-39 and 40-44 i.e. 51-68%.
The contraception use was found to be very
low in the age group of 20-24 i.e. 28%
Unpublished
presented in
Bhopal
NFHS 3 - NFHS 4
survey report
Gender gap in
contraceptive use
Unmet need for family planning marginally
decreased from 14 (2005-06) to 13% (2015-
16), MCPR highest in HP (75%) and lowest in
Bihar (34%), MCPr is around 60% in 20% of
the districts. Female family planning method
usage (87.6%) and male FP method (12.6%)
5.3.4 Results of studies with ASHA as an intervention (N=4)
Author, year of
publication
Objective/Intervention Results and recommendations
Nimavat et al,
2013 [260]
To find out effects of new ASHA
incentive scheme under NRHM on
the performance of ASHA in
motivating couples to undergo
permanent sterilization method
ASHAs performance was increased; 1.13 times for
eligible couples and 1.14 times for couples having
two or less children after introduction of an
incentive, and incentive showed a significant impact
on motivation of eligible couples
Fotso et al, 2015
[262]
Engaging male CHWs to
complement the work of ASHAs
the engagement of male counterparts have
improved the performance of ASHA program
(statistically non significant), and unveils the
complementarity of male and female CHWs in
increased demand for MNCH services.
Karol, 2014 [122] Checking knowledge of ASHA
workers
ASHA's capacity is low in motivating family
planning cases for restricting high fertility in rural
areas (30.49%)
Bajpai et al, 2009
[261]
ASHA, Pregnancy Tracking system More than 90% ASHA workers interviewed
informed that they are involved in promoting
contraceptive usage and family planning measures
and all other services, go training about doses and
side effects of OCPs, 77% ASHAs help ANM and
AWW in preparation of list of eligible couples,
Tracking of married couples and pregnant women
for family planning counselling became easy.
5.4 ADOLESCENT HEALTH
5.4.1 Studies included in forest plot with outcome as prevalence of Anemia
Author, year of
publication
Study period Impact Results
Vir et al 2008 [282]
(Cross sectional)
Sept 2001 to
Dec 2006
Reduction in
anaemia
overall prevalence of anaemia reduced from 73.3%
to 25.4%
Dongre et al 2011
(Cross sectional)
[364]
March to July
2008
Reduction in
nutritional
anaemia
Among adolescent girls, the prevalence of anemia
declined significantly from 73.8% at baseline to
54.6% at endline (p < .001). The median
hemoglobin level increased from 10 to 11 g/dL.
There were significant declines in the prevalence of
moderate anemia (p = .003) and severe anemia (p
= .002)
Vani et al 2015
(Cross sectional)
[284]
Jan to Dec 2004 Prevalence of
Anaemia
78.3% adolescent girls had anaemia, only 11%girls
had the knowledge about anaemia
Shah et al 2016
(Cross sectional)
[285]
April to June
2013
Reduction in
anaemia
anaemia in girl reduced from 79.5 % to 58% and in
boys it declined from 64%to 9%.
Diwakar et al 2017
(Cross sectional)
[286]
Not mentioned Decline in
anaemia
BMI does not improved much, No severe anaemia
found
Meta-analysis of 5 cross sectional studies on WIFS
5.4.2Studies included in forest plot with outcome as mean change in Hb levels
Author, year of
publication
Study period Impact Results
Sen et al 2007
[288]
Not mentioned Change in mean Hb
levels post intervention
(IFA daily vs IFA once
weekly vs IFA twice
weekly vs No IFA
Highest change was found in IFA
daily group (1.9g/dL) followed by IFA
twice weekly group (1.6 g/dL)
Bhoite et al 2012
[287]
Not mentioned IFA once weekly +
deworming vs
Deworming only
IFA + deworming showed 17.3%
increase in Hb levels as compared
to deworming only
Joshi et al 2013
[289]
June 2011 to
October 2012
IFA daily vs IFA weekly Mean rise in Hb was almost equal
IFA daily (1.0+0.7 g/dL vs 1.0+0.8
g/dL)
Bansal et al 2016
[290]
January 2012 to
March 2013
IFA + cynocobalamin vs
IFA
Mean increase in similar in both the
groups i.e. 108.9 ± 8.91 g/l and
106.7 ± 11.2 g/l respectively
Results of RCTs on WIFS (N=4)
5. 4.3 Studies included in forest plot with outcome as awareness about AFHCs
5.4.4. Studies included in forest plot with outcome as awareness about Menstrual Hygiene
Author, year of
publication
Study period Impact Results
Prateek et al 2011 [266]
Sept 2010 to Novemeber
2010
knowledge, attitude, and
practices regarding
menstruation and
menstrual hygiene
among adolescent girls in
rural areas.
49 (20.3%) have
awareness about
menstruation before
menarche
Author, year of
publication
Study period Impact Results
Kotecha et al, 2009
[312]
not mentioned readiness to use AFCs if
available
70% participants were ready to use the clinics
Nair et al, 2011 [313] not mentioned attitude of parents and
teachers towards imparting
RSH education to
adolescents
8 (1.1%) parents and 6 teachers discussed the
sexual health related issues with adolescents
Ray et al 2012 [310]
3 months
issues and challenges of
menstruation faced by
adolescents
Presence of Pre-
menarchial Knowledge
Regarding Menstruation
80(42%)
Nair et al, 2012
[389]
not mentioned gain in knowledge about
RSH
Among girls, percentage of poor knowledge had
reduced significantly from 64.1% to 8.3% and
among boys from 37.7% to 3.5%. less than 20% of
boys (17.7% 9th and 16.5% 11th standard) and
less than 10% of girls (5.1% 9th and 1.2% 11
th
standard) knew about symptoms of STDs before
intervention. increase in knowledge was observed
after intervention
Nair et al, 2013 [314] Two years Knowledge about Menstrual
hygiene practices,
knowledge attitude and
practices of 10-20 age group
regarding RSH issues
56% adolescents know the age of menarche
Nair et al, 2013 [315] Two years Knowledge about
contraceptive measures,
ideal age of pregnancy and
other RSH indicators
92% boys had knowledge about condoms as
compared to 56% girls having knowledge about
cu-T.
Mehra et al, 2013
[319]
Jan to April
2012
knowledge and utilization of
ARSH clinics
595 (78%) were aware of ARSH clinics, 61%
adolescents visited ARSh clinics
Chauhan et al, 2015
[316]
Feb 2014-Aug
2014
awareness and utilization of
AFHCs, barriers in utilization
14.1% were aware, 38.67% out of them visited,
major reason of non untilization was
shynessamong 54.35% girls
Shah et al 2013 [298]
Jan-July 2011
awareness about
menstrual hygiene
practices
65 out of 164 were aware
of menses before its
onset, 59 subjects knew
about sanitary pads, at
baseline 90% girls were
using old cloths but at the
end of the study 68%
chose fatalin cloths as
first choice and 32%
chose sanitary pads.
Paul et al 2014 [296]
2012
knowledge, attitude and
practices during
menstruation among the
adolescent school girls
363 (72.6%) adolescent
girls were aware about
menstrualtion till its onset
in 2012 as compared to
147 (29.4%) in 2007, use
of sanitary napkins also
increased from 23.8% to
74% from 2007 to 2012
Paria et al 2014 [295]
April 2013 - September
2013
knowledge, attitude and
practices during
menstruation among the
adolescent school girls
Awareness about
menstrual hygiene- 203
(37.52 %), Use of
sanitary pads was more
in urban girls as
compared t0 rural girls
(176 vs 120), Cleaning of
genetilia was satisfactory
Gupta et al, 2015
[363]
Feb to april
2011
Knowledge about ARSH and
access to the ARSH clinics
76% were aware of balanced diet, 17% were
aware of RTI/STI, utilization of ARSh was 7.4%
only
Kamath et al, 2015
[317]
Aug2012 to Jan
2015
Knowledge about
reproductive health
Only 8 (11%) boys were aware ARSH services
Mahalakshmy et al,
2018 [318]
Not mentioned awareness and utilization of
AFHCs
50% were aware, 2-10% utilized the services
in 47% urban and 38% in
rural girls
Ramchandra et al 2016
[301]
not mentioned
impact of menstrual
hygiene program under
NRHM on knowledge
and awareness on
menstrual hygiene
among adolescents
83 (34%) participants
were aware about
menstruation and 69%
were using sanitary
napkins
Nagaraj 2016 [390]
not mentioned
awareness about
menarche, items used for
menstruation, factors
associated with school
absence during
menstruation
awareness before
menarche 91 (29.93%),
after health education
campaign awareness
about cause of
mensturation increased
from 34% to 80%, the
awareness about source
of discharge increased
from 37.5% to 50.3%.
Vijaykeerthi et al 2016
[391]
Jan to Aug 2016
awareness about
menarche, items used for
menstruation
Awareness about
menstrual hygiene-
45.7%
Dudeja et al 2016 [293]
Jan-16
Knowledge about
menstruation hygiene
119 (56.4%) were aware
about menarche before
its onset, 191 (90%) use
sanitary pads, 88% use
dustbin for disposal
Kansal et al 2016 [294]
January to June 2011
Knowledge about
menstruation hygiene
174 (29.4%) were aware
about menarche before
its onset, source of
information was sister,
183 (31%) were using
sanitary pads and 69%
were using cloths, those
who were following
hygienic practices less
no. of RTIs were there as
compared to those who
wer not following (5 vs
27)
Syed 2017 [392]
not mentioned
Knowledge about
menstruation hygiene
67.5% participants were
aware about
menstruation before
intervention as compared
to 80% postintervention,
57% of subjects stated
hat shout for help in case
of any appropriate touch.
Deshpande et al 2018
[304]
June to August 2017
Knowledge about
menstruation hygiene
only 24% girls had the
knowledge of menarche
prior to menstruation,
60% of girls used
sanitary pads
Sivakami et al 2019 [311]
2015
knowledge about
menstrual hygiene
40% girls were aware of
menstruation before its
onset and 48% were
aware at the time of 1st
period. Parents were the
major source (68%), 87%
girls reported going to
school during
menstruation, 45% of the
girls reported
concentration problems
at school during
menstruation
Chaudhary & Gupta 2019
[305]
April to July 2018
knowledge about
menstrual hygiene and
HIV
Awareness about
menstruation was more
among urban girls (159,
67.7%) as compared to
rural girls (127, 59%),
usage of sanitary pads
was more in urban areas
(132, 56.2%) than rural
area (63, 29.3%),
awareness about
subsidized sanitary pads
was 30% in urban and
13% in rural girls.
Mamilla et al 2019 [306]
not mentioned
knowledge about
menstrual hygiene
75 (60%) were ware
about menstruation,
mother was the major
source, 84% used
sanitary pads, 85 % used
dustbin for disposal of
absorbent, 47% used
soap and water for
cleaning genitals, 50%
did not know about any
contraceptive method
Studies included in forest plot with outcome as usage of sanitary napkins, n=16
Author, year of
publication
Study period Impact Results
Thakre et al 2012 [299] Jan to March 2011 awareness about
menstrual hygiene
practices
191(49.3%)used
sanitary pads, more in
urban as compared to
rural, washing of
genetalia was
satisfactory with 34% of
participants
Shah et al 2013 [298] Jan-July 2011 awareness about
menstrual hygiene
practices
65 out of 164 were
aware of menses before
its onset, 59 subjects
knew about sanitary
pads, at baseline 90%
girls were using old
cloths but at the end of
the study 68% chose
fatalin cloths as first
choice and 32% chose
sanitary pads.
Paul et al 2014 [296] 2012 knowledge, attitude and
practices during
menstruation among the
adolescent school girls
363 (72.6%) adolescent
girls were aware about
menstruation till its onset
in 2012 as compared to
147 (29.4%) in 2007,
use of sanitary napkins
also increased from
23.8% to 74% from 2007
to 2012
Paria et al 2014 [295] April 2013 - September
2013
knowledge, attitude and
practices during
menstruation among the
adolescent school girls
Awareness about
menstrual hygiene- 203
(37.52 %), Use of
sanitary pads was more
in urban girls as
compared t0 rural girls
(176 vs 120), Cleaning
of genetilia was
satisfactory in 47%
urban and 38% in rural
girls
Rana et al 2015 [297] not mentioned knowledge, attitude and
practices during
menstruation among the
adolescent school girls
156 (39%) were using
sanitary pads, 208
(54.7%) use only water
to clean genitals
Udayar et al 2016 [178] April to Sept 2015 prevalence of
unhygienic practices in
the study area
230 (78.5%) were using
sanitary pads. 108
(37%) were changing
the absorbent twice a
day, 243 (82.9%) are
using only water for
cleaning external
genitalia
Vijayshree et al 2016
[393]
1st to 15th October 2013 awareness about gender
equity, abuse, violence
60% of the subjects
were scared when they
attained menarche, 78%
subjects used sanitary
napkins, 64% dispose
the used napkin in
dustbin, 87% wash their
hands after changing the
pads
Dudeja et al [293] Jan-16 Knowledge about
menstruation hygiene
119 (56.4%) were aware
about menarche before
its onset, 191 (90%) use
sanitary pads, 88% use
dustbin for disposal
Kansal et al 2016 [294] January to June 2011 Knowledge about
menstruation hygiene
174 (29.4%) were aware
about menarche before
its onset, source of
information was sister,
183 (31%) were using
sanitary pads and 69%
were using cloths, those
who were following
hygienic practices less
no. of RTIs were there
as compared to those
who wer not following (5
vs 27)
Agarwal et al 2017 [394] Feb-16 Knowledge about
menstruation hygiene
usage of sanitary
napkins was 37 (14%),
sanitary pads and cloths
91 (36%), the frequency
of change was once in a
day 129 (51.6%)
Ramchandra et al 2016
[301]
not mentioned impact of menstrual
hygiene program under
NRHM on knowledge
and awareness on
menstrual hygiene
among adolescents
83 (34%) participants
were aware about
menstruation and 69%
were using sanitary
napkins
Jain et al 2017 [302] May-16 Knowledge about
menstruation hygiene
222 (78%) subjects used
sanitary pads during
menstruation while
washed clothes were
used by 19%, mother is
the main source of
information followed by
peer group
Krishnaleela 2018 [303] not mentioned knowledge and source
of info about
menstruation and its
perceptions and
practices
Dysmenoorhea was
present in 90% of the
participants, 55% used
sanitary napkins, 15%
were aware of frequency
of change in sanitary
napkins, only 3% were
aware about nutritional
status with menstrual
irregularities
Deshpande et al 2018
[304]
June to August 2017 Knowledge about
menstruation hygiene
only 24% girls had the
knowledge of menarche
prior to menstruation,
60% of girls used
sanitary pads
Chaudhary & Gupta
2019 [305]
April to July 2018 knowledge about
menstrual hygiene and
HIV
Awareness about
menstruation was more
among urban girls (159,
67.7%) as compared to
rural girls (127, 59%),
usage of sanitary pads
was more in urban areas
(132, 56.2%) than rural
area (63, 29.3%),
awareness about
subsidized sanitary pads
was 30% in urban and
13% in rural girls.
Mamilla 2019 [306]
not mentioned knowledge about
menstrual hygiene
75 (60%) were ware
about menstruation,
mother was the major
source, 84% used
sanitary pads, 85 %
used dustbin for
disposal of absorbent,
47% used soap and
water for cleaning
genitals, 50% did not
know about any
contraceptive method
Kumar et al 2011 Not mentioned menstrual pattern and
menstrual hygiene
practices
41.2% in residential area
and 45.5% in slum area
- aware of menarche
before its onset, girls in
residential areas use
sanitary napkins girls in
the slum areas who use
cloth.
Social restrictions 4% in
residential area and
more than 45% in slums.
Bhudagaonkar 2014
[307]
Not mentioned awareness generation
about menstrual hygiene
practices
Knowledge about
staining of clothes
increase from 48% to
85%, absorbent can
provide media for
organism growth
increase from 41% to
94% and that it may
spread infection
increase from 31% to
70%
Patel et al 2016 [308] Baseline in 2013-14 and
intervention in 2016-17
Knowledge about
menstruation hygiene,
anaemia, reproductive
and sexual health,
program awareness and
utilization
Awareness about
nutritional status
including anemia-
increased in 15-18 years
age group and
decreased in 11-14
years age group,
menstrual hygiene
practice- there is
increase in the use of
sanitary napkins in
intervention as well as
control block (4.6% and
7% respectively).
awareness about
programs- increase in
the awareness and
compliance to WIFS,
poor knowledge and
access to AFHC was
reported.
5.5 Studies on RCH Inequalities
Author Journal name Study area Study
Type
Interven
tion
Results
Gupta M et al,
2017 [5]
PLOS one Ambala and
Mewat
Districts of
Haryana
Qualitative
study
NRHM
(MCH
plans)
Geographic inequalities reduction-
Increased utilization of MCH services
like ANC, institutional deliveries and
reduction in maternal and child death
gaps in urban and rural parts.
Socioeconomic inequalities between
rich and poor decreased to some
extent because of availability of free
ambulances, medicines, and diet
during hospital stay for the poor.
However, it was reported that food
security in general would reduce this.
Gender Inequality between girls and
boys- Small size of the families and
increased educational status
reported to have led to the changes
in gender inequality; Gender
inequality was less seen in Mewat
district
Randive B, et
al 2014 [73]
ELSEVIER,
Social Science
and Medicine
9 low
performing
states: RJ,
MP, CG, BR,
JH, UP, UK,
OR and AS.
Secondar
y analysis
of data
(DLHS3)
JSY Reduced inequalities in institutional
deliveries during the JSY program,
maternal mortality decline was
slower in the poorest areas
compared to richest ones. Absolute
increase in proportion of institutional
deliveries during JSY program was
about similar across all
socioeconomic groups, differential
rate of relative increase (i.e. from
16% to 45% in poorest district
quintile vs from 40% to 69%
in richest ones).
Degree of inequality in male literacy
contribute to 30% of inequality in
institutional delivery. Relative
increase in institutional delivery=
29% increase in poorest districts also
in richest district.
Jain R et al,
2016 [320]
India Human
Development
Survey Report
India Pre post
study,
(IHDS 1
and IHDS
2)
JSY Odds of receiving full ANC among
women educated up to the high
school level during the pre-JSY
period was 3.651 times as great as
for illiterate women whereas it was
only 2.261 times as great during the
JSY period. The relative odds of
women receiving safe delivery had
significantly gone down among
women who were college graduates
from 6.371 times as great as illiterate
women during the pre-JSY period to
1.846 times during the JSY period.
The odds of full ANC declined from
1.031 per asset in IHDS-I to 1.025 in
IHDS-II. For postnatal care, the odds
declined from 1.050 per assets in
IHDS-I to non-significance in IHDS.
Likelihood of safe delivery increased
from IHDS 1 to IHDS 2 among
Muslims and forward caste Hindus.
Vellakkal S et
al, 2017 [64]
Health Policy
and Planning,
Oxford
8 EAG and 7
North-east
states
excluding
Nagaland
Quasi-
natural
experimen
t study
design
using data
from
DLHS1, 2,
3, 4 and
AHS
NRHM Wealth-related relative index for
inequalities for institutional delivery
fell from 14.5 in 1995– 99 to 11.7 in
2000–04 to 3.6 in 2007–08 to 1.3 in
2011–12 . Inequities in institutional
delivery and ANC were already
declining between the pre-NRHM
Period 1 (1995–99) and the pre-
NRHM Period 2 (2000–04), but
declined at steeper rates in the post-
NRHM periods. effects were stronger
for institutional delivery than ANC
Ali B. et al,
2018 [322]
Journal of Bio
social Science
India Secondar
y data
analysis of
NFHS 3
(2005-06)
andNFHS
4 (2015-
16), last
two
rounds
were
considere
d.
ANC,
PNC,
SBA
The usage gap of MCH services
between the poor and non-poor
remained large which was difference
of
- 4.3% (poor) and 15.3% (non
poor) for utilization of ANC.
Same for PNC
- 43% (poor) and 38% (non
poor) for SBA
This gap was higher in urban areas
in 2005–06, but more in rural areas
in 2015–16.
Poor women from SCs had higher
utilization of SBA and PNC than
women from OBCs and General
Castes in 2015–16.
Seth A. et al,
2017 [45]
International
Journal for
Equity in Health
Uttar
Pradesh
Survey
study
ASHA Women belonging to SC/ST and
OBC castes were less likely, as
compared to General Caste women,
to participate in at least 4 ANC visits.
Positive relationship between visits
by a community health worker and
likelihood of utilizing critical maternal
health services. Contact with ASHA
increased the odds of participation in
at least 4 ANC among lower wealth
women.
Gupta M. et al,
2016 [61]
PLOS One Haryana Secondar
y analysis
of DLHS
data
NRHM Geographic inequalities : Significant
(p<0.05) decline in difference of MCH
indicators between urban and rural
areas for pregnant women in urban
and rural areas –
3 ANCs from 23% to 5.4%
Full ANC from 8% to 6.8%
PNC from 2.8% to 1.5%
Full child vaccination10% to 3.5%
ORS fro diarrhoea from 11% to -
2.2%
Socioeconomic inequalities :
Significantly (p<0.05) decline in
difference of MCH indicators
between rich and poor-
TT injections in pregnant women
from 30.3% to 7%
Institutional deliveries : 48.2% to
13%
Fully immunized children from 48.3%
to 14%
ORS for diarrhoea from 41% to 5%
Although inequalities have been
increased between lowest and
highest wealth quintile groups related
to ANC pre and post NRHM ( 0.2 to
23%)
Gender inequalities : Difference of
inequalities between male and
female children was significantly
(p<0.05) reversed-
Full immunization (5.7% to -0.6%)
BCG from 1.9 to -0.9 points
Oral polio vaccine from 4% to 0%
Measles vaccine from 4.2% to 0.1%
Gupta M et al,
2017 [80]
BMC public
health
Haryana Explanato
ry
sequential
mixed
methods
study
NRHM Significant reduction in inequalities
pertaining to various MCH indicators
between poor and rich
(socioeconomic), rural and urban
(geographical), and girls and boys
(gender) across time period. But
reduction in gender based
inequalities was associated with
increase in educational status and
acceptance of small family size.
Mújica JO et
al, 2014 [323]
Bull world
health organ
BRICS
(Brazil,
Russia,
India, China,
South Africa)
Secondar
y data
analysis
MCH
inequalit
ies from
1990 to
2010
Maternal mortality- difference of 400
deaths per 1, 00,000 live births.
Infant mortality- 32.4 deaths per
1000 live births.
Child mortality- 50.8 deaths per 1000
live births
Pathak PK et
al, 2010 [324]
PLOS one UP, MH, TL NFHS
survey
data
analysis
PNC
and
SBA
Use of PNC among rural mothers in
India increased by 8 percentage
points (from 13% in 1992–1993 to
21% in 2005–2006). While it
improved by 19 % points (33% in
1992–1993 to 52% in 2005–2006)
among urban mothers during 1992–
2006. Use of
PNC remained significantly lower
among poor mothers than among
their non poor counterparts.
Gopichandra V
et al, 2012
[325]
PUBLIC
HEALTH
ETHICS
UP Review
study
(Data
adapted
from
UNFPA’s
Concurren
t
Assessme
nt of JSY)
JSY JSY beneficiaries=
Hindu = 38.8, Muslims = 23.5
SC/St = 32.5,others= 38.9
BPL= 38.1, Above BPL= 35.8
Living in huts= 33.5, living in
cemented houses= 43.1
Singh A. et al,
2012 [326]
PLOS one India
Secondar
y data
analysis
(DLHS)
PNC Mothers received check up within 48
hours- Home= 18 %, Institution =
80.8%
Newborn received check up -
Home= 18.8%, Institution = 82%
Newborn check in govt. facility -
Home = 17%, facility = 52.7%
Newborn check in private facility-
Home = 83%, institutional = 47%
Patel P et al,
2018 [321]
Reproductive
Health Matters
Purnia
district, Bihar
Qualitative
study
NRHM=
ASHA,
JSY ,
JSSK,
ANM
27% women received facilities from
ASHA. Only 5 % received PNC from
ANM. SC caste women did not
received needed care. USHA were
absents in urban slum due to caste
discrimination. Participants did not
receive JSY money and poor quality
of service was offered at PHC due to
belonging from lower caste. 16%
women discussed only being treated
at the PHC after women of higher
caste.
Kant S etal,
2016 [330]
International
Journal of
Gynecology
and Obstetrics
Haryana Observati
onal study
Delivery
huts in
rural
areas
The services successfully reached
pregnant women belonging to
disadvantaged caste groups, in
addition to those from higher castes.
There was also a significant increase
in the proportion of women attending
the huts who were illiterate over the
study period.
Saikia N. et al,
2016 [329]
Asian
Population
Studies
India Trend
analysis
Secondar
y data
analysis
SRS data
(1981-
2011)
- 1981= NMR with difference of 37
between urban and rural India.
2011= NMR with difference of 17
between urban and rural.
Bhatia M et al,
2018 [327]
SSM -
Population
Health
ELSEVIER
India Secondar
y data
analysis
- Relative change in inequalities in
infant and under five mortality over
the survey periods from NHFS-I to 3,
NHFS 3 to 4 and NHFS-1 to 4.
IMR = -30 among poorest and -38
among richest. Which was -25 and -
23 for NFHS 1 to 3 respectively?
U5MR = -39 -38 among poorest and
richest respectively during NFHS 3 to
4 and with no difference among poor
and rich during NFHS 1-NFHS 3.
The worst performing states (e.g.
Chhattisgarh, Odisha, Uttarakhand),
both in terms of high mortality and
high differentials between rich and
poor.
Motkuri V et al,
2018 [328]
Status of
Maternal and
Child Health
(MCH) in
Telangana
Telangana Secondar
y data
analysis
(SRS and
NFHS 4)
- Rural urban difference in Telangana=
11, AP= 14 India=15
Inequalities across social groups in
general and in the health dimension
are very narrow-
Rural and urban health
inequalities(maternal and child) -
2002-04 =0.478 and 2012-13= 0.750
Fertility rates low and harmonized
across social and religious groups in
the state.
Contraception rates are lower in
Muslims tribe.
IMR is high among ST and SC. Child
vaccination do not vary much with
respect to background.
ANC is low among ST women and
high among Muslims.
5.6 IMPACT OF OTHER VARIABLES ON HEALTH OUTCOMES
5.6.1 Results of studies on mobile connectivity (9 studies)
Author
and
year
Study
area
Study
Period
Study Type Intervention Results
Chib A,
2012
[332]
Udham
Sing
Nagar
District,
Uttrakha
nd
2008-
09
Qualitative
study
Mobile phone
use by
community
health workers
under NHM
scheme
(ICTH4H
model)
Improved communication flow during
emergencies. Increase in connectivity
with higher medical officers regarding
delivery and vaccination.
Balakris
hnan R.
et al
2016
[331]
Saharsa
District,
Bihar
July
2012
to
March
2015
Case control Continuum of
Care Services
(CCS)
(Maternal and
Child) by using
an mHealth
platform
Improved reporting and service
delivery.
21% more ANC visits in intervention
group in comparison to control group.
14% more cases of early breast feeding
in intervention group.
Hazra
A. et al
2018
[333]
Jhansi,
Uttar
Pradesh
April to
May,
2014
Quasi-
experimental
Voice
messages to
husbands of
pregnant
women on 5
health
behaviours ;
ANC check up,
Postnatal
check up, Early
breastfeeding,
Clean cord
care, Bathing of
baby
Improved knowledge. 39% asked their
wives and 13% asked their mothers to
follow the instructions. 80% of
husbands knew the importance of ANC,
40% knew about early initiation of
breast feeding. Uptake of one ANC,
PNC with in 7 days and delayed
bathing with odd of 1.72, 3.02 and 1.93
respectively.
Nair H.
et al,
2018
[335]
Pune,
Mahara
shtra
2015 Case control
study
Smartphone
with a track
care app.
Under 5 children with diarrhoea and
sought care ; Case= 75%, longitudinal
Control = 80%, cross-sectional control
=78%
Under 5 children with fever who sought
care; Case = 83%, longitudinal control
= 79%, cross sectional control = 79%
Under 5 children with fever and cough
who sought care; Case = 88%, cross
sectional control =84%, longitudinal
control = 89%.
No significant difference between case
and control. This could be due to
Hawthorne effect or due to repeated
study contacts.
Pai N. et
al, 2013
[336]
Low
income
area of
Mumbai
Hospital based
mixed method
study ( case
control and
qualitative
study)
Voice calls for
IFA supplement
The treatment group improved Hb by
0.43 g/dL (95% CI = -0.13 0.98 g/dL)
more than the control group. This
improvement is not statistically
significant (p=0.13).
Qualitative finding; Women offered
positive feedback regarding the voice
messages, describing them as
informative, entertaining, and a service
that they would recommend to friends.
Patel A.
et al,
2018
[337]
Nagpur 2010
to
2012
Hospital based
case control
study
Cell phone
counselling
The rates of exclusive breastfeeding
were sustained above 95% at all visits
in the cell phone group but dropped
from 81% at 6 weeks to 48.5% at 6
months in the control group.
Intervention group was 6 time more
exclusively breastfed than control
group. 13% higher rates of early
breastfeeding in intervention group.
Shah S.
et al,
2018
[338]
Bharuch
and
Narmad
a
districts
of
Gujarat
2016 Nested cross
sectional study
with a
randomized
controlled trial
ImTECHO Significantly higher knowledge and
skills of MNCH in the intervention arm
compared to the control arm with
difference of 18%. Intervention group
demonstrated better skills for
measuring temperature of new-borns
and preventing hypothermia compared
to the control group with difference of
30% and 15% respectively.
Spindler
H. et al,
2017
[339]
Bihar 2015
to
2017
Cross sectional
study
Mobile nurse
mentoring
programme
Communication with mother improved .
85 % improvement in debriefing. 77%
complicated deliveries were conducted
by nurses. Improvement in vaginal
delivery, non vigorous infant and
postpartum haemorrhage.
Modi D.
et al,
2016
[334]
Bharuch
district,
Gujarat
April-
May
2015
Cross sectional
study
ImTECHO
(Support and
supervision of
ASHA and
PHC staff)
Higher sensitivity for registration of
pregnancy, delivery and child death i.e.
97%, 99% and 100% respectively.
5.6.2 Results of studies on road connectivity (8 studies)
Author
and year
Study
area
Stud
y
Perio
d
Study
Type
Intervention Results
Bawdekar
M, 2008
[340]
Mahara
s-htra,
33
districts
2003 Secondar
y data
analysis
(DLHS-
RCH
Round II)
Road length
Female
literacy rate
Health
facilities
Toilet
facilities
Temperature
Road length and percentage female literacy had
an inverse relationship with severe malnutrition
and the association was significant at p<0·05.
Children in the households with either a personal
or public toilet facility are 11% less likely to suffer
from severe malnourishment as compared with
those with no toilet facility at all. Climate on
health facilities have insignificant association with
server malnutrition.
Ghosh A.
et al 2016
[341]
India 2016 Secondar
y data
analysis
((DLHS-
3)
Road
connectivity
Weather
Health
center
Mother
literacy
Availability
of ANM and
ASHA
Indicators of village-level general infrastructure,
like availability of electricity and all weather road
connectivity with the sub center or PHC, are
associated with both higher chances of receiving
of at least one DPT dose and higher chances of
completing the three-dose series among infants
who have received at least one dose of DPT.
36% and 46 % difference in DPT 3 and DPT 1
coverage respectively among children of mothers
educated up to 10th or higher education and
mothers without any schooling.
Lalmalsa
wmzauva
KC et al,
2009
[342]
India Secondar
y data
analysis
(NFHS 3,
India's
Year
Book,
Census
of India
2001)
Road
density
Positive correlations between surface road
density and all the indicators of utilization of
maternity services at a high 0.05 significant level
with ranges from(r=0.936) for institutional birth,
(r=0.950) for delivery assisted by health
personnel, (r=0.939) for any postnatal check-up
and (r=0.947) for postnatal check up within two
days of birth.
1. Very high surface road density areas - ANC
(36%), Institutional deliveries(70.8%), health
personnel attended delivery(77.88%) , PNC
(70.65%)
2. High density surface road areas- ANC(17.1%),
Institutional deliveries(40.94%), health persona;
attended delivery(52.11%), PNC(48.24%).
3. Medium density surface road areas-
ANC(17%), Institutional deliveries(41%), health
persona; attended delivery(48.38%),
PNC(39.08%).
4. Low density surface road areas- ANC(9.72%),
Institutional deliveries(28%), health personal;
attended delivery(36%), PNC(26.08%).
5. Very low density surface road areas-
ANC(10.2%), Institutional deliveries(41.87%),
health personal attended delivery(45.8%),
PNC(40.5%)
Kumar S.
et al,
2012
[344]
India 2013 Secondar
y data
analysis
from
DLHS 3
and
Demogra
phic
health
Surveys
Road
connectivity
and access
to health
facility
focusing on
delay 3
Distance to the nearest health facility is inversely
associated with the probability of in-facility
delivery.
With in 5 km of health facility- 42% of IFD.
With in 5 and 9 km- 32% of IFD
More than 10 Km- 26% of IFD.
Banerjee
R. et al,
2015
[345]
India Secondar
y data
analysis
(DLHS 3),
village
directory
of the
2001
Census
data
Road
connectivity/
Pradhan
Mantri Gram
Sadak
Yojana
(PMGSY)
Connecting villages with an all-weather road
increases the usage of preventive healthcare.
Women are 20% more likely to use ante-natal
care. Women rely more on female sterilization
and 12% less chances of use of withdrawal
methods. 3% more likely to enroll in government
health schemes. 30% and 25% likelihood of
having ASHA and ANM in the village
respectively.
Aggarwal
S, 2018
[300]
India Secondar
y data
analysis
(DLHS-3)
Road
connectivity
Better quality prenatal care , more likely to
receive micronutrient supplements, tetanus
shots. Full road connectivity = 4% less chances
of complications in delivery. Children are more
likely to receive vaccination except polio, reason
could be massive initiative to attain universal
polio vaccination rates.
Author Study
Location
Study
Period
Study Type Intervention Results
Sahoo
M. et al,
2017
[346]
Odisa 2014 to
2015
Descriptive
study
Supply side
barriers
The supply side barriers are; physical
barriers faced by the service providers
due to lack of proper roads and the
absence of transportation to the
interior villages. 38% respondents had
travelled 5 km distance for delivery,
15.2% of respondents had travelled
10 km, 9.4% had travelled for 15km
for delivery
Studies with road connectivity/distance as barrier, not as intervention
Barman
D. et al,
2009
[343]
Murshidabad
district of West
Bengal
2008 secondary
data
analysis
( RCH-
DLHS)
Supply side
and demand
side barriers
Supply side barriers- Distance to
travel by health workers,
Infrastructure
Demand side barriers- mother
education and awareness, use of
private or government health sector.
In comparison to illiterate mothers,
educated mother’s children were
more likely to get fully immunized.
Who used private sector were 28%
less likely to be fully immunized.
If ANM did not visit the household
during the pregnancy or after child
birth the child was 31% less likely to
be fully immunized. Better village
infrastructure score, child was more
likely to be fully immunized. If a
mother was employed her child was
found to be 33% less likely to be fully
immunized. Muslim children were
found 45 % less likely to be
completely immunized compared to
their Hindu counterparts
5.6.3 Results of studies on water supply and sanitation (7 studies)
Author
and
year
Study
area
Study
Period
Study
Type
Intervention Results
Bajpai
N. et al,
2006
[395]
Jalore
and
Chittorgar
h
districts,
Rajastha
n
April-
May
2006
Cross
sectional
NRHM
coordination
with sub
sectors like
sanitation,
Nutrition,
Safe
drinking
water.
Usage of safe water- 68% to 70% of the
households. Unsafe water practices-
30% of the household's Tap water
facility- 2% to 3%. Toilet facility at
home- none of the households. No
regular waste removal facility.
Percentage of sickness (2005)- 42% in
Jalore and 43% in Chittorgarh.
Incidence of hospitalization-
11% in Jalore but only 5% in Chittorgarh.
Institutional deliveries- 4% in Jalore and
8% in Chittorgarh district.
ANC- 3% in Jalore and 9% in Chittorgarh
received such care.
Incidence of still birth-5.3% in Jalore
and 3.3% in Chittorgarh.
Vaccination of children-In Jalore 95%
and in Chittorgarh 98% of the poor
families got their children vaccinated. This
could be due to polio erradication
program
Butala N
M. et al,
2010
[352]
Ahmadab
ad
2001-
08
Case and
control
design
used
secondary
data
(micro
insurance
provider
VIMO
Slum
Upgrading
Significant reduction in waterborne illness
from 25% to 10%. Reduction in
waterborne illness claims 32% before the
intervention to 14% after the intervention.
SEWA in
the years
2001- 2008
)
Nandi A.
et al,
2016
[349]
India Secondary
data
analysis
(DLHS-3)
Access to
piped water
and
improved
sanitation
(Intervention
1; 95%
coverage at
random,
Intervention
2; At least
95%
coverage in
each state)
Intervention 1; Diarrheal incidence
averted- 43,126, deaths averted- 68.
Intervention 2; Diarrheal incidence
averted-43352, deaths averted- 68.
Intervention could avert could avert
43,352 diarrheal episodes and 68
diarrheal deaths per 100,000 under-5
children per year, compared with the
baseline.
Ercume
n A. et
al, 2015
[348]
Hubli-
Dharwad,
Karnatak
a
Nov
2010
to Feb
2012
Matched
cohort
study
Intermittent
water supply
and
continuous
water
supply.
No significant overall association was
found between continuous versus
intermittent supply and diarrhea bloody
diarrhea or weight for age. In continuous
supply wards, 42% fewer households had
at least one reported case of typhoid
fever compared to intermittent supply
wards. No significant association between
continuous versus intermittent supply and
cholera. Lower <2-y-old mortality
associated with continuous versus
intermittent supply. (No reason listed out
because of small number of deaths).
Berende
s D et
al, 2017
[347]
Vellore,
India
2010
to
2014
Cohort
study
Household
sanitation
(toilets)
Risk of enteric infection was 9% lower in
children in households with toilets
compared to those without toilets. Risks
of bacterial and protozoal infections for
children in households with toilets were
13% and 36% lower than for children in
households without toilets. But these
relationships were not significant.
Patil S
R. et al,
2014
[351]
Dhar and
Khargone
districts,
Madhya
Pradesh
2011 Cluster
randomize
d control
trial
Total
Sanitation
Program
Diarrhea prevalence did not differ
between groups (7.4% intervention
versus 7.7% control).
Padhi B
K, et al,
2015
[350]
Odisha Population
based
prospective
cohort
study
Sanitation 58.2%)had no access to a latrine and
reported open defecation at recruitment.
About half (45.8%) of the pregnant
women living in a household with latrine
access. 32% reported rare use of the
facility. Compared to latrine access, open
defecation was associated with higher
odds of APO , preterm birth, and low
birth weight . Other factors associated
with higher odd of APO are ; Occasional
use of toilets, non availability of water in
latrines, washing of body with water from
open sources.
Other study (Self-help group)
Author and
year
Study
area
Study
Period
Study
Type
Intervention Results
Saha S. et
al, 2013
[396]
India Secondary
data
analysis
(DLHS-3)
Self Help
Groups
The presence of a SHG in a village is
associated with 19 % higher odds of
mother’s delivering in an institution. 8
% higher odds of an increase in
colostrum feeding. Presence of a
health and sanitation committee in
a village or accessibility of a
CHC/RH does not appear to
influence the outcome.
5.6.4 Impact of food availability on health outcomes (N=6)
Author
and year
Study area Study
Period
Study Type
/Intervention
Results
Singh V et
al,2017
Barabanki
and Unnao
ditrict of
Uttar
Pradesh
May-Aug
2005
quasi
experimental
randomized
longitudinal
study/
Integrated
nutririon and
health program
Impact on breastfeeding practices:
Early initiation was more frequently
reported in the intervention arm
(17.4% vs. 2.7%)In the intervention
group, 34.7% of the women reported
giving colostrum to their
babies versus 8.4% in the
comparison district (p<0.001)
Impact on complementary feeding
practices: Improvement in total
quantity of food given in the
intervention area from 12±18
months, whereas, no such increase
in the comparison district was
observed .
Passi R et
al
22
VHSNCs of
Chandigarh
January
and May
2015
cross‑section
al mix method
study
The villages showed good
performance regarding the nutritional
status of children aged 0–3 years but
performance of providing
complimentary feeding to children of
age 6–12 months was average.
Alim F et
al, 2012
16
Anganwadi
s
in 5 villages
in Aligarh,
Uttar
Pradesh
(U.P.)
January-
June, 2011
Survey based
study/ ICDS
Only76.4% of children had received
the supplementary nutrition through
ICDS and 23.6% of children did not
received supplementary nutrition.
Children who received supp
nutrition:62.7 % of children, were
having normal weight for age, 13.7%
were underweight, and 49.4% of the
children were of normal height for
their age.
Children who did not received
supplementary nutrition: majority
14.3 % of their children was
underweight, 68% children were
stunted.
Thakur J
et al, 2010
45
Anganwadi
centres
(AWCs)
in
Chandigarh
April
to August
2007
Prevalence of underweight among
under-five children remained almost
stagnant in the last one decade from
51.6% (1997) to 50.4% (2007). There
was insignificant difference (P=0.3) in
prevalence of underweight among
children registered under ICDS
program (52.1%) and those not
registered (48.4%) in 2007.
Vaid S et
al, 2005
Resham
Ghar
colony
of Jammu
city
(Jammu
and
Kashmir
State)
- Cross
sectional study
children who attended Anganwadi
centres had good health or
appearance as compared to their
counterparts, also ICDS children had
good dietary intake as compared to
the children who did not attend ICDS
centres.
Kumar A
et al,2009
field
practice
area
encompass
ing 35
Anganwadi
s
in 11
villages by
the
Community
Medicine
Department
of
Kasturba
Medical
College
situated in
July 2009 cross-sectional
study/ICDS
Assessment of the growth chart
revealed that malnourishment was
evident in 189 (32.3%)
of the children, of which 166 children
were grade I
malnourished and 23 children were
grade II malnourished.
Proportionally girls (46.2%) were
more malnourished than
boys (33.6%).
Southern
India
ANNEXURE 6: LIST OF GOOD QUALITY STUDIES INCLUDED IN THE SYSTEMATIC
REVIEW.
S. No. Author and
Year
Journal Geographic area Study design Intervention Target
Population
Sample
size
Outcome Odd ratio
controlled
Confounders
controlled
Grading
JSY
1 Lim et al, 2010 LANCET India Secondary data
analysis
JSY Pregnant
females
Institutional
deliveries
√ √ +++
2 Randive B. et
al, 2013
PLOS ONE India Secondary data
analysis
JSY pregnant
females
Institutional
births
√ +++
3 Panja TK et al,
2019
Indian Journal of Public Health West Bengal Cross sectional
community
based study
JSY pregnant
females
Institutional
deliveries
√ √ +++
4 Mukhopadhyay
DK et al,
201
Indian Journal of Public Health West Bengal Cross sectional
study
JSY JSY eligible
women
946 Institutional
deliveries
√ √ +++
5 Gopalan d et al,
2012
BMC Health Services Research Orissa Mixed method
design
JSY Pregnant
females
Institutional
deliveries
× × ++
6 Amudhan S et
al, 2013
International J of Epidemiology Ballabgarh, Haryana Quasi
experimental
study
JSY Post-natal
females
1884 Institutional
deliveries
√ √ +++
7 Sidney K et al,
2012
BMC Reproductive Health Ujjain Cross sectional
study
JSY Pregnant
females
418 Institutional
deliveries
√ √ +++
8 Ng M et al,
2014
Global Health Action Madhya Pradesh Continuous time
series
JSY Reproductive
age group
females
MMR reduction √ +++
9 Ved R et al,
2012
BMC proceeding oral presentation EAG states Survey Women of
institutional and
home delivery
Institutional
delivery
× × +
10 Randive B et al,
2014
Social Science and Medicine 9 states( RJ, MP, CG, BR, JH, UP, UK,
OR, AS)
Ecological study
with secondary
data analysis
JSY MMR reduction
and institutional
deliveries.
Inequalities in
institutional
deliveries
× × ++
11 Gaur A et
al,2015
Journal of Evidence based Medicine and
Healthcare
M.P. retrospective
hospital based,
observational
comparative
study
JSY Perinatal
mortality
× × ++
12. Carvalho N et
al, 2014
PLOS one
34 states and union territories in India
(excluding Nagaland)
Secondary data
analysis
(District Level
Household
Survey (DLHS-
3)
JSY
12–23 months
chldren
37289
Immunization
rate
√
×
++
13 Kaur et al ;
2017
International Journal of Community
Medicine and Public Health
Punjab Secondary data
analysis ( DLHS
, SRS for Punjab)
Institutional
deleveries
Postnatal
women
IMR × × +
ASHA
14 Padda et al INDIAN JOURNAL OF COMMUNITY
HEALTH
Malwa region of Punjab survey ASHA PREGNANT
women
PNMR × × ++
15 Tripathy P et
al,2016
Lancet Glob Health Five rural districts of Jharkhand and
Odisha
RCT ASHA women of
reproductive
age (15–49
years)
PNMR √ √ +++
16 Tripathy P et
al,2016
Lancet Glob Health Five rural districts of Jharkhand and
Odisha
RCT ASHA women of
reproductive
age (15–49
years)
NMR √ √ +++
17 Seth A et al.
2017
International Journal for Equity in Health Secondary data
analysis
ASHA women who
gave birth in
one year
4912 ANC and
Institutional
deliveries
√ √ +++
18 Farah N.
Fathima et al,
2015
BMC J HEALTH POPUL NUTR Karnatka Cross sectional
study
ASHA Mothers and
ASHAs
1800
mothers,
300
ASHAs
Institutional
deliveries
× × ++
19 Gupta M et al,
2017
PLOS One
Haryana Secondary data
analysis
ASHA
Immunization × × ++
20 Wagner AL et
al, 2017
Journal of public health India(21 states) Secondary data
analysis(DLHS)
ASHA 12-23 months
children
Immunization √ √ +++
21 Prinja S et al,
2017
Tropical Medicine and International Health
Community development blocks of
Kaushambi district.
pre- and post-
quasi-
experimental
design
ASHA (m-
health)
12-23 months
3201
Immunization
rate
× × ++
22 Sheila C.
Vir,2014
Food and Nutrition Bulletin
Chhattisgarh
Quasi-
experimental
mixed methods
Mitanin
programme
(Nutritional
Security
Innovation
project)
Under 3 yrs
children
3628
children
under 3
yrs of
age
Nutritional
status, AARR
× × ++
23 Gupta M et al,
2017
BMC Public Health Haryana Mixed method
study
NRHM MCH
plans: ASHA,
JSY, JSSK
MMR × × ++
24 Gupta M et al,
2016
PLOS ONE Haryana Comparative
study of DLHS
2, 3 ,4
NRHM Currently
married women
18,227 MMR × × ++
25 Gupta M et al,
2017
BMC Public Health Haryana Mixed method
study
NRHM MCH
plans: ASHA,
JSY, JSSK
IMR × × +
26 Gupta et al;
2016
PLOS One Haryana Comparative
study of DLHS
2, 3 ,4
NRHM Currently
married women
18,227 ORS, Diarrhoea
uptake in
children
× × +
27 Fathima et al;
2015
Journal of Health, Population, and Nutrition
Karnataka Cross sectional
study
ASHA ASHA 300 Knowledge
regarding CH
practices
× × +
Referral Transport
28 Prinja S et al,
2014
Indian J Med Res Haryana, 3 districts=
Ambala, Hisar, Narnaul
Secondary data
analysis
National
ambulance
system
utilization
116562 Institutional
deliveries
√ √ +++
29 Strehlow M C at
el, 2016
BMJ Open Andhra Pradesh, Assam,
Gujarat, Karnataka and Meghalaya
Prospective
observational
study
free of charge
ambulance
transport
women in third
trimester of
pregnancy
calling with a
‘pregnancy-
1684 Method of
delivery and
Death.
√ √ +++
related’
problem for free
of charge
ambulance
30 Sidney K et al,
2014
PLOS ONE MP cross-sectional
study
JEY( Janani
Express Yojna)
State Run
Public Private
Emergency
Transportation
Service
women who
delivered in
hospital
Utilization of
JEY and ASHA
role
× × ++
Quality Management
31 Agarwal R et al,
2018
BMJ Global Health Haryana cluster
randomised
trial
Quality
management
activities
Pregnant
females
approaching to
PHC
7345 Quality
management
√ √ +++
Immunization
32 Nath B et al,
2007
Indian journal of medical sciences
Urban slums of Lucknow survey
Immunization 12-23 months
Children
510
Full
Immunization
√ √ +++
33 Devasenapathy
N et al, 2016
BMJ Open
Urban poor community in the
Southeast district of Delhi, India
cross-sectional
study
Immunization 1–3.5 years
1849
children
Full
Immunization
√ √ +++
34 Gill N et al,2016
International Journal of Community
Medicine and Public Health
Mumbai
Descriptive
Immunization
1-2 years
210
Full
Immunization
√
× ++
35 Kurane A et al,
2018
International Journal of Contemporary
Pediatrics
Paediatric OPD, immunization clinics
and children admitted in Paediatric
ward in D. Y. Patil hospital, Kolhapur.
Immunization
2-5 years
2000
children
Full
Immunization
× × ++
36 Francis M et al,
2019
Vaccine, Elsevier science direct
Thimiri, a rural administrative
block comprising 67 villages in Vellore
district in Tamil Nadu
cross-sectional
household
survey
Immunization
12–23 months
606
children
Full
Immunization
√ √ +++
37 Goel S et al,
2012
Indian Paediatrics Bihar Observational
study,
Immunization 12-23 months
children
Increase in
proportion of
× × ++
Comparison of
the
immunization
coverage before
and after launch
of campaign
with other
(EAG) states in
the
corresponding
period
immunization
rate
38 Bawankule R et
al, 2017
PLOS one
India
Secondary data
analysis from
NFHS 3
Immunization
12-59 months.
27354
Occurrence of
ARI and
diarrhoea
√ √ +++
39 Prinja et al ;
2010
Bulletin of the World Health Organization
Khizrabad in the Yamunanagar district
of Haryana
Cohort design
Immunization
12-18 months 4336 Immunization
rate
× × ++
NRC
40 SINGH K et al,
2014
INDIAN PEDIATRICS
12 functional NRCs of Uttar
Pradesh.
Review of data
of all children
with SAM
NRC
6-59 months
1181
Recovery rate × × ++
41. Dhanalakshmi
K. et al, 2017
International Journal of Contemporary
Pediatrics
NRC At Vani Vilas children’s Hospital,
attached to Bangalore Medical College
and Research Institute, Bangalore,
Karnataka
retrospective
hospital based
study
NRC
1m to 59 m
736
Recovery rate × × ++
Vitamin A
42 Semba R et
al,2009
The Journal of Nutrition
29 states of India
secondary data
analysis
(NFHS)
Vitamin A Preschool
children(12-59
mo)
4459
children
Under 5
mortality,
Vitamin A
supplementation
√ √ +++
43 Agrawal S et al,
2013
Int J Med Public Health
India
Secondary data
analysis
Vitamin A
12-35 months
20,802
children
Vi t A suppl. √ √ +++
NFHS 3(2005-
2006)
44 Aguayo V et al,
2014
Public Health Nutrition
Seven Indian states
(Bihar,Chhattisgarh,Jharkhand,Madhya
Pradesh,Odisha,Rajasthan, Uttar
Pradesh)with the highest burden of
mortality in children
Analysis of VAS
programme
coverage data,
data from
India’s District
Level
Household
Survey, India’s
Office of the
Registrar
General and
Census
Commissioner
Vitamin A
under 5
children(6–59
months)
VAS Coverage
× × ++
45 Mazumdar et al
; 2015
Lancet
Randomized
control trial
Vitamin A
supplementation
Children upto 6
months of age
44 984 IMR × √ ++
ENC
46 Malhotra S et
al,2014
J HEALTH POPUL NUTR Nagaur district in Rajasthan and
Chhatarpur
district in Madhya Pradesh
Record review Essential new
born care
SBR × × ++
47 Agarwal et al;
2007, India
Journal of Perinatology
India Before-and-
after
intervention
trial
Essential new
born care
Neonates 7938 NMR × × ++
48 Sodani et al;
2011
Indian Journal of Public Health
CHC, Bharatpur district, Rajasthan
Cross sectional
study
Essential new
born care
CHC 13 ENC Practices × × ++
49 Kumar et al;
2016
BMC Pregnancy and Childbirth Rajasthan, India Quasi-
experimental
Essential new
born care
Healthcare
facilities
16 ENC × × ++
50 Gosain et al;
2017
Journal of Tropical Paediatrics
Ballabgarh, Faridabad District,
Haryana
Cross sectional
study
Essential new
born care
Healthcare
facilities
45 ENC, SNCU × × ++
51 Kumaravel
al;2015,
Journal of Evolution of Medicine and
Dental sciences
Dharmapuri district, Tamil Nadu
Descriptive-
retrospective
study
Facility based
new born care
Neonates 2350 NMR × × ++
HBPNC
52
Baquai et al;
2008
Bulletin of the World Health Organization
Uttar Pradesh Quasi
experimental
study
HBPNC
NMR × × ++
53 Sinha et al;2014
Western Pacific Surveillance and Response
Journal
Mewat, Haryana
Cross sectional
study
HBPNC Postnatal
mothers
320 Newborn care
practices
√ × +++
54 Srivastava et al
; 2012
Rural and Remote Health
Thane district of Maharashtra
Cross sectional
study
HBPNC ASHA 150 Knowledge
regarding child
health practices
× × +
55 Karol et al ;
2014
International Journal of Humanities and
Social Science
Rajasthan Cross sectional
study
HBPNC ASHA 200 Knowledge
regarding CH
practices
× × +
56 Pandit at al ;
2016
International Journal of Health Sciences
and Research
Rural area of Maharashtra
Cross sectional
study
HBPNC ASHA 37 Knowledge
regarding CH
practices
× × +
57 Panda et
al;2019
International Journal of Community
Medicine and Public Health
Odisha Cross sectional
study
HBPNC
ASHA 1218 Knowledge
regarding CH
practices
× × +
IMNCI
58 Bhandari et
al;2012
BMJ
Faridabad, Haryana Cluster
randomised
trial.
IMNCI Live births 60 702 NMR √ √ +++
59 Mohan et
al;2011,
Journal of Health, Population and Nutrition
12 districts of India
Mixed methods
study
IMNCI Training of
health workers
BF,
Immunization
√ √ +++
60 Taneja et
al;2015
Journal of Global Health
Faridabad, Haryana Cluster–
randomized
controlled trial
IMNCI Live births 30000 NMR, IMR,
newborn care
practices
× √ ++
61 Som et al;2017
International Journal of Health Sciences &
Research
Odisha
Cross sectional
IMNCI AWWs 381 AWWs
knowledge
× × +
62 Venkatachala J
et al ; 2011
Indian Journal of public health
Panchkula district of Haryana stat
Cohort study
IMNCI HCWs(ANM,
AWW)
85 Knowledge.
Skills of HCWs
× × +
63 Biswas B et al;
2011.
Journal of Tropical Paediatrics
West Bengal Cross sectional
study
IMNCI FLWs 155 Skills of FLWs × × +
64 Chowdhury et
al ; 2017
BMJ
Palwal and Faridabad distr. If Hariyana Secondary data
analysis
IMNCI Infants 60 480 IMR √ √ +++
65 Bora et al;2018
Plos One
India Secondary data
analysis
NFHS 3
IMNCI Neonates NMR × × +
66 Thummakomma
; 2016,
Journal of Evidence Based Medicine and
Healthcare
Kakatiya Medical College, Warangal
Prospective
observational
study
IMNCI Infants 500 IMR × × +
Breastfeeding
67 Phukan et
al;2018
International Breastfeeding Journal
India Secondary data
analysis
BF Postnatal
women
NMR √ √ +++
NHM
68 Narwal et al ;
2013
International Journal of MCH and AIDS
India Secondary data
analysis
NRHM IMR × × +
CPR
69 Ambure et al International Journal of Medical Science
and Public Health
Shimoga, Karnataka Cross sectional females who
had delivered in
the last–36
months
210 Prevalence of
Contraception
and its
association with
postnatal
checkups
× × +
70 Nimavat et al International Journal of Medical Science
and Public Health
Gujarat Cross sectional ASHA incentive
scheme
ASHA workers
of ten talukas
and PHCs
Permanent
sterilization
× × ++
71 Subramanian et
al
Global Health: Science and Practice Bihar Quasi-
experimental
evaluation
PRACHAR
strategies
Contraceptive
usage
√ √ +++
72 Gupta et al Journal of Urban Health: Bulletin of the
New York Academy of Medicine
Chandigarh Cross sectional women in the
age group of
15-49 years
Contraceptive
practices
× × +
73 Speizer et al Journal of Urban Health: Bulletin of the
New York Academy of Medicine
Six districts of UP Cross sectional NRHM and
Urban health
Initiative funded
by BMGF
women in the
age group of
15-49 years
17643 Contraceptive
practices
× × ++
74 Prateek et al African Health Sciences Urban health centre in South India Cross sectional Married women
in reproductive
age group (15-
49years)
180 Awareness,
practice and
reasons of
adoption and
non-adoption
46of
co47ntraception
× × +
75 Shaheen
Rahman
International Journal of Scientific Study Guwahati Cross sectional Cu-T currently
married women
260 Cu-T utilization
stateu
× × ++
76 NIRANKAR
SINGH
The Journal of Family Welfare Patiala, Punjab Cross sectional Married women
in the age
group of 15-
49years
1123 Contraception
usage
× × +
77 Chandrasekhar
et al.
Journal of Young Pharmacists Kerala Quasi
experimental
Saheli program women in age
group of 15-45
years
140 Knowledge
about family
planning, child
care and
maternal health
× × +
78 Mcdougal et al PLOS One Bihar Quasi
experimental
Ananya
program
married women
15-49 years
with 0-5 months
old child
Bseline-
7191
and
follow
up-6143
Improvement in
postpartum
contraceptive
use
√ √ +++
ARSH
79 Nair & 2013 Indian J Pediatr Kerala Cross sectional ARSH Adolescents
and young
adults (10-24
years)
4223 Knowledge
about Menstrual
hygiene
practices,
knowledge
attitude and
practices of 10-
2 age group
regarding RSH
issues
++
80 Nair & 2013 Indian J Pediatr Kerala Cross sectional ARSH Adolescents
and young
adults (10-24
years)
4220 Knowledge
about
contraceptive
measures, ideal
age of
pregnancy and
other RSH
indicators
++
81 Gupta 2015 Indian Journal of Public Health Chandigarh Cross sectional ARSH Adolescent age
group(10-19
years)
854 Knowledge
about ARSH
and access to
the ARSH
clinics
++
RBSK
82 Tiwari J et al,
2015
International Journal of Community
Medicine and Public Health
Panna Distt Madhya Pradesh
Cross sectional
survey
RBSK Children up to
18 years
26977 Early diagnosis
and screening
× × +
83 Balat M et al,
2018
International Journal of Community
Medicine and Public Health
Ahmedabad Cross sectional
survey
RBSK Children up to 3
years
169 Early diagnosis
and screening
× × +
WIFS
84 Vir 2008 SAGE Journal Food and Nutrition Bulletin UP Community
based
intervention
study
WIFS Adolescents
10-19 years
150700 Reduction in
anaemia
× × ++
85 Dongre 2011 SAGE Journal Food and Nutrition Bulletin Wardha, Maharashtra participatory
action research
IFA prophylaxis
for 100 days in
a year through
community
participation
Adolescent girls
12-19 years
249 Reduction in
nutritional
anaemia
× × ++
Menstrual Hygiene
86 Shah et al 2013 ELSEVIER Reproductive Health Matters Gujarat cross sectional Adolescents
girls
164 Awareness
about menstrual
hygiene
practices
× × +
87 Sivakami et al
2019
Journal of Global Health Maharashtra, Chhatisgarh, Tamilnadu cross sectional Adolescent girls
above 12 years
of age
2564 Knowledge
about menstrual
hygiene
× × +
Health Inequalities
88 Gupta M et al,
2017
PLOS one Ambala and Mewat Districts of
Haryana
Qualitative
study
NRHM (MCH
plans)
Program
officers,
community
representatives,
mothers, health
service
providers
72 Maternal and
child health
inequalities
× × +
89 Vellakkal S et
al, 2017
Health Policy and Planning, Oxford 8 EAG and 7 North-east states quasi-natural
experiment
study design
using data from
DLHS1, 2, 3, 4
and AHS
NRHM Married women socioeconomic
inequities in the
uptake of
institutional
delivery and
antenatal care
(ANC)
√ ++
90 Seth A. et al,
2017
International Journal for Equity in Health Uttar Pradesh Survey ASHA Women who
gave birth in
last 12 months
4912 Social inequities
and health
disparities.
√ √ +++
91 Gupta M. et al,
2016
PLOS One Haryana Secondary
analysis of
DLHS data
NRHM Currently
married women
18227 Geographical,
socioeconomic,
and gender
inequality in
MCH pre and
post NRHM
× × +
92 Gupta M et al,
2017
BMC public health Haryana Explanatory
sequential
mixed methods
study
NRHM Currently
married women
and Health
workers, health
managers
MCH
inequalities
× × +
93 Bhatia M et al,
2018
SSM - Population Health ELSEVIER India NFHS data
analysis
child health
inequalities
× × +
94 Patel P et al,
2018
Reproductive Health Matters Purnia district, Bihar Qualitative
study
NRHM= ASHA,
JSY , JSSK,
ANM
SC caste
women
18 Utilization × × +
95 Randive B, et al
2014
ELSEVIER, Social Science and Medicine Rajasthan, Madhya Pradesh,
Chhattisgarh, Bihar, Jharkhand, Uttar
Pradesh, Uttarakhand, Orissa and
Assam
Ecological
study,
secondary
analysis of data
(DLHS3)
JSY JSY
beneficiaries
Inequalities in
institutional
deliveries and
maternal
mortality
× × +
Secondary
data analysis
96 Rammohan et
al;2013
Plos One
India secondary
analysis of data
(DLHS3
NMR × √ ++
97 Jha P et al,
2017
Lancet
India Secondary data
analysis
Comparison of
NFHS 3 Data
with NFHS 4
U5MR × × +
98 Jha P et al,
2017
Lancet
India Secondary data
analysis
NMR
× × +
Comparison of
NFHS 3 Data
with NFHS 4
ANNEXURE 7. MATERNAL HEALTH INDICATORS OF WOMEN AGED 15 -49 YEARS WHO
HAD A LIVE BIRTH IN THE FIVE YEARS PRECEDING THE SURVEY.
Maternal Health Pre NHM (%) Post NHM
#
(%)
Adjusted Odds
Ratio
95%
Confidence
Interval
p-value
Adequate ANC Care 50.2 86.3 6.3 (5.837, 6.648)
<0.01*
Three ANC Check ups 52.4 55.3 1.1 (1.072, 1.177)
<0.01*
Anaemia During
Pregnancy
58.7 54.6 0.9 (0.765, 0.936)
<0.01*
100 Iron Folic Acid 15.6 18.8 1.3 (1.195, 1.318)
<0.01*
Breastfeeding within
one hour
24.5 41.8 2.2 (2.115, 2.310)
<0.01*
Tetanus Toxoid
Injection
82.6 92.7 2.7 (2.524, 2.800)
<0.01*
*Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for place of residence, maternal
age, education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health
worker density, road density, telephone-density.
Proportion of women for various maternal health indicators in 2005 and 2015.
50.2
52.4
58.7
15.6
24.5
82.6
86.3
55.3 54.6
18.8
41.8
92.7
0
10
20
30
40
50
60
70
80
90
100
Adequate
ANC Care
Three ANC
Check ups
Anemia
During
Pregnancy
100 Iron Folic
Acid
Breastfeeding
within one
hour
Tetanus
Toxoid
Injection
Percentage (%)
20052015
ANNEXURE 8. CONTRACEPTIVE METHODS CURRENTLY USED FOR FAMILY PLANNING
BY MARRIED WOMEN AGED 15 -49 YEARS.
Family Planning Pre NHM (%) Post NHM
#
(%)
Adjusted Odds
Ratio
95% Confidence
Interval
p-value
Female Sterilization 37.3 44.2 1.3 (1.293, 1.370)
<0.01*
Male Sterilization 0.1 0.2 0.2 (0.167, 0.241)
<0.01*
Condom 5.2 3.9 0.7 (0.710, 0.778)
<0.01*
Contraceptive Pills 3.1 5.3 1.7 (1.616, 1.857)
<0.01*
Inter Uterine Device 1.7 0.8 0.5 (0.444, 0.519)
<0.01*
* Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for place of residence,
maternal age, education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply,
cooking fuel, health worker density, road density, Telephone-density.
Proportion of women by contraceptive methods used for family planning in 2005 and 2015
37.3
1.0
5.2
3.1
1.7
44.2
0.2
3.9
5.3
0.8
0
10
20
30
40
50
Female
Sterilization
Male
Sterilization
CondomContraceptive
Pills
Intra Uterine
Devices
Percentage (%)
20052015
ANNEXURE 9. IMMUNIZATION OF CHILDREN AGED 12 -23 MONTHS WHO RECEIVED
SPECIFIC VACCINES AT ANY TIME BEFORE THE SURVEY.
Child Health Indicators Pre NHM (%) Post NHM
#
(%)
Adjusted
Odds Ratio
95% Confidence
Interval
p-value
BCG 78.4 90.9 2.8 (2.435, 3.125)
<0.01*
DPT1 76.3 88.6 2.5 (2.152, 2.690)
<0.01*
DPT3 55.8 77.5 2.7 (2.484, 2.985)
<0.01*
Measles 60.0 79.8 2.6 (2.391, 2.897)
<0.01*
Vitamin A1 50.8 76.8 3.3 (2.932, 3.510)
<0.01*
* Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for institutional
delivery, place of residence, maternal age, education, religion, caste, wealth index, type of housing, availability of
toilet, safe water supply, cooking fuel, health worker density, road density, telephone- density.
Percentage of children aged 12-23 months who received specific vaccines at any time before the
survey
78.4
76.3
55.8
60.0
50.8
90.9
88.6
77.5
79.8
76.8
0.0
20.0
40.0
60.0
80.0
100.0
BCG DPT1 DPT3 MeaslesVitamin A1
Percentage (%)
20052015
ANNEXURE 10. CHILD HEALTH INDICATORS OF CHILDREN UNDER 5 YEARS OF AGE IN
2 WEEKS PRECEDING THE SURVEY.
Child Health Pre NHM (%) Post NHM
#
(%)
Adjusted
Odds Ratio
95% Confidence
Interval
p-value
Diarrhoea Treatment 60.4 62.7 1.1 (0.974, 1.248) 0.122
Number of days after
Diarrhoea Treatment
1.5 1.3 0.9 (0.774, 0.889)
<0.01*
Family Size 2.5 2.2 0.9 (0.881, 0.895)
<0.01*
* Significant;
#
adjusted percentage of NFHS4; Source: NFHS data round 3 and 4; adjusted for place of residence, maternal age,
education, religion, caste, wealth index, type of housing, availability of toilet, safe water supply, cooking fuel, health worker density,
road density, telephone-density.
Proportion of children under age 5 years in 2005 and 2015
Proportion of children under 5 years of age in 2005 and 2015
60.462.7
0
20
40
60
80
20052015
Percentage (%)
Seek Treatment or Advice for Diarrhoea
1.5
2.5
1.3
2.2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Days after DiarrhoeaFamily Size
Mean Value
2005 2015
ANNEXURE 11: THE ITS ESTIMATES OF PRE SLOPE, POST SLOPE AND CHANGE AT
STATE AND NATIONAL LEVEL
State Pre-
Slope
Post-
Slope
Change P-
Value
LCI UCI Remark
India -1.6 -2.2 -0.7 0.058 -1.41 0.033744 Significant
Andhra
Pradesh
-1.0 -2.2 -1.2 0.068 -2.49 0.11 Significant
Assam -0.9 -2.5 -1.6 0.007 -2.72 -0.47 Significant
Bihar -1.0 -1.4 -0.4 0.472 -1.47 0.71 Non-
Significant
Delhi -0.5 -2.2 -1.7 0.122 -3.98 0.53 Non-
Significant
Gujrat -1.1 -2.3 -1.3 0.045 -2.55 -0.016 Significant
Haryana -1.0 -2.5 -1.6 0.017 -2.84 -0.30 Significant
Karnataka -1.5 -2.3 -0.8 0.328 -2.49 0.89 Non-
Significant
Kerala -0.2 -0.4 -0.2 0.633 -0.87 0.54 Non-
Significant
Madhya
Pradesh
-2.4 -2.4 -0.1 0.811 -0.80 0.64 Non-
Significant
Maharashtra -1.5 -1.4 0.1 0.745 -0.77 1.05 Non-
Significant
Orissa -2.9 -2.7 0.2 0.757 -1.29 1.74 Non-
Significant
Punjab -1.0 -2.3 -1.3 0.019 -2.44 -0.22 Significant
Rajasthan -1.3 -2.6 -1.3 0.191 -3.26 0.71 Non-
Significant
Tamil Nadu -1.6 -1.5 0.2 0.827 -1.359 1.68 Non-
Significant
Uttar
Pradesh
-1.8 -3.1 -1.2 0.021 -2.30 -0.20 Significant
West
Bengal
-1.8 -1.2 0.6 0.191 -0.35 1.60 Non-
Significant
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