Publications

Background: Eliminating unmet need for family planning by 2030 is a global priority for ensuring healthy lives and promoting well-being for all at all ages. We estimate the sub-national trends in prevalence of unmet need for family planning over 30 years in India and study diferences based on socio-economic and demographic factors.

Methods: We used data from fve National Family Health Surveys (NFHS) conducted between 1993 to 2021 for the 36 states/Union Territories (UTs) of India. The study population included women of ages 15–49 years who were married or in a union at the time of the survey. The outcome was unmet need for family planning which captures the prevalence of fecund and sexually active women not using contraception, who want to delay or limit childbearing. We calculated the standardized absolute change to estimate the change in prevalence on an annual basis across all states/ UTs. We examined the patterning of prevalence of across demographic and socioeconomic characteristics and estimated the headcount of women with unmet need in 2021.

Results: The prevalence of unmet need in India decreased from 20·6% (95% CI: 20·1– 21·2%) in 1993, to 9·4% (95% CI: 9·3–9·6%) in 2021. Median unmet need prevalence across states/UTs decreased from 17·80% in 1993 to 8·95% in 2021. The north-eastern states of Meghalaya (26·9%, 95% CI: 25·3–28·6%) and Mizoram (18·9%, 95% CI: 17·2–20·6%), followed by the northern states of Bihar (13·6%, 95% CI: 13·1–14·1%) and Uttar Pradesh (12·9%, 95% CI: 12·5–13·2%), had the highest unmet need prevalence in 2021. As of 2021, the estimated number of women with an unmet need for family planning was 24,194,428. Uttar Pradesh, Bihar, Maharashtra, and West Bengal accounted for half of this headcount. Women of ages 15–19 and those belonging the poorest wealth quintile had a relatively high prevalence of unmet need in 2021.

Conclusions: The existing initiatives under the National Family Planning Programme should be strengthened, and new policies should be developed with a focus on states/UTs with high prevalence, to ensure unmet need for family planning is eliminated by 2030. 

Achieving India's 2030 SDG goals will require strong and sustained political support and accountability - not just at the national level, but also at the level of the 543 parliamentary constituencies with elected representatives. Creating a robust constituency-level data surveillance and monitoring system for the health and well-being of their populations will be critical for enabling the political synergy and accountability needed to accomplish India's SDGs.

Importance  
The introduction of solid or semisolid foods alongside breast milk plays a vital role in meeting nutritional requirements during early childhood, which is crucial for child growth and development. Understanding the prevalence of zero-food children (defined for research purposes as children aged 6 to 23 months who did not consume animal milk, formula, or solid or semisolid food during the last 24 hours) is essential for targeted interventions to improve feeding practices.

Objective  
To estimate the percentage of zero-food children in 92 low- and middle-income countries.

Design, Setting, and Participants  
This cross-sectional study analyzed nationally representative cross-sectional household data of children aged 6 to 23 months from the Demographic and Health Surveys and the Multiple Indicator Cluster Surveys conducted between May 20, 2010, and January 27, 2022. Data were obtained from 92 low- and middle-income countries. Standardized procedures were followed to ensure data comparability and reliability. Both percentage and number of zero-food children were estimated.

Main Outcomes and Measures  
The outcome studied was defined as a binary variable indicating children aged 6 to 23 months who had not been fed any animal milk, formula, or solid or semisolid foods during the 24 hours before each survey, as reported by the mother or caretaker.

Results  
A sample of 276 379 children aged 6 to 23 months (mean age, 14.2 months [95% CI, 14.15-14.26 months]) in 92 low- and middle-income countries was obtained, of whom 51.4% (95% CI, 51.1%-51.8%) were boys. The estimated percentage of zero-food children was 10.4% (95% CI, 10.1%-10.7%) in the pooled sample, ranging from 0.1% (95% CI, 0%-0.6%) in Costa Rica to 21.8% (95% CI, 19.3%-24.4%) in Guinea. The prevalence of zero-food children was particularly high in West and Central Africa, where the overall prevalence was 10.5% (95% CI, 10.1%-11.0%), and in India, where the prevalence was 19.3% (95% CI, 18.9%-19.8%). India accounted for almost half of zero-food children in this study.

Conclusions and Relevance  
In this cross-sectional study of 276 379 children aged 6 to 23 months, substantial disparities in the estimates of food consumption across 92 low- and middle-income countries were found. The prevalence of zero-food children underscores the need for targeted interventions to improve infant and young child feeding practices and ensure optimal nutrition during this critical period of development. The issue is particularly urgent in West and Central Africa and India.

Abstract

We evaluate the impact of oral polio vaccines on the incidence of all disabilities (locomotor, hearing, visual, speech, and mental) in India, focusing on polio-related disability, which constitutes the largest fraction of locomotor disabilities. Polio was hyperendemic in India even as recently as the early 1990s, but the country was declared wild polio virus-free in 2014. Intent-to-treat effects from difference-in-differences with multiple time period models that condition on demographic and socio-economic characteristics reveal that access to oral polio vaccines in the year of birth reduced the incidence of any disability, locomotor disability, and polio-related disability by 20.5%, 11.6%, and 7.2%, respectively, signaling substantial gains. Impacts on any disability underline that polio vaccines had positive spillover effects on other disability categories as well. The eradication of polio in India, while relatively late, brought significant health benefits and is a notable health economics success story in a developing context.

Background

India's success in eliminating child marriage is crucial to the achievement of the Sustainable Development Goal target 5.3. We aimed to estimate the prevalence of child marriage in girls and boys in India and describe its change across 36 states and Union Territories between 1993 and 2021.

Methods

For this cross-sectional study, data from five National Family Health Surveys from 1993, 1999, 2006, 2016, and 2021 were used. The study included 310 721 women aged 20–24 years between 1993 and 2021 and 43 436 men aged 20–24 years between 2006 and 2021. Child marriage was defined as marriage in individuals younger than 18 years for men and women. We calculated the annual change in prevalence during the study period for states and Union Territories and estimated the population headcount of child brides and grooms.

Findings

Child marriage declined during 1993 to 2021. The all-India prevalence of child marriage in girls declined from 49·4% (95% CI 48·1–50·8) in 1993 to 22·3% (21·9–22·7) in 2021. Child marriage in boys declined from 7·1% (6·9–30·8) in 2006 to 2·2% (1·8–2·7) in 2021. The largest decreases in child marriage occurred between 2006 and 2016. Between 2016 and 2021, a few states and Union Territories saw an increase in prevalence of child marriage in girls (n=6) and boys (n=8) despite declines in the all-India prevalence. In 2021, 13 464 450 women aged 20–24 years and 1 454 894 men aged 20–24 years were estimated to be married as children.

Interpretation

One in five girls and nearly one in six boys are still married below the legal age of marriage in India. There remains an urgent need for strengthened national and state-level policy to eliminate child marriage by 2030.

 

Introduction 
‘Zero-dose’ children (infants who fail to receive the first dose of diphtheria-tetanus-pertussis-containing vaccine) face substantial adversity in early childhood and may be at risk of failure to thrive. To inform a new global policy, we studied the relationship between zero-dose vaccination status in early childhood and learning attainment in preadolescence, and considered whether community socioeconomic development moderated these relationships.

Methods 
We constructed a population cohort from the 2019 India Human Development Survey panel dataset to study the comparative performance of zero-dose versus vaccinated children identified in wave I (2004–2005) on basic learning tests at ages 8–11 in wave II (2011–2012). The outcome was a sum of reading, writing and math scores ranging from 0 (no knowledge) to 8. We fit three linear regression models examining whether child zero-dose status predicts learning attainment: a crude model, a main effects model including all prespecified covariates, and a model including an interaction between child zero-dose status and community development level.

Results 
The analytic sample included 3781 children from 3781 households in 1699 communities, representing 18.2 million children. Predicted learning attainment scores for zero-dose children were lower than those for vaccinated children by −1.698 (95% CI −2.02 to −1.37; p<0.001) points (crude model) and −0.477 (95% CI −0.78 to −0.18; p<0.001) points (adjusted for all prespecified covariates). We found strong evidence of effect modification. The model including all prespecified correlates and an interaction predicted no effect of child zero-dose status in urban areas (p=0.830) or more developed rural villages (p=0.279), but an important effect in the least developed rural villages, where zero-dose children were expected to have test scores −0.750 (95% CI −1.15 to −0.344; p<0.001) points lower than vaccinated children.

Conclusion 
Zero-dose children living in contexts of very low socioeconomic development are at elevated risk of poor learning attainment in preadolescence.

Due to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM_2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM_2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM_2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM_2.5 levels corresponding to 0.127 μg/m³ (95% CI 0.062 μg/m³, 0.192 μg/m³) and 0.199 μg/m³ (95% CI 0.116 μg/m³, 0.283 μg/m³, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM_2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM_2.5 levels and different SES parameters.

Objectives With an aging population, India is facing a growing burden of cardiovascular diseases (CVDs). Existing programs on CVD risk factors are mostly based on state and district data, which overlook health disparities within macro units. This study quantifies and geovisualises the extent of small area variability within districts in CVD risk factors (hypertension, diabetes, and obesity) in India.

Design, Settings, and Participants This cross-sectional study analyzed nationally representative data from the National Family Health Survey 2019-2021, encompassing individuals aged 15 years or older, for hypertension (n = 1 715 895), diabetes (n = 1 807 566), and obesity (n = 776 023). Data analyses were conducted from July 1, 2022, through August 1, 2023.

Results The final analytic sample consisted of 1 71,5 895 individuals analyzed for hypertension, 1 80,7 566 for diabetes, and 776 ,023 for obesity.  Overall, 21.2% of female and 24.1% of male participants had hypertension, 5.0% of female and 5.4% of men had diabetes, and 6.3% of female and 4.0% of male participants had obesity. For female participants, small areas (32.0% for diabetes, 34.5% for obesity, and 56.2% for hypertension) and states (30.0% for hypertension, 46.6% for obesity, and 52.8% for diabetes) accounted for the majority of the total geographic variability, while districts accounted for the least (13.8% for hypertension, 15.2% for diabetes, and 18.9% for obesity). There were moderate to strong positive correlations between district-wide mean and within-district variability (r = 0.66 for hypertension, 0.94 for obesity, and 0.96 for diabetes). For hypertension, a significant discordance between district-wide mean and within-district small area variability was found. Results were largely similar for male participants across all categories.

Conclusion and Relevance This cross-sectional study found a substantial small area variability, suggesting the necessity of precise policy attention specifically to small areas in program formulation and intervention to prevent and manage CVD risk factors. Targeted action on policy-priority districts with high prevalence and substantial inequality is required for accelerating India’s efforts to reduce the burden of noncommunicable diseases.

This comment examines the performance and status of Schedule Tribes (STs) in India across 129 population health and welfare indicators from 2016 to 2021. While progress has been made in areas such as improved sanitation facilities and full vaccination among children aged 12-23 months, STs continue to lag Non-STs on a majority of indicators in 2021. A timely and sustained policy focus on these underperforming indicators is critical for India to meet its SDG targets for Indigenous Communities. 

Background

Ensuring universal access to safe sanitation by 2030 is a development priority for India. Doing so can help ensure improved physical and mental health outcomes. While the proportion of people in India with safe sanitation has risen dramatically over the past thirty years, much less is known about who has been most at risk for not having access to safe sanitation across India’s states and Union Territories (UT) over this time period. We introduce the concept of zero-sanitation to fill this gap.

Methods

Data from five National Family Health Surveys (NFHS) conducted in 1993, 1999, 2006, 2016, and 2021 from 36 states and UT were used for this study. The study population consisted for all household individuals regardless of age in each survey round. Zero-sanitation was defined as those who have no access to a household toilet, and thus defecate in the open. We analyzed the percent prevalence of zero-sanitation in every state / UT at each time period in both urban and rural communities, as well as the population headcount burden in 2021. We calculated the absolute change on an annual basis to assess the change in percentage points of zero-sanitation across time periods at the all-India and state / UT levels.

Results

The all-India prevalence of zero-sanitation declined from 70.3% (95% confidence interval (CI) = 70.2%-70.5%) in 1993 to 17.8% (95% CI = 17.7%-17.9%) in 2021. The median percent prevalence of zero-sanitation across states and UTs was 65.9% in 1993. By 2021, the median percent prevalence of zero-sanitation across states and UTs was 5.7%. This reduction corresponded with a reduction in the between state / UT inequality in zero-sanitation. Nevertheless, as of 2021, the prevalence of zero-sanitation was still above 20% in Bihar, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, and Uttar Pradesh. Additionally, as of 2021, almost 92% of individuals who were defecating in the open were experiencing zero-sanitation. Zero-sanitation remains most common in states such as Bihar, Punjab, Uttar Pradesh, and Assam. Nevertheless, at this current rate of improvement, every state and UT except for Sikkim and Chandigarh are on track to end open defecation by 2030.

Conclusions

The concept of zero-sanitation is a useful tool in helping policy makers assess the extent to which sanitation coverage remains incomplete. When viewed through this lens, we see that open defecation remains most common among those who do not have a toilet. Addressing the myriad social determinants of sanitation access can help fill these gaps and ensure equitable sanitation coverage throughout India.

Wealth inequality in anthropometric failure is a persistent concern for policymakers in India. This necessitates a comprehensive analysis and identification of various risk factors that can explain the poor-rich gap in anthropometric failure among children in India. We analyze the fifth and fourth rounds of the Indian National Family Health Survey collected from June 2019 to April 2021 and January 2015 to December 2016, respectively. Two samples of children aged 0–59 and 6–23 months old with singleton birth, alive at the time of the survey with non-pregnant mothers, and with valid data on stunting, severe stunting, underweight, severely underweight, wasting, and severe wasting are included in the analytical samples from both rounds.

We estimate the wealth gradients and distribution of wealth among children with anthropometric failure. Wealth gap in anthropometric failure is identified using logistic regression analysis. The contribution of risk factors in explaining the poor-rich gap in AF is estimated by the multivariate decomposition analysis. We observe a negative wealth gradient for each measure of anthropometric failure. Wealth distributions indicate that at least 60% of the population burden of anthropometric failure is among the poor and poorest wealth groups.

Even among children with similar modifiable risk factors, children from poor and poorest backgrounds have a higher prevalence of anthropometric failure compared to children from the richest backgrounds.

Maternal BMI, exposure to mass media, and access to sanitary facility are the most significant risk factors that explain the poor-rich gap in anthropometric failure. This evidence suggests that the burden of anthropometric failure and its risk factors are unevenly distributed in India.

The policy interventions focusing on maternal and child health, implemented with a targeted approach prioritizing the vulnerable groups, can only partially bridge the poor-rich gap in anthropometric failure. The role of anti-poverty programs and growth is essential to narrow this gap in anthropometric failure.

In this paper, we use the nationally representative Time Use Survey (TUS) data from India to estimate the proportion of people that spend any time of the day exercising. We found that overall, less than 7% of the adult population (age ≥18 Years) spent any time of the day exercising. Our estimates also revealed that the proportion of population exercising varied across states, by rural and urban sectors, and by social and religious groups. We also estimated logistic regressions to model the probability of people exercising. We found that males had three times higher odds of exercising than females. Relative to less educated people (primary school and below), those with educational level of graduate and above had almost 2.5 times higher odds of exercising. People in the higher strata of consumption class, the top 10%, had 1.7 times higher odds of exercising relative to the bottom 50%. From a public policy perspective, the low level of exercise across all geographies and social, economic, and demographic characteristics indicates the need for population-wide interventions in India to encourage exercise.

Background
The extent of food deprivation and insecurity among infants and young children—a critical phase for children's current and future health and well-being—in India is unknown. We estimate the prevalence of food deprivation among infants and young children in India and describe its evolution over time at sub-national levels.

Methods
Data from five National Family Health Surveys (NFHS) conducted in 1993, 1999, 2006, 2016 and 2021 for the 36 states/Union Territories (UTs) of India were used. The study population consisted of the most recent children (6–23 months) born to mothers (aged 15–49 years), who were alive and living with the mother at the time of survey (n = 175,614 after excluding observations that had no responses to the food question). Food deprivation was defined based on the mother's reporting of the child having not eaten any food of substantial calorific content (i.e., any solid/semi-solid/soft/mushy food types, infant formula and powdered/tinned/fresh milk) in the past 24 hours (h), which we labelled as “Zero-Food”. In this study, we analyzed Zero-Food in terms of percent prevalence as well as population headcount burden. We calculated the Absolute Change (AC) to quantify the change in the percentage points of Zero-Food across time periods for all-India and by states/UTs.

Findings
The prevalence of Zero-Food in India marginally declined from 20.0% (95% CI: 19.3%–20.7%) in 1993 to 17.8% (95% CI: 17.5%–18.1%) in 2021. There were considerable differences in the trajectories of change in the prevalence of Zero-Food across states. Chhattisgarh, Mizoram, and Jammu and Kashmir experienced high increase in the prevalence of Zero-Food over this time period, while Nagaland, Odisha, Rajasthan and Madhya Pradesh witnessed a significant decline. In 2021, Uttar Pradesh (27.4%), Chhattisgarh (24.6%), Jharkhand (21%), Rajasthan (19.8%) and Assam (19.4%) were states with the highest prevalence of Zero-Food. As of 2021, the estimated number of Zero-Food children in India was 5,998,138, with the states of Uttar Pradesh (28.4%), Bihar (14.2%), Maharashtra (7.1%), Rajasthan (6.5%), and Madhya Pradesh (6%) accounting for nearly two-thirds of the total Zero-Food children in India. Zero-Food in 2021 was concerningly high among children aged 6–11 months (30.6%) and substantial even among children aged 18–23 months (8.5%). Overall, socioeconomically advantaged groups had lower prevalence of Zero-Food than disadvantaged groups.

Interpretation
Concerted efforts at the national and state levels are required to further strengthen existing policies, and design and develop new ones to provide affordable food to children in a timely and equitable manner to ensure food security among infants and young children.

Introduction
The COVID-19 pandemic and subsequent national lockdowns in many countries disrupted access to basic services.¹ Several welfare programs were put in place, even in resource-limited settings, to mitigate the socioeconomic and health consequences.² To assess the overall implication of COVID-19 for population health, data ideally should be collected immediately before and after the outbreak. We used the 2019 to 2021 National Family Health Survey (NFHS)³ in India, a country with the second-highest number of COVID-19 cases and the third-highest death tolls in the world as of January 2023,⁴ to examine the systematic differences in various child health outcomes before vs after the outbreak.

Methods
The cross-sectional data of the 2019 to 2021 NFHS provided a unique opportunity to perform an empirical assessment, as the data were collected both before and after March 2020, when the national lockdown was declared in 13 of the 36 states or Union Territories in India, facilitating a natural comparison in health outcomes. For this cross-sectional study, data collected from June 17, 2019, to February 29, 2020, were defined as before COVID-19 and those from March 1, 2020, to May 20, 2021, were defined as after COVID-19. Further details on the survey design are available elsewhere.³ The Harvard Longwood Campus Institutional Review Board deemed this study exempt from ethics review because it was a secondary use of anonymized information. This study followed the STROBE reporting guideline.

Child health outcomes with a short reference period and deemed most likely to be affected by disruptions in health services were selected (Table 1). Twenty-six indicators related to pregnancy and child health and health care, feeding and nutrition, anthropometric failures, and vaccination were included. Absolute differences (in percentage points) were calculated by comparing the prevalence of outcomes before vs after the outbreak (eg, prevalence [stunting] after COVID-19 − prevalence [stunting] before COVID-19).

Statistical significance was determined using logistic regression models adjusted for child age, sex, and state fixed effects. To account for the multistage, stratified cluster-sampling design, survey weights were applied to all statistical analyses. Two-sided P = .05 indicated statistical significance. Analyses were performed between October 2022 and January 2023, using Stata 17 (StataCorp LLC).

Results
The sample size for the most complete outcome was 125 812 (65 574 boys [52.1%], 60 238 girls [47.9%]; mean [SD] age, 30.0 [17.6] months) (Table 1). Compared with before-COVID-19 data, after-COVID-19 data showed small but significant deterioration in neonatal mortality (0.49 percentage points), feeding and nutrition (eg, 4.22 percentage points reduction in solid or semisolid food intake), and anthropometric failures (eg, 1.87 percentage points increase in underweight) (Table 2). The most substantial difference was found in vaccination indicators, with 7.74 percentage points and 6.51 percentage points reduction in first dose of DPT (diphtheria, pertussis, tetanus) and polio, respectively. Other indicators, including many related to health services, either remained constant or marginally improved during the outbreak.

Discussion
Mixed results from this analysis suggested that adverse consequences of COVID-19 and national lockdown were countered, to some extent, by emergency relief programs. For example, the Indian government launched Pradhan Mantri Garib Kalyan Ann Yojana in 2020 to distribute 5 kg of food grains and 1 kg of pulses per month to approximately 800 million individuals (approximately two-thirds of India’s population).⁵ This initiative may explain the relatively constant or minimally worsened patterns in child nutrition status before and after the outbreak. It also underscored the need to sustain relief programs in nonpandemic times to promote children’s health. Improvements in child health outcomes, such as diarrhea and acute respiratory infection rates, may be attributed to the wider promotion of interpersonal hygiene during the pandemic.⁶

Study limitations included the cross-sectional design, which prohibited any causal inferences from being drawn, and the inability to distinguish COVID-19’s implications from those of longer-term exposures to harmful conditions. Nevertheless, the results showed that nationally representative surveys, even with COVID-19-related disruptions in data collection, can aid in understanding the pandemic’s outcome.

The Multicentre Growth Reference Study (MGRS) currently serves as a universal standard to assess stunting, wasting and underweight prevalence in children as a means to develop international and country-specific targets for reducing child undernutrition. However, height-based anthropometric measures are highly sensitive to the choice of growth reference charts.

Our recent NFHS-5 analysis of 211,164 children in India uses the Indian Urban Middle Class (IUMC) reference instead, and reveals a significantly lower prevalence of stunting and wasting in India compared to MGRS. In order to achieve its target SDG goals in the next 8 years, India should give careful consideration to the most realistic and appropriate reference for setting national targets around child undernutrition, to ensure that effort and resources are being directed to the children in the most need.

Background

India has committed itself to accomplishing the Sustainable Development Goals (SDGs) by 2030. Meeting these goals would require prioritizing and targeting specific areas within India. We provide a mid-line assessment of the progress across 707 districts of India for 33 SDG indicators related to health and social determinants of health.

Methods

We used data collected on children and adults from two rounds of the National Family Health Survey (NFHS) conducted in 2016 and 2021. We identified 33 indicators that cover 9 of the 17 official SDGs. We used the goals and targets outlined by the Global Indicator Framework, Government of India and World Health Organization (WHO) to determine SDG targets to be met by 2030. Using precision-weighted multilevel models, we estimated district mean for 2016 and 2021, and using these values, computed the Annual Absolute Change (AAC) for each indicator. Using the AAC and targets, we classified India and each district as: Achieved-I, Achieved-II, On-Target and Off-Target. Further, when a district was Off-Target on a given indicator, we further identified the calendar year in which the target will be met post-2030.

Findings

India is not On-Target for 19 of the 33 SDGs indicators. The critical Off-Target indicators include Access to Basic Services, Wasting and Overweight Children, Anaemia, Child Marriage, Partner Violence, Tobacco Use, and Modern Contraceptive Use. For these indicators, more than 75% of the districts were Off-Target. Because of a worsening trend observed between 2016 and 2021, and assuming no course correction occurs, many districts will never meet the targets on the SDGs even well after 2030. These Off-Target districts are concentrated in the states of Madhya Pradesh, Chhattisgarh, Jharkhand, Bihar, and Odisha. Finally, it does not appear that Aspirational Districts, on average, are performing better in meeting the SDG targets than other districts on majority of the indicators.

Interpretation

A mid-line assessment of districts' progress on SDGs suggests an urgent need to increase the pace and momentum on four SDG goals: No Poverty (SDG 1), Zero Hunger (SDG 2), Good Health and Well-Being (SDG 3) and Gender Equality (SDG 5). Developing a strategic roadmap at this time will help India ensure success with regards to meeting the SDGs. India's emergence and sustenance as a leading economic power depends on meeting some of the more basic health and social determinants of health-related SDGs in an immediate and equitable manner.

Importance  
Children who do not receive any routine vaccinations (ie, who have 0-dose status) are at elevated risk of death, morbidity, and socioeconomic vulnerabilities that limit their development over the life course. India has the world’s highest number of children with 0-dose status; analysis of national and subnational patterns is the first important step to addressing this problem.

Objectives  
To examine the patterns among children with 0-dose immunization status across all 36 states and union territories (UTs) in India over 29 years, from 1993 to 2021, and to elucidate the relative share of multiple geographic regions in the total geographic variation in 0-dose immunization.

Design, Setting, and Participants 
This repeated cross-sectional study analyzed all 5 rounds of India’s National Family Health Survey (1992-1993, 1998-1999, 2005-2006, 2015-2016, and 2019-2021) to compare the prevalence of children with 0-dose status across time-space and geographic regions. The Integrated Public Use of Microdata Series was used to construct comparable geographic boundaries for states and UTs across surveys. The study included a total of 125 619 live children aged 12 to 23 months who were born to participating women.

Results  
Among 125 619 children, the national prevalence of those with 0-dose status in India decreased from 33.4% (95% CI, 32.5%-34.2%) in 1993 to 6.6% (95% CI, 6.4%-6.8%) in 2021. A substantial reduction in the IQR of 0-dose prevalence across states from 30.1% in 1993 to 3.1% in 2021 suggested a convergence in state disparities. The prevalence in the northeastern states of Meghalaya (17.0%), Nagaland (16.1%), Mizoram (14.3%), and Arunachal Pradesh (12.6%) remained relatively high in 2021. Prevalence increased between 2016 and 2021 in 10 states, including several traditionally high-performing states and UTs, such as Telangana (1.16 percentage points) and Sikkim (0.92 percentage points). In 2021, 53.0% of children with 0-dose status resided in the populous states of Uttar Pradesh, Bihar, and Maharashtra. A multilevel analysis comparing the share of variation at the state, district, and cluster (primary sampling unit) levels revealed that clusters accounted for the highest share of the total variation in 2016 (44.7%; VPC [SE], 1.04 [0.32]) and 2021 (64.3%; VPC [SE], 0.38 [0.12]).

Conclusions and Relevance 
In this cross-sectional study, findings from approximately 3 decades of analysis suggest the need for sustained efforts to target populous states like Uttar Pradesh and Bihar and northeastern parts of India. The resurgence of 0-dose prevalence in 10 states highlights the importance of programs like Intensified Mission Indradhanush 4.0, a major national initiative to improve immunization coverage. Prioritizing small administrative units will be important to strengthening India’s efforts to bring every child into the immunization regime.

India has seen enormous reductions in poverty in the past few decades. However, much of this progress has been unequal throughout the country. This paper examined the 2019–2021 National Family Health Survey to examine small area variations in four measures of household poverty. Overall, the results show that clusters and states were the largest sources of variation for the four measures of poverty. These findings also show persistent within-district inequality when examining the bottom 10th wealth percentile, bottom 20th wealth percentile, and multidimensional poverty. Thus, these findings pinpoint the precise districts where between-cluster inequality in poverty is most prevalent. This can help guide policy makers in terms of targeting policies aimed at reducing poverty.

Intellectual disability in India is substantially under-reported, especially amongst females. This study quantifies the prevalence and gender bias in household reporting of intellectual disability by estimating the age-and-gender specific prevalence of the intellectually disabled by education, Socio-Demographic Index (SDI) score, place of residence, (rural/urban) and income of household head. We estimated prevalence (per 100,000) at 179 (95% CI: 173 to 185) for males and 120 (95% CI: 115 to 125) for females. Gender differences declined sharply with increased education, was higher for lower ages and low income and varied little by state development. Under-identification and under-reporting due to stigma are two plausible reasons for the gender differences in prevalence that increase with age.

Question  
How much do small areas contribute to the geographic variation in quality of maternal and newborn care in India?

Findings  
In this cross-sectional study including 123 257 children, the largest share of geographic variance in maternal and newborn care quality was attributed to small areas in India. The lower the mean composite quality score the districts had, the larger the variation between small areas within the district.

Meaning  
These findings highlight the importance of considering heterogeneity within districts to improve maternal and newborn outcomes in India.