Women's empowerment and child anthropometric failures across 28 sub-Saharan African countries: A cross-level interaction by Gender Inequality Index.

Background: Child undernutrition remains a major global health issue, particularly in sub-Saharan Africa (SSA). Given the important role mothers play in early childhood health and development, we examined how individual-level women's empowerment and country-level Gender Inequality Index (GII) are jointly related with child undernutrition in SSA. Methods: We pooled recent Demographic and Health Surveys from 28 SSA countries. For 137,699 children <5 years old, undernutrition was defined using anthropometric failures (stunting, underweight, wasting). Women's empowerment was assessed using three domains of Survey-based Women's EmPowERment (SWPER) index: attitude to violence, social independence, and decision-making; and country-level gender inequality was measured using GII from United Nations Development Programme. Three-level logistic regression was conducted to examine the joint associations of SWPER and GII as well as their interactions with child anthropometric failures, after adjusting for sociodemographic covariates. Results: Overall, 32.85% of children were stunted, 17.63% were underweight, and 6.68% had wasting. Children of mothers with low-level of empowerment for all domains of SWPER had higher odds of stunting (attitude to violence: OR=1.15; 95% CI, 1.11-1.19; social independence: OR=1.21; 95% CI, 1.17-1.25; decision-making: OR=1.16; 95% CI, 1.12-1.20), and consistent results were found for underweight and wasting. Independent of women's empowerment, country-level GII increased the probability of underweight (ranging ORs=1.46; 95% CI, 1.15-1.85 to 1.50; 95% CI, 1.18-1.90) and wasting (ranging ORs=1.56; 95% CI, 1.24-1.97 to 1.61; 95% CI, 1.27-2.03). Significant interaction was found between women's empowerment and country-level GII for stunting and underweight (p<0.05). Conclusions: In SSA countries with greater gender inequality, improving women's social independence and decision-making power in particular can reduce their children's risk of anthropometric failures. Policies and interventions targeted at strengthening women's empowerment should consider the degree of gender inequality in each country.

Prevalence, trend, and inequality of prolonged exclusive breastfeeding among children aged 6-23 months old in India from 1992-2021: A cross-sectional study of nationally representative, individual-level data.

Background: Prolonged exclusive breastfeeding (PEB) for children older than six months old is a threat to appropriate complementary feeding practices. This study aims to examine the trend of PEB among children aged 6-23 months in India. Methods: We adopted five waves of National Family Health Survey (NFHS) data between 1992-93 and 2019-21. PEB was defined as children aged six months and above currently consuming breastmilk as the only source of energy, protein and micronutrients. We generated descriptive statistics and a series of multivariable logistic regressions to estimate the prevalence and trend in the PEB rate. Moreover, we assessed how child age and socioeconomic factors (i.e. child gender and age, place of residence, household wealth, and maternal education) were related with PEB using mutually and single-adjusted model. Results: There were 184 891 Indian children aged 6-23 months old included in this study with 48.0% being female. We found that the proportion of PEB increased from 4.3% in 1992 to 7.7% in 2021, of which the rate for children aged six-eight months rose from 14.0 to 20.1%. Our results showed that children who were from poorer households or with lower-educated mothers were more likely to experience prolonged exclusive breastfed. Take the year of 2019-21 as an example, compared to the households of the richest quintile, children from households of the poorer quintile were significantly more likely to experience PEB, with odds ratio (OR) of 1.33 (95% confidence interval (CI) = 1.09-1.61). Moreover, children with illiterate mothers had 21% higher odds of having prolonged exclusively breastfeeding (OR = 1.21; 95% CI = 1.01-1.44) compared with children with mothers who have college and above education. Conclusions: PEB among children over six months old is prevalent in India, particularly among children from disadvantaged households. Poverty reduction and maternal education are of great potential importance for policymakers to promote appropriate complementary feeding practice.

How economic development affects healthcare access for people with disabilities: A multilevel study in China.

Meeting the healthcare needs of people with disabilities is an important challenge in achieving the central promise of "leave no one behind" during the Sustainable Development Goals era. In this study, we describe the accessibility of healthcare for people living with disabilities, as well as the potential influences of individuals' socioeconomic status and regional economic development. Our data covered 324 prefectural cities in China in 2019 and captured the access to healthcare services for people with disabilities. First, we used linear probability regression models to investigate the association between individual socioeconomic status, including residence, poverty status, education, and healthcare access. Second, we conducted an ecological analysis to test the association between prefectural economic indicators, including GDP (gross domestic product) per capita, urbanization ratio, average years of education, Engel's coefficient, and the overall prevalence of access to healthcare for people with disabilities within prefectures. Third, we used multilevel regression models to explore the association between the individual's socio-economic status, prefectural economic indicators, and access to healthcare at the individual level for people with disabilities. The results showed, first, that higher individual socioeconomic status (urban residence or higher educational level) was associated with better access to healthcare for people with disabilities. Second, regional economic indicators were positively associated with access to healthcare at the aggregate and individual levels. This study suggests that local governments, particularly in low- and middle-income countries, should promote economic development and conduct poverty alleviation policies to improve healthcare access for disadvantaged groups.

The association of a disability-targeted cash transfer programme with disability status and health-care access: a quasi-experimental study using a nationwide cohort of 4·3 million Chinese adults living with severe disabilities.

BACKGROUND: Cash transfer is a crucial policy tool to address inequality. The objective of this study was to investigate the association between China's disability-targeted cash transfer programme and disability status, as well as equitable access to rehabilitation and medical services. METHODS: For this quasi-experimental study, we drew data from the nationwide administrative cohort of individuals with disabilities between Jan 1, 2015, and Dec 31, 2019. Individuals were enrolled in the cohort if they were aged 18 years or older, had severe disabilities as defined by the Chinese Government, and had available cash transfer information for at least 4 consecutive years, without having started receiving cash transfer benefits at the time of enrolment. We used a quasi-experimental design with propensity score matching to estimate the effects of cash transfers on disability status, access to rehabilitation services, and access to medical treatment. The primary outcomes were development of new disability and reduction of existing disabilities. Secondary outcomes were use of rehabilitation services, financial barriers as a major obstacle to accessing rehabilitation services, use of medical services by individuals who had an illness in the previous 2 weeks, and financial barriers as a major obstacle to accessing medical services. FINDINGS: From an initial pool of 51 356 125 individuals with disabilities registered in the administrative system, 2 686 024 individuals were eligible for analysis, of whom 2 165 335 (80·6%) were cash transfer beneficiaries and 520 689 (19·4%) non-beneficiaries. After propensity score matching, the cohort included 4 330 122 adults with severe disabilities. Cash transfer beneficiaries had significantly lower odds of developing new disabilities over time than non-beneficiaries (odds ratio [OR] 0·90, 95% CI 0·86-0·94; p<0·0001) and higher odds of having a reduced number of disabilities over time (1·17, 1·10-1·25; p<0·0001). Compared with non-beneficiaries, cash transfer beneficiaries were more likely to use rehabilitation services (2·12, 2·11-2·13; p<0·0001) and medical services (1·74, 1·69-1·78; p<0·0001), and less likely to report financial hardship to access rehabilitation services (0·53, 0·52-0·54; p<0·0001) and medical services (0·88, 0·84-0·93; p<0·0001) at the study endpoint. INTERPRETATION: The receipt of cash transfers was associated with improved disability status and increased access to disability-related services. The findings suggest that cash transfers could be a potential method for promoting universal health coverage among individuals living with disabilities. FUNDING: China National Natural Science Foundation.

Prevalence and changes of intimate partner violence against women aged 15 to 49 years in 53 low-income and middle-income countries from 2000 to 2021: a secondary analysis of population-based surveys.

BACKGROUND: In low-income and middle-income countries (LMICs), intimate partner violence poses a substantial barrier to accomplishing target 5.2 of the Sustainable Development Goals: to eliminate all forms of violence against women and girls. Our study aimed to assess the prevalence and changes of intimate partner violence against women in LMICs. We also explored the association between women's empowerment and intimate partner violence. METHODS: In this secondary analysis of population-based surveys, we obtained data from the nationally representative Demographic and Health Surveys conducted in LMICs between 2000 and 2021. We selected countries with available data on the domestic violence module, and women aged 15 to 49 years who currently or formerly had a husband or partner, and who had provided information about intimate partner violence, were included in the analysis. We first estimated the weighted prevalence of intimate partner violence in LMICs with available data, and then we assessed the average annual rate of change using Poisson regression with robust error variance in a subset of countries with at least two surveys. We used multilevel analysis to investigate the association between intimate partner violence and women's empowerment measured at both the country and individual levels. Country-level empowerment was measured by gender inequality index, while individual-level empowerment considered social independence, decision making, and attitude to violence. FINDINGS: A total of 359 479 women aged 15 to 49 years were included from 53 LMICs. 336 811 women from 21 countries with two surveys provided data for assessing the trends of intimate partner violence. The weighted prevalence of any type of intimate partner violence was 37·2% (95% CI 36·6 to 37·8). A significant overall decline in the prevalence of any type of intimate partner violence was observed with an average annual rate of change of -0·2% (95% CI -0·4 to -0·03); however six countries showed significant increasing trends, with average annual rates of change ranging from 1·2% (95% CI 0·7 to 1·7) in Nigeria to 6·6% (5·3 to 7·8) in Sierra Leone. Notably, the prevalence of psychological intimate partner violence has risen (average annual rate of change, 2·3% [95% CI 2·1 to 2·6]), reflected in increased rates across eight countries. Higher levels of country-level women's empowerment were associated with a lower risk of intimate partner violence: women from countries with the highest tertile of gender inequality index had an increased odds of any type of intimate partner violence (odds ratio 1·58 [95% CI 1·12 to 2·23]). Similarly, better individual-level women's empowerment also showed significant associations with a lower risk of intimate partner violence. INTERPRETATION: The prevalence of intimate partner violence remains high, and some countries have shown an increasing trend. The strong relationship between both country-level and individual-level women's empowerment and the prevalence of intimate partner violence suggests that accelerating women's empowerment could be one strategy to further reduce intimate partner violence against women. FUNDING: National Natural Science Foundation; Vanke School of Public Health, Tsinghua University; and Sanming Project of Medicine in Shenzhen.

An environmental justice analysis of air pollution in India.

Due to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 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 PM2.5 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 PM2.5 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-PM2.5 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 PM2.5 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 PM2.5 levels and different SES parameters.

Socio-economic distribution of modifiable risk factors for cardiovascular diseases: An analysis of the national longitudinal ageing study in India.

The association of socioeconomic status (SES) with modifiable risk factors for cardiovascular diseases (CVDs) is unclear in developing nations. We studied SES variations in major risk factors and their percentage distribution for adults aged 45 years or above in India. Using individual records of 59,672 individuals aged 45 years or above from the Longitudinal Ageing Study in India Wave 1 (cross-sectional study design), 2017-18, we chart age-and-sex-adjusted prevalence of clinical risk factors such as measured high blood pressure, hypertension, overweight, obesity, central adiposity and self-reported high blood glucose; and lifestyle risk factors such as excessive use of alcohol, current use of smoking and smokeless tobacco and physical inactivity across SES variables of education, quintiles of mean per capita expenditure and social caste. Multivariable analysis was used to explore the SES gradient of risk factors. The sample used in the study is predominantly rural (69.9%), illiterate (50.7%), has more females (54.2%), and belongs to other backward classes (45.6%). Prevalence of high blood pressure, overweight, obesity, central adiposity, high blood glucose, and physical inactivity increased; and excessive alcohol consumption and current use of smoking/smokeless tobacco decreased with income, education, and social caste. However, no significant income gradient was noted for lifestyle risk factors except the use of smokeless tobacco. The income gradient was largest for central adiposity (waist-circumference) with a difference of 23.4 percentage points as it increased from 38.7% among the poorest to 62.1% among the richest. The major burden of CVDs risk factors among older adults aged 45+ years falls among high SES.

Explaining the poor-rich gap in anthropometric failure among children in India: An econometric analysis of the NFHS, 2021 and 2016.

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.

Socioeconomic and geographic variation in coverage of health insurance across India.

Introduction: In India, regular monitoring of health insurance at district levels (the most essential administrative unit) is important for its effective uptake to contain the high out of pocket health expenditures. Given that the last individual data on health insurance coverage at district levels in India was in 2016, we update the evidence using the latest round of the National Family Health Survey conducted in 2019-2021. Methods: We use the unit records of households from the latest round (2021) of the nationally representative National Family Health Survey to calculate the weighted percentage (and 95% CI) of households with at least one member covered by any form of health insurance and its types across socio-economic characteristics and geographies of India. Further, we used a random intercept logistic regression to measure the variation in coverage across communities, district and state. Such household level study of coverage is helpful as it represents awareness and outreach for at least one member, which can percolate easily to the entire household with further interventions. Results: We found that only 2/5th of households in India had insurance coverage for at least one of its members, with vast geographic variation emphasizing need for aggressive expansion. About 15.5% were covered by national schemes, 47.1% by state health scheme, 13.2% by employer provided health insurance, 3.3% had purchased health insurance privately and 25.6% were covered by other health insurance schemes (not covered above). About 30.5% of the total variation in coverage was attributable to state, 2.7% to districts and 9.5% to clusters. Household size, gender, marital status and education of household head show weak gradient for coverage under "any" insurance. Discussion: Despite substantial increase in population eligible for state sponsored health insurance and rise in private health insurance companies, nearly 60% of families do not have a single person covered under any health insurance scheme. Further, the existing coverage is fragmented, with significant rural/urban and geographic variation within districts. It is essential to consider these disparities and adopt rigorous place-based interventions for improving health insurance coverage.

When social identities intersect: understanding inequities in growth outcomes by religion- caste and religion-tribe as intersecting strata of social hierarchy for Muslim and Hindu children in India.

BACKGROUND: Minority social status determined by religion, caste and tribal group affiliations, are usually treated as independent dimensions of inequities in India. This masks relative privileges and disadvantages at the intersections of religion-caste and religion-tribal group affiliations, and their associations with population health disparities. METHODS: Our analysis was motivated by applications of the intersectionality framework in public health, which underlines how different systems of social stratification mutually inform relative access to material resources and social privilege, that are associated with distributions of population health. Based on this framework and using nationally representative National Family Health Surveys of 1992-93, 1998-99, 2005-06, 2015-16 and 2019-21, we estimated joint disparities by religion-caste and religion-tribe, for prevalence of stunting, underweight and wasting in children between 0-5 years of age. As indicators of long- and short-term growth interruptions, these are key population health indicators capturing developmental potential of children. Our sample included Hindu and Muslim children of < = 5 years, who belonged to Other (forward) castes (the most privileged social group), Other Backward Classes (OBCs), Schedule Castes (SCs) and Schedule Tribe (STs). Hindu-Other (forward) caste, as the strata with the dual advantages of religion and social group was specified as the reference category. We specified Log Poisson models to estimate multiplicative interactions of religion- caste and religion-tribe identities on risk ratio scales. We specified variables that may be associated with caste, tribe, or religion, as dimensions of social hierarchy, and/or with child growth as covariates, including fixed effects for states, survey years, child's age, sex, household urbanicity, wealth, maternal education, mother's height, and weight. We assessed patterns in growth outcomes by intersectional religion-caste and religion-tribe subgroups nationally, assessed their trends over the last 30 years, and across states. FINDINGS: The sample comprised 6,594, 4,824, 8,595, 40,950 and 3,352 Muslim children, and 37,231, 24,551, 35,499, 1,87,573 and 171,055 Hindu children over NFHS 1, 2, 3, 4, and 5, respectively. As one example anthropometric outcome, predicted prevalence of stunting among different subgroups were as follows- Hindu Other: 34.7% (95%CI: 33.8, 35.7), Muslim Other: 39.2% (95% CI: 38, 40.5), Hindu OBC: 38.2 (95%CI: 37.1, 39.3), Muslim OBC: 39.6% (95%CI: 38.3, 41), Hindu SCs: 39.5% (95%CI: 38.2, 40.8), Muslims identifying as SCs: 38.5% (95%CI: 35.1, 42.3), Hindu STs: 40.6% (95% CI: 39.4, 41.9), Muslim STs: 39.7% (95%CI: 37.2, 42.4). Over the last three decades, Muslims always had higher prevalence of stunting than Hindus across caste groups. But this difference doubled for the most advantaged castes (Others) and reduced for OBCs (less privileged caste group). For SCs, who are the most disadvantaged caste group, the Muslim disadvantage reversed to an advantage. Among tribes (STs), Muslims always had an advantage, which reduced over time. Similar directions and effect sizes were estimated for prevalence of underweight. For prevalence of wasting, effect sizes were in the same range, but not statistically significant for two minority castes-OBCs and SCs. INTERPRETATION: Hindu children had the highest advantages over Muslim children when they belonged to the most privileged castes. Muslim forward caste children were also disadvantaged compared to Hindu children from deprived castes (Hindu OBCs and Hindu SCs), in the case of stunting. Thus, disadvantages from a socially underprivileged religious identity, seemed to override relative social advantages of forward caste identity for Muslim children. Disadvantages born of caste identity seemed to take precedence over the social advantages of Hindu religious identity, for Hindu children of deprived castes and tribes. The doubly marginalized Muslim children from deprived castes were always behind their Hindu counter parts, although their differentials were less than that of Muslim-Hindu children of forward castes. For tribal children, Muslim identity seemed to play a protective role. Our findings indicate monitoring child development outcomes by subgroups capturing intersectional social experiences of relative privilege and access from intersecting religion and social group identities, could inform policies to target health disparities.

Progress on Sustainable Development Goal indicators in 707 districts of India: a quantitative mid-line assessment using the National Family Health Surveys, 2016 and 2021.

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. Funding: This work was funded by the Bill and Melinda Gates Foundation, INV-002992.

Prevalence of Zero-Food among infants and young children in India: patterns of change across the States and Union Territories of India, 1993-2021.

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. Funding: This study was supported by a grant from the Bill & Melinda Gates Foundation INV-002992.

Small area variations in four measures of poverty among Indian households: Econometric analysis of National Family Health Survey 2019-2021.

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.

Distribution of self-reported health in India: The role of income and geography.

An important new large-scale survey database is brought to bear on measuring and analysing self-reported health in India. The most important correlates are age, income and location. There is substantial variation of health across the 102 'homogeneous regions' within the country, after controlling for household and individual characteristics. Higher income is correlated with better health in only 40% of India. We create novel maps showing regions with poor health, that is attributable to the location, that diverge from the conventional wisdom. These results suggest the need for epidemiological studies in the hotspots of ill-health and in regions where higher income does not correlate with improved health.

The Psychological Costs of the COVID-19 Pandemic and Heterogeneous Effects in South Korea: Evidence from a Difference-in-Differences Analysis.

This study estimates the effects of the COVID-19 pandemic on life satisfaction and stress and examines whether these effects vary across different sociodemographic groups using a nationally representative sample in South Korea. We estimate the causal effects of COVID-19 on psychological well-being by exploiting regional variation in the spread of the pandemic in South Korea. While the number of confirmed cases was very small in other provinces in the first half of 2020, the coronavirus spread rapidly in Daegu after an outbreak in one church. We employ a difference-in-differences approach that compares changes in people's life satisfaction and stress before-and-after the initial surge of COVID-19 cases in Daegu and other provinces. Our results show that the proportion of people who are dissatisfied with life increased by 2.8-6.5 percentage points more in Daegu than in other provinces after the COVID-19 outbreak. During the same period, the proportion of people who reported feeling stressed increased more in Daegu than in other provinces by 5.8-8.9 percentage points. Our results also suggest that the negative impact of the COVID-19 outbreak on psychological well-being is significantly greater for men, young adults, middle-aged adults, self-employed workers, and middle-income individuals. On the other hand, the proportion of people who report feeling stressed among the highest-educated (a master's degree or higher) and high-income individuals decreased after the onset of the COVID-19 outbreak.

Small Area Variation in the Quality of Maternal and Newborn Care in India.

Importance: In India, the district serves as the primary policy unit for implementing and allocating resources for various programs aimed at improving key developmental and health indicators. Recent evidence highlights that high-quality care for mothers and newborns is critical to reduce preventable mortality. However, the geographic variation in maternal and newborn health service quality has never been investigated. Objective: To examine the variation between smaller areas within districts in the quality of maternal and newborn care in India. Design, Setting, and Participants: This cross-sectional study assessed data from women aged 15 to 49 years on the most recent birth (singleton or multiples) in the 5 years that preceded the fifth National Family Health Survey (June 17, 2019, to April 30, 2021). Exposures: Maternal and newborn care in 36 states and union territories (UTs), 707 districts, and 28 113 clusters (small areas) in India. Main Outcomes and Measures: The composite quality score of maternal and newborn care was defined as the proportion of components of care received of the total 11 essential components of antenatal and postnatal care. Four-level logistic and linear regression was used for analyses of individual components of care and composite score, respectively. Precision-weighted prevalence of each component of care and mean composite score across districts as well as their between-small area SD were calculated. Results: The final analytic sample for the composite score was composed of 123 257 births nested in 28 113 small areas, 707 districts, and 36 states/UTs. For the composite score, 58.3% of the total geographic variance was attributable to small areas, 29.3% to states and UTs, and 12.4% to districts. Of 11 individual components of care, the small areas accounted for the largest proportion of geographic variation for 6 individual components of care (ranging from 42.3% for blood pressure taken to 73.0% for tetanus injection), and the state/UT was the largest contributor for 4 components of care (ranging from 41.7% for being weighed to 52.3% for ultrasound test taken). District-level composite score and prevalence of individual care components and their variation across small areas within the districts showed a consistently strong negative correlation (Spearman rank correlation ρ = -0.981 to -0.886). Low-quality scores and large between-small area disparities were not necessarily concentrated in aspirational districts (mean district composite score [SD within districts], 92.7% [2.1%] among aspirational districts and 93.7% [1.8%] among nonaspirational districts). Conclusions and Relevance: The findings of this cross-sectional study suggest that the policy around maternal and child health care needs to be designed more precisely to consider district mean and between-small area heterogeneity in India. This study may have implications for other low- and middle-income countries seeking to improve maternal and newborn outcomes, particularly for large countries with geographic heterogeneity.

Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases.

The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%-32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%-16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%-145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.

Association of Neighborhood Conditions and Resources for Children With Life Expectancy at Birth in the US.

Importance: To address inequities in life expectancy, we must understand the associations of modifiable socioeconomic and structural factors with life expectancy. However, the association of limited neighborhood resources and deleterious physical conditions with life expectancy is not well understood. Objective: To evaluate the association of community social and economic conditions and resources for children with life expectancy at birth. Design, Setting, and Participants: This cross-sectional study examined neighborhood child opportunity and life expectancy using data from residents of 65 662 US Census tracts in 2015. The analysis was conducted from July 6 to October 1, 2021. Exposures: Neighborhood conditions and resources for children in 2015. Main Outcomes and Measures: The primary outcome was life expectancy at birth at the Census tract level based on data from the US Small-Area Life Expectancy Estimates Project (January 1, 2010, to December 31, 2015). Neighborhood conditions and resources for children were quantified by Census tract Child Opportunity Index (COI) 2.0 scores for 2015. This index captures community conditions associated with children's health and long-term outcomes categorized into 5 levels, from very low to very high opportunity. It includes 29 indicators in 3 domains: education, health and environment, and social and economic factors. Mixed-effects and simple linear regression models were used to estimate the associations between standardized COI scores (composite and domain-specific) and life expectancy. Results: The study included residents from 65 662 of 73 057 US Census tracts (89.9%). Life expectancy at birth across Census tracts ranged from 56.3 years to 93.6 years (mean [SD], 78.2 [4.0] years). Life expectancy in Census tracts with very low COI scores was lower than life expectancy in Census tracts with very high COI scores (-7.06 years [95% CI, -7.13 to -6.99 years]). Stepwise associations were observed between COI scores and life expectancy. For each domain, life expectancy was shortest in Census tracts with very low compared with very high COI scores (education: ß = -2.02 years [95% CI, -2.12 to -1.92 years]); health and environment: ß = -2.30 years [95% CI, -2.41 to -2.20 years]; social and economic: ß = -4.16 years [95% CI, -4.26 to -4.06 years]). The models accounted for 41% to 54% of variability in life expectancy at birth (R2 = 0.41-0.54). Conclusions and Relevance: In this study, neighborhood conditions and resources for children were significantly associated with life expectancy at birth, accounting for substantial variability in life expectancy at the Census tract level. These findings suggest that community resources and conditions are important targets for antipoverty interventions and policies to improve life expectancy and address health inequities.

Assessment of the predictive power of a causal variable: An application to the Head Start impact study.

In a study attempting to estimate a causal effect of a causal variable, an assessment of the predictive power of the causal variable can shed light on the heterogeneity around its average effect. Using data from the Head Start Impact Study, a randomized controlled trial of the Head Start, a nation-wide early childhood education program in the United States, we provide a parallel comparison between measures of average effect and predictive power of the Head Start on five cognitive outcomes. We observed that one year of the Head Start increased scores for all five outcomes, with effect sizes ranging from 0.12 to 0.19 standard deviations. Percent variation explained by the Head Start ranged from 0.56 to 1.62%. For binary versions of the outcomes, the overall pattern remained; the Head Start on average improved the outcomes by meaningful magnitudes. In contrast, in a fully adjusted model, the Head Start only improved area under the curve (AUC) by less than 1% and its influence on the variance of predicted probabilities was negligible. The Head-Start-only model only achieved AUC ranging from 50.22 to 55.24%. Negligible predictive power despite the significant average effect suggests that the heterogeneity in effects may be large. The average effect estimates may not generalize well to different populations or different Head Start program settings. Assessment of the predictive power of a causal variable in randomized data should be a routine practice as it can provide helpful information on the causal effect and especially its heterogeneity.

Components of Out-of-Pocket Expenditure and Their Relative Contribution to Economic Burden of Diseases in India.

Importance: High out-of-pocket expenditure (OOPE) on health in India may limit achieving universal health coverage. A clear insight on the components of health expenditure may be necessary to make allocative decisions to reduce OOPE, and such details by sociodemographic group and state have not been studied in India. Objective: To analyze the relative contribution of drugs, diagnostic tests, doctor and surgeon fees, and expenditure on other medical services and nonmedical health-related services, such as transport, lodging, and food, by sociodemographic characteristics of patients, geography, and type of illness. Design, Setting, and Participants: A population-based cross-sectional health consumption survey conducted by the National Sample Survey Organisation in 2018 was analyzed in this cross-sectional study. Respondents who provided complete information on costs of medicine, doctors, diagnostics tests, other medical costs, and nonmedical costs were selected. Data were analyzed from August through September 2021. Main Outcomes and Measures: Mean and median share of components (ie, medicine, diagnostic tests, doctor fees, other medical costs, and nonmedical costs) in total health care expenditure and income were calculated. Bivariate survey-weighted mean (with 95% CI) and median (IQR) expenditures were calculated for each component across sociodemographic characteristics. The proportion of total expenditure and income contributed by each cost was calculated for each individual. Mean and median were then used to summarize such proportions at the population level. The association between state net domestic product per capita and component share of each health care service was graphically explored. Results: Health expenditure details were analyzed for 43 781 individuals for inpatient costs (27 272 [64.3%] women; 26 830 individuals aged 25-64 years [59.9%]) and 8914 individuals for outpatient costs (4176 [48.2%] women; 4901 individuals aged 25-64 years [54.2%]); most individuals were rural residents (24 106 inpatients [67.0]; 4591 outpatients [63.9%]). Medicines accounted for a mean of 29.1% (95% CI, 28.9%-29.2%) of OOPE among inpatients and 60.3% (95% CI, 59.7%-60.9%) of OOPE among outpatients. Doctor consultation charges were a mean of 15.3% (95% CI, 15.1%-15.4%) of OOPE among inpatients and 12.4% (95% CI, 12.1%-12.6%) of OOPE among outpatients. Diagnostic tests accounted for a mean of 12.3% (95% CI, 12.2%-12.4%) of OOPE for inpatient and 9.2% (95% CI, 8.9%-9.5%) of OOPE for outpatient services. Nonmedical costs accounted for a mean of 23.6% (95% CI, 23.3%-23.8%) of OOPE among inpatients and 14.6% (95% CI, 14.1%-15.1%) of OOPE among outpatients. Mean share of OOPE from doctor consultations and diagnostic test charges increased with socioeconomic status. For example, for the lowest vs highest monthly per capita income quintile among inpatients, doctor consultations accounted for 11.5% (95% CI, 11.1%-11.8%) vs 21.2% (95% CI, 20.8%-21.6%), and diagnostic test charges accounted for 10.9% (95% CI, 10.6%-11.1%) vs 14.3% (95% CI, 14.0%-14.5%). The proportion of mean annual health expenditure from mean annual income was $299 of $1918 (15.6%) for inpatient and $391 of $1788 (21.9%) for outpatient services. Conclusions and Relevance: This study found that nonmedical costs were significant, share of total health care OOPE from doctor consultation and diagnostic test charges increased with socioeconomic status, and annual cost as a proportion of annual income was lower for inpatient than outpatient services.