@article {1809121, title = {Call for action: presenting constituency-level data on population, health and socioeconomic wellbeing related to 2030 Sustainable Development Goals for India}, journal = {The Lancet Regional Health {\textendash} Southeast Asia }, volume = {22}, year = {2024}, pages = {100358}, abstract = {Achieving India{\textquoteright}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{\textquoteright}s SDGs.}, url = {https://doi.org/10.1016/j.lansea.2024.100358}, author = {Subramanian, S V and Amar Patnaik and Rockli Kim} } @article {1809116, title = {Prevalence of Children Aged 6 to 23 Months Who Did Not Consume Animal Milk, Formula, or Solid or Semisolid Food During the Last 24 Hours Across Low- and Middle-Income Countries}, journal = {JAMA Netw Open}, volume = {7}, number = {2}, year = {2024}, pages = {e2355465}, abstract = { 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. }, url = {https://doi.org/10.1001/jamanetworkopen.2023.55465}, author = {Karlsson, Omar and Rockli Kim and Subramanian, S. V.} } @article {1809106, title = {The impact of early-life access to oral polio vaccines on disability: evidence from India}, journal = { Journal of Population Economics}, volume = {32}, number = {23}, year = {2024}, abstract = { 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. }, url = {https://doi.org/10.1007/s00148-024-01006-x}, author = {Mayanka Ambade and Nidhiya Menon and Subramanian, S. V.} } @article {1789531, title = {Prevalence of girl and boy child marriage across states and Union Territories in India, 1993{\textendash}2021: a repeated cross-sectional study}, journal = {The Lancet Global Health}, year = {2023}, abstract = { Background India{\textquoteright}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{\textendash}24 years between 1993 and 2021 and 43 436 men aged 20{\textendash}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{\textperiodcentered}4\% (95\% CI 48{\textperiodcentered}1{\textendash}50{\textperiodcentered}8) in 1993 to 22{\textperiodcentered}3\% (21{\textperiodcentered}9{\textendash}22{\textperiodcentered}7) in 2021. Child marriage in boys declined from 7{\textperiodcentered}1\% (6{\textperiodcentered}9{\textendash}30{\textperiodcentered}8) in 2006 to 2{\textperiodcentered}2\% (1{\textperiodcentered}8{\textendash}2{\textperiodcentered}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{\textendash}24 years and 1 454 894 men aged 20{\textendash}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. }, url = {https://doi.org/10.1016/S2214-109X(23)00470-9}, author = {Gausman, Jewel and Rockli Kim and Akhil Kumar and Ravi, Shamika and Subramanian, S V} } @article {1785066, title = {Effects of zero-dose vaccination status in early childhood and level of community socioeconomic development on learning attainment in preadolescence in India: a population-based cohort study}, journal = {BMJ Public Health}, volume = {1}, number = {1}, year = {2023}, abstract = { \  Introduction\ {\textquoteleft}Zero-dose{\textquoteright} 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{\textendash}2005) on basic learning tests at ages 8{\textendash}11 in wave II (2011{\textendash}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. }, url = {https://doi.org/10.1136/bmjph-2023-000022}, author = {Mira Johri and Edmond SW Ng and Alyssa Sharkey and Delphine Bosson-Rieutort and Georges K Kone and Subramanian, S V} } @article {1768796, title = {An environmental justice analysis of air pollution in India}, journal = {Scientific Reports}, volume = {13}, year = {2023}, pages = {16690}, abstract = {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.}, url = {https://doi.org/10.1038/s41598-023-43628-3}, author = {Priyanka N. deSouza and Ekta Chaudhary and Sagnk Dey and Soohyeon Ko and Jeremy N{\'e}meth and Sarath Guttikunda and Sourangsu Chowdhury and Kinney, Patrick and Subramanian, S. V. and Bell, Michelle L. and Rockli Kim} } @article {1768791, title = {Small Area Geographic Estimates of Cardiovascular Disease Risk Factors in India}, journal = {JAMA Network Open}, volume = {6}, number = {10}, year = {2023}, pages = {e2337171}, abstract = { ObjectivesWith 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 ParticipantsThis 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. ResultsThe 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 RelevanceThis 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{\textquoteright}s efforts to reduce the burden of noncommunicable diseases. }, url = {https://doi.org/10.1001/jamanetworkopen.2023.37171}, author = {Soohyeon Ko and Oh, Hannah and Subramanian, S. V.} } @article {1759911, title = {Population, health and nutrition profile of the Scheduled Tribes in India: a comparative perspective, 2016{\textendash}2021}, journal = {The Lancet Regional Health - Southeast Asia}, year = {2023}, pages = {100266}, abstract = {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.\ }, url = { https://doi.org/10.1016/j.lansea.2023.100266}, author = {Subramanian, S V and William Joe} } @article {1739761, title = {Prevalence of zero-sanitation in India: Patterns of change across the states and Union Territories, 1993-2021}, journal = {J Glob Health}, volume = {13}, year = {2023}, pages = {04082}, abstract = { 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{\textquoteright}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. }, url = {https://doi.org/10.7189/jogh.13.04082}, author = {Anoop Jain and Akhil Kumar and Rockli Kim and Subramanian, S V} } @article {1739681, title = {Explaining the poor-rich gap in anthropometric failure among children in India: An econometric analysis of the NFHS, 2021 and 2016}, journal = {SSM - Population Health}, volume = {23}, year = {2023}, pages = {101482}, abstract = { 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{\textendash}59 and 6{\textendash}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. }, url = {https://doi.org/10.1016/j.ssmph.2023.101482}, author = {Gaurav Dhamija and Kapoor, Mudit and Rockli Kim and Subramanian, S V} } @article {1739671, title = {Exercising in Inda: An Exploratory Analysis Using the Time Use Survey, 2019}, journal = {Coll Antropol}, volume = {47}, number = {1}, year = {2023}, pages = {39{\textendash}48}, abstract = {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.}, url = {https://www.collantropol.hr/antropo/article/view/2001}, author = {Kapoor, Mudit and Ravi, Shamika and Rockli Kim and Subramanian, S V} } @article {1708856, title = {Prevalence of Zero-Food among infants and young children in India: patterns of change across the States and Union Territories of India, 1993{\textendash}2021}, journal = {eClinicalMedicine}, volume = {58}, year = {2023}, pages = {101890}, abstract = { BackgroundThe extent of food deprivation and insecurity among infants and young children{\textemdash}a critical phase for children{\textquoteright}s current and future health and well-being{\textemdash}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. MethodsData 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{\textendash}23 months) born to mothers (aged 15{\textendash}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{\textquoteright}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 {\textquotedblleft}Zero-Food{\textquotedblright}. 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. FindingsThe prevalence of Zero-Food in India marginally declined from 20.0\% (95\% CI: 19.3\%{\textendash}20.7\%) in 1993 to 17.8\% (95\% CI: 17.5\%{\textendash}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{\textendash}11 months (30.6\%) and substantial even among children aged 18{\textendash}23 months (8.5\%). Overall, socioeconomically advantaged groups had lower prevalence of Zero-Food than disadvantaged groups. InterpretationConcerted 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. }, url = {https://doi.org/10.1016/j.eclinm.2023.101890}, author = {Subramanian, S. V. and Mayanka Ambade and Sharma, Smriti and Akhil Kumar and Rockli Kim} } @article {1708851, title = {Patterns in Child Health Outcomes Before and After the COVID-19 Outbreak in India}, journal = {JAMA Network Open}, volume = {6}, number = {6}, year = {2023}, pages = {e2317055}, abstract = { IntroductionThe 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. MethodsThe 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). ResultsThe 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. DiscussionMixed 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{\textquoteright}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{\textquoteright}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{\textquoteright}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{\textquoteright}s outcome. }, url = {https://doi.org/10.1001/jamanetworkopen.2023.17055}, author = {Soohyeon Ko and Rockli Kim and Subramanian, S. V.} } @article {1667887, title = {Should India adopt a country-specific growth reference to measure undernutrition among its children?}, journal = {The Lancet Regional Health - Southeast Asia}, volume = {9}, year = {2023}, pages = {100107}, abstract = { 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. }, url = {https://doi.org/10.1016/j.lansea.2022.100107}, author = {Subramanian, S. V. and Anuradha Khailkar and Karlsson, Omar and et al.} } @article {1667880, title = {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}, journal = {The Lancet Regional Health - Southeast Asia}, year = {2023}, pages = {100155}, abstract = { 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{\textquoteright} 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{\textquoteright}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. }, url = {https://doi.org/10.1016/j.lansea.2023.100155}, author = {Subramanian, S. V. and Mayanka Ambade and Akhil Kumar and et al.} } @article {1667875, title = {Patterns in the Prevalence of Unvaccinated Children Across 36 States and Union Territories in India, 1993-2021}, journal = {JAMA Network Open}, volume = {6}, number = {2}, year = {2023}, pages = {e2254919}, abstract = { 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{\textquoteright}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{\textquoteright}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{\textquoteright}s efforts to bring every child into the immunization regime. }, url = {https://doi.org/10.1001/jamanetworkopen.2022.54919}, author = {Rajpal, Sunil and Akhil Kumar and Mira Johri and et al.} } @article {1667874, title = {Small area variations in four measures of poverty among Indian households: Econometric analysis of National Family Health Survey 2019{\textendash}2021}, journal = {Humanities and Social Sciences Communications}, volume = {10}, year = {2023}, pages = {18}, abstract = {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{\textendash}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.}, url = {https://doi.org/10.1057/s41599-023-01509-0}, author = {Anoop Jain and Rajpal, Sunil and Md Juel Rana and et al.} } @article {1667873, title = {Age- and Gender-Specific Prevalence of Intellectually Disabled Population in India}, journal = {Journal of Autism and Developmental Disorders}, year = {2023}, abstract = {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.}, url = { https://doi.org/10.1007/s10803-022-05849-9}, author = {Kapoor, Mudit and Mayanka Ambade and Ravi, Shamika and Subramanian, S. V.} } @article {1667886, title = {Small Area Variation in the Quality of Maternal and Newborn Care in India}, journal = {JAMA Network Open}, volume = {11}, year = {2022}, pages = {e2242666}, abstract = { 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. }, url = {https://doi.org/10.1001/jamanetworkopen.2022.42666}, author = {Lee, Hwa-Young and Md Juel Rana and Rockli Kim and et al.} } @article {1667884, title = {Independent and cumulative effects of risk factors associated with stillbirths in 50 low- and middle-income countries: A multi-country cross-sectional study}, journal = {eClinicalMedicine}, volume = {54}, year = {2022}, pages = {101706}, abstract = { Background Early identification of high-risk pregnancies could reduce stillbirths, yet remains a challenge in low- and middle-income countries (LMICs). This study aims to estimate the associations between easily observable risk factors and stillbirths, and construct a risk score which could be adopted in LMICs to identify pregnancies with high risk of stillbirths. Methods Using the most recent Demographic and Health Surveys from 50 low- and middle-income countries (LMICs) with available data between January 1, 2010 and December 31, 2021, we analysed a total of 22 factors associated with stillbirths in a series of single-adjusted and mutually adjusted logistic regression models. Upon identification of the risk factors with the strongest associations, we constructed a risk score on the basis of the magnitude of the β coefficient to examine the cumulative effects of risk factors on stillbirths. To assess whether the associations between risk scores and stillbirths were moderated by protective factors, we added an interaction term between the identified protective factor and risk scores to the regression model. We also conducted two sets\ of subgroup analyses for previous history of pregnancy and maternal age at pregnancy and four sets of supplementary analyses to test the robustness of the results. Findings Among the 795,642 women identified for analysis with at least one pregnancy within the five years before the survey, the most recent pregnancy of 8968 (1.13\%) ended as stillbirths. Using a mutually adjusted regression model, we found that the top factors showing the strongest associations with stillbirths were short maternal height (odds ratio [OR]: 1.99, 95\% confidence interval [CI]: 1.48{\textendash}2.67,\ P\ \<\ 0.001), interpregnancy interval less than six months (OR: 1.84, 95\% CI: 1.42{\textendash}2.38,\ P\ \<\ 0.001), previous stillbirth history (OR: 1.55, 95\% CI: 1.07{\textendash}2.26,\ P\ \<\ 0.020), low maternal education (OR: 1.50, 95\% CI: 1.01{\textendash}2.24,\ P\ =\ 0.045), and lowest household wealth (OR: 1.32, 95\% CI: 1.08{\textendash}1.61,\ P\ =\ 0.008). A female household head was a protective factor with an OR of 0.71 (95\% CI: 0.55{\textendash}0.90,\ P\ =\ 0.005). Single-adjusted models, subgroup analyses, and sensitivity analyses showed generally consistent results. We also found that the odds of stillbirths increased with a larger risk score with a\ P\ trend \<0.001. Compared with women without any risk factors, women with a risk score of 5 or more were 4.11 (95\% CI: 2.83{\textendash}5.97,\ P\ \<\ 0.001) times more likely to have their pregnancies ending up as stillbirths. However, these associations were weakened if the head of household was female. Interpretation Our study suggested that short maternal height, low socioeconomic status, previous stillbirth history, low maternal education, and very short interpregnancy interval had the strongest associations with stillbirths. The construction of risk scores using easily observable risk factors could be an effective way to identify high-risk pregnancies in resource-poor settings. }, url = {https://doi.org/10.1016/j.eclinm.2022.101706}, author = {Li, Zhihui and Yuhao Kong and Shaoru Chen} } @article {1667883, title = {Food group consumption patterns among children meeting and not meeting WHO{\textquoteright}s recommended dietary diversity: Evidence from 197,514 children in 59 countries}, journal = {Food Policy}, volume = {112}, year = {2022}, pages = {102368}, abstract = {The minimum dietary diversity (MDD) indicator as defined by the WHO is commonly used to assess micronutrient deficiency in young children. However, individual food item-specific consumption patterns may be overlooked when focusing solely on this indicator. We provide a comprehensive view on food item and food group consumption patterns of children aged 6{\textendash}23\ months old using DHS data from 59 low- and middle-income countries. Consumption levels of food items ranged from 79.0\ \% for breastfeeding to 5.9\ \% for organ meats, showing particularly low levels for protein rich food items. There were significant differences in food item consumption levels for different countries as well as household correlates{\textquoteright} relevance such as a household{\textquoteright}s wealth decile and the child{\textquoteright}s age group, hinting towards potential underlying mechanisms such as regional availability, household{\textquoteright}s available resources and awareness of food group{\textquoteright}s importance from early age. The results suggest that the analysis of MDD should be complemented with information on individual food item consumption to identify priorities for policy makers aiming to fight undernutrition across the globe..}, url = {https://doi.org/10.1016/j.foodpol.2022.102368}, author = {Markus Heemann and Rockli Kim and Sharma, Smriti} } @article {1667882, title = {Age Distribution of All-Cause Mortality Among Children Younger Than 5 Years in Low- and Middle-Income Countries}, journal = {JAMA Network Open}, volume = {5}, number = {5}, year = {2022}, pages = {e2212692}, abstract = { Question\ \ What share of deaths among children younger than 5 years occur before 2 years of age in low- and middle-income countries? Findings\ \ In this cross-sectional study of 2 827 515 children younger than 5 years from 77 countries, a large majority (81.5\%) of deaths occurred before 2 years of age in all countries, among boys and girls, and in the households with the highest and lowest living standards. Meaning\ \ These findings suggest that coverage of potentially life-saving interventions should be ensured for children younger than 2 years of age in low- and middle-income countries. }, url = {https://doi.org/10.1001/jamanetworkopen.2022.12692}, author = {Karlsson, Omar and Rockli Kim and Andreas Hasman and et al.} } @article {1667870, title = {Small Area Variations in Dietary Diversity Among Children in India: A Multilevel Analysis of 6{\textendash}23-Month-Old Children}, journal = {Frontiers in Nutrition}, volume = {8}, year = {2022}, abstract = {Dietary diversity is an important indicator of child malnutrition. However, little is known about the geographic variation of diet indicators across India, particularly within districts and across states. As such, the purpose of this paper was to elucidate the small area variations in diet indicators between clusters within districts of India. Overall, we found that clusters were the largest source of variation for children not eating grains, roots, and tubers, legumes and nuts, dairy, vitamin A-rich vegetables and fruits, and other vegetables and fruits. We also found positive correlations between the district percent and cluster standard deviations of children not breastfeeding or eating grains, roots, and tubers, but negative correlations between the district percent and cluster standard deviation for the remaining seven outcomes. These findings underscore the importance of targeting clusters to improve child dietary diversity.}, url = {https://doi.org/10.3389/fnut.2021.791509}, author = {Anoop Jain and Weiyu Wang and K. S. James and et al.} } @article {1667869, title = {Small area variation in child undernutrition across 640 districts and 543 parliamentary constituencies in India}, journal = {Scientific Reports}, volume = {11}, number = {1}, year = {2022}, pages = {1-9}, abstract = {In India, districts serve as central policy unit for program development, administration and implementation. The one-size-fits-all approach based on average prevalence estimates at the district level fails to capture the substantial small area variation. In addition to district average, heterogeneity within districts should be considered in policy design. The objective of this study was to quantify the extent of small area variation in child stunting, underweight and wasting across 36 states/Union Territories (UTs), 640 districts (and 543 PCs), and villages/blocks in India. We utilized the 4th round of Indian National Family Health Survey (NFHS-4) conducted in 2015{\textendash}2016. The study population included 225,002 children aged 0{\textendash}59\ months whose height and weight information were available. Stunting was defined as height-for-age z-score below 2 SD from the World Health Organization child growth reference standards. Similarly, underweight and wasting were each defined as weight-for-age \< -2 SD and weight-for-height \< -2 SD from the age- and sex-specific medians. We adopted a four-level logistic regression model to partition the total variation in stunting, underweight and wasting. We computed precision-weighted prevalence of child anthropometric failures across districts and PCs as well as within-district/PC variation using standard deviation (SD) measures. For stunting, 56.4\% (var: 0.237; SE: 0.008) of the total variation was attributed to villages/blocks, followed by 25.8\% (var: 0.109; SE: 0.030) to states/UTs, and 17.7\% (Var: 0.074; SE: 0.006) to districts. For underweight and wasting, villages/blocks accounted for 38.4\% (var: 0.224; SE: 0.007) and 50\% (var: 0.285; SE: 0.009), respectively, of the total contextual variance in India. Similar findings were shown in multilevel models incorporating PC as a geographical unit instead of districts. We found high positive correlations between mean prevalence and SD for stunting (r = 0.780,\ p \< 0.001), underweight (r = 0.860,\ p \< 0.001), and wasting (r = 0.857,\ p \< 0.001) across all districts in India. A similar pattern of correlation was found for PCs. Within-district and within-PC variation are the primary source of variation for child malnutrition in India. Our results suggest the importance of considering heterogeneity within districts and PCs when planning and administering child nutrition policies.}, url = {https://doi.org/10.1038/s41598-021-83992-6}, author = {Rajpal, Sunil and Julie Kim and William Joe and et al.} } @article {1667868, title = {Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India}, journal = {Proceedings of the National Academy of Sciences}, volume = {118}, number = {18}, year = {2022}, pages = { e2025865118}, url = {https://doi.org/10.1073/pnas.2025865118}, author = {Rockli Kim and Avleen S. Bijral and Yun Xu and Subramanian, S. V.} } @article {1667866, title = {TB notification rates across parliamentary constituencies in India: a step towards data-driven political engagement}, journal = {Tropical Medicine \& International Health }, volume = {26}, number = {7}, year = {2022}, pages = {730-742}, abstract = { Objective National averages obscure geographic variation in program performance. We determined Parliamentary Constituency (PC)-wise estimates of TB notification to guide political engagement. Methods We extracted district-level TB notification data from the 2018 annual TB report. We derived PC-level estimates by building a {\textquoteleft}cross-walk{\textquoteright} between districts and PCs using boundary shapefiles. We described the spatial distribution of the PC-wise estimates of Total Notification Rate and percentage of Private Sector Notification. Results The median PC-wise Total Notification Rate was 126.24/100\ 000 (IQR: 94.86/100\ 000, 162.22/100\ 000). The median PC-wise Percentage Private Sector Notification was 18.03\% (IQR: 9.56\%, 26.84\%). Only 16 (2.94\%) PCs met the target of 50\% private sector notification. Most of high notification rates in PCs were driven by high notification in public sector. There was geographic {\textendash} both interstate and within state inter-PC {\textendash} variation in the estimates of these indicators. The study identified some geographic patterns of notification {\textendash} high positive outlier PCs with adjoining PCs in lower deciles of notification rates, intra-state differences in PC performance, and similarities in notification rates of adjoining PCs in different states. Conclusion In addition to regional inequality, the study identified geospatial patterns that can aid in the formulation of suitable interventions. These include decongestion of overburdened facilities by strengthening poorly performing units. The PCs with a high percentage Private Sector Notification can act as role models for neighbouring PCs to improve private sector engagement. MPs can play a crucial role in mobilising additional resources, creating awareness, and establishing inter-PC and inter-state collaboration to improve TB program performance. }, url = {https://doi.org/10.1111/tmi.13574}, author = {Geeta Pardeshi and Weiyu Wang and Julie Kim and et al.} } @article {1667864, title = {Multilevel analysis of geographic variation among correlates of child undernutrition in India}, journal = {Maternal \& Child Nutrition}, volume = {17}, number = {3}, year = {2022}, pages = {e13197}, abstract = {Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual-level risk factors are geographically distributed. Assessing the geographic distribution, especially at multiple levels, matters as it can inform where, and at what level, interventions should be targeted. The three levels of significance in the Indian context are villages, districts, and states. Thus, the purpose of this paper was to (a) examine what proportion of the variation in 21 risk factors is attributable to villages, districts, and states in India and (b) elucidate the specific states where these risk factors are clustered within India. Using the fourth National Family Health Survey dataset, from 2015 to 2016, we found that the proportion of variation attributable to villages ranged from 14\% to 63\%, 10\% to 29\% for districts and 17\% to 62\% for states. Furthermore, we found that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh were in the highest risk quintile for more than 10 of the risk factors included in our study. This is an indication of geographic clustering of risk factors. The risk factors that are clustered in states such as Bihar, Jharkhand, Madhya Pradesh and Uttar Pradesh underscore the need for policies and interventions that address a broader set of child malnutrition determinants beyond those that are nutrition specific.}, url = {https://doi.org/10.1111/mcn.13197}, author = {Anoop Jain and Rodgers, Justin and Li, Zhihui and et al.} } @article {1667862, title = {Trends in underweight, stunting, and wasting prevalence and inequality among children under three in Indian states, 1993{\textendash}2016}, journal = {Scientific Reports}, volume = {11}, number = {1}, year = {2022}, pages = {1-11}, abstract = {Child undernutrition remains high in India with far-reaching consequences for child health and development. Anthropometry reflects undernutrition. We examined the state-level trends in underweight, stunting, and wasting prevalence and inequality by living standards using four rounds of the National Family Health Surveys in 26 states in India, conducted in 1992{\textendash}1993, 1998{\textendash}1999, 2005{\textendash}2006, and 2015{\textendash}2016. The average annual reduction (AAR) for underweight ranged from 0.04 percentage points (pp) (95\% CI - 0.12, 0.20) in Haryana to 1.05\ pp (95\% CI 0.88, 1.22) in West Bengal for underweight; 0.35\ pp (95\% CI 0.11, 0.59) in Manipur to 1.47 (95\% CI 1.19, 1.75) in Himachal Pradesh for stunting; and - 0.65\ pp (95\% CI - 0.77, - 0.52) in Haryana to 0.36\ pp (95\% CI 0.22, 0.51) in Bihar \& Jharkhand for wasting. We find that change in the pp difference between children with the poorest and richest household living standards varied by states: statistically significant decline (increase) was observed in 5 (3) states for underweight, 5 (4) states for stunting, and 2 (1) states for wasting. Prevalence of poor anthropometric outcomes as well as disparities by states and living standards remain a problem in India.}, url = {https://doi.org/10.1038/s41598-021-93493-1}, author = {Karlsson, Omar and Rockli Kim and Rakesh Sarwal and et al.} } @article {1667599, title = {Estimating the Burden of Child Undernutrition for Smaller Electoral Units in India}, journal = {JAMA Network Open}, volume = {4}, number = {10}, year = {2022}, pages = { e2129416-e2129416}, abstract = { Importance\ \ Geographic targeting of public health interventions is needed in resource-constrained developing countries. Objective\ \ To develop methods for estimating health and development indicators across micropolicy units, using assembly constituencies (ACs) in India as an example. Design, Setting, and Participants\ \ This cross-sectional study included children younger than 5 years who participated in the fourth National Family and Health Survey (NFHS-4), conducted between January 2015 and December 2016. Participants lived in 36 states and union territories and 640 districts in India. Children who had valid weight and height measures were selected for stunting, underweight, and wasting analysis, and children between age 6 and 59 months with valid blood hemoglobin concentration levels were included in the anemia analysis sample. The analysis was performed between February 1 and August 15, 2020. Exposures\ \ A total of 3940 ACs were identified from the geographic location of primary sampling units in which the children{\textquoteright}s households were surveyed in NFHS-4. Main Outcomes and Measures\ \ Stunting, underweight, and wasting were defined according to the World Health Organization Child Growth Standards. Anemia was defined as blood hemoglobin concentration less than 11.0 g/dL. Results\ \ The main analytic sample included 222 172 children (mean [SD] age, 30.03 [17.01] months; 114 902 [51.72\%] boys) from 3940 ACs in the stunting, underweight, and wasting analysis and 215 593 children (mean [SD] age, 32.63 [15.47] months; 112 259 [52.07\%] boys) from 3941 ACs in the anemia analysis. The burden of child undernutrition varied substantially across ACs: from 18.02\% to 60.94\% for stunting, with a median (IQR) of 35.56\% (29.82\%-42.42\%); from 10.40\% to 63.24\% for underweight, with a median (IQR) of 32.82\% (25.50\%-40.96\%); from 5.56\% to 39.91\% for wasting, with a median (IQR) of 19.91\% (15.70\%-24.27\%); and from 18.63\% to 83.05\% for anemia, with a median (IQR) of 55.74\% (48.41\%-63.01\%). The degree of inequality within states varied across states; those with high stunting, underweight, and wasting prevalence tended to have high levels of inequality. For example, Uttar Pradesh, Jharkhand, and Karnataka had high mean AC-level prevalence of child stunting (Uttar Pradesh, 45.29\%; Jharkhand, 43.76\%; Karnataka, 39.77\%) and also large SDs (Uttar Pradesh, 6.90; Jharkhand, 6.02; Karnataka, 6.72). The Moran\ I\ indices ranged from 0.25 to 0.80, indicating varying levels of spatial autocorrelation in child undernutrition across the states in India. No substantial difference in AC-level child undernutrition prevalence was found after adjusting for possible random displacement of geographic location data. Conclusions and Relevance\ \ In this cross-sectional study, substantial inequality in child undernutrition was found across ACs in India, suggesting the importance of considering local electoral units in designing targeted interventions. The methods presented in this paper can be further applied to measuring health and development indicators in small electoral units for enhanced geographic precision of public health data in developing countries. }, url = {http://doi.org/:10.1001/jamanetworkopen.2021.29416}, author = {Julie Kim and Yuning Liu and Weiyu Wang and et al.} } @article {1667598, title = {The relative importance of households as a source of variation in child malnutrition: a multilevel analysis in India}, journal = {International Journal for Equity in Health}, volume = {20}, number = {1}, year = {2022}, pages = {1-11}, abstract = { Background Child malnutrition remains a major public health issue in India. Along with myriad upstream and social determinants of these adverse outcomes, recent studies have highlighted regional differences in mean child malnutrition rates. This research helps policy makers look between urban and rural communities and states to take a population-level approach to addressing the root causes of child malnutrition. However, one gap in this between-population approach has been the omission of households as a unit of analysis. Households could represent important sources of variation in child malnutrition within communities, districts, and states. Methods Using the fourth round of India{\textquoteright}s National Family Health Survey from 2015 to 2016, we analyzed four and five-level multilevel models to estimate the proportion of variation in child malnutrition attributable to states, districts, communities, households, and children. Results Overall, we found that of the four levels that children were nested in (households, communities, districts, and states), the greatest proportion of variation in child height-for-age Z score, weight-for-age Z score, weight-for-height Z score, hemoglobin, birthweight, stunting, underweight, wasting, anemia, and low birthweight was attributable to households. Furthermore, we found that when the household level is omitted from models, the variance estimates for communities and children are overestimated. Conclusions These findings highlight the importance of households as an important source of clustering and variation in child malnutrition outcomes. As such, policies and interventions should address household-level social determinants, such as asset and social deprivations, in order to prevent poor child growth outcomes among the most vulnerable households in India. }, url = {https://doi.org/10.1186/s12939-021-01563-7}, author = {Anoop Jain and Rodgers, Justin and Rockli Kim and et al.} } @article {1667596, title = {Geographic variation in caesarean delivery in India}, journal = {Epidemiology}, volume = {36}, number = {1}, year = {2022}, pages = {92-103}, abstract = { Background The rate of caesarean delivery has increased markedly both globally and within India. However, there is considerable variation within countries. No previous studies have examined the relative importance of multiple geographic levels in shaping the distribution of caesarean delivery and to what extent they can be explained by individual-level risk factors. Objectives To describe geographic variation in caesarean delivery and quantify the contribution of individual-level risk factors to the variation in India. Methods We conducted four-level logistic regression analysis to partition total variation in caesarean delivery to three geographic levels (states, districts and communities) and quantify the extent to which variance at each level was explained by a set of 20 sociodemographic, medical and institutional risk factors. Stratified analyses were conducted by the type of delivery facility (public/private). Results Overall prevalence of caesarean delivery was 19.3\% in India in 2016. Most geographic variation was attributable to states (44\%), followed by communities (32\%), and lastly districts (24\%). Adjustment for all risk factors explained 44\%, 52\% and 46\% of variance for states, districts and communities, respectively. The proportion explained by individual risk factors was larger in public facilities than in private facilities at all three levels. A substantial proportion of between-population variation still existed even after clustering of individual risk factors was comprehensively adjusted for. Conclusions Diverse contextual factors driving high or low rate of caesarean delivery at each geographic level should be explored in future studies so that tailored intervention can be implemented to reduce the overall variation in caesarean delivery. }, url = {https://doi.org/10.1111/ppe.12807}, author = {Rodgers, Justin and Lee, Hwa-Young and Rockli Kim and et al.} } @article {1667595, title = {The Associations between Member of Parliament Characteristics and Child Malnutrition and Mortality in India}, journal = {Health Systems \& Reform}, volume = {8}, number = {1}, year = {2022}, pages = {e2030291}, abstract = {Child health outcomes vary between Parliamentary Constituencies (PCs) in India. There are a total of 543 PCs in India, each of which is a geographical unit represented by a Member of Parliament (MP). MP characteristics, such as age, gender, education, the number of terms they have served, and whether they belong to a Scheduled Caste or Scheduled Tribe, might be associated with indicators of child malnutrition and child mortality. The purpose of this paper was to examine the associations between MP characteristics and measures of child malnutrition and mortality. We did not find any meaningful associations between MP characteristics and child anthropometry, anemia, and mortality. Future research should consider the size of a constituency served by an MP along with MP party affiliations as these factors might help explain between-PC variations in child health outcomes. Our findings also underscore the need to better support female MPs and MPs from marginalized caste and tribal groups.}, url = {https://doi.org/10.1080/23288604.2022.2030291}, author = {Anoop Jain and Rockli Kim and Subramanian, S. V. and et al.} } @article {1667594, title = {Small area variation in severe, moderate, and mild anemia among women and children: A multilevel analysis of 707 districts in India}, journal = {Frontiers in Public Health}, volume = {10}, year = {2022}, url = {https://doi.org/10.3389/fpubh.2022.945970}, author = {Rajpal, Sunil and Akhil Kumar and Md Juel Rana and et al.} } @article {1667593, title = {COVID-19 metrics across parliamentary constituencies and districts in India}, journal = {Annals of GIS}, volume = {28}, number = {4}, year = {2022}, pages = {435-443}, abstract = {In India, Parliamentary Constituencies (PCs) could serve as a regional unit of COVID-19 monitoring that facilitates evidence-based policy decisions. In this study, we presented the first estimates of COVID-19 cumulative cases and deaths per 100,000 population and the case fatality rate (CFR) between 7 January 2020 and 31 January 2021 across PCs and districts of India. We adopted a novel geographic information science-based methodology called crosswalk to estimate COVID-19 outcomes at the PC-level from district-level information. We found a substantial variation of COVID-19 burden within each state and across the country. Access to PC-level and district-level COVID-19 information can enhance both central and regional governmental accountability of safe reopening policies.}, url = {https://doi.org/10.1080/19475683.2022.2044903}, author = {Weiyu Wang and Jeffrey Blossom and Julie Kim and et al.} } @article {1667472, title = {Small area variations in low birth weight and small size of births in India}, journal = {Maternal and Child Nutrition}, volume = {18}, number = {3}, year = {2022}, pages = {e13369}, abstract = {The states and districts are the primary focal points for policy formulation and programme intervention in India. The within-districts variation of key health indicators is not well understood and consequently underemphasised. This study aims to partition geographic variation in low birthweight (LBW) and small birth size (SBS) in India and geovisualize the distribution of small area estimates. Applying a four-level logistic regression model to the latest round of the National Family Health Survey (2015{\textendash}2016) covering 640 districts within 36 states and union territories of India, the variance partitioning coefficient and precision-weighted prevalence of LBW (\<2.5 kg) and SBS (mother{\textquoteright}s self-report) were estimated. For each outcome, the spatial distribution by districts of mean prevalence and small area variation (as measured by standard deviation) and the correlation between them were computed. Of the total valid sample, 17.6\% (out of 193,345 children) had LBW and 12.4\% (out of 253,213 children) had SBS. The small areas contributed the highest share of total geographic variance in LBW (52\%) and SBS (78\%). The variance of LBW attributed to small areas was unevenly distributed across the regions of India. While a strong correlation between district-wide percent and within-district standard deviation was identified in both LBW (r = 0.88) and SBS (r = 0.87), they were not necessarily concentrated in the aspirational districts. We find the necessity of precise policy attention specifically to the small areas in the districts of India with a high prevalence of LBW and SBS in programme formulation and intervention that may be beneficial to improve childbirth outcomes.}, url = {https://doi.org/10.1111/mcn.13369}, author = {Md Juel Rana and Rockli Kim and Soohyeon Ko} } @article {1667466, title = {Components of Out-of-Pocket Expenditure and Their Relative Contribution to Economic Burden of Diseases in India}, journal = {JAMA Network Open}, volume = {5}, number = {5}, year = {2022}, pages = {e2210040}, abstract = { 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. }, url = {https://doi.org/10.1001/jamanetworkopen.2022.10040}, author = {Mayanka Ambade and Rakesh Sarwal and Nachiket Mor and et al.} } @article {1667464, title = {Spatial Variations of Village-Level Environmental Variables from Satellite Big Data and Implications for Public Health{\textendash}Related Sustainable Development Goals}, journal = { Sustainability}, volume = {14}, number = {16}, year = {2022}, pages = {10450}, abstract = {The United Nations Sustainable Development Goals (SDGs) include 17 interlinked goals designed to be a blueprint for the world{\textquoteright}s nations to achieve a better and more sustainable future, and the specific SDG 3 is a public health{\textendash}related goal to ensure healthy living and promote well-being for all population groups. To facilitate SDG planning, implementation, and progress monitoring, many SDG indicators have been developed. Based on the United Nations General Assembly resolutions, SDG indicators need to be disaggregated by geographic locations and thematic environmental and socioeconomic characteristics for achieving the most accurate planning and progress assessment. High-resolution data such as those captured at the village level can provide comparatively more precise insights into the different socioeconomic and environmental factors relevant to SDGs, therefore enabling more effective sustainable development decision-making. Using India as our study area and the child malnutrition indicators stunting, underweight, and wasting as examples of public health{\textendash}related SDG indicators, we have demonstrated a process to effectively derive environmental variables at the village level from satellite big datasets on a cloud platform for SDG research and applications. Spatial analysis of environmental variables regarding vegetation, climate, and terrain have shown spatial grouping patterns across the entire study area, with each village group having different statistics. Correlation analysis between these environmental variables and stunting, underweight, and wasting indicators show a meaningful relationship between these indicators and vegetation index, land surface temperature, rainfall, elevation, and slope. Identifying the spatial variation patterns of environmental variables at the village level and their correlations with child malnutrition indicators can be an invaluable tool to facilitate a clearer understanding of the causes of child malnutrition and to improve area-specific SDG 3 implementation planning. This analysis can also provide meaningful support in assessing and monitoring SDG implementation progress at the village level by spatially predicting SDG indicators using available socioeconomic and environmental independent variables. The methodology used in this study has the potential to be applied to other similar regions, especially low-to-middle income countries where a high number of children are severely affected by malnutrition, as well as to other environmentally related SDGs, such as Goal 1 (No Poverty) and Goal 2 (Zero Hunger).}, url = {https://doi.org/10.3390/su141610450}, author = {Xue Liu and Rockli Kim and Weixing Zhang and et al} } @article {1651331, title = {COVID-19 metrics across parliamentary constituencies and districts in India}, journal = {Annals of GIS}, year = {2022}, author = {Weiyu Wang and Jeffrey Blossom and Julie Kim and Priyanka deSouza and Weixing Zhang and Rockli Kim and Rakesh Sarwal and Subramanian, S V} } @article {1651329, title = {TB notification rates across parliamentary constituencies in India: a step towards data-driven political engagement}, journal = {Tropical Medicine and International Health}, year = {2021}, author = {Geeta Pardeshi and Weiyu Wang and Julie Kim and Jeffrey Blossom and Rockli Kim and Subramanian, S. V.} } @article {1603570, title = {TB notification rates across parliamentary constituencies in India: a step towards data-driven political engagement}, journal = {Tropical Medicine \& International Health}, volume = {26}, number = {7}, year = {2021}, pages = {730-742}, abstract = { \  ObjectiveNational averages obscure geographic variation in program performance. We determined Parliamentary Constituency (PC)-wise estimates of TB notification to guide political engagement. MethodsWe extracted district-level TB notification data from the 2018 annual TB report. We derived PC-level estimates by building a {\textquoteleft}cross-walk{\textquoteright} between districts and PCs using boundary shapefiles. We described the spatial distribution of the PC-wise estimates of Total Notification Rate and percentage of Private Sector Notification. ResultsThe median PC-wise Total Notification Rate was 126.24/100 000 (IQR: 94.86/100 000, 162.22/100 000). The median PC-wise Percentage Private Sector Notification was 18.03\% (IQR: 9.56\%, 26.84\%). Only 16 (2.94\%) PCs met the target of 50\% private sector notification. Most of high notification rates in PCs were driven by high notification in public sector. There was geographic {\textendash} both interstate and within state inter-PC {\textendash} variation in the estimates of these indicators. The study identified some geographic patterns of notification {\textendash} high positive outlier PCs with adjoining PCs in lower deciles of notification rates, intra-state differences in PC performance, and similarities in notification rates of adjoining PCs in different states. ConclusionIn addition to regional inequality, the study identified geospatial patterns that can aid in the formulation of suitable interventions. These include decongestion of overburdened facilities by strengthening poorly performing units. The PCs with a high percentage Private Sector Notification can act as role models for neighbouring PCs to improve private sector engagement. MPs can play a crucial role in mobilising additional resources, creating awareness, and establishing inter-PC and inter-state collaboration to improve TB program performance. \  }, url = {https://doi.org/10.1111/tmi.13574}, author = {Geeta Pardeshi and Weiyu Wang and Julie Kim and Jeffrey Blossom and Rockli Kim and Subramanian, S V} } @article {1595377, title = {Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {118}, number = {18}, year = {2021}, abstract = {There are emerging opportunities to assess health indicators at truly small areas with increasing availability of data geocoded to micro geographic units and advanced modeling techniques. The utility of such fine-grained data can be fully leveraged if linked to local governance units that are accountable for implementation of programs and interventions. We used data from the 2011 Indian Census for village-level demographic and amenities features and the 2016 Indian Demographic and Health Survey in a bias-corrected semisupervised regression framework to predict child anthropometric failures for all villages in India. Of the total geographic variation in predicted child anthropometric failure estimates, 54.2 to 72.3\% were attributed to the village level followed by 20.6 to 39.5\% to the state level. The mean predicted stunting was 37.9\% (SD: 10.1\%; IQR: 31.2 to 44.7\%), and substantial variation was found across villages ranging from less than 5\% for 691 villages to over 70\% in 453 villages. Estimates at the village level can potentially shift the paradigm of policy discussion in India by enabling more informed prioritization and precise targeting. The proposed methodology can be adapted and applied to diverse population health indicators, and in other contexts, to reveal spatial heterogeneity at a finer geographic scale and identify local areas with the greatest needs and with direct implications for actions to take place.}, author = {Rockli Kim and Avleen S Bijral and Yun Xu and Xiuyuan Zhang and Blossom, Jeffrey C and Akshay Swaminathan and Gary King and Alok Kumar and Rakesh Sarwal and Juan M Lavista Ferres and Subramanian, S V} } @article {1582328, title = {Small area variation in child undernutrition across 640 districts and 543 parliamentary constituencies in India}, journal = {Scientific Reports}, volume = {11}, number = {1}, year = {2021}, month = {Feb}, pages = {4558}, abstract = {In India, districts serve as central policy unit for program development, administration and implementation. The one-size-fits-all approach based on average prevalence estimates at the district level fails to capture the substantial small area variation. In addition to district average, heterogeneity within districts should be considered in policy design. The objective of this study was to quantify the extent of small area variation in child stunting, underweight and wasting across 36 states/Union Territories (UTs), 640 districts (and 543 PCs), and villages/blocks in India. We utilized the 4th round of Indian National Family Health Survey (NFHS-4) conducted in 2015{\textendash}2016. The study population included 225,002 children aged 0{\textendash}59\ months whose height and weight information were available. Stunting was defined as height-for-age z-score below 2 SD from the World Health Organization child growth reference standards. Similarly, underweight and wasting were each defined as weight-for-age{\th}inspace}\< -2 SD and weight-for-height{\th}inspace}\< -2 SD from the age- and sex-specific medians. We adopted a four-level logistic regression model to partition the total variation in stunting, underweight and wasting. We computed precision-weighted prevalence of child anthropometric failures across districts and PCs as well as within-district/PC variation using standard deviation (SD) measures. For stunting, 56.4\% (var: 0.237; SE: 0.008) of the total variation was attributed to villages/blocks, followed by 25.8\% (var: 0.109; SE: 0.030) to states/UTs, and 17.7\% (Var: 0.074; SE: 0.006) to districts. For underweight and wasting, villages/blocks accounted for 38.4\% (var: 0.224; SE: 0.007) and 50\% (var: 0.285; SE: 0.009), respectively, of the total contextual variance in India. Similar findings were shown in multilevel models incorporating PC as a geographical unit instead of districts. We found high positive correlations between mean prevalence and SD for stunting (r{\th}inspace}={\th}inspace}0.780, p{\th}inspace}\<{\th}inspace}0.001), underweight (r{\th}inspace}={\th}inspace}0.860, p{\th}inspace}\<{\th}inspace}0.001), and wasting (r{\th}inspace}={\th}inspace}0.857, p{\th}inspace}\<{\th}inspace}0.001) across all districts in India. A similar pattern of correlation was found for PCs. Within-district and within-PC variation are the primary source of variation for child malnutrition in India. Our results suggest the importance of considering heterogeneity within districts and PCs when planning and administering child nutrition policies.}, doi = {10.1038/s41598-021-83992-6}, author = {Rajpal, S. and Kim, J. and W. Joe and Kim, R. and Subramanian, S V} } @article {1651328, title = {Geo-Mapping of COVID-19 Risk Correlates Across Districts and Parliamentary Constituencies in India}, journal = {Harvard Data Science Review}, year = {2020}, author = {Subramanian, S V and Karlsson, Omar and Weixing Zhang and Rockli Kim} } @article {1651327, title = {Estimating vulnerability to COVID-19 in India}, journal = {The Lancet Global Health}, year = {2020}, author = {Rockli Kim and Subramanian, S V} } @article {1582338, title = {Child Undernutrition and Convergence of Multisectoral Interventions in India: An Econometric Analysis of National Family Health Survey 2015{\textendash}16}, journal = {Frontiers in Public Health}, volume = {8}, year = {2020}, pages = {129}, publisher = {Frontiers}, abstract = { In India and worldwide, there has been increased strategic focus on multisectoral convergence of nutrition-specific and nutrition-sensitive interventions to attain rapid reductions in child undernutrition. For instance, a Convergence Action Plan in India has been formed to synchronize and converge various nutrition-related interventions across ministries of union and state governments under a single umbrella. Given the large variation in number, nature and impact of these interventions, this paper aims to quantify the contribution of each intervention (proxied by relevant covariates) toward reducing child stunting and underweight in India. The interventions are classified under six sectors: (a) health, (b) women and child development, (c)education, (d) water, sanitation, and hygiene, (e) clean energy, and (f) growth sector. We estimate the potential reduction in child stunting and underweight in a counterfactual scenario of {\textquotedblleft}convergence{\textquotedblright} where all the interventions across all the sectors are simultaneously and successfully implemented. The findings from our econometric analysis suggests that under this counterfactual scenario, a reduction of 18.37\% points (95\% CI: 16.77; 19.95) in stunting and 20.26\% points (95\% CI: 19.13; 21.39) in underweight can be potentially achieved. Across all the sectors, women and child development and clean energy were identified as the biggest contributors to the potential reductions in stunting and underweight, underscoring the importance of improving sanitation-related practices and clean cooking fuel. The overall impact of this convergent action was relatively stronger for less developed districts. These findings reiterate a clear role and scope of convergent action in achieving India{\textquoteright}s national nutritional goals. This warrants a complete outreach of all the interventions from different sectors. }, isbn = {2296-2565}, author = {Rajpal, Sunil and William Joe and Rockli Kim and Alok Kumar and Subramanian, S V} } @article {1582334, title = {COVID-19 across United States congressional districts}, journal = {Journal of Global Health Sciences}, volume = {2}, number = {22}, year = {2020}, abstract = { The congressional district (CD) geography in the United States (US) represents a policy-relevant and a politically important scale at which to monitor the coronavirus disease 2019 (COVID-19) crisis. In this study, we present the first estimates of COVID-19 cumulative cases and deaths (per 1,000 people) and the case fatality rate as of July 13, 2020, as well as for the recent period between June 13 and July 13, 2020 using a population-weighting methodology for the 436 CDs in the US. Access to CD-level information about the impact of COVID-19 can enhance the ability of elected officials and the constituents they represent, to monitor and develop testing strategies and other measures to allow the US to open safely. }, author = {PN deSouza and Subramanian, S V} } @database {1582335, title = {COVID-19 across United States congressional districts for three cumulative time periods}, year = {2020}, abstract = {The data replicate tables and figures from "COVID-19 across United States congressional districts", by deSouza and Subramanian. (2020-07-20)}, author = {PN deSouza and Subramanian, S V} } @article {1582339, title = {Dietary Variation among Children Meeting and Not Meeting Minimum Dietary Diversity: An Empirical Investigation of Food Group Consumption Patterns among 73,036 Children in India}, journal = {The Journal of Nutrition}, volume = {150}, number = {10}, year = {2020}, pages = {2818-2824}, publisher = {Oxford University Press}, abstract = { Minimum Dietary Diversity (MDD) is a widely used indicator of adequatedietary micronutrient density for children 6{\textendash}23 mo old. MDD food-group dataremain underutilized, despite their potential for further informing nutritionprograms and policies. We aimed to describe the diets of children meetingMDD and not meeting MDD in India using food group data, nationally andsubnationally. Food group data for children 6{\textendash}23 mo old (n = 73,036) fromthe 2015{\textendash}16 National Family Health Survey in India were analyzed. Per WHOstandards, children consuming >=5 of the following food groups in the pastday or night met MDD: breast milk; grains, roots, or tubers; legumes or nuts;dairy; flesh foods; eggs; vitamin A{\textendash}rich fruits and vegetables; and other fruitsand vegetables. Children not meeting MDD consumed \<5 food groups. Weanalyzed the number and types of foods consumed by children meetingMDD and not meeting MDD at the national and subnational geographiclevels. Nationally, children not meeting MDD most often consumed breastmilk (84.5\%), grains, roots, and tubers (62.0\%), and/or dairy (42.9\%). Childrenmeeting MDD most often consumed grains, roots, and tubers (97.6\%), vitaminA{\textendash}rich fruits and vegetables (93.8\%), breast milk (84.1\%), dairy (82.1\%), otherfruits and vegetables (79.5\%), and/or eggs (56.5\%). For children not meetingMDD, district-level dairy consumption varied the most (6.4\%{\textendash}79.9\%), whereasflesh foods consumption varied the least (0.0\%{\textendash}43.8\%). For children meetingMDD, district-level egg consumption varied the most (0.0\%{\textendash}100.0\%), whereasgrains, roots, and tubers consumption varied the least (66.8\%{\textendash}100.0\%).Children not meeting MDD had low fruit, vegetable, and protein-rich foodconsumption. Many children meeting MDD also had low protein-rich foodconsumption. Examining the number and types of foods consumed highlightspriorities for children experiencing the greatest dietary deprivation, providingvaluable complementary information to MDD. }, isbn = {0022-3166}, author = {Beckerman-Hsu, Jacob P and Rockli Kim and Sharma, Smriti and Subramanian, S V} } @article {1582340, title = {Does the Choice of Metric Matter for Identifying Areas for Policy Priority? An Empirical Assessment Using Child Undernutrition in India}, journal = {Social Indicators Research}, volume = {152}, number = {3}, year = {2020}, pages = {823-841}, publisher = {Springer}, abstract = { Ratio-based prevalence and absolute headcounts are the two mostcommonly accepted metrics to measure the burden of various socioeconomicphenomenon. However, ratio-based prevalence, calculated as the number ofcases with certain conditions relative to the total population, is by far themost widely used to rank burden and consequently for targeting, acrossdifferent populations, often defined in terms of geographical areas. In thisregard, targeting areas exclusively based on prevalence-based metric posescertain fundamental difficulties with some serious policy implications.Drawing the data from the National Family Health Survey 2015{\textendash}2016, andCensus 2011, this paper takes four indicators of child undernutrition in Indiaas an example to examine two contextual questions: first, does the choiceof metric matter for targeting areas for reducing child undernutrition inIndia? and second; which metric should be used to facilitate comparisonsand targeting across variable populations? Our findings suggest a moderatecorrelation between prevalence estimates and absolute headcounts implyingthat choice of metric does matter when targeting child undernutrition. Hugevariations were observed between prevalence-based and absolute countbasedranking of the districts. In fact, in various cases, districts with thehighest absolute number of undernourished children were ranked as relativelylower-burden districts based on prevalence. A simple comparison betweenthe two approaches{\textemdash}when applied to targeting undernourished children inIndia{\textemdash}indicates that prevalence-based prioritization may miss high-burdenareas where substantially higher number of undernourished children areconcentrated. For developing populous countries like India, which is alreadygrappling with high levels of maternal and child malnutrition and poor healthinfrastructure along with intrinsic socioeconomic inequalities, it is critical toadopt an appropriate metric for effective targeting and prioritization. }, isbn = {1573-0921}, author = {Rajpal, Sunil and Rockli Kim and Liou, Lathan and William Joe and Subramanian, S V} } @article {1582341, title = {Frequently asked questions on child anthropometric failures in India}, journal = {Joe, William and Kim, Rockli and Kumar, Alok and Sankar, Rajan and Rajpal, Sunil and Subramanian, SV, Frequently Asked Questions on Child Anthropometric Failures in India (February 8, 2020). Economic \& Political Weekly}, volume = {55}, number = {6}, year = {2020}, abstract = { The National Family Health Survey is analysed to develop critical insights on child anthropometric failure in India. The analysis finds non-response of economicgrowth on nutritional well-being and greater burden among the poor as twofundamental concerns. This calls for strengthening developmental financefor socio-economic upliftment as well as enhanced programmatic supportfor nutritional interventions. The gaps in analytical inputs for programmaticpurposes also deserves attention to unravel intricacies that otherwise remainobscured through customary enquiries. On the one hand, this may serve wellto improve policy targeting, and on the other, this can help comprehend thenature and reasons of heterogeneities and inequities in nutritional outcomesacross subgroups. Strengthening the analytical capacities of programmemanagers and health functionaries is recommended.Against this backdrop,this paper outlines key programmatic concerns that require substantiallocal-level insights for strategic feedback and course corrections to achieveaccelerated reductions in child undernutrition. The issues discussed are basedon the analysis of household survey data from NFHS 2015{\textendash}16. }, author = {Rajpal, Sunil and Rockli Kim and Sankar, Rajan and Alok Kumar and William Joe and Subramanian, S V} } @article {1582331, title = {Geo-visualising Diet, Anthroprometric and Clinical Indicators for Children in India}, journal = {Harvard Dataverse}, year = {2020}, abstract = { Researchers from the Geographic Insights Lab at the Harvard Center for Population and Development Studies and the Institute of Economic Growth geo-visualised diet, anthropometric and clinical indicators for children across districts in India and provide a clear snapshot of high priority districts for targeting nutritional interventions among children in India. }, author = {Subramanian, S V and R Sarwal and J William and Kim, R} } @article {1582342, title = {Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India}, journal = {SSM-population health}, volume = {10}, year = {2020}, pages = {100524}, publisher = {Elsevier}, abstract = { We assessed district-level geospatial trends in precision weighted prevalenceand absolute wealth disparity in stunting, underweight, wasting, lowbirthweight, and anemia among children under five in India. The largestwealth disparities were found for anthropometric failures and substantialvariation existed across states. We identified statistically significant (p \< 0.001)geospatial patterns in district-wide wealth disparities for all outcomes, whichdiffered from geospatial patterns for the overall prevalence. We characterizedeach district as either a {\textquotedblleft}Disparity{\textquotedblright}, {\textquotedblleft}Pitfall{\textquotedblright}, {\textquotedblleft}Intensity{\textquotedblright}, or {\textquotedblleft}Prosperity{\textquotedblright} areabased on its overall burden and wealth disparity, as well as discuss theimportance of considering both measures for geographically-targeted publichealth interventions to improve health equity. }, isbn = {2352-8273}, author = {Liou, Lathan and Rockli Kim and Subramanian, S V} } @webarticle {1582329, title = {It{\textquoteright}s not yet mission accomplished on the Centre{\textquoteright}s Poshan Abhiyaan}, journal = {Mint}, year = {2020}, abstract = { While some improvement has been made by the country, efforts to ensure nutritional security are more important than ever \  It{\textquoteright}s been three years since the Government of India launched the Prime Minister{\textquoteright}s Overarching Scheme for Holistic Nutrition, or Poshan Abhiyaan . The goal was to improve the nutritional status of children and adolescent girls, as well as pregnant and lactating mothers. The urgency was evident as a clear time-frame of three years was set, and five indicators{\textemdash}prevalence of low birthweight, stunting, underweight and anaemia among children and women{\textemdash}were identified for substantial improvement. The government showed its commitment by putting money where its mouth was; it allocated ₹9,046.17 crore for the mission. \  The trigger to go on an all-India mission was the disconcerting statistics revealed by the fourth National Family Health Survey (NFHS-4, 2015-16) on the above indicators. The fact sheets for 342 districts from 17 states and five Union territories (UTs) from the NFHS-5 , (bit.ly/2WQA51y) conducted in 2019-20, are now out. With the exception of prevalence of low birthweight, the just released district fact sheets provide data on four of the five Poshan Abhiyaan indicators. So, how have the 342 districts done with regard to meeting the targets set? \  Comparing performance across districts: Of the four indicators, stunting across districts improved the most, with 69/342 districts experiencing a decline of more than 6 percentage points (the Poshan Abhiyaan target) between the two surveys. Child underweight followed a pattern similar to stunting with 42/342 districts meeting the target. Anaemia, however, is a different story; the Poshan Abhiyaan target of a 9-percentage-point decline in three years was observed for only 18/342 (women and adolescent girls) and 20/342 (children) districts. \  \  [[{"fid":"3881956","view_mode":"default","type":"media","attributes":{"height":"291","width":"535","alt":"A Mixed Bag","class":"media-element file-default"}}]] Some degree of decline in the prevalence of stunting and underweight was observed in nearly half of the districts. At the same time, a little over half of them also disconcertingly experienced a reversal. In 74/342 (stunting) and 66/342 (underweight) districts, the reversal was of the same magnitude as the target (i.e., 6 percentage point), but in the detrimental direction. \  Anaemia not only showed minimal improvement across districts, it reversed in 81.3\% (278/342 for children) and 74.3\% (254/342 for adolescent girls/women) of the districts. Disturbingly, the reversal was greater than 9 percentage points in 186/342 (children) and 139/342 (adolescent girls and women) districts. The way forward: The following two insights emerging from the data patterns would be crucial to consider if India chooses to upgrade and implement Poshan Abhiyaan 2.0. \  First, within the same state, there are districts that experienced improvement as well as reversal, especially with regards to stunting and underweight findings. It is important that an immediate effort is made to learn from both success and failure in these districts. Such learning can focus on both the distinct components of the Poshan Abhiyaan programme, as well as how synergistically they were implemented. Second, the fact that a notable number of districts experienced improvement and reversal suggests that inequality between districts (even within the same state) has increased. This might be an unintended consequence of a concentrated focus on certain districts over others in recent years. \  Prioritizing certain districts over others is inevitable in any policy formulation and implementation. An examination of the districts that experienced substantial improvement or reversal, and whether they were priority districts for Poshan Abhiyaan or not would be necessary. Learning from this should then be used to modify or tweak using other methods for prioritization, both for efficiency as well as for promoting geographic equity. Further indicator-specific prioritization is also necessary as the data reveals different patterns for anthropometric-based nutritional measures of stunting/underweight from the more direct measures of dietary deficiency. \  Recent evidence also makes it clear that it would be prudent to equally focus on within-district variation, in particular between villages. Villages are not only a setting for social engagement, but also are the unit where public policies and programmes come to fruition for the target population. The three-year time-frame of Poshan Abhiyaan, incidentally, ended this month. It is unclear what the future of Poshan Abhiyaan will be. Regardless, the NFHS-5 data makes it obvious that reducing the burden of undernutrition, especially among children and women, will need to remain a greater priority than ever before. It is, therefore, imperative that the government undertakes a rigorous assessment of Poshan Abhiyaan, including an exploration of any changes and course corrections that may be necessary. \  It is critical to remember that these statistics reflect a scenario prior to the covid pandemic and the 2020 lockdown. From all accounts, these two events hurt health and nutrition services, which are vital to any child{\textquoteright}s first 1,000 days and a core feature of Poshan Abhiyaan. Whatever form the next phase of India{\textquoteright}s mission to eliminate undernutrition takes, reversals experienced by a majority of districts on nutrition indicators suggest that India needs to make food security a centrepiece of its overall development agenda. Laxmi Kant Dwivedi of International Institute for Population Sciences and Weiyu Wang and Weixing Zhang of Harvard Center for Population and Development Studies assisted with this article. \  S.V. Subramanian is professor of population health and geography, Harvard Center for Population and Development Studies. }, author = {Subramanian, S V} } @article {1582336, title = {Lessons from COVID-19 pandemic for the child survival agenda}, journal = {Journal of Global Health}, volume = {10}, number = {2}, year = {2020}, abstract = { The public discourse around the COVID-19 pandemic has been strikingly quantitative. Worldwide, the mainstream media has regularly informed the public of confirmed COVID-19 cases and deaths, including projections of worst-case scenarios drawn from esoteric epidemiological models. The prominence and visibility of data, regardless of its completeness or quality, underscored the threat of COVID-19 to policy makers and lay individuals alike. It also prompted governments to swiftly lock down their societies, despite the socioeconomic disruptions and human suffering associated with such lockdowns. The widespread media coverage of COVID-19 data and swift response from governments highlight the potency of real-time data, and contain important lessons for public health policy, which when applied, could raise the profile of other health issues and spur action among key stakeholders. }, author = {Subramanian, S V and Chatterjee, Pritha and Karlsson, Omar} } @article {1582343, title = {Living on the edge? Sensitivity of child undernutrition prevalence to bodyweight shocks in the context of the 2020 national lockdown strategy in India}, journal = {Journal of Global Health Science}, volume = {2}, year = {2020}, abstract = { The National Family Health Survey (NFHS) 2015{\textendash}16, finds that every secondchild in India suffers from at least one form of nutrition failure. Dichotomisedindicators of underweight and wasting based on z-score cut-off does notprovide any information regarding those children who are clustered aroundthe threshold and are at an elevated risk of undernutrition through any minorweight-loss. This paper aims to estimate the effect of bodyweight shocks onnet increments in the prevalence of child underweight and wasting amongthe poorest households in India. We used cross-sectional information fromNFHS 2015{\textendash}16 to estimate possible increase in the prevalence of childunderweight and wasting as a result of reduction in their bodyweight. Theshocks are presumed to range from a minimum of 0.5\% to a maximum5\% reduction in the bodyweight for every child from the poorest 20\%households. Various raw weight measures scenarios were developed andtransformed into age- specific z-scores using World Health Organization childgrowth standards. Nutritional status of children is sensitive to smallest of theshocks to bodyweight. In fact, a reduction of 0.5 and 1 percent in weight canlead to substantial increase in underweight and wasting prevalence. Under ascenario of bodyweight shock of 0.5 percent, the prevalence of underweightand wasting will increase by 1.42 and 1.36 percentage points, respectively.These estimates get translated into 410,413 and 392,886 additional casesof underweight and wasting, respectively. With such high concentration ofchildren around the undernutrition threshold, any minor shock to nutritionalhealth of the children can have major implications. In the current scenario ofnational lockdown and restrictions due to coronavirus disease 2019 pandemic,it is critical to ensure an uninterrupted supply of nutritious meals and foodsupplements to the poor children while arresting the infection spread. }, isbn = {2671-6933}, author = {Rajpal, Sunil and William Joe and Subramanian, S V} } @webarticle {1582333, title = {NFHS shows stunting increased in {\textquoteleft}better-performing{\textquoteright} Kerala, Goa. India must not lose focus}, journal = {The Print}, year = {2020}, abstract = { Reducing the burden of child undernutrition has been central to the developmental goals of the Government of India. The flagship programme, POSHAN Abhiyaan, launched in 2018, provided a much-needed fillip to the nutrition agenda. Dedicated budgetary allocation, and administrative and community efforts are expected to accelerate nutritional improvements in the years to come. Until now, the latest available estimates on various measures of children{\textquoteright}s nutritional status came from the fourth round of the National Family Health Survey, or the NFHS, conducted in 2015-16. The much-awaited statistics on the\ prevalence of nutritional status\ among children from the fifth round of the NFHS conducted in 2019 in 17 states and five Union Territories (UTs) is out. What can we learn with regards to the progress the country is making in terms of reducing the burden of undernutrition among Indian children? Stunting prevalence Considering the commonly used measure of anthropometric failure as an indication of undernutrition, it is clear that there cannot be any let up to the efforts that have been put in place recently. On all three measures of anthropometric failure (stunting, underweight and wasting) the mean prevalence across these 22 states/UTs has increased\ (see table). Stunting prevalence decreased in nine states/UTs and increased in 13 states/UTs. Greatest reduction occurred in Sikkim, Manipur and Bihar. However, stunting increased in Kerala, Goa and Himachal Pradesh, i.e., states typically seen as {\textquoteleft}better performing{\textquoteright}. It also increased in Maharashtra, Gujarat, and West Bengal. The prevalence of underweight, meanwhile, shows reduction in six states/UTs whereas wasting reduced in only eight states/UTs. The POSHAN Abhiyaan had set a target of achieving two percentage points per annum reduction in stunting and underweight prevalence. None of the 22 states/UTs were able to achieve these aspirational targets in stunting or underweight, with Tripura and Nagaland showing an increase of more than two percentage points per annum. It is concerning that in seven states/UTs, all the three indicators have worsened since NFHS 2015-16. These include Himachal Pradesh, Kerala, Lakshadweep, Mizoram, Nagaland, Telangana and Tripura. Only three states i.e., Andhra Pradesh, Karnataka and Sikkim showed improvements in these three anthropometric indicators. The decline in stunting by 5.4 per cent for Bihar is a bright spot in what appears to be a disconcerting trend. We hope there are opportunities to learn from this decline that can then be useful for other states, and to ensure that Bihar sustains this trajectory of decline. Notwithstanding this welcome trend, Bihar remains the state with the highest prevalence for stunting and underweight. With the economy shrinking in the first two quarters of FY21, the Union and the state governments will also find themselves constrained in enhancing developmental spending directly related to nutritional health and well-being. But it is important that flagship schemes of the government of India display the same commitment as before, pandemic or not. In fact, these areas need an ever-greater intent and purpose in supporting states/UTs in their mission to reduce the burden of undernutrition among children. What needs to be done? It should be noted that {\textquoteleft}averages{\textquoteright} in India {\textendash} even at the state level {\textendash} mask more than they reveal, whether it relates to the geographic differences within a state (e.g., districts) or the differences in\  the prevalence across socio-economic groups. It is well known that the most crucial determinant of a child{\textquoteright}s anthropometric status is the household socio-economic well-being. It is crucial that the POSHAN Abhiyaan should find means to enhance and optimise resource allocations with a targeted focus on the poor and deprived sections. In addition to the programmes that are directly related to nutrition (e.g., food), the time is ripe to link sector- specific initiatives with the broader goal of poverty alleviation and improving the overall standard of living through employment generation and asset creation. Since the burden of anthropometric failure is known to be a consequence of multiple factors, the response to reducing it needs to embrace this perspective by convergence across sectors. It should be noted that the sobering statistics delivered by the latest NFHS predates the Covid- 19 pandemic and the subsequent 2020 lockdown that followed as a response. Thus, the data that got released for 22 states/UTs, especially for those that appeared to have experienced a decline, needs to be interpreted cautiously as situation may have worsened. Similarly, states that experienced an increase, the magnitude could be even greater. The NFHS 2019-20 is currently underway in the remaining 14 states/UTs, and we may be able to use this creatively to assess the impact of the 2020 lockdown that has relegated the economy and brought widespread disruptions, impacting the lower socio-economic groups disproportionately. For the first time since NFHS started measuring nutritional status systematically, India finds itself at an elevated risk of experiencing a trend-reversal in the prevalence of stunting and underweight. It may seem that child undernutrition {\textemdash} at least as measured through anthropometry {\textemdash} is turning out to be the Achilles{\textquoteright} heel of India. }, author = {William Joe and Subramanian, S V} } @article {1582337, title = {Precision-weighted estimates of neonatal, postneonatal and child mortality for 640 districts in India, National Family Health Survey 2016}, journal = {Journal of Global Health}, volume = {10}, number = {2}, year = {2020}, abstract = { Background The conventional indicators of infant and under-five mortality are aggregate deaths occurring in the first year and the first five years, respectively. Monitoring deaths by \<1 month (neonatal), 1-11 months (post-neonatal), and 12- 59 months (child) can be more informative given various etiological causes that may require different interventions across these three mutually exclusive periods. For optimal resource allocation, it is also necessary to track progress in robust estimates of child survival at a smaller geographic and administrative level. Methods Data on 259627 children came from the 2015-2016 Indian National Family Health Survey. We used a random effects model to account for the complex survey design and sampling variability, and predicted district-specific probabilities of neonatal, post-neonatal, and child mortality. The resulting precision-weighted estimates are more reliable as they pool information and borrow strength from other districts that share the same state membership. The Pearson correlation and Spearman{\textquoteright}s rank correlation were assessed for the three mortality estimates, and the Moran{\textquoteright}s I measure was used to detect spatial clustering of high burden districts for each outcome. Results The majority of under-five deaths was disproportionately concentrated in the neonatal period. Across all districts, the predicted probability of neonatal, post-neonatal, and child mortality varied from 6.0 to 63.9 deaths, 3.8 to 47.6 deaths, and 1.7 to 11.8 deaths per 1000 live births, respectively. The overall correlation between district-wide probabilities of mortality for the three mutually exclusive periods was moderate (Pearson correlation=0.47-0.58, Spearman{\textquoteright}s rank correlation=0.58-0.64). For each outcome, a relatively strong spatial clustering was detected across districts that transcended state boundaries (Moran{\textquoteright}s I=0.61-0.76). Conclusions Sufficiently breaking down the under-five mortality to distinct age groups and using the precision-weighted estimations to monitor performances at smaller geographic and administrative units can inform more targeted interventions and foster accountability to improve child survival }, author = {Rockli Kim and Liou, Lathan and Yun Xu and Rakesh Kumar and George Leckie and Kapoor, Mudit and R Venkataramanan and Alok Kumar and William Joe and Subramanian, S V} } @article {1582330, title = {Prevalence of Anemia, Underweight and Stunting in 342 Districts of India}, journal = {Harvard Dataverse}, year = {2020}, abstract = { This document presents the prevalence of anemia, underweight and stunting among children, adolescent and women for 342 Districts (17 States and 5 Union Territories) of India from the fourth (2015-16) and fifth (2019-20) National Family Health Survey (NFHS) and percentage point changes between the two surveys. }, author = {Wang, W. and Zhang, W. and Subramanian, S V} } @webarticle {1582332, title = {Putting food at the centre of India{\textquoteright}s nutrition agenda}, journal = {The Hindu}, year = {2020}, abstract = { The provisional verdict from the fifth round of the\ National Family Health Survey (NFHS 2019-20 factsheets\ on the burden of child undernutrition is not encouraging, with few exceptions. For the most part, this assessment has relied on the measure of a child{\textquoteright}s anthropometry, i.e., children are defined as stunted, underweight or wasted if their standardised height-for-age, weight-for-age or weight-for-height, respectively, is more than two standard deviations below the\ World Health Organization (WHO) Child Growth Standards\ median. However, undernutrition can also be measured by observing the adequacy and sufficiency of food or dietary intake among children. So how do Indian children fare when we bring a food measure to tell us about their nutritional status? Diet-related undernutrition Across the 22 States/Union Territories for which the NFHS-5 has released the factsheets, the percentage of children (aged 6-23 months) who do not meet the\ minimum dietary adequacy\ {\textemdash} as defined under the Infant and Young Child Feeding (IYCF) practices by WHO {\textemdash} is 83.9\%; a decline of just over 2 percentage points from what was observed in NFHS-4 (2015-16). Thus, eight out of 10 children appear to be experiencing a dietary shortfall. It would not be surprising if this situation has worsened (https://bit.ly/3nrJloI) with the spread of the COVID-19 pandemic and the ensuing 2020 lockdown. Although 17 of the 22 States/Union Territories did experience a decline, the percentage of children not meeting the dietary adequacy norms increased in five States/Union Territories. Goa experienced the largest percentage point decline (11.1\%), and Jammu and Kashmir observed the highest increase in its percentage of children not meeting dietary adequacy over the last three years (76.5\% to 86.4\%). While there are some variations, in every State more than 75\% of the children do not receive the minimum adequate diet. Analysis\ based on NFHS-4 has shown that consumption of protein-rich food as well as fruit and vegetables were substantially low. Since the disaggregated child-level data on consumption of various food groups has not been released, we will have to wait to see what specific aspects are children experiencing a dietary shortfall. Prevalence of anaemia Fortunately, the factsheets provide the percentage of children who are anaemic {\textemdash}\ an indication of iron deficiency\ {\textemdash} and the trends should raise concern. Across the 22 States/Union Territories, anaemia prevalence among children increased by about eight percentage points from 51.8\% to 60.2\%. The prevalence of anaemia in childhood increased in 18 of the 22 States/Union Territories. In the majority of the States, two out of three children have possible iron-deficiency. The State-wise trends for adults are mixed, although it is clear that women are substantially at a far greater risk for anaemia than men. The Prime Minister{\textquoteright}s Overarching Scheme for Holistic Nutrition (POSHAN) Abhiyaan and, particularly, the\ Anemia Mukt Bharat, or AMB, Strategy was launched in 2018 with efforts to improve Iron and Folic Acid (IFA) supplementation, behaviour change and anaemia-related care and treatment across six target groups including pregnant women, lactating mothers, and children, and the provisional verdict is mixed for women and concerning for children. Diet-related measures Viewing the burden of child undernutrition from a food or dietary lens is sobering, and raises serious concerns than what has been well-revealed by measures based on anthropometry. It is time that undernutrition is not only viewed simply through the measures of anthropometric failure, but is complemented through explicit attention to diet-related measures. A classification of nutritional status using a combined typology based on children who experience dietary failure and anthropometric failure is crucial.\ A recent NFHS-4 based study\ using this typology found that 36.3\% of children who experienced a dietary failure do not show anthropometric failure. Anthropometric-centric measures thus run the risk of omitting such children from policy discussions. A combined typology is also necessary to highlight groups that may need most immediate priority (e.g., children experiencing both dietary and anthropometric failures, 44\%). Indeed, the prevalence of children who experience anthropometric failure only but no dietary failure was only 9.8\%. Dietary factors can clearly be a major determinant of stagnancy in the nutritional status of Indian children. The true burden of child undernutrition thus may well be underestimated by the sole reliance on anthropometric measures. Besides, a child{\textquoteright}s anthropometric status is a consequence of several complex factors, including inter-generational, which current policies and interventions cannot alter in the short term. Importantly, food and diet have an intrinsic importance, regardless of their impact on a child{\textquoteright}s anthropometry. Therefore the\ nutrition agenda needs to be considered from {\textquotedblleft}food as a right{\textquotedblright}\ perspective. A disproportionate focus on anthropometric measures inadvertently precludes meaningful and direct engagement with strategies and data necessary to address diet and food security concerns. Data, available in a timely manner and in public domain, is empowering, as the NFHS has demonstrated over the last 25-plus years. But systematic and quality data on what Indians eat remains largely unknown. Data initiative needed It is important to emphasise that India does not have a dedicated nationally representative survey on the dietary intake and nutritional status of children or adults. A modern data initiative leveraging and combining aspects of the NFHS, the National Nutrition Monitoring Bureau and the National Sample Surveys that collected data on detailed household-level consumption and expenditure on various food items should be considered. In summary, decluttering our current approach to reducing the burden of child undernutrition and keeping it simple with a policy goal to providing affordable (economic and physical) access to quality food items, particularly for lower socioeconomic populations groups, should be prioritised. This may serve well as India tries to realise the Sustainable Development Goals (SDGs 2 and 3) related to zero hunger and good health and well-being. S.V. Subramanian is Professor of Population Health and Geography, Harvard Center for Population and Development Studies, Cambridge, MA, U.S. William Joe is Assistant Professor, Population Research Centre, Institute of Economic Growth, Delhi. Inputs by Abhishek Kumar, a doctoral candidate at the Central University of Gujarat. }, author = {Subramanian, S V and William Joe} } @article {1582344, title = {The relationship of household assets and amenities with child health outcomes: An exploratory cross-sectional study in India 2015{\textendash}2016}, journal = {SSM-population health}, volume = {10}, year = {2020}, pages = {100513}, publisher = {Elsevier}, abstract = { Healthy development of children in India is far from ensured. Proximatedeterminants of poor child health outcomes are infectious diseases andundernutrition, which are linked to socioeconomic status. In low- andmiddle-income countries, researchers rely on wealth indices, constructedfrom information on households{\textquoteright} asset ownership and amenities, to studysocioeconomic disparities in child health. Some of these wealth index itemscan, however, directly affect the proximate determinants of child health. Thispaper explores the independent association of each item used to constructthe Demographic and Health Surveys{\textquoteright} wealth index with diverse child healthoutcomes. This cross-sectional study used nationally representative sampleof 245,866 children, age 0-59 months, from the Indian National Family HealthSurveys conducted in 2015-16. The study used conditional Poisson regressionmodels as well as a range of sensitivity specifications. After controlling forsocioeconomic status, health care use, maternal factors, community-levelfactors, and all wealth index items, the following wealth index items were themost consistently associated with child health; type of toilet facilities, watersource, refrigerator, pressure cooker, type of cooking fuel, land usable foragriculture, household building material, mobile phone, and motorcycle/scooter. The association with type of toilet facilities and water source wasparticularly strong for mortality, showing a 16-35\% and 14-28\% lowermortality, respectively. Most items used to construct the Demographic andHealth Surveys{\textquoteright} wealth index only indicate household socioeconomic status,while a few items may affect child health directly, and can be useful targetsfor policy intervention. }, isbn = {2352-8273}, author = {Karlsson, Omar and Rockli Kim and William Joe and Subramanian, S V} } @article {1582345, title = {A typology of dietary and anthropometric measures of nutritional need among children across districts and parliamentary constituencies in India, 2016}, journal = {Journal of Global Health}, volume = {10}, number = {2}, year = {2020}, publisher = {International Society for Global Health}, abstract = { Anthropometry is the most commonly used approach for assessingnutritional need among children. Anthropometry alone, however, cannotdifferentiate between the two immediate causes of undernutrition:inadequate diet vs disease. We present a typology of nutritional need bysimultaneously considering dietary and anthropometric measures, dietaryand anthropometric failures (DAF), and assess its distribution among childrenin India. We used the 2015-16 National Family Health Survey, a nationallyrepresentative sample of children aged 6-23 months (n = 67 247), fromIndia. Dietary failure was operationalized using World Health Organization(WHO) standards for minimum dietary diversity. Anthropometric failure wasoperationalized using WHO child growth reference standard z-score of \<-2for height-for-age (stunting), weight-for-age (underweight) and weight-forheight(wasting). We also created a combined anthropometric measure forchildren who had any one of these three anthropometric failures. We crosstabulateddietary and anthropometric failures to produce four combinations:Dietary Failure Only (DFO), Anthropometric Failure Only (AFO), Both Failures(BF), and Neither Failure (NF). We estimated the prevalence and distributionof the four types, nationally, and across 640 administrative districts and 543Parliamentary Constituencies (PCs) in India. Nationally, 80.3\% of childrenhad dietary failure and 53.7\% had at least one anthropometric failure. Theprevalence for the four DAF types was: 44.0\% (BF), 36.3\% (DFO), 9.8\% (AFO),and 9.9\% (NF). Dietary and anthropometric measures were discordant for46.1\% of children; these children had nutritional needs identified by only oneof the two measures. Nationally, this translates to 12 181 627 children withDFO and 3 281 913 children with AFO; the nutritional needs of these childrenwould not be captured if using only dietary or anthropometric assessment.Substantial variation was observed across districts and PCs for all DAF types.The interquartile ranges for districts were largest for BF (29.8\%-53.0\%) andlowest for AFO (5.5\%-13.4\%). The current emphasis on anthropometry formeasuring nutritional need should be complemented with diet- and foodbasedmeasures. By differentiating inadequate food intake from other causesof undernutrition, the DAF typology brings precision in identifying nutritionalneeds among children. These insights may improve the development andtargeting of nutrition interventions. }, author = {Beckerman-Hsu, Jacob P and Chatterjee, Pritha and Rockli Kim and Sharma, Smriti and Subramanian, S V} } @article {1582346, title = {Utilization of integrated child development services in India: programmatic insights from national family health survey, 2016}, journal = {International Journal of Environmental Research and Public Health}, volume = {17}, number = {9}, year = {2020}, pages = {3197}, publisher = {Multidisciplinary Digital Publishing Institute}, abstract = { The Integrated Child Development Services (ICDS) program launched inIndia in 1975 is one of the world{\textquoteright}s largest flagship programs that aims toimprove early childhood care and development via a range of healthcare,nutrition and early education services. The key to success of ICDS is in findingsolutions to the historical challenges of geographic and socioeconomicinequalities in access to various services under this umbrella scheme. Usingbirth history data from the National Family Health Survey (Demographic andHealth Survey), 2015-2016, this study presents (a) socioeconomic patterningin service uptake across rural and urban India, and (b) continuum in serviceutilization at three points (i.e., by mothers during pregnancy, by motherswhile breastfeeding and by children aged 0-72 months) in India. We usedan intersectional approach and ran a series multilevel logistic regression(random effects) models to understand patterning in utilization amongmothers across socioeconomic groups. We also computed the area underthe receiver operating characteristic curve (ROC-AUC) based on a logisticregression model to examine concordance between service utilization acrossthree different points. The service utilization (any service) by mothers duringpregnancy was about 20 percentage points higher for rural areas (60.5percent; 95\% CI: 60.3; 30.7) than urban areas (38.8 percent; 95\% CI: 38.4;39.1). We also found a lower uptake of services related to health and nutritioneducation during pregnancy (41.9 percent in rural) and early childcare(preschool) (42.4 percent). One in every two mother-child pairs did not availany benefits from ICDS in urban areas. Estimates from random effects modelrevealed higher odds of utilization among schedule caste mothers frommiddle-class households in rural households. AUC estimates suggested ahigh concordance between service utilization by mothers and their children(AUC: 0.79 in rural; 0.84 in urban) implying a higher likelihood of continuum ifservice utilization commences at pregnancy. }, author = {Rajpal, Sunil and William Joe and Subramanyam, Malavika A and Sankar, Rajan and Sharma, Smriti and Alok Kumar and Rockli Kim and Subramanian, S V} } @article {1651330, title = {From Administrative to Political Evaluation: Estimating Water, Sanitation, and Hygiene Indicators for Parliamentary Constituencies in India}, journal = {Journal of Development Policy and Practice}, year = {2019}, author = {Chatterjee, Pritha and Rockli Kim and Akshay Swaminathan and Rakesh Kumar and Subramanian, S. V.} } @report {1651326, title = {State of Nutrition among Children in Parliamentary Constituenciesof India}, year = {2019}, institution = {Tata Trusts}, author = {Subramanian, S. V. and Wiliam Joe and Rockli Kim} } @article {1651325, title = {Robust Parliamentary Constituency Estimates: Geographic Data Science Approaches}, journal = {Economic and Political Weekly}, year = {2019}, author = {Blossom, Jeffrey C and Akshay Swaminathan and William Joe and Rockli Kim and Subramanian, S V} } @article {1651324, title = {Burden of Child Malnutrition in India: A View from Parliamentary Constituencies}, journal = {Economic and Political Weekly}, year = {2019}, author = {Akshay Swaminathan and Rockli Kim and Yun Xu and Blossom, Jeffrey C and William Joe and R Venkataramanan and Alok Kumar and Subramanian, S V} } @article {1651310, title = {Estimating the burden of child malnutrition across parliamentary constituencies in India: A methodological comparison}, journal = {SSM - Population Health}, year = {2019}, author = {Rockli Kim and Akshay Swaminathan and Rakesh Kumar and Yun Xu and Blossom, Jeffrey C. and R. Venkataramanan and Alok Kumar and William Joe and Subramanian, S. V.} } @article {1582348, title = {Assessing associational strength of 23 correlates of child anthropometric failure: an econometric analysis of the 2015-2016 National Family Health Survey, India}, journal = {Social Science \& Medicine}, volume = {238}, year = {2019}, pages = {112374}, publisher = {Elsevier}, abstract = { Despite the broad consensus that investments in nutrition-sensitiveprogrammes are required to reduce child undernutrition, in practice empiricalstudies and interventions tend to focus on few nutrition-specific risk factorsin isolation. The 2015-16 National Family Health Survey provides the firstopportunity in more than a decade to conduct an up-to-date comprehensiveevaluation of the relative importance of various maternal and child healthand nutrition (MCHN) factors in respect to child anthropometric failures inIndia. The primary analysis included 140,444 children aged 6-59 months withcomplete data on 20 MCHN factors, and the secondary analysis included asubset of 25,603 children with additional paternal data. Outcome variableswere stunting, underweight and wasting. We conducted logistic regressionmodels to first evaluate each correlate separately in age- and sex-adjustedmodels, and then jointly in a mutually adjusted model. For all anthropometricfailures, indicators of past and present socioeconomic conditions showed themost robust associations. The strongest correlates for stunting were shortmaternal stature (OR: 4.39; 95\%CI: 4.00, 4.81), lack of maternal education(OR: 1.74; 95\%CI: 1.60, 1.89), low maternal BMI (OR: 1.64; 95\%CI: 1.54, 1.75),poor household wealth (OR: 1.25; 95\%CI: 1.15, 1.35) and poor householdair quality (OR: 1.22; 95\%CI: 1.16, 1.29). Weaker associations were foundfor other correlates, including dietary diversity, vitamin A supplementationand breastfeeding initiation. Paternal factors were also important predictorsof anthropometric failures, but to a lesser degree than maternal factors.The results remained consistent when stratified by children{\textquoteright}s age (6-23vs 24-59 months) and sex (girls vs boys), and when low birth weight wasadditionally considered. Our findings indicate the limitation of nutritionspecificinterventions. Breaking multi-generational poverty and improvingenvironmental factors are promising investments to prevent anthropometricfailures in early childhood. }, isbn = {0277-9536}, author = {Rockli Kim and Rajpal, Sunil and William Joe and Corsi, Daniel J and Sankar, Rajan and Alok Kumar and Subramanian, S V} } @article {1582349, title = {Association between anthropometric-based and food-based nutritional failure among children in India, 2015}, journal = {Maternal \& child nutrition}, volume = {15}, number = {4}, year = {2019}, pages = {e12830}, publisher = {Wiley Online Library}, abstract = { Inadequate dietary intake is a critical underlying determinant of childundernutrition. This study examined the association between anthropometricbasedand food-based nutritional failure among children in India. We used the2015-2016 National Nutrition Monitoring Bureau data where anthropometricoutcomes and food intake were both measured for each child. We followedthe World Health Organization child growth reference standards to defineanthropometric failures (i.e., height-for-age z score \< -2 SD for stunting,weight-for-age z score \< -2 SD for underweight, and weight-for-heightz score \< -2 SD for wasting), and the Indian Council of Medical Researchrecommended dietary allowance (RDA) to define adequacy in intake of calorie,protein, and fat. We used descriptive and regression-based assessments totest the association between the two indicators of nutritional failure and alsocomputed the area under the receiver operating characteristic curve (AUC).The prevalence of stunting, underweight, and wasting was 28.6\%, 24.3\%,and 12.8\%, respectively, whereas 78.2\%, 27.4\%, and 50.8\% of the childrenhad below RDA norms consumption of calorie, protein, and fat, respectively.We found weak-to-null correlation between anthropometric failures andfood failures (Pearson correlation ranging from -0.013 to 0.147) and poordiscriminatory accuracy (AUC \< 0.62), suggesting that in the Indian context,anthropometric failures are not directly associated with food intake. This\ finding highlights the need for improving adequate intake of macronutrientsand draws attention toward adopting a multifactorial approach to improvechild nutrition in India. Poor food intake itself merits exclusive policy focus asit is an important nutrition and health concern. }, isbn = {1740-8695}, author = {William Joe and Rajpal, Sunil and Rockli Kim and Laxmaiah, Avula and Harikumar, Rachakulla and Arlappa, Nimmathota and Meshram, Indrapal and Balakrishna, Nagalla and Radhika, Madhari and Swaminathan, Soumya} } @article {1582350, title = {Burden of Child Malnutrition in India: A View from Parliamentary Constituencies}, journal = {Economic \& Political Weekly}, volume = {54}, number = {2}, year = {2019}, abstract = { In India, monitoring and surveillance of health and well-being indicators have been focused primarily on the state and district levels. Analysing population data at the level of parliamentary constituencies has the potential to bring political accountability to the data-driven policy discourse that is currently based on district-level estimates. Using data from the fourth National Family Health Survey 2016, two geographic information systems methodologies have been developed and applied to provide estimates of four child malnutrition indicators (stunting, underweight, wasting, and anemia) for the 543 parliamentary constituencies in India. The results indicate that several constituencies experience a multiple burden of child malnutrition that must be addressed concurrently and as a priority. }, author = {A Swaminathan and Kim, R and Xu, Y. and JC Blossom and W Joe and R Venkatraman and Kumar, A, A and Subramanian, S V} } @article {1582351, title = {Determinants of childhood anemia in india}, journal = {Scientific reports}, volume = {9}, number = {1}, year = {2019}, pages = {1-7}, publisher = {Nature Publishing Group}, abstract = { We analyzed a sample of 112714 children from the 2015-2016 Indian NationalFertility and Health Survey with available data on hemoglobin. Multinomiallogistic regression models were used to establish associations betweenparent anemia, household characteristics and nutritional intake of children.Linear regression analysis was also conducted to see the link between thehousehold characteristic and childhood nutritional intake on one hand andhemoglobin levels on the other hand. A number of socio-demographicfactors, namely maternal age, type of residence and maternal education, aswell as wealth index, among others correlate with incidence of childhoodanemia. For instance, whereas 52.9\% of children in the richest householdswere anemic, 63.2\% of children in the poorest household were anemic (p\< 0.001). Mean Vitamin A intake in the last six months was 0.63 (0.626-0.634) which was 0.18\% of the recommended intake. Mean iron intake, fromsources other than breast milk, in the last 24 hours was 0.29 (0.286-0.294)and 2.42\% of the recommended daily intake. Fifty-nine percent (58.5\%) ofthe children surveyed were anemic (Hb level: 9.75 g/dL [9.59-9.91]). Childrenwith anemia were more prone to being iron deficient (odds ratio [OR]: 0.981(0.961-1.001), Vitamin A deficient (OR: 0.813 (0.794-0.833)), and have lowermaternal hemoglobin level (OR: 1.992 (1.957-2.027)). Combining nutritionalsupplementation and food-fortification programmes with reduction inmaternal anemia and family poverty may yield optimal improvement ofchildhood anemia in India. }, isbn = {2045-2322}, author = {Onyeneho, Nkechi G and Ozumba, Benjamin C and Subramanian, S V} } @article {1582352, title = {Estimating the burden of child malnutrition across parliamentary constituencies in India: A methodological comparison}, journal = {SSM-Population Health}, volume = {7}, year = {2019}, abstract = { In India, data on key developmental indicators used to formulate policies and interventions are routinely available for the administrative unit of districts but not for the political unit of parliamentary constituencies (PC). Recently, Swaminathan et al. proposed two methodologies to generate PC estimates using randomly displaced GPS locations of the sampling clusters ({\textquoteleft}direct{\textquoteright}) and by building a crosswalk between districts and PCs using boundary shapefiles ({\textquoteleft}indirect{\textquoteright}). We advance these methodologies by using precision-weighted estimations based on hierarchical logistic regression modeling to account for the complex survey design and sampling variability. We exemplify this application using the latest National Family Health Survey (NFHS, 2016) to generate PC-level estimates for two important indicators of child\ malnutrition\ {\textendash} stunting and low birth weight {\textendash} that are being monitored by the Government of India for the National Nutrition Mission targets. Overall, we found a substantial variation in child malnutrition across 543 PCs. The different methodologies yielded highly consistent estimates with correlation ranging r = 0.92-0.99 for stunting and r = 0.81-0.98 for low birth weight. For analyses involving data with comparable nature to the NFHS (i.e., complex data structure and possibility to identify a potential PC membership), modeling for precision-weighted estimates and direct methodology are preferable. Further field work and data collection at the PC level are necessary to accurately validate our estimates. An ideal solution to overcome this gap in data for PCs would be to make PC identifiers available in routinely collected surveys and the Census. }, author = {Kim, R and A Swaminathan and Kumar, R and Xu, Y. and JC Blossom and R Venkataramanan and Kumar, A, A and W Joe and Subramanian, S. V.} } @article {1582353, title = {Explaining Within-vs Between-Population Variation in Child Anthropometry and Hemoglobin Measures in India: A Multilevel Analysis of the National Family Health Survey 2015{\textendash}2016}, journal = {Journal of Epidemiology}, year = {2019}, pages = {JE20190064}, publisher = {Japan Epidemiological Association}, abstract = { The complex etiology of child growth failure and anemia{\textemdash}commonly usedindicators of child undernutrition{\textemdash}involving proximate and distal risk factorsat multiple levels is generally recognized. However, their independent andjoint effects are often assessed with no clear conceptualization of inferentialtargets.We utilized hierarchical linear modeling and a nationally representativesample of 139,116 children aged 6{\textendash}59 months from India (2015{\textendash}2016) toestimate the extent to which a comprehensive set of 27 covariates explainedthe within- and between-population variation in height-for-age, weightfor-age, weight-for-height, and hemoglobin level.Most of the variation inchild anthropometry and hemoglobin measures was attributable to withinpopulationdifferences (80{\textendash}85\%), whereas between-population differences(including communities, districts, and states) accounted for only 15{\textendash}20\%.The proximate and distal covariates explained 0.2{\textendash}7.5\% of within-populationvariation and 2.1{\textendash}34.0\% of between-population variation, depending onthe indicator of interest. Substantial heterogeneity was observed in themagnitude of within-population variation, and the fraction explained, inchild anthropometry and hemoglobin measures across the 36 states/unionterritories of India.Policies and interventions aimed at reducing betweenpopulationinequalities in child undernutrition may require a different set ofcomponents than those concerned with within-population inequalities. Bothare needed to promote the health of the general population, as well as thatof high-risk children. }, isbn = {0917-5040}, author = {Rodgers, Justin and Rockli Kim and SV, Subramanian} } @article {1582354, title = {Parliamentary Constituency Factsheet for Indicators of Nutrition, Health and Development in India}, journal = {Harvard Center for Population and Development Studies}, volume = {18}, number = {4}, year = {2019}, abstract = { In India, data on key developmental indicators that formulate policies and interventions are routinely available for the administrative units of districts but not for the political units of Parliamentary Constituencies (PC). Members of Parliament (MPs) in the Lok Sabha, each representing 543 PCs as per the 2014 India map, are the representatives with the most direct interaction with their constituents. The MPs are responsible for articulating the vision and the implementation of public policies at the national level and for their respective constituencies. In order for MPs to efficiently and effectively serve their people, and also for the constituents to understand the performance of their MPs, it is critical to produce the most accurate and up-to-date evidence on the state of health and well-being at the PC-level. However, absence of PC identifiers in nationally representative surveys or the Census has eluded an assessment of how a PC is doing with regards to key indicators of nutrition, health and development. }, author = {Kim, R and A Swaminathan and G Swaminathan and Kumar, R and S Rajpal and JC Blossom and W Joe and Subramanian, S V} } @article {1582347, title = {Robust Parliamentary Constituency Estimates: Geographic Data Science Approaches}, journal = {Economic and Political Weekly}, volume = {54}, number = {19}, year = {2019}, abstract = { This article is a response to Srinivas Goli{\textquoteright}s article {\textquotedblleft}Unreliable Estimates of Child Malnutrition{\textquotedblright} (EPW, 9 February 2019) that had questioned the reliability of methodologies of Akshay Swaminathan et al{\textquoteright}s article {\textquotedblleft}Burden of Child Malnutrition\ in India: A View from Parliamentary Constituencies{\textquotedblright} (EPW, 12 January 2019). The reliability and usability of the methodologies proposed by Swaminathan et al have been reiterated, emphasising that these can provide broad assessments at the parliamentary constituency level. }, author = {JC Blossom and A Swaminathan and W Joe and Kim, R and Subramanian, S V} } @article {1582355, title = {Socio-economic patterning of food consumption and dietary diversity among Indian children: evidence from NFHS-4}, journal = {European journal of clinical nutrition}, volume = {73}, number = {10}, year = {2019}, pages = {1361-1372}, publisher = {Nature Publishing Group}, abstract = { Most interventions to foster child growth and development in India focuson improving food quality and quantity. We aimed to assess the pattern infood consumption and dietary diversity by socioeconomic status (SES) amongIndian children. The most recent nationally representative, cross-sectionaldata from the National Family Health Survey (NFHS-4, 2015-16) was usedfor analysis of 73,852-74,038 children aged 6-23 months. Consumption of21 food items, seven food groups, and adequately diversified dietary intake(ADDI) was collected through mother{\textquoteright}s 24-h dietary recall. Logistic regressionmodels were conducted to assess the association between household wealthand maternal education with food consumption and ADDI, after controllingfor covariates. Overall, the mean dietary diversity score was low (2.26; 95\%CI:2.24-2.27) and the prevalence of ADDI was only 23\%. Both householdwealth and maternal education were significantly associated with ADDI(OR:1.28; 95\% CI:1.18-1.38 and OR:1.75; 95\% CI:1.63-1.90, respectively), butthe SES gradient was not particularly strong. Furthermore, the associationsbetween SES and consumption of individual food items and food groupswere not consistent. Maternal education was more strongly associated withconsumption of essential food items and all food groups, but householdwealth was found to have significant influence on intake of dairy group only.CONCLUSIONS: Interventions designed to improve food consumption anddiversified dietary intake among Indian children need to be universal in theirtargeting given the overall high prevalence of inadequate dietary diversityand the relatively small differentials by SES. }, isbn = {1476-5640}, author = {Agrawal, Sutapa and Rockli Kim and Gausman, Jewel and Sharma, Smriti and Sankar, Rajan and William Joe and Subramanian, S V} } @article {1582356, title = {Stunting trajectories from post-infancy to adolescence in Ethiopia, India, Peru, and Vietnam}, journal = {Maternal \& child nutrition}, volume = {15}, number = {4}, year = {2019}, pages = {e12835}, publisher = {Wiley Online Library}, abstract = { Many interventions focus on preventing stunting in the first 1,000 days of life.We take a broader perspective on childhood growth to assess the proportionsof children who suffer persistent stunting, recover, and falter and becomenewly stunted between birth and adolescence. We use longitudinal datacollected on 7,128 children in Ethiopia, India, Peru, and Vietnam. Data werecollected in five survey waves between the ages of 1 to 15 years. We usedescriptive and graphical approaches to compare the trajectories of childrenfirst stunted by age 1, first stunted by age 5, and those remained not stunteduntil age 5. On average, 29.6\% of children were first stunted by age 1, 12.9\%of children were first stunted by the age 5, and 68.7\% of children were notstunted at either age 1 or age 5. A larger percentage of children stunted byage 1 remained stunted at age 15 (40.7\%) compared with those who were first\ stunted by age 5 (32.3\%); 33.7\% of children first stunted by age 1 and 31.1\%of children first stunted by age 5 go on to recover, but then falter duringlater childhood. 13.1\% of children who were not stunted at age 1 or age 5become newly stunted between the ages of 8 and 15. Our results show thatchildren both become stunted and recover from stunting into adolescence.More attention should be paid to interventions to support healthy growththroughout childhood. }, isbn = {1740-8695}, author = {Gausman, Jewel and Rockli Kim and Subramanian, S V} } @article {1582358, title = {Distinct clusters of stunted children in India: An observational study}, journal = {Maternal \& child nutrition}, volume = {14}, number = {3}, year = {2018}, pages = {e12592}, publisher = {Wiley Online Library}, abstract = { Childhood stunting is often conceptualised as a singular concept (i.e., stuntedor not), and such an approach implies similarity in the experiences of childrenwho are stunted. Furthermore, risk factors for stunting are often treated inisolation, and limited research has examined how multiple risk factors interacttogether. Our aim was to examine whether there are subgroups amongstunted children, and if parental characteristics influence the likelihood ofthese subgroups among children. Children who were stunted were identifiedfrom the 2005-2006 Indian National Family Health Survey (n = 12,417).Latent class analysis was used to explore the existence of subgroups amongstunted children by their social, demographic, and health characteristics.We examined whether parental characteristics predicted the likelihood ofa child belonging to each latent class using a multinomial logit regressionmodel. We found there to be 5 distinct groups of stunted children; {\textquotedblleft}poor,older, and poor health-related outcomes,{\textquotedblright} {\textquotedblleft}poor, young, and poorest healthrelatedoutcomes,{\textquotedblright} {\textquotedblleft}poor with mixed health-related outcomes,{\textquotedblright} {\textquotedblleft}wealthyand good health-related outcomes,{\textquotedblright} and {\textquotedblleft}typical traits.{\textquotedblright} Both mother andfather{\textquoteright}s educational attainment, body mass index, and height were importantpredictors of class membership. Our findings demonstrate evidence thatthere is heterogeneity of the risk factors and behaviours among children whoare stunted. It suggests that stunting is not a singular concept; rather, thereare multiple experiences represented by our {\textquotedblleft}types{\textquotedblright} of stunting. Adopting amultidimensional approach to conceptualising stunting may be important forimproving the design and targeting of interventions for managing stunting. }, isbn = {1740-8695}, author = {Green, Mark A and Corsi, Daniel J and Mej{\'\i}a-Guevara, Ivan and Subramanian, S V} } @article {1582359, title = {Ecological and social patterns of child dietary diversity in India: a population-based study}, journal = {Nutrition}, volume = {53}, year = {2018}, pages = {77-84}, publisher = {Elsevier}, abstract = { Dietary diversity (DD) measures dietary variation in children. Factorsat the child, community, and state levels may be associated with poorchild nutritional outcomes. However, few studies have examined the roleof macro-level factors on child DD. This study seeks to 1) describe thedistribution of child DD in India, 2) examine the variation in DD attributableto the child, community and state levels, and 3) explore the relationshipbetween community socioeconomic context and child DD. Using nationallyrepresentative data from children aged 6-23 months in India, multilevelmodels were used to determine the associations between child DD andindividual- and community-level factors. There was substantial variation inchild DD score across demographic and socioeconomic characteristics. In anage and sex-only adjusted regression model, the largest portion of variationin child DD was attributable to the child level (75\%) while the portions ofvariance attributable to the community-level and state level were similar toeach other (15\% and 11\%). Including individual-level socioeconomic factorsexplained 35.6 percent of the total variation attributed to child DD at thecommunity level and 24.8 percent of the total variation attributed to childDD at the state level. Finally, measures of community disadvantage wereassociated with child DD in when added to the fully adjusted model. Thisstudy suggests that both individual and contextual factors are associated withchild DD. These results suggest that a population-based approach combinedwith a targeted intervention for at-risk children may be needed to improvechild DD in India. }, isbn = {0899-9007}, author = {Gausman, Jewel and Perkins, Jessica M and Lee, Hwa-Young and Mejia-Guevara, Ivan and Nam, You-Seon and Lee, Jong-Koo and Oh, Juhwan and Subramanian, S V} } @article {1582357, title = {Opioid Prescribing Rates by Congressional Districts, United States, 2016}, journal = {American Public Health Association}, volume = {108}, number = {8}, year = {2018}, abstract = { Objectives.\ To determine the extent to which opioid prescribing rates vary across US congressional districts. Methods.\ In an observational cross-sectional framework using secondary data, we constructed 2016 congressional district{\textendash}level opioid prescribing rate estimates using a population-weighted methodology. Results.\ High prescribing rate districts were concentrated in the South, Appalachia, and the rural West. Low-rate districts were concentrated in urban centers. Conclusions.\ In the midst of an opioid overdose crisis, we identified congressional districts of particular concern for opioid prescription saturation. Public Health Implications.\ The congressional district geography represents a policy-relevant boundary and a politically important level at which to monitor the crisis and determine program funding. Furthermore, in the context of the opioid crisis, knowing how congressional districts rank across the country and in states is useful in the creation of policies targeted to areas in need. }, author = {LA Rolheiser and J Cordes and Subramanian, S V} } @webarticle {1582360, title = {Improve nutritional content of school meals to tackle stunting}, journal = {Hindustan Times}, year = {2017}, abstract = { As per the latest National Nutrition Monitoring Bureau, which has been collecting data on diet and nutritional status of rural, tribal and urban populations for almost four decades, the calorie intake of children (1-3 years) in rural areas was only about 70\% of their requirement due to shortage. }, author = {Swaminathan, Soumya and Subramanian, S V} } @article {1582361, title = {Improving household-level nutrition-specific and nutrition-sensitive conditions key to reducing child undernutrition in India}, journal = {Soc Sci Med}, volume = {157}, year = {2016}, pages = {189-92}, abstract = { Since the publication of our study, the Government of India has releasedpreliminary estimates from the on-going latest round of National FamilyHealth Surveys (2015{\textendash}2016) on the prevalence of stunting, underweightand wasting for a limited number of states in India (International Institutefor Population Sciences, 2016). We compared the prevalence from the mostrecent data for 13 states to the corresponding states from 2005{\textendash}06 (Fig. 3).Declines in undernutrition between 2005{\textendash}06 and 2015{\textendash}16 averaged 1.3\%/year for stunting, 1.6\%/year for underweight and 0.4\%/year for wasting since2015 (International Institute for Population Sciences, 2016). The sluggishpace of decline suggests that undernutrition continues to be a major diseaseburden among Indian children. It also suggests that macroeconomic growthexperienced by India in recent years has not contributed to any meaningfulreductions in child undernutrition in India (Subramanian et al., 2016,Subramanian and Subramanyam, 2015, Subramanyam et al., 2011). As weobserved in our original study (Corsi et al., 2015), and elsewhere (Subramanianet al., 2016), there is an urgent need to consider direct investments inconditions that more generally are reflective of the upstream and structuraldeterminants of undernutrition. Specifically, policies and interventions thataim to provide and sustain nutritional security at the household level arecritical to eliminating child undernutrition in India. Pursuing interventions inproximal risk factors without any improvements to broader socioeconomicand structural conditions, to put it bluntly, is likely to be waste of time andresources with little impact on reducing the burden of undernutrition amongchildren in India. }, author = {Corsi, Daniel J and Iv{\'a}n Mej{\'\i}a-Guevara and Subramanian, S V} } @article {1582362, title = {Rethinking policy perspectives on childhood stunting: time to formulate a structural and multifactorial strategy}, journal = {Maternal \& child nutrition}, volume = {12}, year = {2016}, pages = {219-236}, publisher = {Wiley Online Library}, abstract = { Stunting and chronic undernutrition among children in South Asia remaina major unresolved global health issue. There are compelling intrinsic andmoral reasons to ensure that children attain their optimal growth potentialfacilitated via promotion of healthy living conditions. Investments in efforts toensure that children{\textquoteright}s growth is not faltered also have substantial instrumentalbenefits in terms of cognitive and economic development. Using the case ofIndia, we critique three prevailing approaches to reducing undernutritionamong children: an over-reliance on macroeconomic growth as a potentpolicy instrument, a disproportionate focus on interpreting undernutrition asa demand-side problem and an over-reliance on unintegrated single-factorial(one at a time) approaches to a policy and research. Using existing evidence, wedevelop a case for support-led policy approach with a focus on integrated andstructural factors to addressing the problem of undernutrition among childrenin India. }, isbn = {1740-8695}, author = {Subramanian, S V and Mej{\'\i}a-Guevara, Iv{\'a}n and Krishna, Aditi} } @article {1582363, title = {Understanding the null-to-small association between increased macroeconomic growth and reducing child undernutrition in India: role of development expenditures and poverty alleviation}, journal = {Maternal \& child nutrition}, volume = {12}, year = {2016}, pages = {196-209}, publisher = {Wiley Online Library}, abstract = { Empirical evidence suggests that macroeconomic growth in India is notcorrelated with any substantial reductions in the prevalence of child\ undernutrition over time. This study investigates the two commonly hypothesized pathways through which macroeconomic growth is expected to reduce child undernutrition: (1) an increase in public developmental expenditure and (2) a reduction in aggregate income-poverty levels. For the anthropometric data on children, we draw on the data from two crosssectional waves of National Family Health Survey conducted in 1992-1993 and 2005-2006, while the data for per capita net state domestic product and per capita public spending on developmental expenditure and headcount ratio of poverty were obtained from the Reserve Bank of India and the Government of India expert committee reports. We find that between 1992-1993 and 2005-2006, state-level macroeconomic growth was not associated with any substantial increases in public development expenditure or substantial reductions in poverty at the aggregate level. Furthermore, the association between changes in public development expenditure or aggregate poverty and changes in undernutrition was small. In summary, it appears that the inability of macroeconomic growth to translate into reductions in child undernutrition in India is likely a consequence of the macroeconomic growth not translating into substantial investments in development expenditure that could matter for children{\textquoteright}s nutritional status and neither did it substantially improve incomes of the poor, a group where undernutrition is also the highest. The findings here build a case to advocate a {\textquoteleft}support-led{\textquoteright} strategy for reducing undernutrition rather than simply relying on a {\textquoteleft}growth-mediated{\textquoteright} strategy. Key messages Increases in macroeconomic growth have not been accompanied by substantial increases in public developmental spending or reduction in aggregate poverty headcount ratio in India. Association between increases in public development expenditure or poverty headcount ratios and changes in child undernutrition, in particular, child stunting, is small to null. Reducing the burden of undernutrition in India cannot be accomplished solely relying on a growth-mediated strategy, and a concerted support-led strategy is required. }, isbn = {1740-8695}, author = {William Joe and Rajaram, Ramaprasad and Subramanian, S V} } @article {1582364, title = {Limits to economic growth: why direct investments are needed to address child undernutrition in India}, journal = {Journal of Korean medical science}, volume = {30}, number = {Suppl 2}, year = {2015}, pages = {S131-S133}, abstract = { About two of every five undernourished young children of the world livein India. These high levels of child undernutrition have persisted in India forseveral years, even in its relatively well-developed states. Moreover, thispattern was observed during a period of rapid economic growth. Evidencefrom India and other developing countries suggests that economic growth haslittle to no impact on reducing child undernutrition. We argue that a growthmediatedstrategy is unlikely to be effective in tackling child undernutritionunless growth is pro-poor and leads to investment in programs addressing theroot causes of this persistent challenge. }, isbn = {1011-8934}, author = {Subramanian, S V and Subramanyam, Malavika A} } @webarticle {1582365, title = {Why childhood under-nutrition persists in India and how to intervene}, journal = {The Indian Express}, year = {2012}, abstract = { Recently, Prime Minister\ Manmohan Singh\ released a survey on child under-nutrition in rural India in 2010-11 (Hunger and Malnutrition Survey,HUNGaMA). Sadly,the new data reinforced the existence of an India marked by substantially low levels of something absolutely vital for adequate human development. The survey found that 42 per cent of the under-five children were underweight and 59 per cent were stunted in the 100 focus districts. Remarkably,in six districts with the best child development index,the prevalence of underweight (33 per cent) and stunting (43 per cent) among children,while somewhat lower,was still substantially high — suggesting the endemic and persistent nature of the under-nutrition burden. Even though child under-nutrition remains very high,do the data from HUNGaMA suggest an improvement over previous assessments? Data from the district-level health survey (DLHS) of 2002-2004 provide some answers. The DLHS includes data on underweight among children under six from hundreds of districts across India. In the 100 focus districts,the prevalence of underweight appeared to have reduced 11 percentage points from 53 per cent in the DLHS to 42 per cent in the HUNGaMA Survey. A similar comparison of changes in the prevalence of stunting is not possible since DLHS did not measure the height of children. Other aspects of the results from the HUNGaMA survey reiterate older patterns. For instance,under-nutrition is inversely associated with socio-economic status; thus children from low income households or whose mother had low levels of education have higher prevalence of under-nutrition. }, author = {Malavika Subramanyam} } @article {1582366, title = {Commentary: Measuring nutritional status of children}, journal = {International Journal of Epidemiology}, volume = {40}, number = {4}, year = {2011}, pages = {1030-1036}, abstract = { Leg length has been suggested as a proxy for nutritional and environmentalexposures in childhood given the associations observed in some Westernpopulations. Sanjay Kinra et al. present a careful assessment of thishypothesis in an Indian population in this issue of the International Journal ofEpidemiology and observe no association between nutritional supplementation and relative leg length, and relative lower leg length, among adolescents in the Hyderabad cohort. Although intriguing, given previous findings and the proposed sensitivity of {\textquoteleft}lower{\textquoteright} leg length as a marker for nutritional status, the null finding reported by Kinra and colleagues is in accord with other studies in non-Western populations. A number of alternative anthropometric, body compositional and biochemical methods are available for ascertaining nutritional status in children. Depending on the setting and the objective (individual clinical impression vs population nutritional assessment), these methods may have important advantages and disadvantages that we briefly consider. }, isbn = {0300-5771}, doi = {10.1093/ije/dyr108}, url = {https://doi.org/10.1093/ije/dyr108}, author = {Corsi, Daniel J and Subramanyam, Malavika A and Subramanian, S V} } @article {1582367, title = {Is economic growth associated with reduction in child undernutrition in India?}, journal = {PLoS Med}, volume = {8}, number = {3}, year = {2011}, pages = {e1000424}, publisher = {Public Library of Science}, abstract = { Economic growth is widely perceived as a major policy instrument in reducingchildhood undernutrition in India. We assessed the association betweenchanges in state per capita income and the risk of undernutrition amongchildren in India. Data for this analysis came from three cross-sectional wavesof the National Family Health Survey (NFHS) conducted in 1992{\textendash}93, 1998{\textendash}99, and 2005{\textendash}06 in India. The sample sizes in the three waves were 33,816,30,383, and 28,876 children, respectively. After excluding observationsmissing on the child anthropometric measures and the independent variablesincluded in the study, the analytic sample size was 28,066, 26,121, and 23,139,respectively, with a pooled sample size of 77,326 children. The proportionof missing data was 12\%{\textendash}20\%. The outcomes were underweight, stunting,and wasting, defined as more than two standard deviations below the WorldHealth Organization{\textendash}determined median scores by age and gender. We alsoexamined severe underweight, severe stunting, and severe wasting. The mainexposure of interest was per capita income at the state level at each surveyperiod measured as per capita net state domestic product measured in 2008prices. We estimated fixed and random effects logistic models that accountedfor the clustering of the data. In models that did not account for survey-periodeffects, there appeared to be an inverse association between state economicgrowth and risk of undernutrition among children. However, in modelsaccounting for data structure related to repeated cross-sectional designthrough survey period effects, state economic growth was not associatedwith the risk of underweight (OR 1.01, 95\% CI 0.98, 1.04), stunting (OR 1.02,95\% CI 0.99, 1.05), and wasting (OR 0.99, 95\% CI 0.96, 1.02). Adjustment fordemographic and socioeconomic covariates did not alter these estimates.Similar patterns were observed for severe undernutrition outcomes. Wefailed to find consistent evidence that economic growth leads to reductionin childhood undernutrition in India. Direct investments in appropriate healthinterventions may be necessary to reduce childhood undernutrition in India. }, isbn = {1549-1676}, author = {Subramanyam, Malavika A and Ichiro Kawachi and Berkman, Lisa F and Subramanian, S V} } @article {1582368, title = {Socioeconomic inequalities in childhood undernutrition in India: analyzing trends between 1992 and 2005}, journal = {PloS one}, volume = {5}, number = {6}, year = {2010}, pages = {e11392}, publisher = {Public Library of Science}, abstract = { India experienced a rapid economic boom between 1991 and 2007. However,this economic growth has not translated into improved nutritional statusamong young Indian children. Additionally, no study has assessed the trendsin social disparities in childhood undernutrition in the Indian context. Weexamined the trends in social disparities in underweight and stunting amongIndian children aged less than three years using nationally representativedata. We analyzed data from the three cross-sectional rounds of NationalFamily Health Survey of India from 1992, 1998 and 2005. The social factorsof interest were: household wealth, maternal education, caste, and urbanresidence. Using multilevel modeling to account for the nested structure andclustering of data, we fit multivariable logistic regression models to quantifythe association between the social factors and the binary outcome variables.The final models additionally included age, gender, birth order of child,religion, and age of mother. We analyzed the trend by testing for interactionof the social factor and survey year in a dataset pooled from all three surveys.While the overall prevalence rates of undernutrition among Indian childrenless than three decreased over the 1992-2005 period, social disparities inundernutrition over these 14 years either widened or stayed the same. Theabsolute rates of undernutrition decreased for everyone regardless of theirsocial status. The disparities by household wealth were greater than thedisparities by maternal education. There were no disparities in undernutritionby caste, gender or rural residence. There was a steady decrease in therates of stunting in the 1992-2005 period, while the decline in underweightwas greater between 1992 and 1998 than between 1998 and 2005. Socialdisparities in childhood undernutrition in India either widened or stayedthe same during a time of major economic growth. While the advantagesof economic growth might be reaching everyone, children from better-offhouseholds, with better educated mothers appear to have benefited to agreater extent than less privileged children. The high rates of undernutrition(even among the socially advantaged groups) and the persistent socialdisparities need to be addressed in an urgent and comprehensive manner. }, isbn = {1932-6203}, author = {Subramanyam, Malavika A and Ichiro Kawachi and Berkman, Lisa F and Subramanian, S V} } @article {1582369, title = {Association of maternal height with child mortality, anthropometric failure, and anemia in India}, journal = {Jama}, volume = {301}, number = {16}, year = {2009}, pages = {1691-1701}, publisher = {American Medical Association}, abstract = { Prior research on the determinants of child health has focused oncontemporaneous risk factors such as maternal behaviors, dietary factors,and immediate environmental conditions. Research on intergenerationalfactors that might also predispose a child to increased health adversityremains limited. To examine the association between maternal height andchild mortality, anthropometric failure, and anemia. We retrieved data fromthe 2005-2006 National Family Health Survey in India (released in 2008).The study population constitutes a nationally representative cross-sectionalsample of singleton children aged 0 to 59 months and born after January2000 or January 2001 (n = 50 750) to mothers aged 15 to 49 years from all29 states of India. Information on children was obtained by a face-to-faceinterview with mothers, with a response rate of 94.5\%. Height was measuredwith an adjustable measuring board calibrated in millimeters. Demographicand socioeconomic variables were considered as covariates. Modified Poissonregression models that account for multistage survey design and samplingweights were estimated. Mortality was the primary end point; underweight,stunting, wasting, and anemia were included as secondary outcomes. Inadjusted models, a 1-cm increase in maternal height was associated witha decreased risk of child mortality (relative risk [RR], 0.978; 95\% confidenceinterval [CI], 0.970-0.987; P \< .001), underweight (RR, 0.971; 95\% CI, 0.968-0.974; P \< .001), stunting (RR, 0.971; 95\% CI, 0.968-0.0973; P \< .001), wasting(RR, 0.989; 95\% CI, 0.984-0.994; P \< .001), and anemia (RR, 0.998; 95\% CI,0.997-0.999; P = .02). Children born to mothers who were less than 145 cmin height were 1.71 times more likely to die (95\% CI, 1.37-2.13) (absoluteprobability, 0.09; 95\% CI, 0.07-0.12) compared with mothers who were atleast 160 cm in height (absolute probability, 0.05; 95\% CI, 0.04-0.07). Similarpatterns were observed for anthropometric failure related to underweightand stunting. Paternal height was not associated with child mortality oranemia but was associated with child anthropometric failure. CONCLUSION:In a nationally representative sample of households in India, maternal heightwas inversely associated with child mortality and anthropometric failure. }, isbn = {0098-7484}, author = {Subramanian, S V and Ackerson, Leland K and Smith, George Davey and John, Neetu A} } @article {1582370, title = {Poverty, child undernutrition and morbidity: new evidence from India}, journal = {Bulletin of the World Health Organization}, volume = {83}, year = {2005}, pages = {210-216}, publisher = {SciELO Public Health}, abstract = { Undernutrition continues to be a primary cause of ill-health and prematuremortality among children in developing countries. This paper examines howthe prevalence of undernutrition in children is measured and argues thatthe standard indices of stunting, wasting and underweight may each beunderestimating the scale of the problem. This has important implicationsfor policy-makers, planners and organizations seeking to meet internationaldevelopment targets. Using anthropometric data on 24 396 children in India,we constructed an alternative composite index of anthropometric failure(CIAF) and compared it with conventional indices. The CIAF examines therelationship between distinct subgroups of anthropometric failure, povertyand morbidity, showing that children with multiple anthropometric failuresare at a greater risk of morbidity and are more likely to come from poorerhouseholds. While recognizing that stunting, wasting and underweight reflectdistinct biological processes of clear importance, the CIAF is the only measurethat provides a single, aggregated figure of the number of undernourishedchildren in a population. }, isbn = {0042-9686}, author = {Nandy, Shailen and Irving, Michelle and Gordon, David and Subramanian, S V and Smith, George Davey} }