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.

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 January 7th, 2020 and October 18th, 2020 across 543 PCs and 721 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.

The National Family Health Survey is analysed to develop critical insights on child anthropometric failure in India. The analysis finds non-response of economic
growth on nutritional well-being and greater burden among the poor as two
fundamental concerns. This calls for strengthening developmental finance
for socio-economic upliftment as well as enhanced programmatic support
for nutritional interventions. The gaps in analytical inputs for programmatic
purposes also deserves attention to unravel intricacies that otherwise remain
obscured through customary enquiries. On the one hand, this may serve well
to improve policy targeting, and on the other, this can help comprehend the
nature and reasons of heterogeneities and inequities in nutritional outcomes
across subgroups. Strengthening the analytical capacities of programme
managers and health functionaries is recommended.Against this backdrop,
this paper outlines key programmatic concerns that require substantial
local-level insights for strategic feedback and course corrections to achieve
accelerated reductions in child undernutrition. The issues discussed are based
on the analysis of household survey data from NFHS 2015–16.

Childhood stunting is often conceptualised as a singular concept (i.e., stunted
or not), and such an approach implies similarity in the experiences of children
who are stunted. Furthermore, risk factors for stunting are often treated in
isolation, and limited research has examined how multiple risk factors interact
together. Our aim was to examine whether there are subgroups among
stunted children, and if parental characteristics influence the likelihood of
these subgroups among children. Children who were stunted were identified
from the 2005-2006 Indian National Family Health Survey (n = 12,417).
Latent class analysis was used to explore the existence of subgroups among
stunted children by their social, demographic, and health characteristics.
We examined whether parental characteristics predicted the likelihood of
a child belonging to each latent class using a multinomial logit regression
model. We found there to be 5 distinct groups of stunted children; “poor,
older, and poor health-related outcomes,” “poor, young, and poorest healthrelated
outcomes,” “poor with mixed health-related outcomes,” “wealthy
and good health-related outcomes,” and “typical traits.” Both mother and
father’s educational attainment, body mass index, and height were important
predictors of class membership. Our findings demonstrate evidence that
there is heterogeneity of the risk factors and behaviours among children who
are stunted. It suggests that stunting is not a singular concept; rather, there
are multiple experiences represented by our “types” of stunting. Adopting a
multidimensional approach to conceptualising stunting may be important for
improving the design and targeting of interventions for managing stunting.

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.

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.

Economic growth is widely perceived as a major policy instrument in reducing
childhood undernutrition in India. We assessed the association between
changes in state per capita income and the risk of undernutrition among
children in India. Data for this analysis came from three cross-sectional waves
of the National Family Health Survey (NFHS) conducted in 1992–93, 1998–
99, and 2005–06 in India. The sample sizes in the three waves were 33,816,
30,383, and 28,876 children, respectively. After excluding observations
missing on the child anthropometric measures and the independent variables
included 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 proportion
of missing data was 12%–20%. The outcomes were underweight, stunting,
and wasting, defined as more than two standard deviations below the World
Health Organization–determined median scores by age and gender. We also
examined severe underweight, severe stunting, and severe wasting. The main
exposure of interest was per capita income at the state level at each survey
period measured as per capita net state domestic product measured in 2008
prices. We estimated fixed and random effects logistic models that accounted
for the clustering of the data. In models that did not account for survey-period
effects, there appeared to be an inverse association between state economic
growth and risk of undernutrition among children. However, in models
accounting for data structure related to repeated cross-sectional design
through survey period effects, state economic growth was not associated
with 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 for
demographic and socioeconomic covariates did not alter these estimates.
Similar patterns were observed for severe undernutrition outcomes. We
failed to find consistent evidence that economic growth leads to reduction
in childhood undernutrition in India. Direct investments in appropriate health
interventions may be necessary to reduce childhood undernutrition in India.

The National Family Health Survey (NFHS) 2015–16, finds that every second
child in India suffers from at least one form of nutrition failure. Dichotomised
indicators of underweight and wasting based on z-score cut-off does not
provide any information regarding those children who are clustered around
the threshold and are at an elevated risk of undernutrition through any minor
weight-loss. This paper aims to estimate the effect of bodyweight shocks on
net increments in the prevalence of child underweight and wasting among
the poorest households in India. We used cross-sectional information from
NFHS 2015–16 to estimate possible increase in the prevalence of child
underweight and wasting as a result of reduction in their bodyweight. The
shocks are presumed to range from a minimum of 0.5% to a maximum
5% reduction in the bodyweight for every child from the poorest 20%
households. Various raw weight measures scenarios were developed and
transformed into age- specific z-scores using World Health Organization child
growth standards. Nutritional status of children is sensitive to smallest of the
shocks to bodyweight. In fact, a reduction of 0.5 and 1 percent in weight can
lead to substantial increase in underweight and wasting prevalence. Under a
scenario of bodyweight shock of 0.5 percent, the prevalence of underweight
and wasting will increase by 1.42 and 1.36 percentage points, respectively.
These estimates get translated into 410,413 and 392,886 additional cases
of underweight and wasting, respectively. With such high concentration of
children around the undernutrition threshold, any minor shock to nutritional
health of the children can have major implications. In the current scenario of
national lockdown and restrictions due to coronavirus disease 2019 pandemic,
it is critical to ensure an uninterrupted supply of nutritious meals and food
supplements to the poor children while arresting the infection spread.

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.