Geo-visualising Diet, Anthroprometric and Clinical Indicators for Children in India

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 2015–2016. The study population included 225,002 children aged 0–59 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-ageþinspace}< -2 SD and weight-for-heightþinspace}< -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 (rþinspace}=þinspace}0.780, pþinspace}<þinspace}0.001), underweight (rþinspace}=þinspace}0.860, pþinspace}<þinspace}0.001), and wasting (rþinspace}=þinspace}0.857, pþinspace}<þinspace}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.

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 “convergence” 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’s national nutritional goals. This warrants a complete outreach of all the interventions from different sectors.

Minimum Dietary Diversity (MDD) is a widely used indicator of adequate
dietary micronutrient density for children 6–23 mo old. MDD food-group data
remain underutilized, despite their potential for further informing nutrition
programs and policies. We aimed to describe the diets of children meeting
MDD and not meeting MDD in India using food group data, nationally and
subnationally. Food group data for children 6–23 mo old (n = 73,036) from
the 2015–16 National Family Health Survey in India were analyzed. Per WHO
standards, children consuming ≥5 of the following food groups in the past
day or night met MDD: breast milk; grains, roots, or tubers; legumes or nuts;
dairy; flesh foods; eggs; vitamin A–rich fruits and vegetables; and other fruits
and vegetables. Children not meeting MDD consumed <5 food groups. We
analyzed the number and types of foods consumed by children meeting
MDD and not meeting MDD at the national and subnational geographic
levels. Nationally, children not meeting MDD most often consumed breast
milk (84.5%), grains, roots, and tubers (62.0%), and/or dairy (42.9%). Children
meeting MDD most often consumed grains, roots, and tubers (97.6%), vitamin
A–rich fruits and vegetables (93.8%), breast milk (84.1%), dairy (82.1%), other
fruits and vegetables (79.5%), and/or eggs (56.5%). For children not meeting
MDD, district-level dairy consumption varied the most (6.4%–79.9%), whereas
flesh foods consumption varied the least (0.0%–43.8%). For children meeting
MDD, district-level egg consumption varied the most (0.0%–100.0%), whereas
grains, roots, and tubers consumption varied the least (66.8%–100.0%).
Children not meeting MDD had low fruit, vegetable, and protein-rich food
consumption. Many children meeting MDD also had low protein-rich food
consumption. Examining the number and types of foods consumed highlights
priorities for children experiencing the greatest dietary deprivation, providing
valuable complementary information to MDD.

Ratio-based prevalence and absolute headcounts are the two most
commonly accepted metrics to measure the burden of various socioeconomic
phenomenon. However, ratio-based prevalence, calculated as the number of
cases with certain conditions relative to the total population, is by far the
most widely used to rank burden and consequently for targeting, across
different populations, often defined in terms of geographical areas. In this
regard, targeting areas exclusively based on prevalence-based metric poses
certain fundamental difficulties with some serious policy implications.
Drawing the data from the National Family Health Survey 2015–2016, and
Census 2011, this paper takes four indicators of child undernutrition in India
as an example to examine two contextual questions: first, does the choice
of metric matter for targeting areas for reducing child undernutrition in
India? and second; which metric should be used to facilitate comparisons
and targeting across variable populations? Our findings suggest a moderate
correlation between prevalence estimates and absolute headcounts implying
that choice of metric does matter when targeting child undernutrition. Huge
variations were observed between prevalence-based and absolute countbased
ranking of the districts. In fact, in various cases, districts with the
highest absolute number of undernourished children were ranked as relatively
lower-burden districts based on prevalence. A simple comparison between
the two approaches—when applied to targeting undernourished children in
India—indicates that prevalence-based prioritization may miss high-burden
areas where substantially higher number of undernourished children are
concentrated. For developing populous countries like India, which is already
grappling with high levels of maternal and child malnutrition and poor health
infrastructure along with intrinsic socioeconomic inequalities, it is critical to
adopt an appropriate metric for effective targeting and prioritization.

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.

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.

We assessed district-level geospatial trends in precision weighted prevalence
and absolute wealth disparity in stunting, underweight, wasting, low
birthweight, and anemia among children under five in India. The largest
wealth disparities were found for anthropometric failures and substantial
variation existed across states. We identified statistically significant (p < 0.001)
geospatial patterns in district-wide wealth disparities for all outcomes, which
differed from geospatial patterns for the overall prevalence. We characterized
each district as either a “Disparity”, “Pitfall”, “Intensity”, or “Prosperity” area
based on its overall burden and wealth disparity, as well as discuss the
importance of considering both measures for geographically-targeted public
health interventions to improve health equity.

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.

Healthy development of children in India is far from ensured. Proximate
determinants of poor child health outcomes are infectious diseases and
undernutrition, which are linked to socioeconomic status. In low- and
middle-income countries, researchers rely on wealth indices, constructed
from information on households’ asset ownership and amenities, to study
socioeconomic disparities in child health. Some of these wealth index items
can, however, directly affect the proximate determinants of child health. This
paper explores the independent association of each item used to construct
the Demographic and Health Surveys’ wealth index with diverse child health
outcomes. This cross-sectional study used nationally representative sample
of 245,866 children, age 0-59 months, from the Indian National Family Health
Surveys conducted in 2015-16. The study used conditional Poisson regression
models as well as a range of sensitivity specifications. After controlling for
socioeconomic status, health care use, maternal factors, community-level
factors, and all wealth index items, the following wealth index items were the
most consistently associated with child health; type of toilet facilities, water
source, refrigerator, pressure cooker, type of cooking fuel, land usable for
agriculture, household building material, mobile phone, and motorcycle/
scooter. The association with type of toilet facilities and water source was
particularly strong for mortality, showing a 16-35% and 14-28% lower
mortality, respectively. Most items used to construct the Demographic and
Health Surveys’ wealth index only indicate household socioeconomic status,
while a few items may affect child health directly, and can be useful targets
for policy intervention.

Anthropometry is the most commonly used approach for assessing
nutritional need among children. Anthropometry alone, however, cannot
differentiate between the two immediate causes of undernutrition:
inadequate diet vs disease. We present a typology of nutritional need by
simultaneously considering dietary and anthropometric measures, dietary
and anthropometric failures (DAF), and assess its distribution among children
in India. We used the 2015-16 National Family Health Survey, a nationally
representative sample of children aged 6-23 months (n = 67 247), from
India. Dietary failure was operationalized using World Health Organization
(WHO) standards for minimum dietary diversity. Anthropometric failure was
operationalized using WHO child growth reference standard z-score of <-2
for height-for-age (stunting), weight-for-age (underweight) and weight-forheight
(wasting). We also created a combined anthropometric measure for
children who had any one of these three anthropometric failures. We crosstabulated
dietary 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 distribution
of the four types, nationally, and across 640 administrative districts and 543
Parliamentary Constituencies (PCs) in India. Nationally, 80.3% of children
had dietary failure and 53.7% had at least one anthropometric failure. The
prevalence 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 for
46.1% of children; these children had nutritional needs identified by only one
of the two measures. Nationally, this translates to 12 181 627 children with
DFO and 3 281 913 children with AFO; the nutritional needs of these children
would 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%) and
lowest for AFO (5.5%-13.4%). The current emphasis on anthropometry for
measuring nutritional need should be complemented with diet- and foodbased
measures. By differentiating inadequate food intake from other causes
of undernutrition, the DAF typology brings precision in identifying nutritional
needs among children. These insights may improve the development and
targeting of nutrition interventions.

The Integrated Child Development Services (ICDS) program launched in
India in 1975 is one of the world’s largest flagship programs that aims to
improve early childhood care and development via a range of healthcare,
nutrition and early education services. The key to success of ICDS is in finding
solutions to the historical challenges of geographic and socioeconomic
inequalities in access to various services under this umbrella scheme. Using
birth history data from the National Family Health Survey (Demographic and
Health Survey), 2015-2016, this study presents (a) socioeconomic patterning
in service uptake across rural and urban India, and (b) continuum in service
utilization at three points (i.e., by mothers during pregnancy, by mothers
while breastfeeding and by children aged 0-72 months) in India. We used
an intersectional approach and ran a series multilevel logistic regression
(random effects) models to understand patterning in utilization among
mothers across socioeconomic groups. We also computed the area under
the receiver operating characteristic curve (ROC-AUC) based on a logistic
regression model to examine concordance between service utilization across
three different points. The service utilization (any service) by mothers during
pregnancy was about 20 percentage points higher for rural areas (60.5
percent; 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 nutrition
education during pregnancy (41.9 percent in rural) and early childcare
(preschool) (42.4 percent). One in every two mother-child pairs did not avail
any benefits from ICDS in urban areas. Estimates from random effects model
revealed higher odds of utilization among schedule caste mothers from
middle-class households in rural households. AUC estimates suggested a
high concordance between service utilization by mothers and their children
(AUC: 0.79 in rural; 0.84 in urban) implying a higher likelihood of continuum if
service utilization commences at pregnancy.

Despite the broad consensus that investments in nutrition-sensitive
programmes are required to reduce child undernutrition, in practice empirical
studies and interventions tend to focus on few nutrition-specific risk factors
in isolation. The 2015-16 National Family Health Survey provides the first
opportunity in more than a decade to conduct an up-to-date comprehensive
evaluation of the relative importance of various maternal and child health
and nutrition (MCHN) factors in respect to child anthropometric failures in
India. The primary analysis included 140,444 children aged 6-59 months with
complete data on 20 MCHN factors, and the secondary analysis included a
subset of 25,603 children with additional paternal data. Outcome variables
were stunting, underweight and wasting. We conducted logistic regression
models to first evaluate each correlate separately in age- and sex-adjusted
models, and then jointly in a mutually adjusted model. For all anthropometric
failures, indicators of past and present socioeconomic conditions showed the
most robust associations. The strongest correlates for stunting were short
maternal 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 household
air quality (OR: 1.22; 95%CI: 1.16, 1.29). Weaker associations were found
for other correlates, including dietary diversity, vitamin A supplementation
and breastfeeding initiation. Paternal factors were also important predictors
of anthropometric failures, but to a lesser degree than maternal factors.
The results remained consistent when stratified by children’s age (6-23
vs 24-59 months) and sex (girls vs boys), and when low birth weight was
additionally considered. Our findings indicate the limitation of nutritionspecific
interventions. Breaking multi-generational poverty and improving
environmental factors are promising investments to prevent anthropometric
failures in early childhood.

Inadequate dietary intake is a critical underlying determinant of child
undernutrition. This study examined the association between anthropometricbased
and food-based nutritional failure among children in India. We used the
2015-2016 National Nutrition Monitoring Bureau data where anthropometric
outcomes and food intake were both measured for each child. We followed
the World Health Organization child growth reference standards to define
anthropometric failures (i.e., height-for-age z score < -2 SD for stunting,
weight-for-age z score < -2 SD for underweight, and weight-for-height
z score < -2 SD for wasting), and the Indian Council of Medical Research
recommended dietary allowance (RDA) to define adequacy in intake of calorie,
protein, and fat. We used descriptive and regression-based assessments to
test the association between the two indicators of nutritional failure and also
computed 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 children
had below RDA norms consumption of calorie, protein, and fat, respectively.
We found weak-to-null correlation between anthropometric failures and
food failures (Pearson correlation ranging from -0.013 to 0.147) and poor
discriminatory 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 macronutrients
and draws attention toward adopting a multifactorial approach to improve
child nutrition in India. Poor food intake itself merits exclusive policy focus as
it is an important nutrition and health concern.

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.

We analyzed a sample of 112714 children from the 2015-2016 Indian National
Fertility and Health Survey with available data on hemoglobin. Multinomial
logistic regression models were used to establish associations between
parent anemia, household characteristics and nutritional intake of children.
Linear regression analysis was also conducted to see the link between the
household characteristic and childhood nutritional intake on one hand and
hemoglobin levels on the other hand. A number of socio-demographic
factors, namely maternal age, type of residence and maternal education, as
well as wealth index, among others correlate with incidence of childhood
anemia. For instance, whereas 52.9% of children in the richest households
were 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, from
sources 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%) of
the children surveyed were anemic (Hb level: 9.75 g/dL [9.59-9.91]). Children
with 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 lower
maternal hemoglobin level (OR: 1.992 (1.957-2.027)). Combining nutritional
supplementation and food-fortification programmes with reduction in
maternal anemia and family poverty may yield optimal improvement of
childhood anemia in India.

The complex etiology of child growth failure and anemia—commonly used
indicators of child undernutrition—involving proximate and distal risk factors
at multiple levels is generally recognized. However, their independent and
joint effects are often assessed with no clear conceptualization of inferential
targets.We utilized hierarchical linear modeling and a nationally representative
sample of 139,116 children aged 6–59 months from India (2015–2016) to
estimate the extent to which a comprehensive set of 27 covariates explained
the within- and between-population variation in height-for-age, weightfor-
age, weight-for-height, and hemoglobin level.Most of the variation in
child anthropometry and hemoglobin measures was attributable to withinpopulation
differences (80–85%), whereas between-population differences
(including communities, districts, and states) accounted for only 15–20%.
The proximate and distal covariates explained 0.2–7.5% of within-population
variation and 2.1–34.0% of between-population variation, depending on
the indicator of interest. Substantial heterogeneity was observed in the
magnitude of within-population variation, and the fraction explained, in
child anthropometry and hemoglobin measures across the 36 states/union
territories of India.Policies and interventions aimed at reducing betweenpopulation
inequalities in child undernutrition may require a different set of
components than those concerned with within-population inequalities. Both
are needed to promote the health of the general population, as well as that
of high-risk children.

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.

Most interventions to foster child growth and development in India focus
on improving food quality and quantity. We aimed to assess the pattern in
food consumption and dietary diversity by socioeconomic status (SES) among
Indian children. The most recent nationally representative, cross-sectional
data from the National Family Health Survey (NFHS-4, 2015-16) was used
for analysis of 73,852-74,038 children aged 6-23 months. Consumption of
21 food items, seven food groups, and adequately diversified dietary intake
(ADDI) was collected through mother’s 24-h dietary recall. Logistic regression
models were conducted to assess the association between household wealth
and maternal education with food consumption and ADDI, after controlling
for 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 household
wealth 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), but
the SES gradient was not particularly strong. Furthermore, the associations
between SES and consumption of individual food items and food groups
were not consistent. Maternal education was more strongly associated with
consumption of essential food items and all food groups, but household
wealth was found to have significant influence on intake of dairy group only.
CONCLUSIONS: Interventions designed to improve food consumption and
diversified dietary intake among Indian children need to be universal in their
targeting given the overall high prevalence of inadequate dietary diversity
and the relatively small differentials by SES.

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 proportions
of children who suffer persistent stunting, recover, and falter and become
newly stunted between birth and adolescence. We use longitudinal data
collected on 7,128 children in Ethiopia, India, Peru, and Vietnam. Data were
collected in five survey waves between the ages of 1 to 15 years. We use
descriptive and graphical approaches to compare the trajectories of children
first stunted by age 1, first stunted by age 5, and those remained not stunted
until 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 not
stunted at either age 1 or age 5. A larger percentage of children stunted by
age 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 during
later childhood. 13.1% of children who were not stunted at age 1 or age 5
become newly stunted between the ages of 8 and 15. Our results show that
children both become stunted and recover from stunting into adolescence.
More attention should be paid to interventions to support healthy growth
throughout childhood.

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.