Explaining Within- vs Between-Population Variation in Child Anthropometry and Hemoglobin Measures in India: A Multilevel Analysis of the National Family Health Survey 2015–2016

Abstract

Background: 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. Methods: 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, weight-for-age, weight-for-height, and hemoglobin level. Results: Most of the variation in child anthropometry and hemoglobin measures was attributable to within-population 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. Conclusions: Policies and interventions aimed at reducing between-population 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.

Keywords

• child undernutrition
• child growth
• anemia
• multilevel modeling
• variation
• inequalities
• india