Poverty induced inequality in nutrition among children born during 2010-2021 in India.

INTRODUCTION

Almost two-fifth of the children in India is stunted and among various factors, poverty differential in child undernutrition is the largest. Using the latest population-based survey of National Family Health Survey, 2015-16 and 2019-21 this paper examined the poverty induced inequality in child stunting across the sub-populations of India.

METHODS

A sample of 213,136 children aged between 0-5 years from NFHS fourth round and 98,222 children in the same age group from the NFHS fifth round constitute the study sample. The wealth index is used as the proxy of household's economic wellbeing and height-for-age (HAZ) z-score of a child is used to identify the stunting status of the child. Box plots are drawn to understand the distributional characteristics of the HAZ score for both the study sample. We calculate the Erreygers corrected concentration index and decomposed the concentration indices using Gonzalo-Almorox and Urbanos-Garrido method.

RESULTS

During 2015-16, more than half of the children from the poorest wealth quintile were stunted (52%), compared to 22% among the children from richest wealth quintile. In 2015-16, stunting was as high as 65% among the children of mothers with low stature (height less than 145 cm) and from the poorest wealth quintile whereas, the prevalence was observed 56% from the same sub-population during 2019-21. Among various factors, the concentration index of stunting was observed highest among the children of 36-47 months (-0.28) followed by children of age 48-59 months (-0.27) and among the fully immunized children (-0.25). Similar to NFHS-4, NFHS-5 also shows a predominantly higher socio-economic inequality among 24+ months children and among the fully immunised children. Factors like child age, birth order and sanitation showed positive elasticity. Decomposition analysis of NFHS-4 data shows that due to uneven distribution of wealth, mother's education as a determinant of child stunting solely explained 33% of the overall inequality followed by improved access to sanitation (24%), mother's height (8%) and place of residence (5%). Similar to NFHS-4, NFHS-5 data also shows that mother's education, sanitation, mother's height and place of residence predominantly contributes to the overall wealth inequality in child stunting.

CONCLUSIONS

In India, poverty differential in child undernutrition is acute among the different sub-population of children. And the concentration of stunted children is higher among the different sub-population with higher wealth poverty. Mother's education, improved sanitation and mother's height explained larger variation in the overall inequalities in child nutrition across India.