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. 2023 Aug 4:23:101482.
doi: 10.1016/j.ssmph.2023.101482. eCollection 2023 Sep.

Explaining the poor-rich gap in anthropometric failure among children in India: An econometric analysis of the NFHS, 2021 and 2016

Gaurav Dhamija  1 , Mudit Kapoor  2 , Rockli Kim  3   4 , S V Subramanian  5   6
Affiliations

Explaining the poor-rich gap in anthropometric failure among children in India: An econometric analysis of the NFHS, 2021 and 2016

Gaurav Dhamija et al. SSM Popul Health. .

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 0-59 and 6-23 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.

Keywords: Anthropometric failure; India; Poor-rich gap; Risk factors; Wealth inequality.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig. 1
Fig. 1
Schematic representation of the 0–59 months old children from NFHS-5 and NFHS-4 included in the study.
Fig. 2
Fig. 2
Wealth inequality in anthropometric failure among children aged 0–59 months in India, 2019-21.
Fig. 3
Fig. 3
Distribution of wealth status among 0–59 months aged children suffering from stunting, severe stunting, underweight, severely underweight, wasting, and severe wasting in India, 2019-21.
Fig. 4
Fig. 4
Contribution of the risk factors in reducing the poor-rich gap in the prevalence of stunting and severe stunting among 0–59 months aged children.
Fig. 5
Fig. 5
Contribution of the risk factors in reducing the poor-rich gap in the prevalence of underweight and severely underweight among 0–59 months aged children.
Fig. 6
Fig. 6
Contribution of the risk factors in reducing the poor-rich gap in the prevalence of wasting and severe wasting among 0–59 months aged children.
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