A Decomposition Analysis of Inequality in Malnutrition Among Under Five Children in India: Findings from National Family Health Survey-5

Author:

Kabdwal Naresh Chandra1,Yadav Niraj Kumar1,Singh Kh. Jitenkumar,Yadav Jitendra

Affiliation:

1. Banasthali Vidyapith

Abstract

Abstract

Background: Nutrition is essential for good health and human development, particularly during the early stages of life. Nutritional status of children is essential for their development and growth at early stage of lives, with implications extending into adult life. Malnutrition is recognized to be the biggest single threat to the public health worldwide, particularly in developing countries. Nutritional status can be determined anthropometrically which is the outcome of complex interactions between socio-economic and biological variables. This study aimed to measure malnutrition inequality among underfive children in India and we have used a regression-based decomposition analysis to see the impact of socioeconomic determinants on this inequality. Methods: The study utilizes data from the National Family Health Survey (NFHS-5) conducted between 2019 and 2021. To examine the magnitude of socioeconomic inequality in child malnutrition, the concentration indices for stunting, underweight, and wasting are employed. Furthermore, decomposition analysis of the concentration indices is conducted to understand the role of socio-economic factors in child-hood malnutrition inequality. Results: The obtained concentration indices of stunting, underweight, and wasting were respectively -0.126, -0.138, and -0.064. Socioeconomic inequality in underweight and stunting was statistically significant, with children in the lowest socioeconomic quintile bearing a higher burden of malnutrition; however, no socio-economic gradient was observed in wasting. Urban children in the lowest quintiles experienced a higher burden of stunting than rural children, according to the concentration index value derived from the area of residence. Furthermore, socioeconomic status significantly influenced malnutrition inequality, with approximately 36% of the inequality in stunting, 44% in underweight, and over 68% in wasting attributed to family socioeconomic status. Conclusion: The average reduction in the national-level malnutrition indices reflects the impact of malnutrition among children in low-income families. To effectively address this issue, the government and policymakers must implement direct and targeted actions aimed at eliminating current inequities in the socio-economic determinants linked with malnutrition. By prioritizing interventions that specifically target vulnerable populations and address the underlying socioeconomic factors contributing to malnutrition, policymakers can work towards achieving equitable access to nutrition and improving the health outcomes of all children.

Publisher

Research Square Platform LLC

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