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

被引:1
作者
Dhamija, Gaurav [1 ]
Kapoor, Mudit [2 ]
Kim, Rockli [3 ,4 ]
Subramanian, S. V. [5 ,6 ,7 ]
机构
[1] Indian Inst Technol, Hyderabad, Telangana, India
[2] Indian Stat Inst, New Delhi, India
[3] Korea Univ, Coll Hlth Sci, Div Hlth Policy & Management, Seoul, South Korea
[4] Korea Univ, Dept Publ Hlth Sci, Interdisciplinary Program Precis Publ Hlth, Grad Sch, Seoul, South Korea
[5] Harvard TH Chan Sch Publ Hlth, Dept Social & Behav Sci, Boston, MA USA
[6] Harvard Ctr Populat & Dev Studies, Cambridge, MA USA
[7] Harvard TH Chan Sch Publ Hlth, 677 Huntington Ave, Boston, MA 02115 USA
关键词
Anthropometric failure Wealth inequality Poor-rich gap Risk factors India; SOCIOECONOMIC INEQUALITY; RELATIVE IMPORTANCE; MALNUTRITION; UNDERNUTRITION; TRENDS;
D O I
10.1016/j.ssmph.2023.101482
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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 nonpregnant 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.
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页数:11
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