|Socio-economic inequality in malnutrition among children in India: an analysis of 640 districts from National Family Health Survey (2015–16)|
||Shrikant Singh, Swati Srivastava, and Ashish Kumar Upadhyay
||International Journal for Equity in Health, 18: 203; DOI:10.1186/s12939-019-1093-0
Despite a fast-growing economy and the largest anti-malnutrition programme, India has the world’s worst level of child malnutrition. Despite India’s 50% increase in GDP since 1991, more than one third of the world’s malnourished children live in India. Among these, half of the children under age 3 years are underweight and a third of wealthiest children are over-nutrient. One of the major causes for malnutrition in India is economic inequality. Therefore, using the data from the fourth round of National Family Health Survey (2015–16), present study aims to examine the socio-economic inequality in childhood malnutrition across 640 districts of India.
Concentration curve and generalized concentration index were used to examine the socioeconomic inequalities in malnutrition. However, regression-based decomposition methodology was used to decomposes the causes of inequality in childhood malnutrition.
Result shows that about 38% children in India were stunted and 35% were underweight during 2015–16. Prevalence of stunting and underweight children varies considerably across Indian districts (13 to 65% and 7 to 67% respectively). Districts having the higher share of undernourished children is coming from the particular regions like central, east and west part of the country. On an average about 35% of household in a district having the access of safe drinking water and 42% of household in a district exposed to open defecation. The study found the inverse relationship between district’s economic development with childhood stunting and underweight. The concentration of stunted as well as underweight children were found in least developed districts of India. Decomposition approach found that practice of open defecation is positively influenced the inequality in stunting and underweight. Further, inequality in undernutrition is accelerated by the height and education of the mother, and availability of safe drinking water in a district.
The districts that lied out in a spectrum of developmental diversity are required some specific set of information’s that covering socio-economic, demographic and health-related quality of life of people in those backward districts. More generally, policies to avail improved water and sanitation facility to public and female literacy should be continued. It is also important to see that the benefits of both infrastructure and more general economic development are spread more evenly across districts.