Gender Differences in Double Burden of Malnutrition in India: Quantile Regression Estimates

Archana Agnihotri () and Brinda Viswanathan ()
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Archana Agnihotri: (Corresponding author), Research, Chennai, India
Brinda Viswanathan: Professor, Madras School of Economics, Chennai, India

Working Papers from Madras School of Economics,Chennai,India

Abstract: India has witnessed growing prevalence of double burden of malnutrition among both men and women. Based on BMI quantile regression estimates using NFHS-4 data, a comparative assessment on the role of dietary patterns, lifestyle, education, health and hygiene, household’s demographic composition and region of residence on double burden of malnutrition, is provided separately for men and women in India. NFHS-4 data differs in sample size and nature of questions for men and women. In order to provide robustness checks gendered comparisons are also discussed by contrasting the results from full sample with the sub-samples for couples, and women only from the households of male sample. Within each BMI quintile BMI increases with education except for women in top quintile where the magnitude reduces for 10 or more years and even more for 12 or more years of education, after controlling for other factors. This perhaps is a reflection of an expectation for women to be lean than it may be for men as they are more likely to be younger and exposed to media particularly social media. Vegan diets worsen BMI for the lowest quintile while the same diet is beneficial to those at the top quintile. For men sedentary occupations are associated with overweight and for women household drudgery is associated with increased underweight. There is a broad geographic segregation of malnutrition with low BMI more prevalent in Central and Eastern India and high BMI in Southern and Northern India while double burden is more prevalent among men in Western India. Overall, the conditional quantile estimates are discerning of the covariates associated with double burden of malnutrition in India compared to the conditional mean (OLS) estimates.

Keywords: BMI; Quantile Regression; Gendered Difference; Diet; Lifestyle; Sample Size (search for similar items in EconPapers)
JEL-codes: C21 C83 I12 J16 L66 (search for similar items in EconPapers)
Pages: 64 pages
Date: 2021-08
New Economics Papers: this item is included in nep-agr
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