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A quantile regression analysis of dietary diversity and anthropometric outcomes among children and women in the rural–urban interface of Bangalore, India

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  • Purushotham, Anjali
  • Mittal, Nitya
  • Ashwini, B.C.
  • Umesh, K.B.
  • von Cramon-Taubadel, Stephan
  • Vollmer, Sebastian

Abstract

Based on a primary survey conducted in the rural–urban interface of Bangalore, this study contributes to the understanding of the relationship between dietary diversity (DD) and anthropometric outcomes of young children (6 months – 5 years) (measured by weight-for-age (WAZ), weight-for-height (WHZ), and height-for-age (HAZ) z-scores), school-aged children (6–14 years) (measured by Body Mass Index (BMI) z-scores and HAZ scores), and women (15 years and above) (measured by BMI). We examine this association not just at the mean, but also at different points of the conditional distribution of anthropometric outcomes using the quantile regression (QR) method. We use six different measures of individual- and household-level DD to check whether the estimated association depends on the choice of the metric used. Our results show that increased DD is associated with higher z-scores at the lower quantiles of the WAZ distribution. In addition, we find a positive association between DD and upper quantiles of WHZ and BMI z-scores of young and school-aged children, respectively. Except for these, no other associations at any other quantile for any anthropometric outcome of young children, school-aged children, and women are consistently significant for various measures of DD. Our results suggest that policies that focus on improving DD might not be effective in improving (most) anthropometric outcomes especially in areas facing multiple burdens of malnutrition.

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  • Purushotham, Anjali & Mittal, Nitya & Ashwini, B.C. & Umesh, K.B. & von Cramon-Taubadel, Stephan & Vollmer, Sebastian, 2022. "A quantile regression analysis of dietary diversity and anthropometric outcomes among children and women in the rural–urban interface of Bangalore, India," Food Policy, Elsevier, vol. 107(C).
    • Handle: RePEc:eee:jfpoli:v:107:y:2022:i:c:s0306919221001950
    DOI: 10.1016/j.foodpol.2021.102216
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