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Assessing associational strength of 23 correlates of child anthropometric failure: An econometric analysis of the 2015-2016 National Family Health Survey, India

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  • Kim, Rockli
  • Rajpal, Sunil
  • Joe, William
  • Corsi, Daniel J.
  • Sankar, Rajan
  • Kumar, Alok
  • Subramanian, S.V.

Abstract

Despite the broad consensus that investments in nutrition-sensitive programmes are required to reduce child undernutrition, in practice empirical studies and interventions tend to focus on few nutrition-specific risk factors in isolation. The 2015–16 National Family Health Survey provides the first opportunity in more than a decade to conduct an up-to-date comprehensive evaluation of the relative importance of various maternal and child health and nutrition (MCHN) factors in respect to child anthropometric failures in India. The primary analysis included 140,444 children aged 6–59 months with complete data on 20 MCHN factors, and the secondary analysis included a subset of 25,603 children with additional paternal data. Outcome variables were stunting, underweight and wasting. We conducted logistic regression models to first evaluate each correlate separately in age- and sex-adjusted models, and then jointly in a mutually adjusted model. For all anthropometric failures, indicators of past and present socioeconomic conditions showed the most robust associations. The strongest correlates for stunting were short maternal stature (OR: 4.39; 95%CI: 4.00, 4.81), lack of maternal education (OR: 1.74; 95%CI: 1.60, 1.89), low maternal BMI (OR: 1.64; 95%CI: 1.54, 1.75), poor household wealth (OR: 1.25; 95%CI: 1.15, 1.35) and poor household air quality (OR: 1.22; 95%CI: 1.16, 1.29). Weaker associations were found for other correlates, including dietary diversity, vitamin A supplementation and breastfeeding initiation. Paternal factors were also important predictors of anthropometric failures, but to a lesser degree than maternal factors. The results remained consistent when stratified by children's age (6–23 vs 24–59 months) and sex (girls vs boys), and when low birth weight was additionally considered. Our findings indicate the limitation of nutrition-specific interventions. Breaking multi-generational poverty and improving environmental factors are promising investments to prevent anthropometric failures in early childhood.

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  • Kim, Rockli & Rajpal, Sunil & Joe, William & Corsi, Daniel J. & Sankar, Rajan & Kumar, Alok & Subramanian, S.V., 2019. "Assessing associational strength of 23 correlates of child anthropometric failure: An econometric analysis of the 2015-2016 National Family Health Survey, India," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    • Handle: RePEc:eee:socmed:v:238:y:2019:i:c:27
    DOI: 10.1016/j.socscimed.2019.112374
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    References listed on IDEAS

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    1. Perkins, Jessica M. & Kim, Rockli & Krishna, Aditi & McGovern, Mark & Aguayo, Victor M. & Subramanian, S.V., 2017. "Understanding the association between stunting and child development in low- and middle-income countries: Next steps for research and intervention," Social Science & Medicine, Elsevier, vol. 193(C), pages 101-109.
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    4. Corsi, Daniel J. & Mejía-Guevara, Iván & Subramanian, S.V., 2016. "Risk factors for chronic undernutrition among children in India: Estimating relative importance, population attributable risk and fractions," Social Science & Medicine, Elsevier, vol. 157(C), pages 165-185.
    5. Rana Khan & Muhammad Raza, 2016. "Determinants of malnutrition in Indian children: new evidence from IDHS through CIAF," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 299-316, January.
    6. Aluísio J D Barros & Cesar G Victora, 2013. "Measuring Coverage in MNCH: Determining and Interpreting Inequalities in Coverage of Maternal, Newborn, and Child Health Interventions," PLOS Medicine, Public Library of Science, vol. 10(5), pages 1-9, May.
    7. Kim, Rockli & Mejía-Guevara, Iván & Corsi, Daniel J. & Aguayo, Víctor M. & Subramanian, S.V., 2017. "Relative importance of 13 correlates of child stunting in South Asia: Insights from nationally representative data from Afghanistan, Bangladesh, India, Nepal, and Pakistan," Social Science & Medicine, Elsevier, vol. 187(C), pages 144-154.
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    Cited by:

    1. Li, Zhihui & Kim, Rockli & Subramanian, S.V., 2021. "Economic-related inequalities in child health interventions: An analysis of 65 low- and middle-income countries," Social Science & Medicine, Elsevier, vol. 277(C).
    2. Adithya Pradyumna & Mirko S. Winkler & Jürg Utzinger & Andrea Farnham, 2021. "Association of Livestock Ownership and Household Dietary Quality: Results from a Cross-Sectional Survey from Rural India," IJERPH, MDPI, vol. 18(11), pages 1-12, June.
    3. 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).

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