Assessing associational strength of 23 correlates of child anthropometric failure

An econometric analysis of the 2015-2016 National Family Health Survey, India

Bibliographic Data

ID4900217
AuthorsRockli Kim (0000-0002-9864-3957), Sunil Rajpal (0000-0001-8607-1878, Tata Trusts), William Joe (0000-0003-3282-658X, Institute of Economic Growth), Daniel J Corsi (0000-0001-7063-3354, Ottawa Hospital Research Institute), Rajan Sankar (Tata Trusts), Alok Kumar (0000-0002-4549-1400, Government of India), V Subramanian (0000-0003-2365-4165, Harvard University, corresponding author)
Year2019
Volume238
Pages112374
Publication date2019-10-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSocial Science & Medicine (JOURNAL)
Journal identifiersISSN: 0277-9536 • E-ISSN: 1873-5347
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.socscimed.2019.112374
PMID31345611
OpenAlexW2950573897
LanguageEN
Citations received26
References cited29

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

Anthropometry · Body mass index · Breastfeeding · Environmental health · Malnutrition · Overweight · Population · Psychological intervention · Socioeconomic status · Underweight · Wasting · Child Nutrition and Feeding Issues · Child Nutrition and Water Access · Demography · Medicine · Poverty, Education, and Child Welfare · Gerontology · Pediatrics

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