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- Title
Linkage in stunting status of siblings: a new perspective on childhood undernutrition in India.
- Authors
Banerjee, Kajori; Dwivedi, Laxmi Kant
- Abstract
Almost 30% of the world's stunted children reside in India. This study examined sibling linkage in childhood stunting by assessing the extent of clustering of stunted children born to the same mother. Data were taken from 225,002 children under the age of five from the Indian National Family and Health Survey (NFHS)-4 conducted in 2015-16. States with high fertility and lower socioeconomic development displayed higher clustering of childhood stunting among siblings. Simulating removal of this clustered burden showed an almost 10 percentage point reduction in stunting in India. Multinomial regression analysis highlighted that the propensity to have multiple stunted births was higher among less-educated women, scheduled caste/tribes and poor households. The multilevel model results indicated that the odds of stunting for the index child increased by 1.93 if the older sibling was stunted. The odds of the index child being stunted if the previous child was stunted were high, irrespective of the differences in state-level public health performances and political commitments. Although socioeconomic correlates play a crucial role in determining child stunting status, they also act as proxies for poor-quality intra-generational health. Clustering of stunting among siblings is an indicator of both genetic and environmental association with the height-for-age (HAZ) of children. Mothers with repeated stunted births should be prioritized and monitored over a substantial part of their lives. Inclusion of multiple child beneficiaries in nutrition policies and revisiting the 'one size fits all' concept at the micro level, owing to the substantial village/ward-level variation, might be an effective policy measure.
- Subjects
INDIA; MALNUTRITION; SIBLINGS; MULTIPLE birth; CHILD nutrition; MULTILEVEL models; NUTRITION policy; STATISTICS; MOTHERS; FAMILIES; REGRESSION analysis; FAMILY health; CLUSTER analysis (Statistics); GROWTH disorders
- Publication
Journal of Biosocial Science, 2020, Vol 52, Issue 5, p681
- ISSN
0021-9320
- Publication type
Academic Journal
- DOI
10.1017/S0021932019000725