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Multilevel analysis of geographic variation among correlates of child undernutrition in India
Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual‐level risk factors are geographically distri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189194/ https://www.ncbi.nlm.nih.gov/pubmed/33960621 http://dx.doi.org/10.1111/mcn.13197 |
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author | Jain, Anoop Rodgers, Justin Li, Zhihui Kim, Rockli Subramanian, SV |
author_facet | Jain, Anoop Rodgers, Justin Li, Zhihui Kim, Rockli Subramanian, SV |
author_sort | Jain, Anoop |
collection | PubMed |
description | Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual‐level risk factors are geographically distributed. Assessing the geographic distribution, especially at multiple levels, matters as it can inform where, and at what level, interventions should be targeted. The three levels of significance in the Indian context are villages, districts, and states. Thus, the purpose of this paper was to (a) examine what proportion of the variation in 21 risk factors is attributable to villages, districts, and states in India and (b) elucidate the specific states where these risk factors are clustered within India. Using the fourth National Family Health Survey dataset, from 2015 to 2016, we found that the proportion of variation attributable to villages ranged from 14% to 63%, 10% to 29% for districts and 17% to 62% for states. Furthermore, we found that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh were in the highest risk quintile for more than 10 of the risk factors included in our study. This is an indication of geographic clustering of risk factors. The risk factors that are clustered in states such as Bihar, Jharkhand, Madhya Pradesh and Uttar Pradesh underscore the need for policies and interventions that address a broader set of child malnutrition determinants beyond those that are nutrition specific. |
format | Online Article Text |
id | pubmed-8189194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81891942021-06-16 Multilevel analysis of geographic variation among correlates of child undernutrition in India Jain, Anoop Rodgers, Justin Li, Zhihui Kim, Rockli Subramanian, SV Matern Child Nutr Original Articles Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual‐level risk factors are geographically distributed. Assessing the geographic distribution, especially at multiple levels, matters as it can inform where, and at what level, interventions should be targeted. The three levels of significance in the Indian context are villages, districts, and states. Thus, the purpose of this paper was to (a) examine what proportion of the variation in 21 risk factors is attributable to villages, districts, and states in India and (b) elucidate the specific states where these risk factors are clustered within India. Using the fourth National Family Health Survey dataset, from 2015 to 2016, we found that the proportion of variation attributable to villages ranged from 14% to 63%, 10% to 29% for districts and 17% to 62% for states. Furthermore, we found that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh were in the highest risk quintile for more than 10 of the risk factors included in our study. This is an indication of geographic clustering of risk factors. The risk factors that are clustered in states such as Bihar, Jharkhand, Madhya Pradesh and Uttar Pradesh underscore the need for policies and interventions that address a broader set of child malnutrition determinants beyond those that are nutrition specific. John Wiley and Sons Inc. 2021-05-07 /pmc/articles/PMC8189194/ /pubmed/33960621 http://dx.doi.org/10.1111/mcn.13197 Text en © 2021 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Jain, Anoop Rodgers, Justin Li, Zhihui Kim, Rockli Subramanian, SV Multilevel analysis of geographic variation among correlates of child undernutrition in India |
title | Multilevel analysis of geographic variation among correlates of child undernutrition in India |
title_full | Multilevel analysis of geographic variation among correlates of child undernutrition in India |
title_fullStr | Multilevel analysis of geographic variation among correlates of child undernutrition in India |
title_full_unstemmed | Multilevel analysis of geographic variation among correlates of child undernutrition in India |
title_short | Multilevel analysis of geographic variation among correlates of child undernutrition in India |
title_sort | multilevel analysis of geographic variation among correlates of child undernutrition in india |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189194/ https://www.ncbi.nlm.nih.gov/pubmed/33960621 http://dx.doi.org/10.1111/mcn.13197 |
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