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Spatial heterogeneity and correlates of child malnutrition in districts of India

BACKGROUND: Despite sustained economic growth and reduction in money metric poverty in last two decades, prevalence of malnutrition remained high in India. During 1992–2016, the prevalence of underweight among children had declined from 53% to 36%, stunting had declined from 52% to 38% while that of...

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Autores principales: Khan, Junaid, Mohanty, Sanjay K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6098604/
https://www.ncbi.nlm.nih.gov/pubmed/30119652
http://dx.doi.org/10.1186/s12889-018-5873-z
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author Khan, Junaid
Mohanty, Sanjay K
author_facet Khan, Junaid
Mohanty, Sanjay K
author_sort Khan, Junaid
collection PubMed
description BACKGROUND: Despite sustained economic growth and reduction in money metric poverty in last two decades, prevalence of malnutrition remained high in India. During 1992–2016, the prevalence of underweight among children had declined from 53% to 36%, stunting had declined from 52% to 38% while that of wasting had increased from 17% to 21% in India. The national average in the level of malnutrition conceals large variation across districts of India. Using data from the recent round of National Family Health Survey (NFHS), 2015–16 this paper examined the spatial heterogeneity and meso-scale correlates of child malnutrition across 640 districts of India. METHODS: Moran’s I statistics and bivariate LISA maps were used to understand spatial dependence and clustering of child malnutrition. Multiple regression, spatial lag and error models were used to examine the correlates of malnutrition. Poverty, body mass index (BMI) of mother, breastfeeding practices, full immunization, institutional births, improved sanitation and electrification in the household were used as meso scale correlates of malnutrition. RESULTS: The univariate Moran’s I statistics was 0.65, 0.51 and 0.74 for stunting, wasting and underweight respectively suggesting spatial heterogeneity of malnutrition in India. Bivariate Moran’s I statistics of stunting with BMI of mother was 0.52, 0.46 with poverty and − 0.52 with sanitation. The pattern was similar with respect to wasting and underweight suggesting spatial clustering of malnutrition against the meso scale correlates in the geographical hotspots of India. Results of spatial error model suggested that the coefficient of BMI of mother and poverty of household were strong and significant predictors of stunting, wasting and underweight. The coefficient of BMI in spatial error model was largest found for underweight (β = 0.38, 95% CI: 0.29–0.48) followed by stunting (β = 0.23, 95% CI: 0.14–0.33) and wasting (β = 0.11, 95% CI: 0.01–0.22). Women’s educational attainment and breastfeeding practices were also found significant for stunting and underweight. CONCLUSION: Malnutrition across the districts of India is spatially clustered. Reduction of poverty, improving women’s education and health, sanitation and child feeding knowledge can reduce the prevalence of malnutrition across India. Multisectoral and targeted intervention in the geographical hotspots of malnutrition can reduce malnutrition in India. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12889-018-5873-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-60986042018-08-23 Spatial heterogeneity and correlates of child malnutrition in districts of India Khan, Junaid Mohanty, Sanjay K BMC Public Health Research Article BACKGROUND: Despite sustained economic growth and reduction in money metric poverty in last two decades, prevalence of malnutrition remained high in India. During 1992–2016, the prevalence of underweight among children had declined from 53% to 36%, stunting had declined from 52% to 38% while that of wasting had increased from 17% to 21% in India. The national average in the level of malnutrition conceals large variation across districts of India. Using data from the recent round of National Family Health Survey (NFHS), 2015–16 this paper examined the spatial heterogeneity and meso-scale correlates of child malnutrition across 640 districts of India. METHODS: Moran’s I statistics and bivariate LISA maps were used to understand spatial dependence and clustering of child malnutrition. Multiple regression, spatial lag and error models were used to examine the correlates of malnutrition. Poverty, body mass index (BMI) of mother, breastfeeding practices, full immunization, institutional births, improved sanitation and electrification in the household were used as meso scale correlates of malnutrition. RESULTS: The univariate Moran’s I statistics was 0.65, 0.51 and 0.74 for stunting, wasting and underweight respectively suggesting spatial heterogeneity of malnutrition in India. Bivariate Moran’s I statistics of stunting with BMI of mother was 0.52, 0.46 with poverty and − 0.52 with sanitation. The pattern was similar with respect to wasting and underweight suggesting spatial clustering of malnutrition against the meso scale correlates in the geographical hotspots of India. Results of spatial error model suggested that the coefficient of BMI of mother and poverty of household were strong and significant predictors of stunting, wasting and underweight. The coefficient of BMI in spatial error model was largest found for underweight (β = 0.38, 95% CI: 0.29–0.48) followed by stunting (β = 0.23, 95% CI: 0.14–0.33) and wasting (β = 0.11, 95% CI: 0.01–0.22). Women’s educational attainment and breastfeeding practices were also found significant for stunting and underweight. CONCLUSION: Malnutrition across the districts of India is spatially clustered. Reduction of poverty, improving women’s education and health, sanitation and child feeding knowledge can reduce the prevalence of malnutrition across India. Multisectoral and targeted intervention in the geographical hotspots of malnutrition can reduce malnutrition in India. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12889-018-5873-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-08-17 /pmc/articles/PMC6098604/ /pubmed/30119652 http://dx.doi.org/10.1186/s12889-018-5873-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Khan, Junaid
Mohanty, Sanjay K
Spatial heterogeneity and correlates of child malnutrition in districts of India
title Spatial heterogeneity and correlates of child malnutrition in districts of India
title_full Spatial heterogeneity and correlates of child malnutrition in districts of India
title_fullStr Spatial heterogeneity and correlates of child malnutrition in districts of India
title_full_unstemmed Spatial heterogeneity and correlates of child malnutrition in districts of India
title_short Spatial heterogeneity and correlates of child malnutrition in districts of India
title_sort spatial heterogeneity and correlates of child malnutrition in districts of india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6098604/
https://www.ncbi.nlm.nih.gov/pubmed/30119652
http://dx.doi.org/10.1186/s12889-018-5873-z
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