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Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India

We assessed district-level geospatial trends in precision weighted prevalence and absolute wealth disparity in stunting, underweight, wasting, low birthweight, and anemia among children under five in India. The largest wealth disparities were found for anthropometric failures and substantial variati...

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Detalles Bibliográficos
Autores principales: Liou, Lathan, Kim, Rockli, Subramanian, S.V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909160/
https://www.ncbi.nlm.nih.gov/pubmed/31872040
http://dx.doi.org/10.1016/j.ssmph.2019.100524
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author Liou, Lathan
Kim, Rockli
Subramanian, S.V.
author_facet Liou, Lathan
Kim, Rockli
Subramanian, S.V.
author_sort Liou, Lathan
collection PubMed
description We assessed district-level geospatial trends in precision weighted prevalence and absolute wealth disparity in stunting, underweight, wasting, low birthweight, and anemia among children under five in India. The largest wealth disparities were found for anthropometric failures and substantial variation existed across states. We identified statistically significant (p < 0.001) geospatial patterns in district-wide wealth disparities for all outcomes, which differed from geospatial patterns for the overall prevalence. We characterized each district as either a “Disparity”, “Pitfall”, “Intensity”, or “Prosperity” area based on its overall burden and wealth disparity, as well as discuss the importance of considering both measures for geographically-targeted public health interventions to improve health equity.
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spelling pubmed-69091602019-12-23 Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India Liou, Lathan Kim, Rockli Subramanian, S.V. SSM Popul Health Article We assessed district-level geospatial trends in precision weighted prevalence and absolute wealth disparity in stunting, underweight, wasting, low birthweight, and anemia among children under five in India. The largest wealth disparities were found for anthropometric failures and substantial variation existed across states. We identified statistically significant (p < 0.001) geospatial patterns in district-wide wealth disparities for all outcomes, which differed from geospatial patterns for the overall prevalence. We characterized each district as either a “Disparity”, “Pitfall”, “Intensity”, or “Prosperity” area based on its overall burden and wealth disparity, as well as discuss the importance of considering both measures for geographically-targeted public health interventions to improve health equity. Elsevier 2019-11-28 /pmc/articles/PMC6909160/ /pubmed/31872040 http://dx.doi.org/10.1016/j.ssmph.2019.100524 Text en © 2019 The Authors. Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Liou, Lathan
Kim, Rockli
Subramanian, S.V.
Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India
title Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India
title_full Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India
title_fullStr Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India
title_full_unstemmed Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India
title_short Identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in India
title_sort identifying geospatial patterns in wealth disparity in child malnutrition across 640 districts in india
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909160/
https://www.ncbi.nlm.nih.gov/pubmed/31872040
http://dx.doi.org/10.1016/j.ssmph.2019.100524
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