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Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources
Background: Childhood malnutrition contributes to nearly half (45%) of all deaths among children under 5 globally. The United Nations’ Sustainable Development Goals (SDGs) aims to end all forms of malnutrition by 2030; however, measuring progress towards these goals is challenging, particularly in c...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Kerman University of Medical Sciences
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9808187/ https://www.ncbi.nlm.nih.gov/pubmed/33589568 http://dx.doi.org/10.34172/ijhpm.2020.253 |
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author | Kuwornu, John Paul Amoyaw, Jonathan Manyanga, Taru Cooper, Elizabeth J. Donkoh, Elvis Nkrumah, Amos |
author_facet | Kuwornu, John Paul Amoyaw, Jonathan Manyanga, Taru Cooper, Elizabeth J. Donkoh, Elvis Nkrumah, Amos |
author_sort | Kuwornu, John Paul |
collection | PubMed |
description | Background: Childhood malnutrition contributes to nearly half (45%) of all deaths among children under 5 globally. The United Nations’ Sustainable Development Goals (SDGs) aims to end all forms of malnutrition by 2030; however, measuring progress towards these goals is challenging, particularly in countries with emerging economies where nationally-representative data are limited. The primary objective of this study was to estimate the overall burden of childhood malnutrition in Ghana at national and regional levels using 3 data sources. Methods: Using data from the long-standing Ghana Demographic and Health Surveys (GDHS), Ghana Multiple Indicator Cluster Survey (GMICS), and the emerging Ghana Socioeconomic Panel Survey (GSPS), we compared the prevalence of malnutrition using the extended composite index of anthropometric failure (eCIAF) for the period 2008- 2011. This study included data for children aged 6-59 months and calculated all anthropometric z-scores based on the World Health Organization (WHO) Growth Standards. We tested for differences in malnutrition subtypes using two-group configural frequency analysis (CFA). Results: Of the 10 281 children (6532 from GMICS, 2141 from GDHS and 1608 from GSPS) included in the study, the only demographic difference observed was the children included in the GSPS were slightly older than those included in the GDHS and GMICS (median age of 36 vs 30 vs 33 months, P<.001). Based on the eCIAF, the overall prevalence of malnutrition at the national level was higher among children in the GSPS (57.3%, 95% CI: 53.9%–60.6%), followed by the GDHS (39.7%, 95% CI: 37.0%–42.5%), and then those in the GMICS (31.2%, 95% CI: 29.3%–33.1%). The two-group CFA showed that the 3 data sources also estimated different prevalence rates for most of the malnutrition subtypes included in the eCIAF. Conclusion: Depending on the data source adopted, our estimates of eCIAF showed that between one-third and half of all Ghanaian children aged 6-59 months had at least one form of malnutrition over the period 2008-2011. These eCIAF estimates should complement the commonly reported measures such as stunting and wasting when interpreting the severity of malnutrition in the country to inform policy decisions. |
format | Online Article Text |
id | pubmed-9808187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Kerman University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-98081872023-01-10 Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources Kuwornu, John Paul Amoyaw, Jonathan Manyanga, Taru Cooper, Elizabeth J. Donkoh, Elvis Nkrumah, Amos Int J Health Policy Manag Original Article Background: Childhood malnutrition contributes to nearly half (45%) of all deaths among children under 5 globally. The United Nations’ Sustainable Development Goals (SDGs) aims to end all forms of malnutrition by 2030; however, measuring progress towards these goals is challenging, particularly in countries with emerging economies where nationally-representative data are limited. The primary objective of this study was to estimate the overall burden of childhood malnutrition in Ghana at national and regional levels using 3 data sources. Methods: Using data from the long-standing Ghana Demographic and Health Surveys (GDHS), Ghana Multiple Indicator Cluster Survey (GMICS), and the emerging Ghana Socioeconomic Panel Survey (GSPS), we compared the prevalence of malnutrition using the extended composite index of anthropometric failure (eCIAF) for the period 2008- 2011. This study included data for children aged 6-59 months and calculated all anthropometric z-scores based on the World Health Organization (WHO) Growth Standards. We tested for differences in malnutrition subtypes using two-group configural frequency analysis (CFA). Results: Of the 10 281 children (6532 from GMICS, 2141 from GDHS and 1608 from GSPS) included in the study, the only demographic difference observed was the children included in the GSPS were slightly older than those included in the GDHS and GMICS (median age of 36 vs 30 vs 33 months, P<.001). Based on the eCIAF, the overall prevalence of malnutrition at the national level was higher among children in the GSPS (57.3%, 95% CI: 53.9%–60.6%), followed by the GDHS (39.7%, 95% CI: 37.0%–42.5%), and then those in the GMICS (31.2%, 95% CI: 29.3%–33.1%). The two-group CFA showed that the 3 data sources also estimated different prevalence rates for most of the malnutrition subtypes included in the eCIAF. Conclusion: Depending on the data source adopted, our estimates of eCIAF showed that between one-third and half of all Ghanaian children aged 6-59 months had at least one form of malnutrition over the period 2008-2011. These eCIAF estimates should complement the commonly reported measures such as stunting and wasting when interpreting the severity of malnutrition in the country to inform policy decisions. Kerman University of Medical Sciences 2020-12-22 /pmc/articles/PMC9808187/ /pubmed/33589568 http://dx.doi.org/10.34172/ijhpm.2020.253 Text en © 2022 The Author(s); Published by Kerman University of Medical Sciences https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Kuwornu, John Paul Amoyaw, Jonathan Manyanga, Taru Cooper, Elizabeth J. Donkoh, Elvis Nkrumah, Amos Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources |
title | Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources |
title_full | Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources |
title_fullStr | Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources |
title_full_unstemmed | Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources |
title_short | Measuring the Overall Burden of Early Childhood Malnutrition in Ghana: A Comparison of Estimates From Multiple Data Sources |
title_sort | measuring the overall burden of early childhood malnutrition in ghana: a comparison of estimates from multiple data sources |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9808187/ https://www.ncbi.nlm.nih.gov/pubmed/33589568 http://dx.doi.org/10.34172/ijhpm.2020.253 |
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