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Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis
BACKGROUND: Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthro...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8207797/ https://www.ncbi.nlm.nih.gov/pubmed/34130742 http://dx.doi.org/10.1186/s13690-021-00615-2 |
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author | Seboka, Binyam Tariku Hailegebreal, Samuel Yehualashet, Delelegn Emwodew Demeke, Abel Desalegn |
author_facet | Seboka, Binyam Tariku Hailegebreal, Samuel Yehualashet, Delelegn Emwodew Demeke, Abel Desalegn |
author_sort | Seboka, Binyam Tariku |
collection | PubMed |
description | BACKGROUND: Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. This research also includes the Spatio-temporal distribution of childhood anthropometric failures across time. METHODS: Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0–59 months, which is a nationally representative sample in Ethiopia. Other than descriptive statistics, the multivariate multilevel logistic regression was used to identify associated factors, and Getis-Ord spatial statistical tools were employed to identify high and low hotspots areas of anthropometric failures. RESULT: The prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5 %, 51 %, and 46.2 % of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education. CONCLUSIONS: In addition to identifying wasted, stunted, and underweight children, CIAF also identified children with multiple conditions, which are often overlooked in nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The established socio-demographic characteristics and districts with a higher risk of anthropometric failure can be used to develop localized intervention and prevention strategies to improve Ethiopian children’s nutritional status and healthcare. |
format | Online Article Text |
id | pubmed-8207797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82077972021-06-16 Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis Seboka, Binyam Tariku Hailegebreal, Samuel Yehualashet, Delelegn Emwodew Demeke, Abel Desalegn Arch Public Health Research BACKGROUND: Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. This research also includes the Spatio-temporal distribution of childhood anthropometric failures across time. METHODS: Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0–59 months, which is a nationally representative sample in Ethiopia. Other than descriptive statistics, the multivariate multilevel logistic regression was used to identify associated factors, and Getis-Ord spatial statistical tools were employed to identify high and low hotspots areas of anthropometric failures. RESULT: The prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5 %, 51 %, and 46.2 % of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education. CONCLUSIONS: In addition to identifying wasted, stunted, and underweight children, CIAF also identified children with multiple conditions, which are often overlooked in nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The established socio-demographic characteristics and districts with a higher risk of anthropometric failure can be used to develop localized intervention and prevention strategies to improve Ethiopian children’s nutritional status and healthcare. BioMed Central 2021-06-16 /pmc/articles/PMC8207797/ /pubmed/34130742 http://dx.doi.org/10.1186/s13690-021-00615-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Seboka, Binyam Tariku Hailegebreal, Samuel Yehualashet, Delelegn Emwodew Demeke, Abel Desalegn Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis |
title | Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis |
title_full | Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis |
title_fullStr | Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis |
title_full_unstemmed | Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis |
title_short | Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis |
title_sort | tracking progress in anthropometric failure among under-five children in ethiopia: a geospatial and multilevel analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8207797/ https://www.ncbi.nlm.nih.gov/pubmed/34130742 http://dx.doi.org/10.1186/s13690-021-00615-2 |
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