Cargando…

Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework

BACKGROUND AND AIMS: The Sustainable Development Goal is targeted to end all types of malnutrition including underweight by 2030. However, the reduction rate is not as expected to meet the target. Thus, we aimed to investigate the spatiotemporal distributions and drivers of underweight among childre...

Descripción completa

Detalles Bibliográficos
Autores principales: Atalell, Kendalem Asmare, Alemu, Tewodros Getaneh, Wubneh, Chalachew Adugna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9557178/
https://www.ncbi.nlm.nih.gov/pubmed/36245488
http://dx.doi.org/10.3389/fnut.2022.988417
_version_ 1784807246211842048
author Atalell, Kendalem Asmare
Alemu, Tewodros Getaneh
Wubneh, Chalachew Adugna
author_facet Atalell, Kendalem Asmare
Alemu, Tewodros Getaneh
Wubneh, Chalachew Adugna
author_sort Atalell, Kendalem Asmare
collection PubMed
description BACKGROUND AND AIMS: The Sustainable Development Goal is targeted to end all types of malnutrition including underweight by 2030. However, the reduction rate is not as expected to meet the target. Thus, we aimed to investigate the spatiotemporal distributions and drivers of underweight among children aged below 5 years in Ethiopia. METHODS: Geostatistical analysis using the Bayesian framework was conducted to map the spatial and Spatiotemporal distributions of underweight. Data for the primary outcome was obtained from the Ethiopian Demographic and Health Survey 2000–2019. Covariate data were accessed from different credible online sources at high resolutions. Spatial binomial regression was fitted to identify drivers of underweight using the Bayesian approach. RESULTS: The overall national prevalence of underweight was 44.7, 37.7, 35.4, 25.5, and 23.8% in 2000, 2005, 2011, 2016, and 2019, respectively, with a total reduction rate of 46.8%. Significant spatial clustering of underweight was observed in Northern, Northwestern, Southeastern, Eastern borders, and the border between Oromia and SNNPR regions. Mean annual temperature (mean regression coefficient (β): −0.39; 95% credible interval (95% CrI): −0.63, −0.14), altitude (β:−0.30; 95% CrI: 0.57, −0.05), population density (β:−0.03; 95% CrI: −0.03, −0.02), and distance to water bodies (β:−0.03; 95% CrI: −0.05, −0.004) were negatively associated with being underweight. However, travel time to the nearest cities in minutes (β: 0.09; 95% CrI: 0.03, 0.14) was positively associated with being underweight. CONCLUSION: The national prevalence of underweight is reduced slower than expected in Ethiopia, with significant spatial variations across subnational and local levels. Temperature, altitude, population density, and distance to water bodies were negatively associated with underweight, whereas travel time to the nearest cities was positively associated with underweight in Ethiopia. Improving child nutrition through creating awareness and providing clean water should be strengthened.
format Online
Article
Text
id pubmed-9557178
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-95571782022-10-14 Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework Atalell, Kendalem Asmare Alemu, Tewodros Getaneh Wubneh, Chalachew Adugna Front Nutr Nutrition BACKGROUND AND AIMS: The Sustainable Development Goal is targeted to end all types of malnutrition including underweight by 2030. However, the reduction rate is not as expected to meet the target. Thus, we aimed to investigate the spatiotemporal distributions and drivers of underweight among children aged below 5 years in Ethiopia. METHODS: Geostatistical analysis using the Bayesian framework was conducted to map the spatial and Spatiotemporal distributions of underweight. Data for the primary outcome was obtained from the Ethiopian Demographic and Health Survey 2000–2019. Covariate data were accessed from different credible online sources at high resolutions. Spatial binomial regression was fitted to identify drivers of underweight using the Bayesian approach. RESULTS: The overall national prevalence of underweight was 44.7, 37.7, 35.4, 25.5, and 23.8% in 2000, 2005, 2011, 2016, and 2019, respectively, with a total reduction rate of 46.8%. Significant spatial clustering of underweight was observed in Northern, Northwestern, Southeastern, Eastern borders, and the border between Oromia and SNNPR regions. Mean annual temperature (mean regression coefficient (β): −0.39; 95% credible interval (95% CrI): −0.63, −0.14), altitude (β:−0.30; 95% CrI: 0.57, −0.05), population density (β:−0.03; 95% CrI: −0.03, −0.02), and distance to water bodies (β:−0.03; 95% CrI: −0.05, −0.004) were negatively associated with being underweight. However, travel time to the nearest cities in minutes (β: 0.09; 95% CrI: 0.03, 0.14) was positively associated with being underweight. CONCLUSION: The national prevalence of underweight is reduced slower than expected in Ethiopia, with significant spatial variations across subnational and local levels. Temperature, altitude, population density, and distance to water bodies were negatively associated with underweight, whereas travel time to the nearest cities was positively associated with underweight in Ethiopia. Improving child nutrition through creating awareness and providing clean water should be strengthened. Frontiers Media S.A. 2022-09-29 /pmc/articles/PMC9557178/ /pubmed/36245488 http://dx.doi.org/10.3389/fnut.2022.988417 Text en Copyright © 2022 Atalell, Alemu and Wubneh. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Nutrition
Atalell, Kendalem Asmare
Alemu, Tewodros Getaneh
Wubneh, Chalachew Adugna
Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework
title Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework
title_full Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework
title_fullStr Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework
title_full_unstemmed Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework
title_short Mapping underweight in children using data from the five Ethiopia Demographic and Health Survey data conducted between 2000 and 2019: A geospatial analysis using the Bayesian framework
title_sort mapping underweight in children using data from the five ethiopia demographic and health survey data conducted between 2000 and 2019: a geospatial analysis using the bayesian framework
topic Nutrition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9557178/
https://www.ncbi.nlm.nih.gov/pubmed/36245488
http://dx.doi.org/10.3389/fnut.2022.988417
work_keys_str_mv AT atalellkendalemasmare mappingunderweightinchildrenusingdatafromthefiveethiopiademographicandhealthsurveydataconductedbetween2000and2019ageospatialanalysisusingthebayesianframework
AT alemutewodrosgetaneh mappingunderweightinchildrenusingdatafromthefiveethiopiademographicandhealthsurveydataconductedbetween2000and2019ageospatialanalysisusingthebayesianframework
AT wubnehchalachewadugna mappingunderweightinchildrenusingdatafromthefiveethiopiademographicandhealthsurveydataconductedbetween2000and2019ageospatialanalysisusingthebayesianframework