Cargando…
Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis
In developing countries including Ethiopia stunting remained a major public health burden. It is associated with adverse health consequences, thus, investigating predictors of childhood stunting is crucial to design appropriate strategies to intervene the problem stunting. The study uses data from t...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881183/ https://www.ncbi.nlm.nih.gov/pubmed/33580097 http://dx.doi.org/10.1038/s41598-021-82755-7 |
_version_ | 1783650824126201856 |
---|---|
author | Muche, Amare Gezie, Lemma Derseh Baraki, Adhanom Gebre-egzabher Amsalu, Erkihun Tadesse |
author_facet | Muche, Amare Gezie, Lemma Derseh Baraki, Adhanom Gebre-egzabher Amsalu, Erkihun Tadesse |
author_sort | Muche, Amare |
collection | PubMed |
description | In developing countries including Ethiopia stunting remained a major public health burden. It is associated with adverse health consequences, thus, investigating predictors of childhood stunting is crucial to design appropriate strategies to intervene the problem stunting. The study uses data from the Ethiopian Demographic and Health Survey (EDHS) conducted from January 18 to June 27, 2016 in Ethiopia. A total of 8117 children aged 6–59 months were included in the study with a stratified two stage cluster sampling technique. A Bayesian multilevel logistic regression was fitted using Win BUGS version 1.4.3 software to identify predictors of stunting among children age 6–59 months. Adjusted odds ratio (AOR) with 95% credible intervals was used to ascertain the strength and direction of association. In this study, increasing child’s age (AOR = 1.022; 95% CrI 1.018–1.026), being a male child (AOR = 1.16; 95%CrI 1.05–1.29), a twin (AOR = 2.55; 95% CrI 1.78–3.56), having fever (AOR = 1.23; 95%CrI 1.02–1.46), having no formal education (AOR = 1.99; 95%CrI 1.28–2.96) and primary education (AOR = 83; 95%CrI 1.19–2.73), birth interval less than 24 months (AOR = 1.40; 95% CrI 1.20–1.61), increasing maternal BMI (AOR = 0.95; 95% CrI 0.93–0.97), and poorest household wealth status (AOR = 1.78; 95% CrI 1.35–2.30) were predictors of childhood stunting at individual level. Similarly, region and type of toilet facility were predictors of childhood stunting at community level. The current study revealed that both individual and community level factors were predictors of childhood stunting in Ethiopia. Thus, more emphasize should be given by the concerned bodies to intervene the problem stunting by improving maternal education, promotion of girl education, improving the economic status of households, promotion of context-specific child feeding practices, improving maternal nutrition education and counseling, and improving sanitation and hygiene practices. |
format | Online Article Text |
id | pubmed-7881183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78811832021-02-16 Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis Muche, Amare Gezie, Lemma Derseh Baraki, Adhanom Gebre-egzabher Amsalu, Erkihun Tadesse Sci Rep Article In developing countries including Ethiopia stunting remained a major public health burden. It is associated with adverse health consequences, thus, investigating predictors of childhood stunting is crucial to design appropriate strategies to intervene the problem stunting. The study uses data from the Ethiopian Demographic and Health Survey (EDHS) conducted from January 18 to June 27, 2016 in Ethiopia. A total of 8117 children aged 6–59 months were included in the study with a stratified two stage cluster sampling technique. A Bayesian multilevel logistic regression was fitted using Win BUGS version 1.4.3 software to identify predictors of stunting among children age 6–59 months. Adjusted odds ratio (AOR) with 95% credible intervals was used to ascertain the strength and direction of association. In this study, increasing child’s age (AOR = 1.022; 95% CrI 1.018–1.026), being a male child (AOR = 1.16; 95%CrI 1.05–1.29), a twin (AOR = 2.55; 95% CrI 1.78–3.56), having fever (AOR = 1.23; 95%CrI 1.02–1.46), having no formal education (AOR = 1.99; 95%CrI 1.28–2.96) and primary education (AOR = 83; 95%CrI 1.19–2.73), birth interval less than 24 months (AOR = 1.40; 95% CrI 1.20–1.61), increasing maternal BMI (AOR = 0.95; 95% CrI 0.93–0.97), and poorest household wealth status (AOR = 1.78; 95% CrI 1.35–2.30) were predictors of childhood stunting at individual level. Similarly, region and type of toilet facility were predictors of childhood stunting at community level. The current study revealed that both individual and community level factors were predictors of childhood stunting in Ethiopia. Thus, more emphasize should be given by the concerned bodies to intervene the problem stunting by improving maternal education, promotion of girl education, improving the economic status of households, promotion of context-specific child feeding practices, improving maternal nutrition education and counseling, and improving sanitation and hygiene practices. Nature Publishing Group UK 2021-02-12 /pmc/articles/PMC7881183/ /pubmed/33580097 http://dx.doi.org/10.1038/s41598-021-82755-7 Text en © The Author(s) 2021 Open Access This 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/. |
spellingShingle | Article Muche, Amare Gezie, Lemma Derseh Baraki, Adhanom Gebre-egzabher Amsalu, Erkihun Tadesse Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis |
title | Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis |
title_full | Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis |
title_fullStr | Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis |
title_full_unstemmed | Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis |
title_short | Predictors of stunting among children age 6–59 months in Ethiopia using Bayesian multi-level analysis |
title_sort | predictors of stunting among children age 6–59 months in ethiopia using bayesian multi-level analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881183/ https://www.ncbi.nlm.nih.gov/pubmed/33580097 http://dx.doi.org/10.1038/s41598-021-82755-7 |
work_keys_str_mv | AT mucheamare predictorsofstuntingamongchildrenage659monthsinethiopiausingbayesianmultilevelanalysis AT gezielemmaderseh predictorsofstuntingamongchildrenage659monthsinethiopiausingbayesianmultilevelanalysis AT barakiadhanomgebreegzabher predictorsofstuntingamongchildrenage659monthsinethiopiausingbayesianmultilevelanalysis AT amsaluerkihuntadesse predictorsofstuntingamongchildrenage659monthsinethiopiausingbayesianmultilevelanalysis |