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Prevalence of malnutrition and associated factors among under-five children in Ethiopia: evidence from the 2016 Ethiopia Demographic and Health Survey.


ABSTRACT: OBJECTIVE:The aim of this study was to assess the risk factors for malnutrition among children aged 0-59 months in Ethiopia. The analyzed data were obtained from the 2016 EDHS and 9495 under-5 years' children were considered in this analysis. The data was extracted, edited and analyzed by using SPSS Version 23.0. Both bivariate and multivariable binary logistic regression model was used to identify the determinants of children malnutrition. RESULTS:The prevalence of stunting, wasting, and underweight were 38.3%, 10.1%, and 23.3%, respectively. About 19.47% of children were both stunted and underweighted, and only 3.87% of children had all the three conditions. Among the factors that considered in this study, age of a child, residence region, mothers' education level, mothers' BMI, household wealth index, sex of a child, family size, water and toilet facility were significantly associated with malnutrition in Ethiopia. The authors concluded that malnutrition among under-five children was one of the public health problems in Ethiopia. Therefore, the influence of these factors should be considered to develop strategies for reducing malnutrition in Ethiopia.

SUBMITTER: Tekile AK 

PROVIDER: S-EPMC6624874 | biostudies-other | 2019 Jul

REPOSITORIES: biostudies-other

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Prevalence of malnutrition and associated factors among under-five children in Ethiopia: evidence from the 2016 Ethiopia Demographic and Health Survey.

Tekile Abay Kassa AK   Woya Ashenafi Abate AA   Basha Garoma Wakjira GW  

BMC research notes 20190711 1


<h4>Objective</h4>The aim of this study was to assess the risk factors for malnutrition among children aged 0-59 months in Ethiopia. The analyzed data were obtained from the 2016 EDHS and 9495 under-5 years' children were considered in this analysis. The data was extracted, edited and analyzed by using SPSS Version 23.0. Both bivariate and multivariable binary logistic regression model was used to identify the determinants of children malnutrition.<h4>Results</h4>The prevalence of stunting, wast  ...[more]

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