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Socioeconomic inequalities in child growth failure in Ethiopia: findings from the 2000 and 2016 Demographic and Health Surveys

OBJECTIVE: Socioeconomic inequalities in child growth failure (CGF) remain one of the main challenges in Ethiopia. This study examined socioeconomic inequalities in CGF and determinants that contributed to these inequalities in Ethiopia. METHODS: The Ethiopia Demographic and Health Surveys 2000 and...

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Detalles Bibliográficos
Autores principales: Bekele, Tolesa, Rawstorne, Patrick, Rahman, Bayzidur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672003/
https://www.ncbi.nlm.nih.gov/pubmed/34907054
http://dx.doi.org/10.1136/bmjopen-2021-051304
Descripción
Sumario:OBJECTIVE: Socioeconomic inequalities in child growth failure (CGF) remain one of the main challenges in Ethiopia. This study examined socioeconomic inequalities in CGF and determinants that contributed to these inequalities in Ethiopia. METHODS: The Ethiopia Demographic and Health Surveys 2000 and 2016 data were used in this study. A pooled unweighted sample of the two surveys yielded 21514 mother–child pairs (10873 in 2000 and 10641 in 2016). We assessed socioeconomic inequalities in CGF indicators using the concentration curve and concentration index (CI). We then decomposed the CI to identify percentage contribution of each determinant to inequalities. RESULTS: Socioeconomic inequalities in CGF have increased in Ethiopia between 2000 and 2016. The CI increased from −0.072 and −0.139 for stunting, −0.088 and −0.131 for underweight and −0.015 and −0.050 for wasting between 2000 and 2016, respectively. Factors that mainly contributed to inequalities in stunting included geographical region (49.43%), number of antenatal care visits (31.40%) and child age in months (22.20%) in 2000. While in 2016, inequality in stunting was contributed mainly by wealth quintile (46.16%) and geographical region (−13.70%). The main contributors to inequality in underweight were geographical regions (82.21%) and wealth quintile (27.21%) in 2000, while in 2016, wealth quintile (29.18%), handwashing (18.59%) and access to improved water facilities (−17.55%) were the main contributors. Inequality in wasting was mainly contributed to by maternal body mass index (−66.07%), wealth quintile (−45.68%), geographical region (36.88%) and paternal education (33.55%) in 2000, while in 2016, wealth quintile (52.87%) and urban areas of residence (-17.81%) were the main driving factors. CONCLUSIONS: This study identified substantial socioeconomic inequalities in CGF, and factors that relatively contributed to the disparities. A plausible approach to tackling rising disparities may involve developing interventions on the identified predictors and prioritising actions for the most socioeconomically disadvantaged groups.