Multilevel Analysis of Determinants of Stunting Prevalence Among Children Under Age Five in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey Data

Background: Stunting is a well established child health indicator of chronic malnutrition related to environmental and socio economic circumstances. In Ethiopia, childhood stunting is the most widely prevalent among children under age five years. Thus, this study aimed to assess and model the determinants of stunting prevalence among children under age five in Ethiopia.

Methods: Samples of 8487 children under age five and 640 community clusters were selected from the 2016 Ethiopian Demographic and Health Survey in this study. The survey sample was designed to provide national, urban/rural, and regional representative estimates for key health and demographic indicators. The sample was selected using a two-stage stratified sampling process. The statistical model applied to determine the individual and community level factors associated with childhood stunting in Ethiopia was multilevel logistic regression model.

Results: This study revealed that the prevalence of stunting among children under age five years in Ethiopia was around 39.39%. The multilevel binary logistic regression analysis was performed to investigate the variation of predictor variables of the prevalence of stunting among children under age five. Accordingly, it has been identified that ages of the child above 12 months, male gender, children from poor households and no mother education have a significant effect on prevalence of stunting in Ethiopia. It is found that variances related to the random term were statistically significant implying that there is variation in prevalence of stunting across the regional states of Ethiopia.

Conclusion: The current study confirmed that prevalence of stunting among children under aged five years in Ethiopia was severe public health problem, where 39.39% of them are stunting. Therefore, governmental and nongovernmental organizations or stakeholders should pay attention to all significant factors mentioned in the analysis of this study.