Variations in Under-five Child Mortality among Regional States of Ethiopia: A Multi-level Modelling Approach

Abstract

Background: Improvements in child survival have been one of the major targets of development programs during the past three decades. The main aim of this study is to investigate under-five child mortality variations among regional states of Ethiopia. In this study, single level and multilevel binary logistic regression models is adopted for the analysis. Methods: This study is conducted based on Demographic and Health Survey (DHS) 2011 data, collected for 10,156 children under-five years of age in Ethiopia. Results: Based on the model adequacy tests the random intercept binary logistic regression model is found to be best fitting to the data. The variance of the random component model related to the intercept term is statistically significant, implying the presence of under-five child mortality variations among regional states of the country and it is accounted by the random intercept term. Original Research Article Bedane et al.; BJAST, 15(2): 1-16, 2016; Article no.BJAST.24448 2 Conclusion: The major significant factors affected under-five child mortality are: mother’s education level, birth index, child size at birth, mother’s age at birth, type of birth and breastfeeding status. It also revealed that there is a contribution of those major factors to under-five child mortality variations among regional states. However, those factors significantly affecting under-five child mortality is explicitly did not show significant effects on variations of under-five child mortality across regional states. The implication of the study is that all regional states should makes remedial measures on public health policy, design strategies to improve facilities and aptitudes of stakeholder living in their region toward those major factors affecting under-five child mortality and contributing to its variations among regional states to reduce under-five child mortality in the country.