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Published: 2021-09-01

Page: 924-935


Bule Hora University, Bule Hora, Ethiopia and Arba Minch University, Arba Minch, Ethiopia.


Arba Minch University, Arba Minch, Ethiopia.


Ethiopian Public Health Institute, Addis Ababa, Ethiopia.

*Author to whom correspondence should be addressed.


Introduction: Information on infant mortality is an important indicator of a country’s socioeconomic development; quality of life, help to estimate infant’s risk level and support the development of strategies to reduce this risk such as promoting birth spacing.

Objective: The main objective of this study was to identify and explain the effects of the demographic and socio economic determinant factors of infant mortality in Ethiopia

Methods: 2016 Ethiopian Demographic & Health Survey data was used. The data was analyzed with multilevel logistic regression model and maximum likelihood estimation for parameters.

Results: We noticed the data has nested structure; there exists regional disparity in infant mortality. The result of this study revealed that out of the 31,037 infants considered in the analysis, 45.5/1000 was died, while the remaining was alive. The multilevel logistic regression model result showed that region, place of residence, mother education level, source of drinking water, wealth index of household, mothers exposure to media, birth order, breast feeding, age of mothers at first birth and birth interval were found to be the significant risk factors of infant mortality.

Conclusion: From the multilevel logistic regression model, all the three modelsmay be significant, indicating that there is real multilevel variation among infant death in Ethiopia. From the three multilevel model compared, random intercept model gives better result than the null and random slope model upon analyzing data that have nested structure or hierarchical in nature. The intra correlation coefficient is also suggests that there is clear variation of infant death across the region of Ethiopia. The deviance based chi square value is significant for multilevel random intercept model implies that in comparison to the model with multilevel random intercept and fixed slope model the multilevel random intercept model has a better fit the data.

Keywords: Infant death, region of residence, hierarchical models, risk factors

How to Cite

WAKO, M. G., ASFAW, D., & WALDETENSAI, A. (2021). INFANT MORTALITY AND ITS RISK FACTORS IN ETHIOPIA. Asian Journal of Advances in Research, 4(1), 924–935. Retrieved from


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