ArticleBMC pregnancy and childbirth2022
Multilevel log linear model to estimate the risk factors associated with infant mortality in Ethiopia: further analysis of 2016 EDHS.
Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- A generalized Poisson regression analysis of determinants of early neonatal mortality in Ethiopia using 2019 Ethiopian mini demographic health survey.Scientific reports · 2024Article
- Article
- Community and individual level determinants of infant mortality in rural Ethiopia using data from 2016 Ethiopian demographic and health survey.Scientific reports · 2022Article
- Breastfeeding performance index and associated factors among children aged 0-6 months in Ethiopia: Analysis of the 2019 Ethiopia Mini Demographic and Health Survey.Frontiers in nutrition · 2022Article
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Abstract
backgroundInfant mortality is defined as the death of a child at any time after birth and before the child's first birthday. Sub-Saharan Africa has the highest infant and child mortality rate in the world. Infant and child mortality rates are higher in Ethiopia. A study was carried out to estimate the risk factors that affect infant mortality in Ethiopia.
methodThe EDHS- 2016 data set was used for this study. A total of 10,547 mothers from 11 regions were included in the study's findings. To estimate the risk factors associated with infant mortality in Ethiopia, several count models (Poisson, Negative Binomial, Zero-Infated Poisson, Zero-Infated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial) were considered.
resultThe average number of infant deaths was 0.526, with a variance of 0.994, indicating over-dispersion. The highest mean number of infant death occurred in Somali (0.69) and the lowest in Addis Ababa (0.089). Among the multilevel log linear models, the ZINB regression model with deviance (17,868.74), AIC (17,938.74), and BIC (1892.97) are chosen as the best model for estimating the risk factors affecting infant mortality in Ethiopia. However, the results of a multilevel ZINB model with a random intercept and slope model revealed that residence, mother's age, household size, mother's age at first birth, breast feeding, child weight, contraceptive use, birth order, wealth index, father education level, and birth interval are associated with infant mortality in Ethiopia.
conclusionInfant deaths remains high and infant deaths per mother differ across regions. An optimal fit was found to the data based on a multilevel ZINB model. We suggest fitting the ZINB model to count data with excess zeros originating from unknown sources such as infant mortality.
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