Journal of Big Data (Aug 2020)

The best statistical model to estimate predictors of under-five mortality in Ethiopia

  • Setegn Muche Fenta,
  • Haile Mekonnen Fenta,
  • Girum Meseret Ayenew

DOI
https://doi.org/10.1186/s40537-020-00339-0
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 14

Abstract

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Abstract The under-five mortality rate is one of the most important indicators of the socio-economic wellbeing and public health conditions of a country. Under-five death in Ethiopia has reduced, but the rate is still higher than the sustainable development goal target of 20 deaths per 1000 live births. This study aimed to identify the best statistical model to estimate predictors of under-five mortality in Ethiopia. Ethiopian demography and health survey of 2016 data were accessed and used for the analysis. A total of 14,370 women were included. Various count models (Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial) were considered to identify risk factors associated with the death of under-five in Ethiopia. The mean number of under-five death was 0.9 and its variance was 1. 697. The hurdle negative binomial model had the smallest AIC, Deviance, and BIC, suggesting the best goodness of fit. Besides, the predictive value and probabilities for many counts in the hurdle negative binomial model fitted the observed counts best. The result of hurdle negative binomial model showed that region, mother’s age, educational level of the father, education level of the mother, father’s occupation, family size, age of mother at first birth, vaccination of child, contraceptive use, birth order, preceding birth interval, twin children, place of delivery, antenatal visit predict under-five death in Ethiopia. The rate of Under-five death remains high. Concerned governmental organizations should work properly to reduce under-five mortality through encouraging child vaccinations and antenatal care visits. Attention should also be provided to multiple births and the spacing among order of birth. The Hurdle negative binomial model provided a better fit for the data. It is argued the Hurdle negative binomial model for count data with excess zeros of unknown sources such as the number of under-five death should be fitted.

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