Identifying the determinants and associated factors of mortality under age five in Ethiopia

Abstract

Background Mortality rate under the age of five is the proportion of deaths of children below the age of 5 years out of 1000 live births. It is related with the living standard of a population, and it is taken as one of the health and socioeconomic status deterioration index. Mortality rate under the age of five also indicates a poor quality life standards of a population. It is very significantly high in Sub-Saharan African countries. Ethiopia is one of these Sub-Saharan African countries where mortality rate under the age five is high. This research work aims to identify the determinants and associated factors of under-five mortality in Ethiopia. Methods The data for this paper were gathered from the EDHS 2016, collected by CSA. In this study, count family models such as Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial regression were applied for analyzing the data. Each of these count models were compared with different statistical tests like log-likelihood ratio test, Akaike information criteria, mean absolute difference, Vuong test and observed versus predicted probability plot. Results The study revealed that as mothers’ age at first birth increased by one unit, the average number of under-five mortality rate decreased by 2.69%. In the same way the number of under-five mortality of Afar, Benishangul Gumuz and Dire Dawa were 1.3446, 1.6429 and 1.3320 times more likely to Tigray respectively. The risk of under-five mortality for primary and secondary education level of the mother was 28.31 and 40.96% less likely than to mothers who have no education respectively. Conclusion From the result we found that, there were overabundance zeros and broad heterogeneity in the non-zero outcomes. Zero-inflated negative binomial regression model was found to best fit the data, and from the regression model, age of mothers at first birth, mother’s education level, place of residence and region were statistically significant factors of under-five mortality per mother.

Spatial multilevel analysis of age at death of under-5 children and associated determinants: EDHS 2000–2016

“…Especially during pregnancy, they often engage in strenuous work until childbirth, which can affect child nutrition and increase the risk of injuries, potentially leading to child mortality. These findings align with previous studies 6 43…”

“…Over 80% of the 5.2 million child deaths worldwide occur in sub-Saharan Africa and Central and Southern Asia, with more than half happening in sub-Saharan Africa. Ethiopia, Nigeria and the Democratic Republic of the Congo, all located in sub-Saharan Africa, account for half of the world’s child deaths 5 6…”

“…Likewise, this analysis allows us to examine both between and within-group variation 14. Several studies2 6 13 were conducted on deaths of under-5 children and determinant factors in Ethiopia, but they did not show the spatial distribution of the problem within zonal areas in the country and there are still serious problems concerning under-5 children in Ethiopia. The death of under-5 children varies in the country in space and time by changing magnitude.…”

Impact of Water, Sanitation, and Hygiene Components on Under-5 Children's Mortality in Ethiopia: A Comparative Analysis of Count Regression Models

“…determined Ethiopia's underfive mortality rate's contributing factors. The data was best fitted by a zero-inflated negative binomial model (Yohannis et al, 2021).…”

Risk factors of mortality among children under age five in Awi Zone, northwest Ethiopia

“…Factors such as low level of mother's education, unsafe drinking water and sanitation, low family income, birth interval, short breastfeeding time, lack of a place of birth delivery, and periodic famine continue to put children at risk [7]. Furthermore, numerous studies have been conducted in Ethiopia and around the world reported that under-five mortality is influenced by family size [8,9], preceding birth interval [10][11][12][13], mothers occupation [14,15],type of birth [8,10,11,13,16,17], father education level [8,17], antenatal visits during pregnancy [7,17],duration of pregnancy [18], wealth index [19,20], place of delivery [7,8] and mother age group [9,17,21,22].…”