Background: Neonatal mortality is the probability of dying during the first 28 days of life. Of approximately 5 million children who die in the first year of life in the world, about 3 million are within their first 28 days of birth. In Ethiopia, the neonatal mortality rate is high about 37 per 1000 live births, and the factors are not well documented. Then, this study aimed to determine the key factors that have a significant influence on neonatal mortality.
Methods: A total of 5753 neonatal mortality-related data were obtained from Ethiopia Mini Demographic and Health Survey (2019) data. A frequency distribution to summarize the overall data and Binary Logistic Regression to identify the subset of significant risk factors for neonatal mortality were applied to analyze the data.
Results: An estimated 36 per 1000 live children had died before the first 28 days, with the highest in the Benishangul Gumuz region (15.9%) and the lowest in Addis Ababa (2.4%). From the Binary logistic regression analysis, the odds ratio and 95% CI of age 25-34 (OR = 0.263, 95% CI: 0.106-0.653), Afar (OR = 0.384, 95% CI: 0.167-0.884), SNNPR (OR = 0.265, 95% CI: 0.098-0.720), Addis Ababa (OR = 5.741, 95% CI: 1.115-29.566), Urban (OR = 0.253, 95% CI: 0.090, 0.709), toilet facility (OR = 0.603, 95% CI: 0.404-0.900), single birth (OR = 0.261, 95% CI: 0.138-0.495), poorest (OR = 10.573, 95% CI: 2.166-51.615), poorer (OR = 19.573, 95% CI: 4.171-91.848), never breastfed (OR = 35.939, 95% CI: 25.193-51.268), public health delivery (OR = 0.302, 95% CI: 0.106-0.859), private health facility (OR = 0.269, 95% CI: 0.095-0.760).
Conclusion: All regional states of Ethiopia, specially Benishangul Gumuz, and the Somali region must take remedial actions on public health policy, design strategies to improve facilities, and improve the capacities of stakeholders living in their region toward those major factors affecting neonatal mortality in the country.
Copyright: © 2022 Sahile et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.