Under-five mortality is defined as the likelihood of a child born alive to die between birth and fifth birthday. Mortality of under the age of five has been the most targets of public health policies and may be a common indicator of mortality levels. Thus, this study aimed to assess the under-five child mortality and modeling Bayesian zero-inflated regression model of the determinants of under-five child mortality. A community-based cross-sectional study was conducted using the 2016 Ethiopia Demographic and Health Survey data. The sample was stratified and selected in a two-stage cluster sampling design. The Bayesian analytic approach was applied to model the mixture arrangement inherent in zero-inflated count data by using the negative Binomial–logit hurdle model. About 71.09% of the mothers had not faced any under-five deaths in their lifetime while 28.91% of the women experienced the death of their under-five children and the data were found to have excess zeros. From Bayesian Negative Binomial—logit hurdle model it was found that twin (OR = 1.56; HPD CrI 1.23, 1.94), Primary and Secondary education (OR = 0.68; HPD CrI 0.59, 0.79), mother’s age at the first birth: 16–25 (OR = 0.83; HPD CrI 0.75, 0.92) and ≥ 26 (OR = 0.71; HPD CrI 0.52, 0.95), using contraceptive method (OR = 0.73; HPD CrI 0.64, 0.84) and antenatal visits during pregnancy (OR = 0.83; HPD CrI 0.75, 0.92) were statistically associated with the number of non-zero under-five deaths in Ethiopia. The finding from the Bayesian Negative Binomial–logit hurdle model is getting popular in data analysis than the Negative Binomial–logit hurdle model because the technique is more robust and precise. Furthermore, Using the Bayesian Negative Binomial–logit hurdle model helps in selecting the most significant factor: mother’s education, Mothers age, Birth order, type of birth, mother’s age at the first birth, using a contraceptive method, and antenatal visits during pregnancy were the most important determinants of under-five child mortality.

五岁以下儿童的死亡率定义为活产儿在出生至五岁生日之间死亡的可能性。五岁以下的死亡率是公共卫生政策的最大目标，可能是死亡率的常见指标。因此，本研究旨在评估5岁以下儿童的死亡率，并对5岁以下儿童死亡率的决定因素进行贝叶斯零膨胀回归模型建模。使用2016年埃塞俄比亚人口与健康调查数据进行了基于社区的横断面研究。将样品分层，并按两阶段整群抽样设计进行选择。贝叶斯分析方法通过使用负二项式-logit障碍模型对零膨胀计数数据中固有的混合排列进行建模。大约71。09％的母亲一生中没有遇到过5岁以下儿童的死亡，而28.91％的妇女经历了5岁以下儿童的死亡，数据被发现为零。从贝叶斯负二项式logit障碍模型中，发现双胞胎（OR = 1.56； HPD CrI 1.23，1.94），初等和中等教育（OR = 0.68； HPD CrI 0.59，0.79），母亲的第一胎年龄：16– 25（OR = 0.83; HPD CrI 0.75，0.92）和≥26（OR = 0.71; HPD CrI 0.52，0.95），使用避孕方法（OR = 0.73; HPD CrI 0.64，0.84）和怀孕期间的产前检查（OR = 0.83） ； HPD CrI 0.75，0.92）与埃塞俄比亚非零五岁以下儿童死亡人数相关。贝叶斯负二项-logit障碍模型的发现比负二项-logit障碍模型更受欢迎，因为该技术更加健壮和精确。此外，使用贝叶斯负二项式-logit障碍模型有助于选择最重要的因素：母亲的教育程度，母亲的年龄，出生顺序，出生类型，使用避孕方法的第一胎母亲的年龄以及怀孕期间的产前检查五岁以下儿童死亡率的最重要决定因素。