Bayesian geo-additive model to analyze spatial pattern and determinants of maternal mortality in Ethiopia

Abstract

Abstract Background and Aims Maternal mortality is defined as the death of a woman from any cause associated to or made worse by her pregnancy, either during her pregnancy or within 42 days of the pregnancy's termination, regardless of the length of the pregnancy or its location. The objective of this study is to determine the factors influencing maternal mortality as well as to examine the regional distribution of maternal deaths in Ethiopia. Method This study was conducted in Ethiopia and the data was basically secondary which is obtained from 2016 Ethiopian Demographic and Health survey (EDHS). The Bayesian Geo-additive regression model is used to identify the major risk factors and spatial effects (spatial pattern) on maternal death in Ethiopia. Result Pregnancy-related problems or childbirth were the cause of death for 1.43% of the 10,009 women in the research, whose ages ranged from 15 to 49. In contrast to the semi-parametric and generalized linear models, the Bayesian Geo-additive regression model is based on the DIC and better fits the data. According to the Bayesian Geo-additive regression model's results, maternal death is significantly affected by the place of delivery, the number of prenatal care visits, marital status, wealth index, mother's age and the number of birth orders. The Afar, Somali, Benishangul Gumuz, and Gambela regions have higher rates of maternal death, according to evidence of geographic variation in a model. Conclusion The findings of the study revealed that maternal mortality is influenced by numerous social, demographic, and geographic variables. Geographic variations exist in the patterns of maternal mortality.

Keywords

• Bayesian Geo-additive regression model
• Maternal death
• Spatial pattern