Bayesian Modeling of Antenatal Care Utilization and Key Maternal Risk Factors in Mogadishu, Somalia

Antenatal care (ANC) is a critical intervention in reducing maternal and neonatal mortality, particularly in low-resource settings. Despite global recommendations by the World Health Organization (WHO) for at least four ANC visits during pregnancy, the utilization of ANC services remains suboptimal in Somalia. This study investigates the key maternal risk factors affecting ANC utilization among 294 mothers in Mogadishu, Somalia, using Bayesian logistic regression. The objective of this study was to identify sociodemographic and maternal factors that significantly influence ANC attendance. The findings reveal that higher maternal age and greater parity were significantly associated with decreased ANC utilization. Conversely, higher educational attainment and employment status were positively correlated with increased ANC visits. The analysis also demonstrated that women with higher levels of education, especially those with secondary or tertiary education, were more likely to attend ANC visits as recommended. Additionally, socioeconomic factors such as household income and decision-making autonomy played an important role in ANC utilization. The Bayesian model displayed excellent convergence and predictive accuracy, highlighting the complex, multifactorial nature of ANC utilization. These results emphasize the importance of improving access to healthcare services, educational interventions, and economic empowerment to enhance maternal health outcomes. The study also emphasizes the potential of Bayesian methods in providing valuable insights for policymakers in fragile healthcare systems, such as that of Somalia.