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.
| Published in | Science Journal of Public Health (Volume 13, Issue 3) |
| DOI | 10.11648/j.sjph.20251303.13 |
| Page(s) | 123-133 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Bayesian Modelling, Antenatal Care, Bayesian Logistic Regression, Maternal Risk Factors
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APA Style
Ali, A. D., Nalule, R. M. (2025). Bayesian Modeling of Antenatal Care Utilization and Key Maternal Risk Factors in Mogadishu, Somalia. Science Journal of Public Health, 13(3), 123-133. https://doi.org/10.11648/j.sjph.20251303.13
ACS Style
Ali, A. D.; Nalule, R. M. Bayesian Modeling of Antenatal Care Utilization and Key Maternal Risk Factors in Mogadishu, Somalia. Sci. J. Public Health 2025, 13(3), 123-133. doi: 10.11648/j.sjph.20251303.13
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Download@article{10.11648/j.sjph.20251303.13,
author = {Abdinasir Dahir Ali and Rebecca Muhumuza Nalule},
title = {Bayesian Modeling of Antenatal Care Utilization and Key Maternal Risk Factors in Mogadishu, Somalia},
journal = {Science Journal of Public Health},
volume = {13},
number = {3},
pages = {123-133},
doi = {10.11648/j.sjph.20251303.13},
url = {https://doi.org/10.11648/j.sjph.20251303.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.20251303.13},
abstract = {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.},
year = {2025}
}
TY - JOUR T1 - Bayesian Modeling of Antenatal Care Utilization and Key Maternal Risk Factors in Mogadishu, Somalia AU - Abdinasir Dahir Ali AU - Rebecca Muhumuza Nalule Y1 - 2025/06/21 PY - 2025 N1 - https://doi.org/10.11648/j.sjph.20251303.13 DO - 10.11648/j.sjph.20251303.13 T2 - Science Journal of Public Health JF - Science Journal of Public Health JO - Science Journal of Public Health SP - 123 EP - 133 PB - Science Publishing Group SN - 2328-7950 UR - https://doi.org/10.11648/j.sjph.20251303.13 AB - 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. VL - 13 IS - 3 ER -
Department of Mathematics and Statistics, Kampala International University, Kampala, Uganda
Department of Mathematics and Statistics, Kampala International University, Kampala, Uganda; Department of Mathematics, Busitema University, Tororo, Uganda
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