JASIC Volume. 6, Issue 1 (2025)

Contributor(s)

O. Ikpotokin, R. N. Nwaka & L. M. Djekornonde
 

Keywords

Logistic regression Anemia Health conditions Mortality live births
 

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Statistical modeling of health system causes of maternal mortality among pregnant women

Abstract: The problem of maternal death remains a serious universal concern, with nearly 295,000 women dying annually from pregnancy-related complications, the majority of which happen in countries that are not financially balanced. Many African countries accounts for about 60% of these deaths, where the incident of maternal loss proportions exceed 500 of 100,000 living childbirths in many countries. This study examines the influence of health system causes of motherly losses at Mulago Specialized Women and Neonatal Hospital in Kampala, Uganda, using statistical modeling techniques. Adopting logistic regression model, the effect of antenatal care, parity, gravidity, and age conditions on pregnant women death was assessed. Outcome of the model revealed that the significant factors identified in this model, parity (p=0.001) and antenatal care attendance (p=0.018), form a robust predictive model of maternal mortality. The findings confirm that advanced maternal age and high parity, further exacerbate risks, particularly among older women with multiple previous pregnancies. The study's predictive model combines health system factors, providing a valuable tool for early identification of high-risk cases. By incorporating regular ANC services and targeted support for high-risk groups, MSWNH can improve maternal care and reduce mortality.