FACTORS INFLUENCING MATERNAL MORTALITY IN EAST JAVA USING GENERALIZED POISSON REGRESSION - Lully Hanni Endarini; Hardian Bimanto (Jurnal Biometrika dan Kependudukan, 2026)
Elevated maternal mortality rates underscore the limited effectiveness of maternal health improvement efforts to date. In East Java Province, data from 2020 revealed more maternal deaths than the previous year. This increase was partly due to the COVID-19 pandemic, which limited antenatal care visits and made it harder to monitor high-risk pregnancies. This study set out to find the factors that influence maternal mortality in East Java. Researchers used district and city-level data from the 2020 East Java Provincial Health Report and analyzed it as secondary data. They applied Poisson regression analysis, and because the data showed overdispersion, they also used the Generalized Poisson Regression (GPR) model. The main variable studied was the number of maternal deaths (Y), while the independent variables were The availability ratio of healthcare workers (X₁), The rate of complications during obstetric care (X₂), and The availability of health centers (X₃). The results showed overdispersion in the maternal mortality data. Results from the Poisson regression model indicated that every independent variable significantly influenced maternal deaths. In the GPR model, only The availability ratio of healthcare workers (p=0.001) and The rate of complications during obstetric care (p=0.018) were statistically significant. The study determines that the Generalized Poisson Regression model is better for examining maternal mortality factors in East Java, as it fits the data more accurately, as shown by a lower AIC value.