Background Maternal sepsis and other maternal infections (MSMI) remain major contributors to global maternal morbidity and mortality. However, the integration of epidemiological trends with causal inference evidence remains limited. Methods Using data from the Global Burden of Disease (GBD) 2021 study, we assessed temporal trends in MSMI burden from 1990 to 2021 and projected future patterns using ARIMA and Bayesian age–period–cohort (BAPC) models. In parallel, we conducted a two-sample multivariable Mendelian randomization (MVMR) analysis to evaluate the causal effects of inflammatory biomarkers and related factors on MSMI risk. Results Although age-standardized rates declined globally, absolute case numbers increased in low-SDI regions, largely driven by population growth. Forecasting results differed between ARIMA and BAPC models, reflecting distinct underlying assumptions regarding temporal dynamics. MVMR analysis identified inflammatory biomarkers, including CRP, IL-13, IL-10, RANTES, and NT-proBNP, as key causal factors associated with MSMI. Conclusions This study provides the first integrated framework combining global disease burden analysis with multivariable MR. By linking population-level trends with causal inference, our findings offer dual evidence to support targeted prevention strategies and advance precision public health interventions for MSMI.
Jiang et al. (2026) studied this question.