Abstract
BACKGROUND: Postpartum hemorrhage (PPH) is the leading preventable cause of maternal morbidity and mortality globally, occurring in 4-6% of Canadian deliveries with evidence suggesting higher rates among Asian individuals. We compared rates of PPH and severe PPH in Ontario, Canada, among Asian and White individuals, focusing on the intersectional relationships between race, language, and immigration status. METHODS: We performed a population-based cohort study in Ontario, Canada (2013-2021). PPH was identified by diagnosis codes used to indicate blood loss of ≥500 mL (vaginal delivery) or ≥1000 mL (cesarean delivery). Severe PPH was defined as PPH with an intervention to control bleeding. Rates were examined by maternal self-reported race, immigration category, duration in Canada, and language at immigration. Modified Poisson regression models were fit to determine the relationships between race, PPH and severe PPH. Models were adjusted for maternal sociodemographic, clinical and obstetric practice factors. RESULTS: The study included 637,311 deliveries (30.9% Asian, 69.1% White). PPH and severe PPH occurred in 5.5% and 6.8%, respectively, of primipara, and 3.8% and 4.3%, of multipara. Asian race was associated with marginally increased PPH rates among multipara after adjusting for confounding (adjusted rate ratio (aRR) 1.06, 95% CI 1.01-1.10). Asian and White individuals experienced similar rates of severe PPH in an adjusted model (aRR 1.00, 95% CI 0.91-1.09). Overall, immigrants experienced lower rates of PPH than non-immigrants (4.4% vs. 5.5%, p-value <0.01); however, differences were observed after layering primary language, with Southeast Asian language speakers having the highest rates (6.3% vs. 5.5%; aRR of 1.40 (95% CI 1.18-1.54) compared with White individuals. DISCUSSION: Variation in PPH and severe PPH risk was observed across racial, immigration, and language groups in Ontario, with modest differences overall but meaningful heterogeneity across subgroups. More granular consideration of immigration characteristics may improve understanding of maternal health inequities.