Objective: To explore population-level American Indian & Alaska Native-White inequalities in cesarean birth incidence after accounting for differences in cesarean indication, age, and other individual-level risk factors.
Data Sources And Study Setting: We used birth certificate data inclusive of all live births within the United States between January 1 and December 31, 2017.
Study Design: We calculated propensity score weights that simultaneously incorporate age, cesarean indication, and clinical and obstetric risk factors to estimate the American Indian and Alaska Native-White inequality.
Data Collection/extraction Methods: Births to individuals identified as American Indian, Alaska Native, or White, and residing in one of the 50 US states or the District of Columbia were included. Births were excluded if missing maternal race/ethnicity or any other covariate.
Principal Findings: After weighing the American Indian and Alaska Native obstetric population to be comparable to the distribution of cesarean indication, age, and clinical and obstetric risk factors of the White population, the cesarean incidence among American Indian and Alaska Natives increased to 33.4% (95% CI: 32.0-34.8), 3.2 percentage points (95% CI: 1.8-4.7) higher than the observed White incidence. After adjustment, cesarean birth incidence remained higher and increased in magnitude among American Indian and Alaska Natives in Robson groups 1 (low risk, primary), 6 (nulliparous, breech presentation), and 9 (transverse/oblique lie).
Conclusions: The unadjusted lower cesarean birth incidence observed among American Indian and Alaska Native individuals compared to White individuals may be related to their younger mean age at birth. After adjusting for this demographic difference, we demonstrate that American Indian and Alaska Native individuals undergo cesarean birth more frequently than White individuals with similar risk profiles, particularly within the low-risk Robson group 1 and those with non-cephalic presentations (Robson groups 6 and 9). Racism and bias in clinical decision making, structural racism, colonialism, or other unidentified factors may contribute to this inequality.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012218 | PMC |
http://dx.doi.org/10.1111/1475-6773.14122 | DOI Listing |
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