Overlapping social structures behind Brazil's cesarean section births: A decomposition analysis

Increasing cesarean section (CS) rates worldwide have prompted concern for women's access to quality care and calls for interventions to reduce unnecessary and risky CS. Brazil, where CS births outnumber vaginal births, has one of the highest CS rates in the world. Brazil is also a large and diverse nation, and CS rates differ widely between race/ethnic groups, social classes, and geographic regions. Residential segregation by race/ethnicity and their associations with social class complicate the picture of how each contributes to CS rates and disparities. This article untangles the intersecting social and contextual factors to identify opportunities for interventions to reduce overall CS rates as well as disparities in Brazil. Using Brazil's national birth registry data from 2019 (n = 2,567,039), this article quantifies how much socioeconomic, prenatal care, pregnancy risk, and geographic factors contribute to racial and ethnic disparities in CS. We applied the Karlson-Holm-Breen (KHB) decomposition method to multivariate logistic regression models. Our findings show that women's individual risk factors-educational attainment, social status, age, prenatal care, and pregnancy profile-were significant contributors but did not entirely explain racial and ethnic disparities in CS. Geographic factors-where race/ethnic groups tended to live and the region's risk for CS-also emerged as strong correlates of CS and partially explained unequal rates. The findings untangle the overlapping social structures that predispose some race and ethnic groups to a greater risk of CS and increase overall CS prevalence in Brazil.