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

Area of Science:

• Public Health
• Sociology
• Reproductive Health

Background:

• Global rise in cesarean section (CS) rates raises concerns about maternal care quality and unnecessary procedures.
• Brazil exhibits one of the world's highest CS rates, with significant disparities across racial/ethnic groups, social classes, and regions.
• Residential segregation by race/ethnicity and its link to social class complicate understanding of CS rate determinants and disparities.

Purpose of the Study:

• To disentangle intersecting social and contextual factors influencing CS rates and disparities in Brazil.
• To quantify the contributions of socioeconomic, prenatal care, pregnancy risk, and geographic factors to racial/ethnic disparities in CS.
• To identify intervention opportunities for reducing overall CS rates and associated disparities.

Main Methods:

• Analysis of Brazil's national birth registry data from 2019 (n=2,567,039).
• Application of the Karlson-Holm-Breen (KHB) decomposition method.
• Utilized multivariate logistic regression models to assess contributing factors.

Main Results:

• Individual risk factors (education, social status, age, prenatal care, pregnancy profile) significantly contributed to CS rates but did not fully explain racial/ethnic disparities.
• Geographic factors, including residential location and regional CS risk, strongly correlated with CS rates and partially explained disparities.
• Overlapping social structures were identified as key determinants predisposing certain racial/ethnic groups to higher CS risk.

Conclusions:

• While individual factors play a role, geographic segregation and regional characteristics are crucial in understanding and addressing racial/ethnic disparities in CS rates in Brazil.
• Interventions must consider the complex interplay of social, economic, and geographic determinants to effectively reduce both overall CS prevalence and inequities.