OBJECTIVES: We sought to quantify how socioeconomic, health care, demographic, and geographic effects explain racial disparities in low birth weight (LBW) and preterm birth (PTB) rates in Brazil. METHODS: We employed a sample of 8949 infants born between 1995 and 2009 in 15 cities and 7 provinces in Brazil. We focused on disparities in LBW (< 2500 g) and PTB (< 37 gestational weeks) prevalence between infants of African ancestry alone or African mixed with other ancestries, and European ancestry alone. We used a decomposition model to quantify the contributions of conceptually relevant factors to these disparities. RESULTS: The model explained 45% to 94% of LBW and 64% to 94% of PTB disparities between the African ancestry groups and European ancestry. Differences in prenatal care use and geographic location were the most important contributors, followed by socioeconomic differences. The model explained the majority of the disparities for mixed African ancestry and part of the disparity for African ancestry alone. CONCLUSIONS: Public policies to improve children's health should target prenatal care and geographic location differences to reduce health disparities between infants of African and European ancestries in Brazil.
OBJECTIVES: We sought to quantify how socioeconomic, health care, demographic, and geographic effects explain racial disparities in low birth weight (LBW) and preterm birth (PTB) rates in Brazil. METHODS: We employed a sample of 8949 infants born between 1995 and 2009 in 15 cities and 7 provinces in Brazil. We focused on disparities in LBW (< 2500 g) and PTB (< 37 gestational weeks) prevalence between infants of African ancestry alone or African mixed with other ancestries, and European ancestry alone. We used a decomposition model to quantify the contributions of conceptually relevant factors to these disparities. RESULTS: The model explained 45% to 94% of LBW and 64% to 94% of PTB disparities between the African ancestry groups and European ancestry. Differences in prenatal care use and geographic location were the most important contributors, followed by socioeconomic differences. The model explained the majority of the disparities for mixed African ancestry and part of the disparity for African ancestry alone. CONCLUSIONS: Public policies to improve children's health should target prenatal care and geographic location differences to reduce health disparities between infants of African and European ancestries in Brazil.
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