Ethnoracial inequalities and child mortality in Brazil: a nationwide longitudinal study of 19 million newborn babies

Lancet Glob Health. 2022 Oct;10(10):e1453-e1462. doi: 10.1016/S2214-109X(22)00333-3.

Abstract

Background: Racism is a social determinant of health inequities. In Brazil, racial injustices lead to poor outcomes in maternal and child health for Black and Indigenous populations, including greater risks of pregnancy-related complications; decreased access to antenatal, delivery, and postnatal care; and higher childhood mortality rates. In this study, we aimed to estimate inequalities in childhood mortality rates by maternal race and skin colour in a cohort of more than 19 million newborns in Brazil.

Methods: We did a nationwide population-based, retrospective cohort study using linked data on all births and deaths in Brazil between Jan 1, 2012, and Dec 31, 2018. The data consisted of livebirths followed up to age 5 years, death, or Dec 31, 2018. Data for livebirths were extracted from the National Information System for livebirths, SINASC, and for deaths from the Mortality Information System, SIM. The final sample consisted of complete data for all cases regarding maternal race and skin colour, and no inconsistencies were present between date of birth and death after linkage. We fitted Cox proportional hazard regression models to calculate the crude and adjusted hazard ratios (HRs) and 95% CIs for the association between maternal race and skin colour and all-cause and cause-specific younger than age 5 mortality rates, by age subgroups. We calculated the trend of HRs (and 95% CI) by time of observation (calendar year) to indicate trends in inequalities.

Findings: From the 20 526 714 livebirths registered in SINASC between Jan 1, 2012, and Dec 31, 2018, 238 436 were linked to death records identified from SIM. After linkage, 1 010 871 records were excluded due to missing data on maternal race or skin colour or inconsistent date of death. 19 515 843 livebirths were classified by mother's race, of which 224 213 died. Compared with children of White mothers, mortality risk for children younger than age 5 years was higher among children of Indigenous (HR 1·98 [95% CI 1·92-2·06]), Black (HR 1·39 [1·36-1·41]), and Brown or Mixed race (HR 1·19 [1·18-1·20]) mothers. The highest hazard ratios were observed during the post-neonatal period (Indigenous, HR 2·78 [95% CI 2·64-2·95], Black, HR 1·54 [1·48-1·59]), and Brown or Mixed race, HR 1·25 [1·23-1·27]) and between the ages of 1 year and 4 years (Indigenous, HR 3·82 [95% CI 3·52-4·15]), Black, HR 1·51 [1·42-1·60], and Brown or Mixed race, HR 1·30 [1·26-1·35]). Children of Indigenous (HR 16·39 [95% CI 12·88-20·85]), Black (HR 2·34 [1·78-3·06]), and Brown or Mixed race mothers (HR 2·05 [1·71-2·45]) had a higher risk of death from malnutrition than did children of White mothers. Similar patterns were observed for death from diarrhoea (Indigenous, HR 14·28 [95% CI 12·25-16·65]; Black, HR 1·72 [1·44-2·05]; and Brown or Mixed race mothers, HR 1·78 [1·61-1·98]) and influenza and pneumonia (Indigenous, HR 6·49 [95% CI 5·78-7·27]; Black, HR 1·78 [1·62-1·96]; and Brown or Mixed race mothers, HR 1·60 [1·51-1·69]).

Interpretation: Substantial ethnoracial inequalities were observed in child mortality in Brazil, especially among the Indigenous and Black populations. These findings demonstrate the importance of regular racial inequality assessments and monitoring. We suggest implementing policies to promote ethnoracial equity to reduce the impact of racism on child health.

Funding: MCTI/CNPq/MS/SCTIE/Decit/Bill & Melinda Gates Foundation's Grandes Desafios Brasil, Desenvolvimento Saudável para Todas as Crianças, and Wellcome Trust core support grant awarded to CIDACS-Center for Data and Knowledge Integration for Health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil / epidemiology
  • Child
  • Child Mortality*
  • Child, Preschool
  • Female
  • Humans
  • Infant
  • Infant, Newborn
  • Longitudinal Studies
  • Pregnancy
  • Retrospective Studies
  • Socioeconomic Factors