Racial vulnerability and individual barriers for Brazilian women seeking first care following abortion

Racism, xenophobia, and discrimination: mapping pathways to health outcomes

Despite being globally pervasive, racism, xenophobia, and discrimination are not universally recognised determinants of health. We challenge widespread beliefs related to the inevitability of increased mortality and morbidity associated with particular ethnicities and minoritised groups. In refuting that racial categories have a genetic basis and acknowledging that socioeconomic factors offer incomplete explanations in understanding these health disparities, we examine the pathways by which discrimination based on caste, ethnicity, Indigeneity, migratory status, race, religion, and skin colour affect health. Discrimination based on these categories, although having many unique historical and cultural contexts, operates in the same way, with overlapping pathways and health effects. We synthesise how such discrimination affects health systems, spatial determination, and communities, and how these processes manifest at the individual level, across the life course, and intergenerationally. We explore how individuals respond to and internalise these complex mechanisms psychologically, behaviourally, and physiologically. The evidence shows that racism, xenophobia, and discrimination affect a range of health outcomes across all ages around the world, and remain embedded within the universal challenges we face, from COVID-19 to the climate emergency.

Barriers in Accessing Care for Consequence of Unsafe Abortion by Black Women: Evidence of Institutional Racism in Brazil

Women face difficulties in accessing post-abortion care, as hierarchical care operates under discrimination mechanisms that condemn women in abortion. In addition, it is the Black and Brown women who are more subject to unsafe abortions and need hospitalization to complete the termination of pregnancy or treat associated complications. This study aimed at identifying factors associated with the institutional barriers in access to health services for women who underwent abortion by race/color. The survey encompassed 2640 users admitted to public hospitals in Salvador, Recife, and São Luís. Differences among covariables according to race/color (Black, Brown, and White women) were analyzed and tested for statistical significance using Pearson's χ² test. The regression analysis initially included variables that may express the technical criteria of priority in care (time of pregnancy when abortion occurred and conditions of arrival), then the sociodemographic characteristics, and, lastly, the type of abortion declared. Black women faced more institutional difficulties (27.7% vs 19.5% in White women and 18.7% in Brown women), such as waiting to be attended and getting a bed. The association between being Black women and institutional barriers remained, even after adjustments in the regression model. Institutional racism limits access to health services and timely care for Black women, acting as a performative mechanism, legitimizing and generating exclusionary behaviors. The results demonstrate that the intersection between racial discrimination and abortion stigma redouble institutional barriers that are denominated intersectional discrimination.

Effect of income on the cumulative incidence of COVID-19: an ecological study

OBJECTIVE

to analyze the relationship between per capita income and the cumulative incidence of COVID-19 in the neighborhoods of the city of Rio de Janeiro, RJ, Brazil.

METHOD

an ecological study using neighborhoods as units of analysis. The cumulative incidence rate per 100,000 inhabitants and the median of potential confounding variables (sex, race, and age) were calculated. Multiple analysis included quantile regression, estimating the regression coefficients of the variable income for every five percentiles from the 10th to 90th percentiles to verify the relationship between income and incidence.

RESULTS

the city's rate was 36.58 new cases per 100,000 inhabitants. In general, the highest rates were observed in the wealthiest regions. Multiple analysis was consistent with this observation since the per capita income affected all percentiles analyzed, with a median regression coefficient of 0.02 (p-value <0.001; R2 32.93). That is, there is an increase of R$ 0.02 in the neighborhood's per capita income for every unit of incidence.

CONCLUSION

cumulative incident rates of COVID-19 are influenced by one's neighborhood of residency, suggesting that access to testing is uneven.