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Context-dependence of race self-classification: Results from a highly mixed and unequal middle-income country.

Chor, Dóra; Pereira, Alexandre; Pacheco, Antonio G; Santos, Ricardo V; Fonseca, Maria J M; Schmidt, Maria I; Duncan, Bruce B; Barreto, Sandhi M; Aquino, Estela M L; Mill, José G; Molina, Maria delCB; Giatti, Luana; Almeida, Maria daCC; Bensenor, Isabela; Lotufo, Paulo A.
PLoS One; 14(5): e0216653, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-31095585
Ethnic-racial classification criteria are widely recognized to vary according to historical, cultural and political contexts. In Brazil, the strong influence of individual socio-economic factors on race/colour self-classification is well known. With the expansion of genomic technologies, the use of genomic ancestry has been suggested as a substitute for classification procedures such as self-declaring race, as if they represented the same concept. We investigated the association between genomic ancestry, the racial composition of census tracts and individual socioeconomic factors and self-declared race/colour in a cohort of 15,105 Brazilians. Results show that the probability of self-declaring as black or brown increases according to the proportion of African ancestry and varies widely among cities. In Porto Alegre, where most of the population is white, with every 10% increase in the proportion of African ancestry, the odds of self-declaring as black increased 14 times (95%CI 6.08-32.81). In Salvador, where most of the population is black or brown, that increase was of 3.98 times (95%CI 2.96-5.35). The racial composition of the area of residence was also associated with the probability of self-declaring as black or brown. Every 10% increase in the proportion of black and brown inhabitants in the residential census tract increased the odds of self-declaring as black by 1.33 times (95%CI 1.24-1.42). Ancestry alone does not explain self-declared race/colour. An emphasis on multiple situational contexts (both individual and collective) provides a more comprehensive framework for the study of the predictors of self-declared race/colour, a highly relevant construct in many different scenarios, such as public policy, sociology and medicine.
Selo DaSilva