Evidence map›Paper›PMID 31095585›Full record

ArticlePloS one2019

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

Dóra Chor, Alexandre Pereira, Antonio G Pacheco, Ricardo V Santos, Maria J M Fonseca, Maria I Schmidt, Bruce B Duncan, Sandhi M Barreto, Estela M L Aquino, José G Mill and 5 more

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Dóra ChorDepartment of Epidemiology and Quantitative Methods, National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil.ORCID 0000-0002-3941-5786
Alexandre PereiraLaboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo, São Paulo, SP, Brazil.
Antonio G PachecoScientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, RJ Brazil.
Ricardo V SantosDepartment of Epidemiology and Quantitative Methods, National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil.
Maria J M FonsecaDepartment of Epidemiology and Quantitative Methods, National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil.
Maria I SchmidtPostgraduate Program in Epidemiology, School of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, RS Brazil.
Bruce B DuncanPostgraduate Program in Epidemiology, School of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, RS Brazil.
Sandhi M BarretoFaculty of Medicine & Clinical Hospital, Federal University of Minas Gerais, Belo Horizonte, MG Brazil.
Estela M L AquinoInstitute of Collective Health, Federal University of Bahia, Salvador, BA Brazil.
José G MillDepartment of Physiological Sciences, Federal University of Espirito Santo, Vitória, ES Brazil.
Maria delCB MolinaDepartment of Physiological Sciences, Federal University of Espirito Santo, Vitória, ES Brazil.
Luana GiattiFaculty of Medicine & Clinical Hospital, Federal University of Minas Gerais, Belo Horizonte, MG Brazil.
Maria daCC AlmeidaGonçalo Muniz Institute, Oswaldo Cruz Foundation, Salvador, BA Brazil.
Isabela BensenorCenter for Clinical and Epidemiological Research, University Hospital, University of São Paulo, São Paulo, SP Brazil.
Paulo A LotufoCenter for Clinical and Epidemiological Research, University Hospital, University of São Paulo, São Paulo, SP Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

IncomeBrazilCitiesCohort StudiesGenotypeHumansMalePhylogenyRacial Groups

Identifiers

PMID31095585
PMCPMC6522012

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.