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

Posted in Articles, Brazil, Caribbean/Latin America, Census/Demographics, Health/Medicine/Genetics, Media Archive, Politics/Public Policy, Social Science on 2019-10-19 03:08Z by Steven

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

PLOS ONE
2019-05-16
DOI: 10.1371/journal.pone.0216653

Dóra Chor
Department of Epidemiology and Quantitative Methods
National School of Public Health
Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil

Alexandre Pereira
Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor)
University of São Paulo, São Paulo, SP, Brazil

Antonio G. Pacheco
Scientific Computing Program
Oswaldo Cruz Foundation, Rio de Janeiro, RJ Brazil

Ricardo V. Santos
Department of Epidemiology and Quantitative Methods
National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
Department of Anthropology, Museu Nacional, Rio de Janeiro, RJ Brazil

Maria J. M. Fonseca
Department of Epidemiology and Quantitative Methods
National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil

Maria I. Schmidt
Postgraduate Program in Epidemiology, School of Medicine
Federal University of Rio Grande do Sul, Porto Alegre, RS Brazil

Bruce B. Duncan
Postgraduate Program in Epidemiology, School of Medicine
Federal University of Rio Grande do Sul, Porto Alegre, RS Brazil

Sandhi M. Barreto, Faculty of Medicine & Clinical Hospital
Federal University of Minas Gerais, Belo Horizonte, MG Brazil

Estela M. L. Aquino
Institute of Collective Health
Federal University of Bahia, Salvador, BA Brazil

José G. Mill
Department of Physiological Sciences
Federal University of Espirito Santo, Vitória, ES Brazil

Maria delCB Molina
Department of Physiological Science
Federal University of Espirito Santo, Vitória, ES Brazil

Luana Giatti, Faculty of Medicine & Clinical Hospital
Federal University of Minas Gerais, Belo Horizonte, MG Brazil

Maria daCC Almeida
Gonçalo Muniz Institute, Oswaldo Cruz Foundation, Salvador, BA Brazil

Isabela Bensenor
Center for Clinical and Epidemiological Research, University Hospital
University of São Paulo, São Paulo, SP Brazil

Paulo A. Lotufo
Center for Clinical and Epidemiological Research
University Hospital, University of São Paulo, São Paulo, SP Brazil

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.

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this evidence invites a re-evaluation of the relevance of racial/ethnic labels

Posted in Excerpts/Quotes, Health/Medicine/Genetics on 2013-03-23 20:15Z by Steven

In conclusion, based on a consecutive series of patients from an urban medical center in New York City we demonstrate that a spectrum of mixed ancestry is emerging in the largest US minority groups. While consistent with previous descriptive studies, when viewed from the clinical perspective this evidence invites a re-evaluation of the relevance of racial/ethnic labels. In combination with evidence of locus heterogeneity within and between populations, this picture of extensive gene flow lends credence to the argument that the transfer of historical population labels which reflect language and other social categories onto patient samples will in many cases be unwarranted.

Tayo BO, Teil M, Tong L, Qin H, Khitrov G, et al., “Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine,” PLoS ONE, Volume 6, Number 5 (2011-05-04): 8-10. http://dx.doi.org/10.1371/journal.pone.0019166.

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Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine

Posted in Articles, Health/Medicine/Genetics, Media Archive, United States on 2013-03-23 20:09Z by Steven

Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine

PLoS ONE: A peer-reviewed, open access journal
Volume 6, Number 5 (2011-05-04)
11 pages
DOI: 10.1371/journal.pone.0019166

Bamidele O. Tayo
Department of Preventive Medicine and Epidemiology
Loyola University Chicago
Stritch School of Medicine, Maywood, Illinois

Marie Teil
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Liping Tong
Department of Preventive Medicine and Epidemiology
Loyola University Chicago
Stritch School of Medicine, Maywood, Illinois

Huaizhen Qin
Department of Biostatistics and Epidemiology
Case Western University, Cleveland, Ohio

Gregory Khitrov
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Weijia Zhang
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Quinbin Song
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Omri Gottesman
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Xiaofeng Zhu
Department of Biostatistics and Epidemiology
Case Western University, Cleveland, Ohio

Alexandre C. Pereira
University of Sao Paulo Medical School, Sao Paulo, Brazil

Richard S. Cooper
Department of Preventive Medicine and Epidemiology
Loyola University Chicago
Stritch School of Medicine, Maywood, Illinois

Erwin P. Bottinger
Charles R. Bronfman Institute for Personalized Medicine
Mount Sinai School of Medicine, New York, New York

Background

The rapid progress currently being made in genomic science has created interest in potential clinical applications; however, formal translational research has been limited thus far. Studies of population genetics have demonstrated substantial variation in allele frequencies and haplotype structure at loci of medical relevance and the genetic background of patient cohorts may often be complex.

Methods and Findings

To describe the heterogeneity in an unselected clinical sample we used the Affymetrix 6.0 gene array chip to genotype self-identified European Americans (N = 326), African Americans (N = 324) and Hispanics (N = 327) from the medical practice of Mount Sinai Medical Center in Manhattan, NY. Additional data from US minority groups and Brazil were used for external comparison. Substantial variation in ancestral origin was observed for both African Americans and Hispanics; data from the latter group overlapped with both Mexican Americans and Brazilians in the external data sets. A pooled analysis of the African Americans and Hispanics from NY demonstrated a broad continuum of ancestral origin making classification by race/ethnicity uninformative. Selected loci harboring variants associated with medical traits and drug response confirmed substantial within- and between-group heterogeneity.

Conclusion

As a consequence of these complementary levels of heterogeneity group labels offered no guidance at the individual level. These findings demonstrate the complexity involved in clinical translation of the results from genome-wide association studies and suggest that in the genomic era conventional racial/ethnic labels are of little value.

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