Racism as a Determinant of Health: A Systematic Review and Meta-Analysis

Posted in Articles, Health/Medicine/Genetics, Identity Development/Psychology, Media Archive, Oceania, United States on 2015-09-25 02:37Z by Steven

Racism as a Determinant of Health: A Systematic Review and Meta-Analysis

PLOS ONE
2015-09-23
48 pages
DOI: 10.1371/journal.pone.0138511

Yin Paradies, Professor
Alfred Deakin Institute for Citizenship and Globalization, Faculty of Arts and Education
Deakin University, Melbourne, Victoria, Australia

Jehonathan Ben
Alfred Deakin Institute for Citizenship and Globalization, Faculty of Arts and Education
Deakin University, Melbourne, Victoria, Australia

Amanuel Elias
Alfred Deakin Institute for Citizenship and Globalization, Faculty of Arts and Education
Deakin University, Melbourne, Victoria, Australia

Nida Denson
School of Social Sciences and Psychology
University of Western Sydney, Sydney, New South Wales, Australia

Naomi Priest, Senior Research Fellow in child public health and health inequalities
Australian Centre for Applied Social Research Methods
Australian National University, Canberra, Australian Capital Territory, Australia

Alex Pieterse
Division of Counseling Psychology
University at Albany, State University of New York

Arpana Gupta
Oppenheimer Center for Neurobiology of Stress, David Geffen School of Medicine
University of California, Los Angeles

Margaret Kelaher
Centre for Health Policy Programs and Economics, Melbourne School of Population and Global Health
University of Melbourne, Melbourne, Victoria, Australia

Gilbert Gee
Department of Community Health Sciences
University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California

Despite a growing body of epidemiological evidence in recent years documenting the health impacts of racism, the cumulative evidence base has yet to be synthesized in a comprehensive meta-analysis focused specifically on racism as a determinant of health. This meta-analysis reviewed the literature focusing on the relationship between reported racism and mental and physical health outcomes. Data from 293 studies reported in 333 articles published between 1983 and 2013, and conducted predominately in the U.S., were analysed using random effects models and mean weighted effect sizes. Racism was associated with poorer mental health (negative mental health: r = -.23, 95% CI [-.24,-.21], k = 227; positive mental health: r = -.13, 95% CI [-.16,-.10], k = 113), including depression, anxiety, psychological stress and various other outcomes. Racism was also associated with poorer general health (r = -.13 (95% CI [-.18,-.09], k = 30), and poorer physical health (r = -.09, 95% CI [-.12,-.06], k = 50). Moderation effects were found for some outcomes with regard to study and exposure characteristics. Effect sizes of racism on mental health were stronger in cross-sectional compared with longitudinal data and in non-representative samples compared with representative samples. Age, sex, birthplace and education level did not moderate the effects of racism on health. Ethnicity significantly moderated the effect of racism on negative mental health and physical health: the association between racism and negative mental health was significantly stronger for Asian American and Latino(a) American participants compared with African American participants, and the association between racism and physical health was significantly stronger for Latino(a) American participants compared with African American participants. Protocol PROSPERO registration number: CRD42013005464.

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Cause of Death Affects Racial Classification on Death Certificates

Posted in Articles, Census/Demographics, Health/Medicine/Genetics, Media Archive, Social Science, United States on 2014-02-12 07:02Z by Steven

Cause of Death Affects Racial Classification on Death Certificates

PLoS ONE: A peer-reviewed, open access journal
Volume 6, Number 1 (2011-01-26)
e15812
DOI: 10.1371/journal.pone.0015812

Andrew Noymer, Associate Professor of Sociology; Associate Professor of Population Health and Disease Prevention Public Health
University of California, Irvine

Andrew M. Penner, Associate Professor of Sociology
University of California, Irvine

Aliya Saperstein, Assistant Professor of Sociology
Stanford University

Recent research suggests racial classification is responsive to social stereotypes, but how this affects racial classification in national vital statistics is unknown. This study examines whether cause of death influences racial classification on death certificates. We analyze the racial classifications from a nationally representative sample of death certificates and subsequent interviews with the decedents’ next of kin and find notable discrepancies between the two racial classifications by cause of death. Cirrhosis decedents are more likely to be recorded as American Indian on their death certificates, and homicide victims are more likely to be recorded as Black; these results remain net of controls for followback survey racial classification, indicating that the relationship we reveal is not simply a restatement of the fact that these causes of death are more prevalent among certain groups. Our findings suggest that seemingly non-racial characteristics, such as cause of death, affect how people are racially perceived by others and thus shape U.S. official statistics.

Introduction

The accuracy of official data on birth rates and death rates are often taken for granted. However, recent research has drawn attention to inconsistencies in the recording of race across data sources and the resulting variability in estimates of race-specific death rates in the United States. These analyses have sparked debate among researchers over which measure of race should be considered correct. Rather than focus on identifying errors or inaccuracies in the data, we extend previous research by exploring how the discrepancies in race reporting arise and whether they provide insight into why racial disparities in vital statistics persist. In particular, we use a nationally representative sample of death certificates and matched data from a subsequent survey of the decedent’s next of kin to examine whether cause of death and other non-racial characteristics of decedents are related to their racial classification…

…Discussion

While previous research has demonstrated inconsistencies in racial vital statistics, the processes creating these discrepancies are not well understood. We explored whether seemingly non-racial characteristics of individuals, such as their cause of death, affect how they are perceived racially by others. Our results demonstrate that otherwise similar Americans whose underlying cause of death was chronic liver disease or cirrhosis were more likely to be classified as American Indian on their death certificate than Americans who died of other causes – even if they were not classified as American Indian by their next of kin in a subsequent survey. A similar pattern exists between dying of homicide and the likelihood of being classified as Black. These findings suggest that the racial information recorded in vital statistics may be affected by the same kinds of social processes that shape racial classification more broadly. Research shows that changes in how people are racially classified over their lifetime are related to changes in social status that conform to widely held racial stereotypes. Just as Americans are less likely to be seen as white by a survey interviewer after they have been incarcerated, unemployed or fallen into poverty, we conclude that stereotypes about who is likely to die a particular kind of death may color our official vital statistics…

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Looking the Part: Social Status Cues Shape Race Perception

Posted in Articles, Identity Development/Psychology, Media Archive, Social Science, United States on 2013-05-29 19:02Z by Steven

Looking the Part: Social Status Cues Shape Race Perception

PLoS ONE
Volume 6, Issue 9: e25107
Published: 2011-09-26
DOI: 10.1371/journal.pone.0025107

Jonathan B. Freemam,  Assistant Professor of Psychological & Brain Sciences
Dartmouth College, Hanover, New Hampshire

Andrew M. Penner, Associate Professor of Sociology
University of California, Irvine

Aliya Saperstein, Assistant Professor of Sociology
Stanford University

Matthias Scheutz, Associate Professor of Computer Science
Tufts University, Medford, Massachusetts

Nalini Ambady, Professor of Psychology
Stanford University

It is commonly believed that race is perceived through another’s facial features, such as skin color. In the present research, we demonstrate that cues to social status that often surround a face systematically change the perception of its race. Participants categorized the race of faces that varied along White–Black morph continua and that were presented with high-status or low-status attire. Low-status attire increased the likelihood of categorization as Black, whereas high-status attire increased the likelihood of categorization as White; and this influence grew stronger as race became more ambiguous (Experiment 1). When faces with high-status attire were categorized as Black or faces with low-status attire were categorized as White, participants’ hand movements nevertheless revealed a simultaneous attraction to select the other race-category response (stereotypically tied to the status cue) before arriving at a final categorization. Further, this attraction effect grew as race became more ambiguous (Experiment 2). Computational simulations then demonstrated that these effects may be accounted for by a neurally plausible person categorization system, in which contextual cues come to trigger stereotypes that in turn influence race perception. Together, the findings show how stereotypes interact with physical cues to shape person categorization, and suggest that social and contextual factors guide the perception of race.

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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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Estimating Genetic Ancestry Proportions from Faces

Posted in Anthropology, Articles, Media Archive on 2012-07-11 22:48Z by Steven

Estimating Genetic Ancestry Proportions from Faces

PLoS ONE
Volume 4, Number 2, e4460 (February 2009)
8 pages
DOI: 10.1371/journal.pone.0004460

Yann C. Klimentidis
Department of Biostatistics
University of Alabama, Birmingham

Mark D. Shriver, Associate Professor of Anthropology
Pennsylvania State University

Ethnicity can be a means by which people identify themselves and others. This type of identification mediates many kinds of social interactions and may reflect adaptations to a long history of group living in humans. Recent admixture in the US between groups from different continents, and the historically strong emphasis on phenotypic differences between members of these groups, presents an opportunity to examine the degree of concordance between estimates of group membership based on genetic markers and on visually-based estimates of facial features. We first measured the degree of Native American, European, African and East Asian genetic admixture in a sample of 14 self-identified Hispanic individuals, chosen to cover a broad range of Native American and European genetic admixture proportions. We showed frontal and side-view photographs of the 14 individuals to 241 subjects living in New Mexico, and asked them to estimate the degree of NA admixture for each individual. We assess the overall concordance for each observer based on an aggregated measure of the difference between the observer and the genetic estimates. We find that observers reach a significantly higher degree of concordance than expected by chance, and that the degree of concordance as well as the direction of the discrepancy in estimates differs based on the ethnicity of the observer, but not on the observers’ age or sex. This study highlights the potentially high degree of discordance between physical appearance and genetic measures of ethnicity, as well as how perceptions of ethnic affiliation are context-specific. We compare our findings to those of previous studies and discuss their implications.

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