Race and Ethnicity in Medical Research: Requirements Meet Reality

2006 ◽  
Vol 34 (3) ◽  
pp. 520-525 ◽  
Author(s):  
Margaret A. Winker

Race and ethnicity are commonly reported variables in biomedical research, but how they were initially determined is often not described and the rationale for analyzing them is often not provided. JAMA improved the reporting of these factors by implementing a policy and procedure for doing so. However, still lacking are careful consideration of what is actually being measured when race/ethnicity is described, consistent terminology, hypothesis-driven justification for analyzing race/ethnicity, and a consistent and generalizable measurement of socioeconomic status. Furthermore, some studies continue to use race/ethnicity as a proxy for genetics. Research into appropriate measures of race/ethnicity and socioeconomic factors, as well as education of researchers regarding issues of race/ethnicity, is necessary to clarify the meaning of race/ethnicity in the biomedical literature.

2012 ◽  
Vol 130 (2) ◽  
pp. 115-118 ◽  
Author(s):  
Teresa Veronica Catonho Ribeiro ◽  
Luzitano Brandão Ferreira

CONTEXT AND OBJECTIVE: Over recent years, the terms race and ethnicity have been used to ascertain inequities in public health. However, this use depends on the quality of the data available. This study aimed to investigate the description of color/race in Brazilian scientific journals within the field of biomedicine. DESIGN AND SETTING: Descriptive study with systematic search for scientific articles in the SciELO Brazil database. METHODS: A wide-ranging systematic search for original articles involving humans, published in 32 Brazilian biomedical scientific journals in the SciELO Brazil database between January and December 2008, was performed. Articles in which the race/ethnicity of the participants was identified were analyzed. RESULTS: In total, 1,180 articles were analyzed. The terms for describing race or ethnicity were often ambiguous and vague. Descriptions of race or ethnicity occurred in 159 articles (13.4%), but only in 42 (26.4%) was there a description of how individuals were identified. In these, race and ethnicity were used almost interchangeably and definition was according to skin color (71.4%), ancestry (19.0%) and self-definition (9.6%). Twenty-two races or ethnicities were cited, and the most common were white (37.3%), black (19.7%), mixed (12.9%), nonwhite (8.1%) and yellow (8.1%). CONCLUSION: The absence of descriptions of parameters for defining race, as well as the use of vague and ambiguous terms, may hamper and even prevent comparisons between human groups and the use of these data to ascertain inequities in healthcare.


2013 ◽  
Author(s):  
Christopher S. Bartlett ◽  
Tulay Koru-Sengul ◽  
Feng Miao ◽  
Stacey L. Tannenbaum ◽  
David J. Lee ◽  
...  

Author(s):  
Shardé M. Davis

Investigating the role of physiology in communication research is a burgeoning area of study that has gained considerable attention by relational scholars in the past decade. Unfortunately, very few published studies on this topic have evoked important questions about the role of race and ethnicity. Exploring issues of ethnicity and race provides a more holistic and inclusive view of interpersonal communication across diverse groups and communities. This chapter addresses the gap in literature by considering the ways in which race and ethnicity matter in work on physiology and interpersonal interactions. More specifically, this chapter will first discuss the conceptual underpinnings of race, ethnicity, and other relevant concepts and then review extant research within and beyond the field of communication on race, ethnicity, interpersonal interactions, and physiology. These discussions set the foundation for this chapter to propose new lines of research that pointedly connect these four concepts and advance key principles that scholars should consider in future work.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 505-506
Author(s):  
Dominika Seblova ◽  
Kelly Peters ◽  
Susan Lapham ◽  
Laura Zahodne ◽  
Tara Gruenewald ◽  
...  

Abstract Having more years of education is independently associated with lower mortality, but it is unclear whether other attributes of schooling matter. We examined the association of high school quality and all-cause mortality across race/ethnicity. In 1960, about 5% of US high schools participated in Project Talent (PT), which collected information about students and their schools. Over 21,000 PT respondents were followed for mortality into their eighth decade of life using the National Death Index. A school quality factor, capturing term length, class size, and teacher qualifications, was used as the main predictor. First, we estimated overall and sex-stratified Cox proportional hazards models with standard errors clustered at the school level, adjusting for age, sex, composite measure of parental socioeconomic status, and 1960 cognitive ability. Second, we added an interaction between school quality and race/ethnicity. Among this diverse cohort (60% non-Hispanic Whites, 23% non-Hispanic Blacks, 7% Hispanics, 10% classified as another race/s) there were 3,476 deaths (16.5%). School quality was highest for Hispanic respondents and lowest for non-Hispanic Blacks. Non-Hispanic Blacks also had the highest mortality risk. In the whole sample, school quality was not associated with mortality risk. However, higher school quality was associated with lower mortality among those classified as another race/s (HR 0.75, 95% CI: 0.56-0.99). For non-Hispanic Blacks and Whites, the HR point estimates were unreliable, but suggest that higher school quality is associated with increased mortality. Future work will disentangle these differences in association of school quality across race/ethnicity and examine cause-specific mortality.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1098.2-1099
Author(s):  
O. Russell ◽  
S. Lester ◽  
R. Black ◽  
C. Hill

Background:Socioeconomic status (SES) influences disease outcomes in rheumatoid arthritis (RA) patients. (1, 2) Differences in medication use could partly explain this association. (3) A scoping review was used to identify research conducted on this topic and determine what knowledge gaps remain.Objectives:To determine what research has been conducted on this topic, how this research has defined SES and medication use, and establish what knowledge gaps remain.Methods:MEDLINE, EMBASE and PsychInfo were searched from their inception until May 2019 for studies which assessed SES and medication use as outcome variables. Studies were included if they measured medication use and incorporated an SES measure as a comparator variable.SES was defined using any of the “PROGRESS” framework variables (4) including patients’ stated gender, age, educational attainment, employment, occupational class, personal income, marital status, health insurance coverage, area- (neighbourhood) level SES, or patients’ stated race and/or ethnicity. Medication use was broadly defined as either prescription or dispensation of a medicine, medication adherence, or delays in treatment. Data was extracted on studies’ primary objectives, measurement of specific SES measures, patients’ medication use, and whether studies assessed for differences in patients’ medication use according to SES variables.Results:1464 studies were identified by this search from which 74 studies were selected for inclusion, including 52 published articles. Studies’ publication year ranged from 1994-2019, and originated from 20 countries; most commonly from the USA.Studies measured a median of 4 SES variables (IQR 3-6), with educational achievement, area level SES and race/ethnicity the most frequently recorded.Likelihood of disease modifying antirheumatic drug (DMARD) prescription was the most frequent primary objective recorded.96% of studies reported on patients’ use of DMARDs, with glucocorticoids and analgesics being reported in fewer studies (51% and 23% respectively.)Most included studies found at least one SES measure to be significantly associated with differences in patients’ medication use. In some studies, however, this result was not necessarily drawn from the primary outcome and therefore may not have been adjusted for covariates.70% of published studies measuring patients’ income (n=14 of 20) and 58% of those that measured race/ethnicity (n=14 of 24) documented significant differences in patients’ medication use according to these SES variables, although the direction of this effect – whether it led to ‘greater’ or ‘lesser’ medication use – varied between studies.Conclusion:Multiple definitions of SES are used in studies of medication use in RA patients. Despite this, most identified studies found evidence of a difference in medication use by patient groups that differed by an SES variable, although how medication use differed was found to vary between studies. This latter observation may relate to contextual factors pertaining to differences in countries’ healthcare systems. Further prospective studies with clearly defined SES and medication use measures may help confirm the apparent association between SES and differences in medication use.References:[1]Jacobi CE, Mol GD, Boshuizen HC, Rupp I, Dinant HJ, Van Den Bos GA. Impact of socioeconomic status on the course of rheumatoid arthritis and on related use of health care services. Arthritis Rheum. 2003;49(4):567-73.[2]ERAS Study Group. Socioeconomic deprivation and rheumatoid disease: what lessons for the health service? ERAS Study Group. Early Rheumatoid Arthritis Study. Annals of the rheumatic diseases. 2000;59(10):794-9.[3]Verstappen SMM. The impact of socio-economic status in rheumatoid arthritis. Rheumatology (Oxford). 2017;56(7):1051-2.[4]O’Neill J, Tabish H, Welch V, Petticrew M, Pottie K, Clarke M, et al. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014;67(1):56-64.Acknowledgements:This research was supported by an Australian Government Research Training Program Scholarship.Disclosure of Interests:None declared


Sign in / Sign up

Export Citation Format

Share Document