Kawano B. Constructing a South Asian cardiovascular disease: a qualitative analysis on how researchers study cardiovascular disease in South Asians.
JOURNAL OF MEDICAL ETHICS 2023;
50:70-74. [PMID:
35277467 DOI:
10.1136/medethics-2021-107890]
[Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 02/25/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND
Debates on the use of race in biomedical research have typically overlooked immigrant groups outside of the black-white racial dichotomy. Recent biomedical research on South Asians and cardiovascular disease provides an opportunity to understand how scientists define race and interpret racial health disparities from an underexamined perspective.
PURPOSE
To examine how researchers in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study defined a South Asian population, and then compared health differences between South Asians and other populations.
METHODS
Qualitative content analysis was performed on eleven articles from August 2013 to January 2021 that directly compared the South Asian cohort in MASALA to four other groups. The MASALA study design article was also included in this analysis. Articles were analysed for how South Asians were defined, and for how health differences between South Asians and other populations were studied and discussed.
RESULTS
Researchers in MASALA were neither clear nor precise in defining South Asians as either an ancestral group or ethnic group. Their studies also prioritised investigating genetic and molecular causes of the cardiovascular health disparity between South Asians and other populations and failed to examine possible social factors.
CONCLUSIONS
These findings reflect a broader trend in biomedical research in which race and racial health disparities are poorly defined and studied, limiting scientists' understanding of the relationship between race and health. I propose methodologies to help researchers define populations and design studies without relying on biologically reductive assumptions.
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