No abstract

This article published in The New England Journal of Medicine emphasizes the importance of including race and ethnicity in biomedical research and clinical practice. These variables are important in the consideration of epidemiologic information, including social determinants of health such as racism and discrimination, socioeconomic position, and environmental exposures. Thus, eliminating the use of race/ethnicity altogether could lead to inequitable health care systems and the exacerbation of racial/ethnic inequities in health outcomes. Risks and benefits of using race/ethnicity data should be analyzed carefully for specific clinical implications.Race/ethnicity data have been used to assess differences in clinical measures and outcomes, but even when analysts control for socioeconomic indicators, there is frequently a greater risk of adverse health outcomes among Black Americans compared with White Americans. This difference is usually not explained or is explained as "intrinsic biological differences."Race and ethnicity are useful when uncovering genetic variants that may affect the likelihood of developing a certain disease. However, because race and ethnicity are self-ascribed, ancestry is a better predictor of the likelihood of certain genetic variants being present. Further, race/ethnicity categories used in biomedical research and clinical practice are less precise than ancestry. This is largely due to the fact that race/ethnicity relies on self-identification, whereas ancestry is a fixed characteristic of the genome.The National Institutes of Health has made an effort to include racial/ethnic minority populations in funded studies; however, there are still significant gaps in knowledge regarding the generalizability to non-White populations. Currently, less than 2% of National Cancer Institute-funded clinical trials have consisted of non-White participants. Disparities such as this maintain the gap in access to precision medicine for non-White populations. It is critical that globally diverse populations are studied because genetic variation and genome architecture vary within populations.It is also important to note that the use of race/ethnicity data may be important when quantifying the nongenetic causes of health inequities. These inequities can be rooted in socioeconomic factors as well as racial stratification. Looking at genetic ancestry and race/ethnicity together has improved the understanding of disease and led to the development of interventions. However, the relative importance of bias, racial discrimination, culture, socioeconomic status, access to care, environmental factors, and genetics to racial/ethnic differences in disease have not been studied in enough detail. Simply ignoring race and ethnicity in biomedical research and medicine will not solve the health-inequity epidemic. Scientists and clinicians should continue to use racial/ethnic categories to remove health inequities until more precise predictors are available.