This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American
In my last post, I discussed whether there is a place for race in medicine. I wrote that while sensitive consideration of race may sometimes be justified, the burden is on the medical researcher to explain why that is.
That raises the question: what’s the next step? That is, suppose a researcher feels that stratifying her data by race would provide benefits for patient care. Then what? How should she write about race in medicine responsibly?
I would like to share a paper that addressed this exact question. In 2003, Judith B. Kaplan and Trude Bennett published a paper in JAMA that came up with seven thoughtful guidelines for writing about race in biomedical research. (I’m afraid you cannot access the entire paper without a subscription to JAMA, but I am including their conclusions here.)
On supporting science journalism
If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.
“1. When race/ethnicity is used as a study variable, the reason for its use should be specified.”
This first guideline aligns with what I recommended in my last post. As the authors put it, the danger of using race without explanation is that it suggests it as a natural way of categorizing people.
“2. In citing race/ethnicity data from any source, authors should describe the way in which individuals were assigned to racial/ethnic categories. If racial/ ethnic identification was self-reported, authors should specify whether individuals answered an open-ended question or chose from a fixed set of categories.”
The way questions are phrased impacts results. The authors write, for example, that when individuals choose from a fixed set of categories, they may not identify with any of the choices. If these individuals mark something only for lack of a better option, it can skew results. Moreover, the authors explain that response choices differ across studies, making it difficult to compare results. Clarity of methods can help with this problem.
“3. Race/ethnicity should not be used as a proxy for genetic variation. Statements about genetic differences should be supported by evidence from gene studies. Genetic hypotheses should be firmly grounded in existing evidence, clearly stated, and rigorously tested.”
Differences among races could be due to many reasons: shared ancestry, socioeconomic status, cultural differences, and discrimination are just a few. Because we as a society still have a tendency to think “Aha! It’s biology!” when differences between groups are shown, the authors should make clear that racial differences alone say nothing about genetic differences; the only way to say anything about genetic differences is – unsurprisingly – genetics.
“4. In stating hypotheses and describing study results, authors should distinguish between race/ethnicity as a risk factor and race/ethnicity as a risk marker.”
While even epidemiologists disagree about the exact definitions of these terms, one way to see it is this: a risk marker tells about correlation, while a risk factor implies causation. Thus, if race is statistically associated with an outcome but does not play a role in the causal pathway, it is important to classify it as a marker.
“5. In the interpretation of racial/ethnic differences, all conceptually relevant factors should be considered, including racism and discrimination, [socioeconomic status] SES, social class, personal or family wealth, environmental exposures, insurance status, age, diet and nutrition, health beliefs and practices, educational level language spoken, religion, tribal affiliation, country of birth parents’ country of birth, length of time in the country of residence and place of residence.”
This guideline and the following one are related to guideline 3; there are many reasons differences among racial or ethnic groups might be uncovered. This guideline is critical because without considering all these variables, a paper might send the message that the differences uncovered are due to biology. Not only would this be inaccurate, it could also overshadow disparities in environment that warrant our attention.
“6. Because lack of adjustment for [socioeconomic status] SES or social class is the most important potential source of bias in studies of racial/ethnic differences, researchers should make every effort to adjust for conceptually relevant measures of SES or social class when comparing racial/ethnic groups. Unadjusted findings should be clearly labeled as such, and in general they should be reported in conjunction with adjusted findings for comparison purposes.”
It’s challenging to adjust for all relevant variables. But researchers have an obligation to be as comprehensive as possible – especially for factors (like socioeconomic status) that are recurring sources of bias.
“7. In describing racial/ethnic groups, authors should use terminology that is not stigmatizing, does not reflect unscientific classification systems, and does not imply that race/ethnicity is an inherent, immutable attribute of an individual.”
The authors give an example of using the term “Asian” instead of “Oriental” or “Asiatic.” In addition to discouraging stigmatizing terms, they also discourage terminology that is overly broad.
***
The bottom line? Be comprehensive; be as precise as possible; be respectful. I applaud and thank the authors for these guidelines. The ultimate goal of medical research is to help patients. In the discussion over whether there is a place for race in doing so, it would help all sides to make their cases with such care.
(Reference: Kaplan JB, Bennett T. Use of race and ethnicity in biomedical publication. JAMA 2003; 289(20): 2709–16.)
