This is a guest post by Aris Tay, PhD Candidate, Bruce Wang and Diana Laird Labs, Developmental and Stem Cell Biology (DSCB), UCSF
In session 3 of UCSF’s racism and race: the use of race in medicine and implications for health equity discussion, as well as many other works centered around race in medicine, it was mentioned that race, as we use it colloquially, is a social construct. Due to my own identity, I often think about how gender is a social construct and how scientists often use the two terms sex and gender to separate out what is and is not scientifically and empirically biological and hard-wired. However, until this course I had not made the connection that race and racial identity is a social construct just like how gender is.
In many large scale observational genetic studies, specific genetic signatures (typically single nucleotide polymorphisms) are often found to be associated and even predicative for certain diseases. These genetic signatures are often correlated with self-identified racial groups. Thus, the field has often incorrectly assumed that race causes these genetic signatures which leads to a predisposition for disease, and that this is why I often hear statements such as “Tay-Sachs is most common is Ashkenazi Jews” or “Sickle cell anemia is more common in black people”. However, it is difficult, in these large observational studies, to separate lifestyle, family history, etc from the check box self-identified categories that patients are asked to bin themselves into. Self-identified categories of gender and race are much easier to draw correlations from; however, it is now coming to light that detailed family history and lifestyle is much more accurate. Social constructs of gender and race often make up core aspects of someone’s identify. This will definitely affect one’s choices and lifestyle which could then affect which diseases one is predisposed to. However, jumping directly from A to C eliminates a large majority of people that did not follow the most common path, thus disenfranchising them from receiving accurate medical care. Eliminating social constructs from medical treatment and diagnosis is an endeavor that the entire field should embark on.
On the other hand, when it comes to recruiting participants for large scale observational studies, clinical trials, etc. whether or not social constructs such as gender and racial identity should be accounted for is an outstanding question. Using clinical trials as an example, ensuring that the proposed experimental treatment works well on all races and genders is of utmost importance and has often been overlooked in historical trials. However, would using lifestyle in order to recruit not serve the same purpose? And be more accurate? Would taking detailed history and lifestyle cause too much strain during recruitment and completely offset its advantages? Would statistics be too difficult to run on family history and lifestyle when we know it’s possible and established using gender and racial identity. I leave you with some food for thought.