The unfortunate reality in our society right now is that manifestations of systemic racism continue to persist, and the healthcare system is certainly no exception. In my opinion, racial disparities in health and healthcare are among the most impactful on the “quality of life” gaps between ethnic groups. These disparities can of course be influenced by the social determinants of health, or by racism at the level of care itself. A subtle source of racial inequities in healthcare that is rarely acknowledged, however, is that rooted in biomedical research.
Ideally, the practice of medicine implies that physicians try to always remain up-to-date with the scientific literature, translating the data into clinical practice as they see fit. One problem with this process is that the data from the studies may not actually be representative of the population. In fact, some studies suggest that the patient makeup of clinical trials can be up to 80-90% white in some cases. There are many ways to statistically “adjust” for this, but such strategies are far from perfect. What’s more, there often is no “one size fits all” when it comes to extrapolating data from study subjects to the entire population. Healthcare providers must be able to navigate the nuances of the data and approach each case on an individual basis.
Take the ever-expanding epidemic of metabolic syndrome, for example, which incorporates a variety of metrics that contribute to chronic disease risk. The formal diagnosis of metabolic syndrome is defined as having three or more of the following: high blood glucose, low HDL cholesterol, elevated triglycerides, large waist circumference, and high blood pressure. Nick just wrote in our January newsletter about the problem with “normal” lab test values (i.e. triglycerides in the 800s being “normal” but not “healthy”), but another crucial flaw with these reference ranges is that they can be based on patient populations that skew heavily white. A healthcare provider should be able to recognize that Southeast Asians tend to have much lower waist circumferences under the same metabolic conditions as counterparts of other races, and that African Americans frequently have HDL and triglycerides that appear “normal” even when they’re experiencing severe metabolic dysregulation. If an African American patient presents with standard range HDL/triglycerides and we dismiss them as “perfectly fine” without noting that their glucose and insulin are through the roof, that’s clearly a problem. These are just some of the nuances that can go undetected and lead to serious discrepancies in patient outcomes, and this is why it is imperative that clinicians practice individualized medicine.
While doctors–or anyone scrutinizing biomedical research–must be able to navigate the fine details of the data in this way, it’s also important that we rethink the way we carry out scientific studies. Instead of looping the entire population under one umbrella with the rationale that we’re all exactly the same, it’s critical that we remove the stigma around recognizing the observed biological differences between individuals. It is no way any proposition of inequality or discrimination to acknowledge that we’re not all built exactly the same biologically. We’re a diverse species with fine details and differences to take into account when it comes to our health, virtually all of which are impacted by our genetics and/or environment. As we can see, it actually disproportionately hurts disadvantaged and underrepresented populations to turn a blind eye to this.
These inequities in medical research manifest in the form of generalized patient care tailored not to the individual, but more to the white population with which the studies were conducted. Both the ignorance of some healthcare professionals with regards to individualized care and the inadequate format of some studies can contribute to the worse chronic disease outcomes observed for minority populations. While the overall percentage of the U.S. population with type 2 diabetes is currently around 10%, the percentages among African American, Hispanic, and Pacific Islander populations are notably higher. Of course, social determinants probably still account for a majority of these gaps. However, in order to improve health equity for all people, we must further refine the population-level conclusions we make from biomedical research and hold our clinicians accountable for their interpretations of the data.
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