Removing race as a risk factor for cardiovascular disease?

The AHA has announced a new “race-free” assessment tool, but eliminating this variable carries the potential to increase – rather than decrease – racial disparities in healthcare

Peter Attia

Read Time 7 minutes

Race has a complex and troubled history. There is no question that the concept of race has been used for millennia to justify all manner of atrocities, a practice which tragically continues to this day in some parts of the world. But in modern medicine, race has found another purpose: physicians use this variable, which serves as a stand-in for countless genetic, social, and cultural factors, to better estimate an individual’s risk of many life-threatening diseases, including cardiovascular disease (CVD). And yet, the American Heart Association (AHA) plans to change that.

About the announcement

In November, the AHA introduced a new calculator – which they’ve called PREVENT, or “Predicting Risk of cardiovascular disease EVENTs” – to assess an individual’s risk of heart attack, stroke, and heart failure. PREVENT incorporates established risk factors – such as hypertension and cigarette smoking – that had been included in the AHA’s previous CVD risk assessment tool (developed in 2013) and also adds to this list factors such as kidney function metrics and measures of glycemic control. But the new tool has gained more attention for the risk factor that it has removed relative to previous iterations: race. 

The committee responsible for developing PREVENT described race as “a social construct and an historically fraught proxy representing various lived experiences,” rather than a biological factor, and they note that it therefore should not be included in risk assessments. The authors argue that racism – not race itself – is primarily responsible for observed differences in CVD outcomes across populations, suggesting that the inclusion of this variable facilitates the perpetuation of racially motivated disparities in quality of healthcare. They acknowledge that different races are also associated with different levels of CVD risk factors and incidence (indicating that racism in treatment cannot entirely account for the disparities), but the authors make the assumption that these differences are nevertheless attributable to “nonbiological factors.”

Race may be an imperfect variable…

The AHA is not entirely wrong in asserting that race is a “social construct” rather than a variable defined by any single biological metric, but the notion that race has no relationship to biology is a step too far. Racial distinctions are defined by differences in physical appearance (e.g., skin color or eye shape) broadly associated with various geographical regions of ancestral origin. These correlate with genetic similarities, albeit somewhat inconsistently. For instance, a given individual will, in most cases, be more genetically similar to another of the same racial background than to someone of a different racial background, though this is reportedly not the case roughly one-third of the time, regardless of the specific races studied.

It follows that racial designations thus downplay the vast genetic variation that exists within a given race. An analysis of populations from Asia, Africa, and Europe showed that 85-90% of genetic variation across all humans in these regions was present between individuals of the same continent, while differences between separate continents accounted for only 10-15% of total genetic variation. And the level of within-population variation is not uniform. African populations feature greater genetic diversity than all other human populations combined – meaning that, despite two people having the same racial definition of “Black,” if one is from West Africa and another from Southern Africa, they are almost certain to be more genetically distinct from each other than any given Caucasian is from a Pacific Islander, or Asian is from a Native American, etc. And of course, definitions become even muddier when we consider individuals with mixed racial backgrounds.

… But it’s better than no information at all

And yet, despite the many limitations, race still provides valuable information on disease risk that we cannot currently gain from any other variable. The AHA committee argues in favor of replacing race with other socioeconomic metrics such as income and education, but this would imply that race bears no relationship whatsoever to genetics, which as we’ve just seen, is not the case. Race may be an imperfect estimate of genetics, but imperfect is better than no estimate at all. 

Yes, we have the technology to perform genetic sequencing to obtain a more direct assessment of one’s genetic background, but in addition to the many practical roadblocks to universal genetic testing, we have not yet reached a level of understanding of the genetic underpinnings of complex diseases to be able to interpret most of the information we’d gain by poring over genetic code. Moreover, some of the associations we do know with respect to genetic variants and disease risk have been found to be true for some races and not others – for instance, as was recently shown with the FTO gene and obesity. As I’ve explained previously, many of those “known” associations are heavily biased toward those of European descent, so individuals of other races would thus be less likely to receive meaningful or accurate health insights from genetic risk assessments. This problem, combined with the financial cost of genetic sequencing, would therefore have the potential to create greater racial disparities in healthcare quality than currently exist with the use of race itself as a risk variable.

At present, race tells us more than genetics

In contrast to our relatively limited knowledge of genetic associations with disease, a large body of data exists on associations between race and disease, as clinical trials and epidemiology studies commonly collect data on participant racial backgrounds. As a result, we know that certain diseases are more common in some racial groups relative to others. Asian Americans are more likely than their white counterparts to develop stomach cancer. White Americans are more likely than African Americans to develop non-alcoholic fatty liver disease. African Americans are more likely than any other race in the US to develop hypertension. While some of these disparities in risk likely reflect socioeconomic or cultural differences in addition to differences in genetics, the mere fact that races differ in disease risk helps to point physicians toward areas of potential concern and the appropriate course of action, even if we don’t fully understand the social versus genetic mechanisms.

Consider this example: Asians and Pacific Islanders are disproportionately burdened with type 2 diabetes (T2D) and often develop the disease at lower BMI than other groups. These observations led to a national campaign to reduce the recommended BMI threshold for T2D screening to 23 kg/m2 for Asians and Pacific Islanders, in contrast to the cutoff of 25 kg/m2 for the general population. If fully put into practice, the move is estimated to result in the identification of an additional 6,000 cases of T2D among the Asian American population of Massachusetts alone (where the initiative was first passed). In other words, without accounting for race in T2D risk assessments, Asian Americans and Pacific Islanders experience a racial disparity in quality of care due to under-screening and underdiagnosis. This campaign – led by the Asian American community – thus pushed for race to be used as a key consideration in evaluating diabetes risk and is poised to vastly improve health outcomes for this population, regardless of ambiguity as to why Asian Americans have a higher risk.

Politics over science?

When it comes to predicting health outcomes, more information generally leads to better predictions, yet the AHA wishes to throw away a valuable data point. Yes, distinguishing between races creates the potential for discrimination, but some potential will always be there, since removing race from a CVD risk calculator does not remove race (a variable defined largely by appearance) from existence. Further, the logic of reducing risk of bias could easily apply as rationale to exclude nearly every other risk factor as well. Collecting information on a patient’s sex creates the opportunity for sexism. Recording a patient’s weight creates the potential for “sizeism” and discrimination against those who are very obese or very underweight. Asking for information on education history or other socioeconomic factors could lead to classism. And yet we don’t eliminate these variables because, despite the risk, they facilitate better, more informed clinical decisions.

When we look at the issue from this perspective, it becomes clear that the AHA’s decision was motivated by political – rather than scientific – rationale, likely inspired by the wave of reports in recent years of racial inequities in medical care. But despite how progressive and appealing it might sound to go “race-free,” when we stop to consider what it would truly mean to sacrifice this information, it becomes clear that the move is likely to result in greater racial disparities in clinical outcomes.

Thus, as an organization trusted for its medical expertise and its mission to promote health, the AHA sets an alarming precedent in prioritizing popular politics over scientific rigor and medical reality. Will they similarly be swayed to remove sex as a relevant variable, given that the related variable of gender is regarded as fluid? Will they bow to pressures from other political entities, such as pharmaceutical company lobbies or the reigning political party? If the course of the AHA’s decisions isn’t defined strictly by advances in science and medicine, then there is no clear limit to the potential influence of any number of outside interests.

Using available information while understanding limitations

Rather than throwing away information that provides clinical value, we should work to ensure that the medical community is aware of the limitations of that information while simultaneously directing efforts toward elucidating the mechanisms underlying racial associations with disease. If, as the AHA asserts, these associations are entirely social in nature, shouldn’t we wait to remove race as a factor until after we know exactly what those social factors are? And if, as existing data suggest, race does have underpinnings in genetics, shouldn’t we wait to eliminate race as a factor until we understand genetic risk factors, as well?

I certainly look forward to an era in which we have a perfect, thorough understanding of both social variables and genetic variants as they relate to disease risk and in which everyone has equal access to perfectly accurate genetic risk assessments. But in the absence of the “perfect,” we can’t afford to thumb our noses at “the best we have right now,” regardless of what’s politically in vogue at the moment. Race is far from perfect, but it is currently our best proxy for a complex set of genetic variables – and yes, socioeconomic and cultural variables – that impact disease risk and treatment.

The troubled history of race has left many with a negative impression of the entire concept, which undoubtedly motivated the AHA’s announced changes. But we mustn’t place such a high priority on eliminating the formal acknowledgement of race that, in the process, we increase – rather than decrease – racial disparities in healthcare.


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