Race, Ethnicity, and Health Disparities: Biological Anthropology’s Role in Biomedical Research

Walk into any public health conference today and you will hear researchers comparing disease rates across racial and ethnic groups: diabetes prevalence among South Asians, cardiovascular risk among African-descended populations, sickle cell disease among tribal communities. These comparisons shape health policy and clinical guidelines. But they raise a tricky question: what exactly are we comparing when we sort people by race or ethnicity? This is where biological anthropology enters biomedical research, offering both the tools to study human variation and the caution needed to interpret it responsibly.

What biological anthropology actually studies 🔗

Biological anthropology looks at how human bodies vary across populations and why. That variation is real. Skin tone, lactose tolerance, altitude adaptation, and disease resistance all differ across groups, largely because of evolutionary history, migration, and local environments. What biological anthropology does not support is the idea that this variation sorts neatly into a handful of discrete races.

The American Association of Biological Anthropologists has stated plainly that race does not accurately represent human biological variation and that humans are not divided into distinct continental genetic clusters. Most human genetic diversity exists within populations, not between them. A well-known 1972 analysis by geneticist Richard Lewontin found that the vast majority of genetic variation occurs among individuals within the same population rather than across racial categories.

Clines, not categories 🔗

Anthropologists describe human variation as clinal, meaning traits change gradually across geography rather than jumping abruptly at racial boundaries. Skin pigmentation, for instance, shifts gradually with latitude and sun exposure rather than switching sharply from one “race” to another. This is why the biological reality of human variation looks nothing like the racial categories used on census forms or hospital intake sheets.

So why does race keep showing up in health research? 🔗

If race is not a clean biological category, why do epidemiologists keep using it? The honest answer is that race and ethnicity, while social constructs, still correlate with real health outcomes. That correlation exists not because of innate biology, but because race and ethnicity are tied to socioeconomic status, access to healthcare, residential segregation, occupational exposure, diet, and generations of discrimination.

A widely cited analysis in the biomedical literature notes that continental ancestry can still carry pragmatic value in public health genomics, because evolutionary history, migration patterns, and social factors together shape how disease risk and treatment response cluster in populations, even though race itself has no fixed biological definition. In other words, race is often a rough proxy for a tangle of social and environmental exposures that researchers have not measured directly.

A real-world example closer to home 🔗

India offers a good illustration. Sickle cell disease and its trait are far more common among certain Scheduled Tribe communities than in the general population. A nationwide screening effort found that roughly 8.75 percent of the more than 1.1 crore people tested carried the sickle cell trait, with prevalence highest among tribal groups in central, southern, and western India. Research published in the Indian Journal of Medical Research has documented that sickle cell disease tends to run milder in tribal populations than in non-tribal patients, likely because of a higher co-occurrence of alpha thalassaemia and elevated foetal haemoglobin levels among these groups.

This pattern is genuinely biological, tied to specific gene variants that became common in populations historically exposed to malaria. But it is not a “racial” pattern in the old sense. It reflects the evolutionary history of particular endogamous communities, not a broad racial category like “Asian” or “tribal” as a whole. This is exactly the nuance biological anthropology brings to biomedical research: identifying real genetic patterns while resisting lazy generalisations about entire racial groups.

Health disparities as a public health priority 🔗

Recognising these patterns matters because they translate into measurable gaps in health outcomes. In the United States, the Department of Health and Human Services made eliminating health disparities one of the two central goals of its Healthy People 2010 initiative, alongside increasing years of healthy life. The initiative defined health disparities as differences in health that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation.

The scale of the goal was ambitious, and progress was uneven. Reviews of the initiative found that many leading health indicators showed little improvement in disparities over the decade, prompting the follow-up Healthy People 2020 framework, which set an explicit goal to achieve health equity and eliminate disparities across population groups defined by sex, race, ethnicity, education, income, disability, and geography. The persistence of these gaps across two decades of federal initiatives underscores just how deeply health disparities are woven into social structures, not simply individual biology.

Why biological anthropology matters here 🔗

Biological anthropology contributes a specific piece of this puzzle: it helps distinguish which health differences trace back to genuine biological variation, such as inherited blood disorders, and which trace back to unequal social and environmental conditions, such as poor nutrition, limited healthcare access, or occupational hazards. Without that distinction, public health efforts risk either ignoring real genetic risk factors or, worse, misattributing socially caused disparities to imagined biological differences between racial groups.

The problem with using race and ethnicity carelessly 🔗

Even researchers who agree that race is not a biological category still face a practical problem: race and ethnicity remain common variables in epidemiological studies, and how they are used varies enormously. A review of nearly 1,200 articles published in two major public health journals found that researchers frequently failed to define what they meant by race or ethnicity, describe how they measured it, or discuss the limitations of their categories. The same review found an enormous diversity of terms and category counts used to describe race and ethnicity across studies, sometimes ranging from a single category to as many as 24 within one article.

This inconsistency is not a minor technical issue. It affects how health disparities are quantified, whether findings can be compared across studies, and whether policy responses target the right causes. If one study lumps together dozens of distinct communities under a single ethnic label, it can obscure meaningful differences, the way averaging sickle cell rates across all Indian tribal groups would hide the fact that prevalence varies sharply between specific communities such as the Bhil, Gond, or Oraon populations.

Building scientific integrity into research design 🔗

Recognising these gaps, researchers have proposed methodological guidelines to raise the rigour of studies that use race and ethnicity as variables. A set of recommendations for using these concepts in research suggests that scientists should clearly state the purpose for including race or ethnicity, treat these categories as markers of social experience rather than biological fact, allow participants to self-identify, and be transparent about how broad categories were constructed from more specific group data. These steps do not eliminate the complexity of race and ethnicity as scientific variables, but they make the resulting research more honest about what it can and cannot claim.

What this means for the future of biomedical research 🔗

Biological anthropology’s role here is less about producing a single tidy answer and more about holding two truths together. Human biological variation is real, evolutionarily grounded, and clinically relevant in specific, well-documented cases like haemoglobin disorders. At the same time, race as a broad social category is a poor stand-in for that variation and frequently ends up capturing the effects of inequality rather than genetics.

As genomic tools become cheaper and more widely used in Indian hospitals and research institutions, this distinction will only become more important. Screening programmes for conditions like sickle cell disease and thalassemia work best when they target specific, well-studied communities based on actual genetic risk, rather than broad ethnic or caste categories. Biomedical researchers who understand the anthropological nuance behind human variation are better equipped to design studies, and interventions, that actually reduce disparities instead of reinforcing outdated and inaccurate ideas about race.

What do you think? When a health survey asks you to select your race, ethnicity, or community, do you think that category captures anything meaningful about your health risks, or mostly reflects social and economic factors? And should national screening programmes in India focus more narrowly on specific communities with documented genetic risk, rather than broader ethnic or tribal labels?

References

1. https://bioanth.org/about/aaba-statement-on-race-racism/
2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756148/
3. https://telanganatoday.com/sickle-cell-disease-widespread-within-tribal-population
4. https://ijmr.org.in/sickle-cell-disease-in-tribal-populations-in-india/
5. https://www.ncbi.nlm.nih.gov/books/NBK114239/
6. https://www.cdc.gov/nchs/healthy_people/hp2020/health-disparities.htm
7. https://academic.oup.com/aje/article/159/6/611/147734
8. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550522/