The current debate over racial inequalities in health is arguably the most important venue for advancing both scientific and public understanding of race, racism, and human biological variation. In the United States and elsewhere, there are well-defined inequalities between racially defined groups for a range of biological outcomes-cardiovascular disease, diabetes, stroke, certain cancers, low birth weight, preterm delivery, and others. Among biomedical researchers, these patterns are often taken as evidence of fundamental genetic differences between alleged races. However, a growing body of evidence establishes the primacy of social inequalities in the origin and persistence of racial health disparities. Here, I summarize this evidence and argue that the debate over racial inequalities in health presents an opportunity to refine the critique of race in three ways: 1) to reiterate why the race concept is inconsistent with patterns of global human genetic diversity; 2) to refocus attention on the complex, environmental influences on human biology at multiple levels of analysis and across the lifecourse; and 3) to revise the claim that race is a cultural construct and expand research on the sociocultural reality of race and racism. Drawing on recent developments in neighboring disciplines, I present a model for explaining how racial inequality becomes embodied-literally-in the biological well-being of racialized groups and individuals. This model requires a shift in the way we articulate the critique of race as bad biology.

The description and explanation of racial and ethnic health disparities are major initiatives of the public health research establishment. Black Americans suffer on nearly every measure of health in relation to white Americans. Five theoretical models have been proposed to explain these disparities: a racial-genetic model, a health-behavior model, a socioeconomic status model, a psychosocial stress model, and a structural-constructivist model. We selectively review literature on health disparities, emphasizing research on low birth weight and high blood pressure. The psychosocial stress model and the structural-constructivist model offer greatest promise to explain disparities. In future research, theoretical elaboration and operational specificity are needed to distinguish among three distinct factors: (a) genetic variants contributing to disease risk; (b) ethnoracial or folk racial categories masquerading as biology; and (c) ethnic group membership. Such elaboration is necessary to move beyond the conflation of these three distinct constructs that characterizes much of current research.

The results reported here are consistent with the hypothesis that everyday encounters with discrimination are causally associated with poor mental and physical health outcomes. In this sample of African American women, this association holds above and beyond the effects of income and education.

For a brief moment, in the early days of COVID-19, some reports heralded the new coronavirus, SARS-CoV-2, as a "great equalizer." It is unlikely that any anthropologist, human biologist, historian, or public health scientist found this idea tempting. Pandemics always follow the fault lines of society-exposing and often magnifying power inequities that shape population health even in normal times (Wade, 2020). Soon, that stark reality became clear to all. By early April, evidence began to emerge in the United Statesfirst in Milwaukee, then in Detroit, eventually everywhere data were disaggregated by race-that mortality from COVID-19 was disproportionately affecting Black people and communities (Johnson & Buford, 2020). During the entire course of the pandemic so far, data compiled by the non-profit APM Research Lab (2020) has shown that the crude death rate for Black Americans is more than double that for all other racialized groups. When adjusted for age, the risk of death from COVID-19 is as much as nine times higher for African Americans than it is for whites (Bassett, Chen, & Krieger, 2020). This inequity-as appalling as it is-may still underestimate the problem, as data remain woefully incomplete. Despite calls for comprehensive, nationwide data on COVID-19 cases and deaths by race and socioeconomic status, the U.S. federal government has no such system in place, and journalists and scholars have stepped in to collate disaggregated data by race from a patchwork of state health departments. The need for better data remains. But data alone are not enough. We also need an explicit conceptual framework to know what the numbers mean, shape the questions researchers ask, and direct attention to appropriate public health and policy responses. In the absence of such a framework, the legacy of racial-genetic determinism in American medicine makes it likely that excess Black death will be interpreted as intrinsic Black vulnerability-a pattern that has already begun to emerge (Gravlee, 2020). Here I propose that the theory of syndemics may be a useful framework for making sense of the unfolding pandemic and directing future research on COVID-19.

Sample size determination for open-ended questions or qualitative interviews relies primarily on custom and finding the point where little new information is obtained (thematic saturation). Here, we propose and test a refined definition of saturation as obtaining the most salient items in a set of qualitative interviews (where items can be material things or concepts, depending on the topic of study) rather than attempting to obtain all the items. Salient items have higher prevalence and are more culturally important. To do this, we explore saturation, salience, sample size, and domain size in 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains—like kinds of fruits (highly bounded) and things that mothers do (unbounded)—varied greatly in size. The datasets comprise 20–99 interviews each (1,147 total interviews). When saturation was defined as the point where less than one new item per person would be expected, the median sample size for reaching saturation was 75 (range = 15–194). Thematic saturation was, as expected, related to domain size. It was also related to the amount of information contributed by each respondent but, unexpectedly, was reached more quickly when respondents contributed less information. In contrast, a greater amount of information per person increased the retrieval of salient items. Even small samples (n = 10) produced 95% of the most salient ideas with exhaustive listing, but only 53% of those items were captured with limited responses per person (three). For most domains, item salience appeared to be a more useful concept for thinking about sample size adequacy than finding the point of thematic saturation. Thus, we advance the concept of saturation in salience and emphasize probing to increase the amount of information collected per respondent to increase sample efficiency.

Our findings suggest that sociocultural processes mediate the relationship between skin color and blood pressure. They also help to clarify the meaning and measurement of skin color and "race" as social variables in health research.

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