Taking action to advance the study of race and ethnicity: the Women’s Health Initiative (WHI)

Abstract“Race” and “ethnicity” are socially constructed terms, not based on biology - in contrast to biologic ancestry and genetic admixture - and are flexible, contested, and unstable concepts, often driven by power. Although individuals may self-identify with a given race and ethnic group, as multidimensional beings exposed to differential life influencing factors that contribute to disease risk, additional social determinants of health (SDOH) should be explored to understand the relationship of race or ethnicity to health. Potential health effects of structural racism, defined as “the structures, policies, practices, and norms resulting in differential access to goods, services, and opportunities of society by “race,” have been largely ignored in medical research. The Women’s Health Initiative (WHI) was expected to enroll a racially and ethnically diverse cohort of older women at 40 U.S. clinical centers between 1993 and 1998; yet, key information on the racial and ethnic make-up of the WHI cohort of 161,808 women was limited until a 2020–2021 Task Force was charged by the WHI Steering Committee to better characterize the WHI cohort and develop recommendations for WHI investigators who want to include “race” and/or “ethnicity” in papers and presentations. As the lessons learned are of relevance to most cohorts, the essence of the WHI Race and Ethnicity Language and Data Interpretation Guide is presented in this paper. Recommendations from the WHI Race and Ethnicity Language and Data Interpretation Guide include: Studies should be designed to include all populations and researchers should actively, purposefully and with cultural-relevance, commit to recruiting a diverse sample; Researchers should collect robust data on race, ethnicity and SDOH variables that may intersect with participant identities, such as immigration status, country of origin, acculturation, current residence and neighborhood, religion; Authors should use appropriate terminology, based on a participant’s self-identified “race” and “ethnicity”, and provide clear rationale, including a conceptual framework, for including race and ethnicity in the analytic plan; Researchers should employ appropriate analytical methods, including mixed-methods, to study the relationship of these sociocultural variables to health; Authors should address how representative study participants are of the population to which results might apply, such as by age, race and ethnicity.

Well-Being and All-Cause Mortality in Aging Women in the Women's Health Initiative (WHI)

To study the relationship between well-being and all-cause mortality, we estimated mortality among women in four classes of well-being using the well-being profile from the Women’s Health Initiative Study (WHI). Demographic characteristics were self-reported at enrollment (1993-98). All-cause mortality included death from any cause between 2012-2020. We used logistic regression to examine all-cause mortality risk across the classes, using Class 4 (highest hedonic and eudaemonic well-being scores) as the referent, adjusting for age and race. Compared to Class 4, all other classes had higher age- and race-adjusted odds of death. Highest risks were in Class 1 women (OR=2.61; 95% CI: 2.46-2.76) and Class 3 women (OR=1.62; 95% CI: 1.55-1.68). Women in Class 4 had the lowest risk of all-cause mortality over an 18-year follow-up. These results confirm the utility of a profile of well-being for predicting all-cause mortality while preserving ability to identify the differences among well-being indicators across classes.