Racism is a fundamental cause of health inequities. Racism is multidimensional, encompassing: i) interpersonal (i.e., racial discrimination enacted by individuals); ii) institutional (i.e., discriminatory policies and practices occurring within social institutions); iii) structural (i.e., a web of inter-institutional connections which concentrate wealth, power, and health among whites); and iv) cultural (i.e., societal ideologies that place differential value on individuals based on race) processes. To effectively document racism, understand its effects on health, and develop interventions, it is necessary to measure it according to its dimension and the hypothesized pathways to health. This dissertation contributes to the growing racism and health literature, with a specific focus on the conceptualization and measurement of racism across its multiple distinct dimensions.
Chapter 1 examines the association between interpersonal-level racial discrimination and hypertension and depressive symptomatology, two health outcomes that are prevalent among African American women and increase risk of many leading causes of death, including cardiovascular disease. Data are from the African American Women’s Heart and Health Study, a cross-section of African American women in the Bay Area with detailed survey and biomarker data. Given that racial discrimination is believed to harm health through repeated adaptation to chronic psychosocial stress, we investigate a novel approach to coding a commonly used discrimination scale to more accurately capture chronicity of racial discrimination experiences. Specifically, we develop and test a the “chronicity coding approach” and compare it to two conventional coding approaches. Findings suggest that scale coding influences exposure classification (i.e., low, moderate, or high levels of racial discrimination) and whether that discrimination is associated with hypertension but not depressive symptomatology. We discuss implications for scale coding in racism and health, and epidemiologic research more broadly.
Chapter 2 moves from the interpersonal- to the institutional-level. Using administrative data from the Home Mortgage Disclosure Act, we apply a novel measure of institutional racism at the census-tract level, namely the odds that a Black applicant is denied a home mortgage loan relative to an equally qualified White applicant, an indicator of institutional discrimination, neighborhood hostility, and resultant psychosocial stress. We link this measure with 2006-2015 data from the California Cancer Registry, a complete repository of all breast cancer cases in the state, with detailed information on tumor characteristics. Given increasing interest in the structural drivers of triple-negative breast cancer—an aggressive subtype most prevalent among Black females—we examine whether racial bias in home mortgage lending is associated with breast cancer incidence separately by race (non-Hispanic Black and non-Hispanic White) and subtype (triple-negative and Luminal A which is more common and has a more favorable prognosis). We find that racial bias in home mortgage lending is not associated with either subtype among either racial/ethnic group. Possible explanations for null findings, and directions for future research are discussed.
Finally, Chapter 3 presents a systematic review of the emerging literature on the health consequences of area-level racial prejudice, which I conceptualize as an indicator of cultural racism. Across fourteen studies reviewed, area-level racial prejudice is found to be associated with myriad adverse health outcomes, ranging from preterm birth to premature mortality. Findings are most pronounced among racial/ethnic minoritized groups, but several studies also find effects among Whites. After discussing conceptual and measurement considerations and illustrating potential pathways to health, we offer concrete directions for future research.
Taken together, these three chapters contribute to the growing literature on racism as a fundamental cause of health inequities. A primary theme of my dissertation is to contribute to the ongoing conversation of how we can best measure racism to understand its effects on health. I leverage data from a variety of sources—including a small community sample of African American women with rich social, psychosocial, and biomarker data; a large scale publicly available administrative dataset; a state-wide cancer registry; and the peer reviewed literature—to interrogate how racism operating across multiple dimensions is associated with a variety of mental and physical health outcomes and inequities. My dissertation confirms the adverse health consequences of racism, concluding that measurement decisions should be guided by the conceptual definition and level of racism, as well as the hypothesized social or biologic pathway to health. I hope this body of work will encourage the critical reflection and theory-driven measurement required to rigorously document and ultimately eliminate racism’s harmful effects on the health of racially marginalized individuals, families, and communities.
