Electronic Thesis/Dissertation
 

An Intersectional Structural Determinant of PrEP Uptake among Black Heterosexual Cisgender Women

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Neighborhood Poverty

Black heterosexual cisgender women (BHCW) are at high HIV risk but have low uptake rates of pre-exposure prophylaxis (PrEP). The HIV epidemic is particularly alarming among BHCW living in the D.C.-Maryland-Virginia (DMV) metropolitan area. Existing empirical research demonstrates causal links between individual-level psychosocial determinants and HIV prevention behaviors

SD = 8.9 years) PrEP uptake interest and assessed the mediating effects of associated psychosocial (perceived HIV risk, anticipated PrEP stigma) pathways. Results indicated that participants’ PrEP uptake interest was not significantly predicted by neighborhood poverty, perceived HIV risk, nor anticipated PrEP stigma. Higher neighborhood poverty did predict lower perceived HIV risk but did not predict anticipated PrEP stigma. The hypothesized indirect effects of neighborhood poverty on PrEP uptake interest through perceived HIV risk and anticipated PrEP stigma were not supported. Age was negatively associated with BHCW’s PrEP uptake. This dissertation provides empirical evidence about the influence of neighborhood poverty on PrEP uptake for BHCW, a population at high HIV risk, within the DMV, an area with high HIV incidence. Results highlight the importance of transcending exclusively individual-level psychosocial determinants and using multilevel, multidisciplinary, and intersectional approaches to increase PrEP uptake among BHCW.

M = 30.73 years

yet little is known about how intersectional structural determinants affect PrEP uptake for BHCW. Structural intersectionality is a theoretical framework that can shed light on how multiple and interlocking structural determinants (i.e., racism, classism, and sexism) influence PrEP uptake among BHCW. Integrating theories and methodologies from social psychology, sociology, and public health, I conducted a secondary data analysis guided by structural intersectionality. Using structural equation modeling, I evaluated the direct effects of an intersectional structural determinant (neighborhood poverty) across 39 DMV zip codes on BHCW’s (N = 240

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