Intersectionality-informed analysis of durable viral suppression disparities in people with HIV

基于交叉性视角的艾滋病毒感染者持久病毒抑制差异分析

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Abstract

OBJECTIVE: The aim of this study was to examine drivers of durable viral suppression (DVS) disparities among people with HIV (PWH) using quantitative intersectional approaches. DESIGN: A retrospective cohort analysis from electronic health records informed by intersectionality to better capture the concept of interlocking and interacting systems of oppression. METHODS: We analyzed data of PWH seen at a LGBTQ federally qualified health center in Chicago (2012-2019) with at least three viral loads. We identified PWH who achieved DVS using latent trajectory analysis and examined disparities using three intersectional approaches: Adding interactions, latent class analysis (LCA), and qualitative comparative analysis (QCA). Findings were compared with main effects only regression. RESULTS: Among 5967 PWH, 90% showed viral trajectories consistent with DVS. Main effects regression showed that substance use [odds ratio (OR) 0.56, 0.46-0.68] and socioeconomic status like being unhoused (OR: 0.39, 0.29-0.53), but not sexual orientation or gender identity (SOGI) were associated with DVS. Adding interactions, we found that race and ethnicity modified the association between insurance and DVS ( P for interaction <0.05). With LCA, we uncovered four social position categories influenced by SOGI with varying rates of DVS. For example, the transgender women-majority class had worse DVS rates versus the class of mostly nonpoor white cisgender gay men (82 vs. 95%). QCA showed that combinations, rather than single factors alone, were important for achieving DVS. Combinations vary with marginalized populations (e.g. black gay/lesbian transgender women) having distinct sufficient combinations compared with historically privileged groups (e.g. white cisgender gay men). CONCLUSION: Social factors likely interact to produce DVS disparities. Intersectionality-informed analysis uncover nuance that can inform solutions.

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