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

The aim of this study was to examine drivers of durable viral suppression (DVS) disparities among people with HIV (PWH) using quantitative intersectional approaches.

A retrospective cohort analysis from electronic health records informed by intersectionality to better capture the concept of interlocking and interacting systems of oppression.

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.

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).

Social factors likely interact to produce DVS disparities. Intersectionality-informed analysis uncover nuance that can inform solutions.