HIV / STI
Latent class analysis of traumatic life experiences among people living with HIV in Florida. Nanyangwe Siuluta* Nanyangwe Siuluta Karina Villlaba Catalina Lopez-Quintero Yancheng Li Yiyang Liu Robert L. Cook Nichole M. Scaglione
Background:Traumatic Life Experiences (TLE)-perceived events risking health, causing victim helplessness and fear—are more common among people with HIV(PWH) than the general US population. This study used latent class analysis (LCA) to identify unique LTE patterns and examined the consistency of LTE patterns across demographic subgroups in a sample of PWH. Methods:From 2019-2022, the Florida Cohort examined individual, clinical, & community impacts on healthcare utilization and HIV outcomes in 495 PWH. Participants were 42% non-heterosexual men; 42% women; 59% aged 50+; & 43% Black. They self-reported LTE on questionnaires assessing sexual harassment (SH), unwanted sexual touch (UST), forced sex (FS), transactional sex, discrimination (D), physical attack (PAt), stalking (S), hate crimes, verbal (VAb), physical (PAb), & emotional (EAb) abuse. We used PROC LCA (SAS V9.4) to sequentially examine LCAs (2-5 classes); we added demographic covariates to the model that best fit the data. Results:Model fit criteria (Entropy, AIC, BIC) indicated a four-class solution best fit the data. The Abuse & Discrimination class (41%) endorsed relatively high probabilities of VAb, EAb, PAb, PAt, & D. The Sexual Abuse Risk class (14%) reported high probabilities of S, SH, UST& FS in addition to VAb, EAb, & PAb. The Low-Risk class (35%) had consistently low probabilities of all LTEs; the High-Risk class (11%) had the highest probability of experiencing 9/12 LTEs. Subgroup analyses showed class consistency, but membership probabilities varied by sex, sexual orientation, race, & age – e.g. the largest proportion of non-heterosexual men (31%) were in the Abuse & Discrimination class, while the largest proportions of heterosexual men (50%) & women (34%) were in the Low-Risk class. Conclusion: Findings highlight significant variability in LTE patterns. More work is needed to identify predictors of LTE class membership and to link LTE patterns to health outcomes in PWH.