Yendewa, George A.

Objectives To understand the trade-offs between different statistical modeling approaches, using real world data with small sub-populations, with rare exposures and increasingly rare outcomes. In particular, to compare adjusted regression, inverse probability weighting, and matching. Methods Data for these analyses came from the RADAR (N=1,134) and combined CNICS/JHHCC (N=14,434) cohorts. We estimated prevalence ratios (PRs) for self-reported use of specific substances comparing subpopulations (SP), SP-1 vs SP-3 and SP-2 vs SP-3, where SP-1 was the largest proportion (92% in RADAR, 81% in CNICS/JHHCC), SP2 was moderate proportion (18% in CNICS/JHHCC) and SP-3 was the smallest proportion (8% in RADAR, 1% in CNICS/JHHCC) of the population. We calculated PRs using 1) unadjusted relative risk regression (RR); and adjusted estimates controlling for age, race/ethnicity, study site, and year of interview using: 2) standard adjustment in RR; 3) stabilized inverse probability of treatment weighting (IPTW); and 4) matching with up to 3 matches from SP-1 or SP-2 per SP-3 participant. Results For most substances, all methods yielded consistent estimates. There were large weights in some of the IPTW analyses and in three cases these resulted in substantially divergent estimates. For the comparison between SP-1 and SP-3, the estimate for smoking was 1.3-fold greater in the matched analysis (PR=1.33, 95% CI: 1.02-1.75) than in IPTW (PR=1.03, 95% CI: 0.78-1.37 ATE and PR=1.05, 95% CI: 0.88-1.26 ATT). Even more extreme divergence in estimates was observed for differences between SP-2 and SP-3 with respect to methamphetamine/amphetamine, (IPTW-ATE: PR=1.51, 95% CI: 0.79-2.89; IPTW-ATT: PR=2.36, 95% CI: 1.36-4.12); vs Matching: PR=2.71, 95%CI: 1.47-4.99) and cocaine (IPTW-ATE: PR=1.15, 95% CI: 0.55-2.38; IPTW-ATT: PR=1.81, 95% CI: 1.03-3.18); vs Matching: PR=1.38, 95%CI: 0.76-2.53). Conclusion The combination of a rare exposure and a rare outcome can produce challenges for commonly used confounding adjustment strategies, and it is often best to compare different modeling approaches to gain greater insight.

Background: Previous studies suggest that internalized HIV stigma (IHS) results in HIV viral nonsuppression via directly increasing depression, which then reduces adherence leading to nonsuppression; however, the dynamics between IHS and mental health are likely more complex. We sought to better understand IHS-mental health dynamics using data from a longitudinal clinical cohort of people with HIV (PWH) receiving healthcare across 10 US primary care clinics. Methods: Among 8,506 PWH who had ≥2 timepoints in which IHS, depression, and anxiety were measured, we examined changes over time in both two-state (i.e., impact of IHS on depression or anxiety and vice versa) and four-state combinations of depression-IHS (i.e., no depression or IHS, depression/no IHS, no depression/IHS, both depression/IHS) and anxiety-IHS. Transition probabilities between states and factors influencing transitions were identified using multistate Markov models. Results: The impact of IHS on the transition rates of mental health measures (i.e., depression, anxiety) and vice versa were almost the same, suggesting that each influences the other. Over 50% of PWH remained in the same IHS-depression or IHS-anxiety state. PWH with IHS had almost twice the rate of transitioning from no depression/anxiety to having depression/anxiety compared to PWH without IHS; with similar results for the depression or anxiety with no IHS to reporting IHS transition. Conclusions: We demonstrate that IHS and mental health dynamics are more complex than previously suspected and that the associations are bidirectional, which has implications for both future analyses and optimal management of these conditions among PWH.

Background: Internalized HIV stigma (IHS) is associated with reductions in antiretroviral therapy (ART) adherence and HIV viremia mediated through depression. However, there is still a need to quantify the direct impact of IHS on ART adherence to inform interventions to improve medication adherence. Methods: The Center for AIDS Research Network of Integrated Clinical Systems is a longitudinal, US-based, multisite cohort of people with HIV who complete patient-reported outcome assessments as part of HIV-care visits. Patient-reported outcome data include IHS items, ART adherence, depression assessments, substance use, and other outcomes. We examined associations between IHS and ART adherence using generalized linear latent and mixed models with a nonparametric random effects intercept to accommodate repeated measures. Results were compared with analyses using generalized estimating equations and marginal structural models. Results: Among 13,119 people with HIV, the mean age was 47.4 years, 17.6% were women, and 59.3% were non-White. Across 33,139 observations, controlled for repeated measures on individuals, HIV medication adherence was reduced by 1.07% for every point increase in IHS after controlling for age, sex, ethnicity, geographic location, and substance use, and 0.58% when additionally adjusted for depression score. Marginal structural models and generalized estimating equations provided similar results. Conclusions: Our study demonstrates that IHS has a direct association with reductions in ART adherence, which could affect other comorbid health outcomes that are influenced by unsuppressed viremia over time. Developing a thorough understanding of the mechanisms through which IHS affects ART adherence is critical for developing interventions to mitigate IHS and improve health outcomes across the lifespan.

Background: Housing instability and HIV are both associated with early onset of aging-related health conditions, including frailty. However, little is known about the relationship between housing and frailty among people with HIV. Methods: We analyzed data on adults in HIV care collected during routine clinical visits at 6 sites within the US Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) between 2019 and 2024. We measured frailty using a previously validated approach, defined as having at least three of four components (fatigue, weight loss, immobility, inactivity) vs. less than three components. Housing status was based on self-perceived living situation in the past month (“Stable,” “Unstable,” “Homeless,” or “Don’t know”). We estimated the association between most recent housing status and frailty with prevalence ratios from relative risk regression adjusted for sociobehavioral and clinical characteristics. Results: Among 6961 people with HIV (84% men, 16% women) with a median age of 52 years (IQR: 40–60), 11% ( n = 760) were frail and 9% ( n = 625) were unstably housed (5% unstable, 3% homeless, 1% do not know). Compared to individuals with stable housing, the prevalence of frailty more than doubled among those experiencing unstable housing [prevalence ratio = 2.41, 95% confidence interval (95% CI): 1.95–2.97] or homelessness (prevalence ratio = 2.05, 95% CI: 1.56–2.69). Stratified analyses indicated stronger associations among younger vs. older individuals and among those virally suppressed vs. unsuppressed. Conclusion: Housing instability and frailty were both prevalent and strongly associated among adults in HIV care, including within younger and virally suppressed subgroups. These findings highlight the importance of social determinants of health for clinical outcomes among all people with HIV.

Background: Current understanding of associations between alcohol use and falls among people with HIV (PWH) is limited due to few and inconsistent studies. Given the prevalence of heavy episodic alcohol use reported among PWH, this remains an important question. Methods: Alcohol use was measured using the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) and self-reported alcohol use treatment and/or diagnosis of alcohol use disorder (collectively AUD) among PWH at eight CFAR Network of Integrated Clinical Systems (CNICS) sites from 2021 to 2024. Falls were self-reported using the components of the Falls Risk for Older People in the Community (FROP-Com) questionnaire. Cross-sectional associations between alcohol use and falls were examined using relative risk models adjusted for age, sex, race/ethnicity, and geographic location. Results: Among 5729 PWH, mean age was 55 years; 42% reported White and 41% reported Black/African American race/ethnicity; and 81% were male. Mean AUDIT-C score was 1.9 (range: 0–12); 27% reported heavy episodic drinking; 22% had AUD; and 22% reported falling in the past year. Reporting at least one fall in the past year was not associated with any measure of current alcohol use. AUD was associated with reporting at least one fall [prevalence ratio = 1.54; 95% confidence interval (CI) 1.39–1.70] and number of falls [one fall: prevalence ratio = 1.27 (95% CI: 1.08–1.50); at least two falls: prevalence ratio = 1.84 (95% CI: 1.58–2.15)]. Conclusion: Among PWH, 22% reported falling, which was associated with AUD, but not current alcohol use, suggesting that a mechanism other than acute intoxication could be responsible. Further longitudinal research is warranted to explore mechanisms for why AUD, but not current alcohol use, is associated with falls.