Background: Sleep disturbances are prevalent in women living with HIV (WLWH) and can affect mental health and overall quality of life. We examined the prevalence and predictors of poor sleep quality in a US cohort of WLWH and HIV-uninfected controls and the relationship between sleep quality and mental health symptom burden stratified by HIV disease status (viremic WLWH, aviremic WLWH, and HIV-uninfected women). Methods: Sleep quality was assessed using the Pittsburgh Sleep Quality Index in 1583 (400 viremic WLWH, 723 aviremic WLWH, and 460 HIV-uninfected women) Women's Interagency HIV Study participants. Depressive and anxiety symptoms were concurrently assessed using the Center for Epidemiological Studies-Depression (CES-D) scale and General Anxiety Disorder (GAD-7) scale. Associations between poor sleep quality (global Pittsburgh Sleep Quality Index >5) and both high depressive (CES-D ≥16) and anxiety (GAD-7 ≥10) symptoms were each assessed by HIV disease status using multivariable logistic regression models. Results: Prevalence of poor sleep quality in the overall sample was 52%, differed by HIV disease status (P = 0.045), and was significantly associated with high depressive and anxiety symptoms in (1) viremic WLWH, (2) aviremic WLWH, and (3) HIV-uninfected women [CES-D: (1) adjusted odds ratio (aOR) = 7.50, 95% confidence interval (CI): 4.10 to 13.7; (2) aOR = 4.54, 95% CI: 3.07 to 6.73; and (3) aOR = 6.03, 95% CI: 3.50 to 10.4; GAD-7: (1) aOR = 5.20; 95% CI: 2.60 to 10.4, (2) aOR = 6.03; 95% CI: 3.67 to 9.91, and (3) aOR = 6.24; 95% CI: 3.11 to 12.6]. Conclusions: Poor sleep quality is highly prevalent, as is mental health symptom burden, among WLWH and HIV-uninfected controls. Future longitudinal studies are necessary to clarify the directionality of the relationship.

Background: Prior studies suggest neighborhood poverty and deprivation are associated with adverse health outcomes including death, but evidence is limited among persons with HIV, particularly women. We estimated changes in mortality risk from improvement in three measures of area-level socioeconomic context among participants of the Women’s Interagency HIV Study. Methods: Starting in October 2013, we linked geocoded residential census block groups to the 2015 Area Deprivation Index (ADI) and two 2012–2016 American Community Survey poverty variables, categorized into national tertiles. We used parametric g-computation to estimate, through March 2018, impacts on mortality of improving each income or poverty measure by one and two tertiles maximum versus no improvement. Results: Of 1596 women with HIV (median age 49), 91 (5.7%) were lost to follow-up and 83 (5.2%) died. Most women (62%) lived in a block group in the tertile with the highest proportions of individuals with income:poverty <1; 13% lived in areas in the tertile with the lowest proportions. Mortality risk differences comparing a one-tertile improvement (for those in the two highest poverty tertiles) in income:poverty <1 versus no improvement increased over time; the risk difference was −2.2% (95% confidence interval [CI] = −3.7, −0.64) at 4 years. Estimates from family income below poverty level (−1.0%; 95% CI = −2.7, 0.62) and ADI (−1.5%; 95% CI = −2.8, −0.21) exposures were similar. Conclusions: Consistent results from three distinct measures of area-level socioeconomic environment support the hypothesis that interventions to ameliorate neighborhood poverty or deprivation reduce mortality risk for US women with HIV. See video abstract at, http://links.lww.com/EDE/B863.

Background: Nearly a quarter of the 1.1 million individuals with HIV in the United States are women. Racial and ethnic minority women in the Southern United States are disproportionately impacted. Reproductive-age women with HIV are prone to poor HIV outcomes but remain underrepresented in HIV research. We will answer contemporary questions related to the health outcomes in this population by enrolling a prospective cohort of reproductive-age women with and without HIV in the Southern United States. Objective: The Study of Treatment and Reproductive Outcomes (STAR) will enroll and retain 2000 reproductive-age women with and without HIV. The STAR will leverage the infrastructure of the US-based Multicenter AIDS Cohort Study (MACS)/Women’s Interagency HIV Study (WIHS) Combined Cohort Study, comprising the WIHS (a cohort of women with and at risk for HIV, which began in 1993), and the MACS (a cohort of gay and bisexual men with and at risk for HIV, which began in 1984). Although the advancing age of the participants enrolled in the MACS/WIHS Combined Cohort Study provides an opportunity to address the questions related to HIV and aging, the research questions pertinent to the reproductive years must also be addressed. The STAR will conduct high-priority scientific research in key areas with the overall aim of addressing the unique needs of reproductive-age women with HIV. Methods: The STAR is a prospective, observational cohort study that will be conducted at 6 sites in the United States—Atlanta, Georgia; Birmingham, Alabama; Jackson, Mississippi; Chapel Hill, North Carolina; Miami, Florida; and Washington, District of Columbia. Visits will occur semiannually for 2 years, with additional visits for up to 5 years. At each visit, the participating women will complete a structured interview for collecting key demographic, psychosocial, and clinical variables, and undergo biospecimen collection for laboratory testing and repositing (blood, urine, hair, vaginal, anal, and oral specimens). Pregnant women and infants will undergo additional study assessments. The initial scientific focus of the STAR is to understand the roles of key social determinants of health, depression, reproductive health, and oral health on HIV and pregnancy outcomes across the reproductive life span. Results: Enrollment in the STAR commenced in February 2021 and is ongoing. Conclusions: Through in-depth, longitudinal data and biospecimen collection, the newly initiated STAR cohort will create a platform to answer scientific questions regarding reproductive-age women with and without HIV. STAR will be uniquely positioned to enable investigators to conduct high-impact research relevant to this population. Building on the legacy of the MACS and WIHS cohorts, the STAR is designed to foster multidisciplinary collaborations to galvanize scientific discoveries to improve the health of reproductive-age women with HIV and ameliorate the effects of the HIV epidemic in this population in the United States.

Neighborhood characteristics shape sexual risk in HIV-uninfected adults in the United States (US). We assess relationships between census tract characteristics and sexual risk behaviors in a predominantly HIV-infected cohort of women living in the Southern US. This cross-sectional multilevel analysis included data from 737 HIV-infected and HIV-uninfected women enrolled in the Women's Interagency HIV Study. Administrative data captured characteristics of census tracts where women lived; participant-level data were gathered via survey. We used principal components analysis to condense tract-level variables into components: social disorder (e.g., violent crime rate), and social disadvantage (e.g., alcohol outlet density). We used hierarchical generalized linear models to assess relationships between tract-level characteristics and condomless vaginal intercourse, anal intercourse, and condomless anal intercourse. Greater social disorder was associated with less anal intercourse (OR = 0.63, 95% CI = 0.43-0.94) and condomless anal intercourse (OR = 0.49, 95% CI = 0.30-0.80), regardless of HIV status. There were no statistically significant additive or multiplicative interactions between tract characteristics and HIV status. Neighborhood characteristics are associated with sexual risk behaviors among women living in the Southern US, these relationships do not vary by HIV status. Future studies should establish temporality and explore the causal pathways through which neighborhoods influence sexual risk.

Objectives: This study describes prevention behavior and psychosocial health among people living with HIV (PLHIV) and HIV-negative people during the early wave of the coronavirus disease 2019 (COVID-19) pandemic in the United States. We assessed differences by HIV status and associations between social disruption and psychosocial health. Design: A cross-sectional telephone/videoconference administered survey of 3411 PLHIV and HIV-negative participants in the Multicenter AIDS Cohort Study/WIHS Combined Cohort Study (MWCCS). Methods: An instrument combining new and validated measures was developed to assess COVID-19 prevention efforts, social disruptions (loss of employment, childcare, health insurance, and financial supports), experiences of abuse, and psychosocial health. Interviews were performed between April and June 2020. Associations between social disruptions and psychosocial health were explored using multivariable logistic regression, adjusting for sociodemographics and HIV status. Results: Almost all (97.4%) participants reported COVID-19 prevention behavior; 40.1% participants reported social disruptions, and 34.3% reported health care appointment disruption. Men living with HIV were more likely than HIV-negative men to experience social disruptions (40.6% vs. 32.9%; P < 0.01), whereas HIV-negative women were more likely than women with HIV to experience social disruptions (51.1% vs. 39.8%, P < 0.001). Participants who experienced ≥2 social disruptions had significantly higher odds of depression symptoms [aOR = 1.32; 95% confidence interval (CI): 1.12 to 1.56], anxiety (aOR = 1.63; 95% CI: 1.17 to 2.27), and social support dissatisfaction (aOR = 1.81; 95% CI: 1.26 to 2.60). Conclusions: This study builds on emerging literature demonstrating the psychosocial health impact related to the COVID-19 pandemic by providing context specific to PLHIV. The ongoing pandemic requires structural and social interventions to decrease social disruption and address psychosocial health needs among the most vulnerable populations.

Causal inference methods can be applied to estimate the effect of a point exposure or treatment on an outcome of interest using data from observational studies. For example, in the Women’s Interagency HIV Study, it is of interest to understand the effects of incarceration on the number of sexual partners and the number of cigarettes smoked after incarceration. In settings like this where the outcome is a count, the estimand is often the causal mean ratio, that is, the ratio of the counterfactual mean count under exposure to the counterfactual mean count under no exposure. This paper considers estimators of the causal mean ratio based on inverse probability of treatment weights, the parametric g-formula, and doubly robust estimation, each of which can account for overdispersion, zero-inflation, and heaping in the measured outcome. Methods are compared in simulations and are applied to data from the Women’s Interagency HIV Study.