Individual and poly-substance use and condomless sex among HIV-uninfected adults reporting heterosexual sex in a multi-site cohort

STTR was initiated by the National Institute on Drug Abuse and combines data from observational studies and trials intended to improve outcomes along the HIV care continuum for people involved in the criminal justice system and other vulnerable populations, many of whom have substance use disorders [36, 37]. Four US-based STTR studies contributed data to these analyses in order to enhance demographic, clinical, and geographic diversity. These were Brooklyn Community Action Project (BCAP, Brooklyn, NY); Baltimore-Rhode Island Get HIV Tested (BRIGHT, Baltimore, MD and Providence, RI); Seek, Test, and Retain (STAR, New York, NY); and Seek, Test, and Treat Strategies (STTS, Milwaukee County, WI). BRIGHT and STTS consisted of populations involved with the criminal justice system (probationers, parolees, and recent detainees about to be released); BCAP and STAR consisted of populations at high risk of HIV acquisition due to lifestyle factors (Table 1). We selected studies from the STTR consortium based on availability of illicit drug and alcohol use data, hereinafter referred to as substance use, and sexual risk behavior data. All participants ≥18 years of age who reported sexual activity were eligible for inclusion. Data were collected between 12/2011 and 06/2015.

BCAP and STAR used respondent-driven incentivized seed-based recruitment. BRIGHT and STTS used convenience sampling, with BRIGHT recruiting via flyers and posters within a community corrections office, and STTS by uniformly approaching all new detainees to invite participation. Data were collected either via structured self-administered computerized interview (BCAP, STTS) or by trained research interviewers (BRIGHT, STAR).

The STTR data repository integrates data from STTR studies, including clinical data such as standardized HIV-related information, as well as demographic, HIV transmission risk factors, and SU data obtained from enrollment interviews. All SU and CS variables focused on recent activity defined as the prior 1–3 months (timeframes were either 30 or 90 days). For studies including incarcerated participants, only non-incarcerated timeframes prior to incarceration were included. All studies used a variation of the AUDIT for alcohol use, with the exception of BCAP, which asked a single item querying frequency of alcohol use in the past 30 days. For drug use, all studies used variations of the ASSIST appropriate for individual study goals and population needs. SU was parameterized as a binary exposure (yes/no) and was defined as use of any of the following substances: binge alcohol (defined as ≥5 drinks per day for men and ≥ 4 for women), illicit opioids, cocaine/crack, methamphetamines/ stimulants, and other substances (e.g., hallucinogens, inhalants, barbiturates, synthetic drugs). An additional parameterization of illicit SU was also evaluated, which included the same drugs as above with the exception of binge alcohol use and cannabis (any alcohol use and/or cannabis use were included in the referent group). Participants were also asked about the timing of SU (before/during), sexual activity, and condom use over the recall period. Two overall SU exposure variables were created for analysis: 1) Any SU during the reference period, hereinafter referred to as recent substance use, and more specifically, 2) SU before or during sex. Main analyses did not include cannabis as our preliminary findings showed no association between cannabis and CS. We did, however, conduct sensitivity analyses including cannabis as an exposure. Each participant was categorized as either a non-user, a single-substance user, or a polysubstance user. SU before/during sex was included as a binary exposure (yes/no) from two of the included studies (Table 1). The outcome, engagement in any CS during the recall period, was harmonized across studies as a binary variable (yes/no).

All statistical analyses was performed in Stata version 14 [38].

We examined demographic characteristics (including age, gender, race/ethnicity, sexual orientation, and education) and HIV risk factors both overall and by SU category (Table 2). We used individual-study, multivariable relative risk regression with robust confidence intervals to examine the relationship between CS among single- and poly-substance users compared to non-users [39]. Final models included age, race/ethnicity, and gender. Pooled effect estimates were calculated using traditional fixed-effects meta-analysis because we did not believe naïve pooling was appropriate given the heterogeneity of the study populations [40]. Additional analyses stratified by type of sex (vaginal sex only or vaginal and anal sex, from all 4 studies) and by partner self-reported HIV status (HIV-negative partners only, HIV-status unknown partners only, or HIV-negative and HIV-status unknown partners; data available from BRIGHT and STAR only). We assessed interaction between type of sex and substance use category as well as partner(s)’ self-reported HIV status and substance use category, however, we were not specifically powered to detect statistical interaction. Sensitivity analyses including cannabis as a substance and by recall period (30 or 90 days) were also conducted.

We examined demographic and clinical characteristics by SU before/during sex. We used individual-study, multivariable relative risk regression with robust confidence intervals to examine the relationship between CS among PWUS before/during sex compared to those who did not. Final models included age, race/ethnicity, and gender. Again, pooled effect estimates were calculated using traditional fixed-effects meta-analysis [40]. Additional analyses of CS among PWUS before/during sex compared to those who did not were performed after stratifying by type of sex. We assessed interaction between type of sex and substance use before and during sex as well, with the same limitation as previously mentioned.

We performed a time-frame sensitivity analysis to assess the potential effect of heterogenous recall periods.

Of the 6781 sexually active participants in the pooled analyses, median age of participants was 33 years (interquartile range (IQR): 26–45), 82% were male, and the majority had a high school education or less (78%). Approximately half (52%) of the included participants reported substance use, with 19% reporting polysubstance use during the reference period (Table 2, see Supplement Table 1 for demographic differences broken down by study). PWUS differed on some demographic characteristics from non-users. Single- and poly-substance users, compared to non-users, reported more sexual partners on average and more often identified as something other than heterosexual, despite reporting heterosexual sex. Polysubstance users, compared to both non-users and single-substance users, were more likely to be male (90% vs. 80 and 82%, respectively), older (37 years vs. 32 and 34 years, respectively), and white (23% vs. 8 and 9%, respectively). The most commonly reported substances among single-substance users were binge alcohol (80%), followed by illicit opioids (8%), cocaine/crack (5%), and other substances (5%). The most commonly reported substances among polysubstance users were binge alcohol (75%), followed by cocaine/crack (63%), illicit opioids (58%), and other substances (41%).

In regression analyses adjusted for demographic variables, PWUS were significantly more likely to engage in CS compared to non-users. Single-substance users were 8% more likely (95% confidence interval (CI): 5–11%, p < 0.001) to report recent CS and polysubstance users 9% more likely (95% CI: 5–13%, p < 0.001) to engage in this sexual risk behavior. A comparison of polysubstance users to single-substance users found no significant difference in likelihood of engaging in CS (RR = 1.02, 95% CI: 0.99–1.05, p = 0.26) (Table 3). There was no significant interaction by age and SU (results not shown). We also performed this analysis with only illicit substance use as the exposure (binge alcohol use moved to referent group), and inference did not change (see Table 3). As individual substances, binge alcohol, cocaine/crack, and illicit opioid use were each associated with CS [p = .04 (95% CI:1.00–1.07), p = .02 (95% CI:1.01–1.08), and p = .006 (95% CI:1.02–1.09), respectively] (see Supplement Table 2).

Type of sex was associated with CS, with participants reporting vaginal and anal sex 21% more likely (95% CI: 16–26%) to engage in CS compared to those reporting vaginal sex only (p < 0.001). Among participants having only vaginal sex, use of any substances was associated with a higher likelihood of CS compared to non-users, with single-substance users 9% more likely (95% CI: 5–14%, p < 0.001) and polysubstance users 10% more likely (95% CI: 5–15%, p < 0.001) to report CS. Among participants having both vaginal and anal sex, substance use also increased the likelihood of CS compared to non-users, with single-substance users 5% more likely (95% CI: 2–9%, p = 0.004) and polysubstance users 8% more likely (95% CI: 4–12%, p < 0.001) to report CS (Table 3). There was no significant interaction between type of sex and substance use category (results not shown).

Partner(s’) self-reported HIV status was also associated with CS, with an 8% lower likelihood (95% CI: 2–14%, p = 0.01) of CS among participants reporting HIV-status unknown partners only compared to exclusively HIV-negative partners and a 11% higher likelihood (95% CI: 4–19%, p = 0.001) of CS among participants reporting both HIV-negative and HIV-status unknown partners compared to exclusively HIV-negative partners. Substance use was significantly associated with higher likelihood of CS among participants reporting exclusively HIV-negative partners and participants reporting both HIV-negative and HIV-status unknown partners, but not among participants reporting HIV-status unknown partners only. Use of any substances increased the likelihood of CS by 8% (95% CI: 2–13%, p = 0.004) for single-substance users and 7% (95% CI: 1–14%, p = 0.02) for polysubstance users compared to non-users among participants reporting exclusively HIV-negative partners. Use of any substances increased the likelihood of CS by 9% (95% CI: 1–18%, p = 0.03) for single-substance users and 13% (95% CI: 6–20%, p < 0.001) for polysubstance users compared to non-users among participants reporting HIV-negative and HIV-status unknown partners (Table 3). There was no significant interaction between partner(s)’ HIV status and substance use category (results not shown).

For individual study estimates and meta-analytic forest plots for all associations presented for recent substance use, see Supplemental Figures 1, 2, 3, 4, 5, 6, 7, 8 and 9.

Among participants (n = 2915) that had information on substance use before/during sex and CS during the reference period, median age was 40 (IQR: 28–49), 69% male, and most had high school education or less (77%). Just over half (52%) of the participants reported substance use before/during sex (Table 4, see Supplement Table 3 for demographics broken down by study). Similar to what we observed with recent PWUS, participants who used substances before/during sex reported more sexual partners on average and despite reporting heterosexual behavior more often identified as something other than heterosexual. Additionally, those who used substances before/during sex reported higher rates of use across all substance categories, had higher rates of injection drug use (6% vs. 1%), and tended to be male (84% vs. 54%) and Hispanic or Latino (47% vs. 33%). The most commonly reported substances used before/during sex were binge alcohol (65%), polysubstance use (57%), cocaine/crack (21%), and illicit opioids (18%).

In regression analyses adjusted for demographic variables, substance use before/during sex was significantly associated with CS, with a 16% increased likelihood (95% CI: 12–20%, p < 0.001) of CS compared to participants that did not use substances during sex (Table 5). The association between substance use during/before sex and CS did not change across age levels (results not shown). There was no significant interaction by age and substance use before/during sex (results not shown).

Again, type of sex was associated with CS, with an 18% higher likelihood (95% CI: 11–26%, p < 0.001) of CS among participants reporting vaginal and anal sex compared to vaginal sex only. Among participants having only vaginal sex, consumption of one or more substances during sex increased the likelihood of CS by 20% (95% CI: 12–29%, p < 0.001). Among participants having both vaginal and anal sex, consumption of one or more substances during sex increased the likelihood of CS by 7% (95% CI: 3–11%, p = 0.002) (Table 5). There was no significant interaction between type of sex and substance use before/during sex (results not shown).

For individual study estimates and meta-analytic forest plots for all associations presented for substance use before/during sex, see Supplemental Figures 10, 11, 12 and 13.

While the 30-day recall period showed stronger associations, overall inference and patterns were similar (see Supplement Tables 4 and 5).

Sensitivity analyses found that cannabis was not associated with CS when used in the absence of other substances (RR = 0.99, 95% CI: 0.94–1.04, p = 0.61) (Supplement Table 6). Additionally, even with increasing frequency of use, cannabis was not associated with engagement in CS (RR range = 1.00–1.05, p-value range: 0.24–0.92) (Supplement Table 7).

A strength of our study is its sample size and the demographic and geographic diversity of participants.

We note that study sites did not use uniform time frames in their measures. Additionally, because different studies used different instruments, collection of covariates differed by study and data were not necessarily available for all potential confounders. Because the data were cross-sectional, only associations and not causation could be determined. While we used CS as our outcome, we cannot infer any increased level of developing a STI. We note that because nuanced data was not available on partner serosorting, condom use behavior lacked context. We also note the possibility self-report bias in the areas of substance use, sexual behavior, and HIV negative serostatus. In addition, this paper focuses on condomless sex. However, clearly there are other approaches to address in order to reduce HIV/STI transmission, including the use of pre-exposure prophylaxis and needle exchange programs for injection drug use.