Howard Newville 1, James L. Sorensen 1, Donald A. Calsyn 2 1 University of California, San Francisco, San Francisco, CA 2 University of Washington, Seattle,

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Presentation transcript:

Howard Newville 1, James L. Sorensen 1, Donald A. Calsyn 2 1 University of California, San Francisco, San Francisco, CA 2 University of Washington, Seattle, WA Introduction Non-injection drug users (NIDUs) have similar HIV rates as injection drug users (IDUs) (Strathdee, 2003; Des Jarlais, 2010) 13% among IDUs and 12% among NIDUs in a drug treatment program study, 15% and 17% in a respondent-driven sampling (RDS) storefront study (Des Jarlais, 2007) The use of stimulants is associated with increased sex risk behavior (Plankey et al., 2007) HIV+ individuals are more likely to have sex under the influence of stimulants than HIV-negative individuals (Carey et al., 2009) Drug treatment lessens drug use and IDU risk, but its effects on sexual practices are unknown Sex risk behaviors are slower to change (Sorensen & Copeland, 2000) Many substance users in treatment continue to engage in sex risk behaviors (Farrell, Gowing, Marsden, Ling & Ali, 2005) Aims This secondary data analysis will assess the impact of drug treatment on HIV risk behaviors Hypothesis: decreases in drug and alcohol use at follow-up will coincide with decreases in sex risk behaviors Methods Setting and design NIDA Clinical Trials Network (CTN) study testing innovative risk reduction against standard education Participants recruited from 7 methadone maintenance (MMT) and 7 outpatient drug free (ODF) programs Diverse in terms of region, population density, and HIV prevalence rates Urban (e.g., Philadelphia), suburban (e.g., Norwalk, CT) and rural (e.g., Huntington, WV) Located in the Northeast, South, Midwest, Southwest, and West Measures Addiction Severity Index (ASI) Alcohol and drug composite scores Sexual Behavior Interview (SBI) (all behaviors – past 90 days) 1) % protected sex with main sex partner 2) % protected sex with a casual sex partner 3) Number of sex partners (0, 1, >1) 4) Having ≥1 high risk sex partner (“High risk” = IDU, crack/cocaine, or thought to be HIV+) 5) Any sex under the influence Figures Methods (continued) Participants Eligibility requirements: (1) men ≥18 years old, in substance abuse treatment, (2) reported unprotected intercourse (past 6 months) (3) willing to be randomly assigned to one of two interventions, (4) completed all study assessments, and (5) English speaking Exclusion criteria: (1) gross mental status impairment; (2) primary sexual partner intending to become pregnant Data analysis Severity of drug/alcohol use and frequency of risk behaviors calculated at baseline and six month follow-up Paired sample t-tests (for normal data) and Wilcoxon signed-rank tests (for non-normal data) to assess change over time Changes in drug/alcohol use severity by changes in risk behaviors assessed with multinomial logistic regression Due to non-normal distributions, risk behaviors were considered as increasing, decreasing, or stable Intervention sessions attended, treatment modality (MMT vs. ODF), and present engagement in drug treatment (0 vs vs. 30 days) added as covariates Results Bivariate analyses Drug use variables Alcohol CS (Mean [SD]) Baseline – 0.09 (0.15); Follow-up – 0.07 (0.12), p<0.001 Drug CS (Mean [SD]) Baseline – 0.19 (0.14); Follow-up – 0.15 (0.13), p<0.001 Risk variables % protected sex with a regular partner Baseline – 11.6%; Follow-up – 20.7%, p<0.001 % protected sex with a casual partner Baseline – 26.7%; Follow-up – 40.4%, p=0.038 Multiple sex partners Baseline – 40.1%; Follow-up – 26.5%; p<0.001 At least one high risk sex partner Baseline – 28.7%; Follow-up – 24.8%; p=0.302 Sex under the influence Baseline – 70.8%; Follow-up – 51.3%; p<0.001 Treatment engagement (past 30 days) 0 days – 115 (24.9%), 1-29 days – 161 (34.9%), 30 days – 122 (26.5%) Multivariate analyses % protected sex w/ regular partner, % protected sex w/ casual partner All individual items NS (Figures 1 & 3) Results (continued) Multivariate analyses (continued) Number of sex partners ASI alcohol: decreased for those whose number of partners decreased (OR [95% CI]: 8.40 [1.07, 66.67], p=0.043), increased for those whose number of partners increased (OR [95% CI]: [1.08, ], p=0.044) (Figures 1 & 3) Sex under the influence ASI drug: Those who discontinued SUI had greater decreases than those who had no SUI at either time (OR [95% CI]: [1.21, ], p=0.038) (Figures 2 & 4) At least one high risk sex partner ASI drug: Those who had high risk partners at both times had greater decreases than those without high risk partners at either time (OR [95% CI]: [3.91, 2,040.81], p=0.005) (Figures 2 & 4) Discussion Drug/alcohol use severity and most sex risk behaviors decreased for individuals in drug treatment Changes in drug/alcohol use severity associated with decreases in certain risk behaviors As drug treatment can decrease HIV seroconversion (Farrell et al., 2005), it is viable for risk reduction However, not all sex risk behaviors decrease with drug treatment alone, and further interventions within drug treatment are necessary Innovative risk reduction interventions can decrease risk (Calsyn et al., 2010) References Calsyn DA, Hatch-Maillette M, Tross S, et al. Motivational and Skills Training HIV/STI Sexual Risk Reduction Groups for Men. J Subst Abuse Treat September ; 37(2): 138–150. Carey JW, Mejia R, Bingham T, et al. Drug use, high-risk sex behaviors, and increased risk for recent HIV infection among men who have sex with men. AIDS Behav 2009; 13: Des Jarlais DC, Arasteh K, McKnight C, et al. Gender and age patterns in HSV-2 and HIV infection among non-injecting drug users in New York City. Sex Transm Dis 2010; 37:637– 643. Farrell M, Gowing L, Marsden J, Ling W, Ali R. Effectiveness of drug dependence treatment in HIV prevention. Int J Drug Policy 2005; 16S:S67–75. Plankey MW, Ostrow DG, Stall R, et al.. The relationship between methamphetamine and popper use and risk of HIV seroconversion in the multicenter AIDS cohort study. JAIDS 2007; 45: Sorensen JL, Copeland AL. Drug abuse treatment as an HIV prevention strategy: A review. Drug Alc Depend 2000; 59: Strathdee SA, Sherman SG. The role of sexual transmission of HIV infection among injection and non-injection drug users. J Urban Health 2003; 80(suppl 3):iii7–iii14. Relationship between substance abuse treatment outcome and sexual risk behaviors Figure 1 – ASI Alcohol, Condom Use, and Number of Partners Figure 3 – ASI Drug, Condom Use, and Number of Partners Figure 4 – ASI Drug, SUI, and High Risk Partners Funding information: Supported by the National Institute of Drug Abuse (F32 DA032446, U10 DA13714, U10 DA015815, and P50 DA09253) * * * Change in ASI Alcohol CS Figure 2 – ASI Alcohol, SUI, and High Risk Partners Change in ASI Alcohol CS Change in ASI Drug CS Frequency Status Funding information: Supported by the National Institute of Drug Abuse (F32 DA032446, U10 DA13714, U10 DA015815, and P50 DA09253)