Abstract
The aim of this study was to investigate the effects of transitioning from non-injection heroin use to injection drug use on sexual risk behavior. Non-injecting heroin users age 16–30 were enrolled from 2002 to 2005, and were re-interviewed at six-month intervals for up to three years; 561 participants completed at least one follow-up interview. The majority of participants were non-Hispanic (NH) Black (54%), 23% were Hispanic, and 21% were NH white. During follow-up, 154 participants (27.5%) transitioned to injecting drugs. Logistic regression analyses were conducted using generalized estimating equations (GEE) to estimate the effect of transition to injection drug use on changes in sexual risk behavior during follow-up. Transition to injection drug use during follow-up was associated with increased likelihood of sexual risk behavior, especially for men. Harm reduction efforts that focus on preventing initiation or return to injection among non-injecting drug users may also ameliorate HIV sexual risk behaviors.
Keywords: injection drug use, non-injecting, heroin, sexual risk behavior, HIV risk
Introduction
Within the last decade there has been increased attention on sexual risk factors for human immunodeficiency virus (HIV) and, to a lesser extent, hepatitis C (HCV) infections among injection drug users (IDUs). Interventions to combat HIV by targeting injection-related risks in this population--including behavioral interventions, syringe exchange programs, and access to syringes in pharmacies--have led to a substantial decline in HIV incidence in this population (1). Recent studies, however, have highlighted the HIV and HCV risks associated with sexual behavior among male and female IDUs (2–8). For HCV, although the extent of sexual transmission is still being debated, even a low rate of transmission can account for a large number of cases given the high prevalence of this infection (an estimated 4.1million U.S. residents) (9). Injection drug users frequently engage in risky sexual behaviors that increase their susceptibility to infection with HIV, HCV, and sexually transmitted-infections (STIs) through sex with multiple partners, sex without condoms, and exchanging sex for money or drugs, and increase the likelihood of transmitting these viral and bacterial infections to their partners.
In particular, men who have sex with men who also inject drugs are at increased risk for HIV infection (7, 10–12). For women who inject drugs, HIV infection has been associated with having a STI (11, 12), having a male sex partner who is an IDU (10, 11), and exchanging sex for money (12). Female IDUs are more likely than male IDUs to have sexual relationships with partners who inject drugs, and these relationships are often with older men who have a greater likelihood of being HCV-infected (13).
Transition to a parenteral route of drug administration from oral or nasal routes greatly increases the potential for acquisition and transmission of HIV and other bloodborne infections because of the efficiency of injection as a mode of HIV transmission. Factors that are associated with transition to injection drug use have been examined in prior studies (14–22), some of which explored sexual risk issues. For example, results from a prospective study of adolescent and young adult drug users in Baltimore indicate that non-blacks (primarily White) were more likely to transition to injecting drugs, and sex trading was associated with transitioning to drug injection for young women (14). Similarly, among aboriginal peoples in Western Canada, sex work was found to be associated with transitioning from non-injection to injection drug use (15). These studies suggest sex trading may precede or, at a minimum, be associated with initiating injection drug use. However, one question that has not been adequately addressed is whether the transition from non-injection drug use to injection drug use is associated with an increase in risky sexual behaviors. That is, does sexual risk behavior increase concurrently with the transition to injection, or does sexual risk behavior precede the transition to injection? In this paper, we use longitudinal data from a sample of young non-injection heroin users to examine the association between transitioning to injecting drugs and increase in sexual risk behaviors.
Methods
Sample recruitment and study procedures
Data for this study come from the Non-Injecting Heroin Use, HIV, and Injection Transitions Study (NIHU-HIT), a prospective study that used an open cohort design with continuous sampling to investigate the incidence and risk factors for transitions to drug injection and the prevalence, incidence, and risk factors for infection with HIV, HBV, and HCV among young NIHU recruited in community-based settings. All participants provided written consent. The University of Illinois at Chicago Institutional Review Board approved the study procedures. Additional study details are described elsewhere (23).
Participants were recruited between June 2002 and January 2005 using a combination of street outreach and coupon-based chain-referral methods. Eligible participants were 16–30 years old, current NIHU, and English or Spanish speakers. Former injection drug users (IDUs) were eligible if they had not injected in the 6 months prior to the baseline interview. Outreach staff recruited potential participants in Chicago neighborhoods with a high prevalence of illicit drug use and drug markets. For the final 6 months, recruitment was restricted to NIHU 16–23 years old to augment the sample size for this group. Each participant was given 3–6 recruitment coupons to pass to peers and compensated $15 for each person who met the eligibility requirements. Potential participants were given an option to enroll in a concurrent study of 15–30 year old IDUs (24), thus minimizing the need to misrepresent their mode of drug use for the purpose of enrolling in this study. Current heroin use (past 3–5 days) was validated using a urine test for opiate metabolites (Biotechnostix, Canada) and project staff examined participants arms and other visible body parts for recent injection marks. Those with fresh marks or who indicated during any of the study interviews that they injected in the 6 months prior to enrollment were excluded from the study.
All participants were offered pre- and post-test counseling and testing for antibodies to HIV and hepatitis C, and for prior or current hepatitis B infection. Those who tested positive were informed of treatment options and referred for medical, substance abuse and other social services. Those who tested HBV negative were referred for HBV vaccination.
Follow-up data collection was scheduled at 6-month intervals for up to 3 years between December 2002 and August 2006. At each visit, participants completed a 1–2 hour audio-computer-assisted self-interview (ACASI) in a private room. Participants were compensated $30 at baseline and $35 at follow-up. Of the total sample (N=689), we restricted our analysis to those with at least one follow-up interview (N=561, male=352, female=209) for both the baseline and longitudinal analyses. Previous analyses of loss to follow-up (25) indicated that Non-Hispanic (NH) Whites, males, and those who reported an illegal source of income in the 6 months prior to baseline interview were less likely to complete at least one follow-up interview and contributed fewer mean days to follow-up. Additional chi-square and mean analyses were computed to assess associations of loss to follow-up with baseline sexual risk behavior and injection history. Participants with a history of injection completed fewer interviews and contributed fewer mean days to follow-up; participants who reported a sex partner who injected drugs also completed fewer follow-up interviews. Other sexual risk behaviors did not have significant associations with loss to follow-up.
Measures
Participants provided information on socio-demographic characteristics, current and past drug use, and sexual activity.
Socio-demographics
Age was measured as a continuous variable. Race/ethnicity categories were non-Hispanic Black, non-Hispanic White, Hispanic, and other race/ethnicity. Due to the small number of other race/ethnicity (n = 10), this category was combined with Hispanic. High school graduation was used as an indicator of education. Homelessness during the past six months was measured by the questions, “Right now, do you consider yourself homeless,” and “Was there a time during the last 6 months when you considered yourself homeless?”
Heavy alcohol use
As a measure of heavy alcohol use, participants were asked, “Out of the last 30 days, on how many days did you have 5 or more drinks?”
Injection and non-injection drug use
Former drug injection was determined by asking participants, “Have you ever injected drugs, even if you only did it once?” At baseline, non-injection drug use was reported for the past six months, and at each follow-up visit participants were asked about substances used since the last interview, including injection and non-injection use. Substances included alcohol, marijuana, powdered cocaine, rock cocaine (crack), heroin alone, heroin and cocaine together (speedball), Ritalin, heroin and Ritalin mixed together, prescription opiates, amphetamines, Ecstasy (MDMA), tranquilizers or barbiturates, nitrous oxide, other inhalants, PCP, LSD and other hallucinogens, GHB or ketamine, and marijuana with cocaine. Participants were asked their age of first use, and their frequency of use (months, days per month, and times per day) in the past six months for each substance. In the follow-up interviews participants were asked separately about their injection and non-injection use of each substance. Injection drugs included speedball, heroin by itself, cocaine by itself, crystal methadrine, and “any other drug.”
Sexual activity
Participants were asked if they currently had a main sex partner, or if they had had one in the last six months. If they did, they were asked a series of questions about that partner and their sexual activities with that partner, including 1) whether they had vaginal sex in the last six months, 2) how often a condom was used during vaginal sex (7-point scale, 1=all the time to 7=never), 3) whether they had anal sex in the last six months, 4) how often a condom was used during anal sex, 5) whether the partner had ever injected drugs, and 6) whether the partner had injected drugs in the past 6 months. For male participants with male partners, separate questions were asked about receptive and insertive anal sex.
Participants were then asked for the number of (other) people they had sexual contact with during the last six months. If they had other partners, they were asked questions about their sexual activities with those partners, including whether they had had vaginal sex and anal sex, how often a condom was used during vaginal sex and during anal sex, and whether any of the partners had ever injected or currently injected drugs.
Participants were asked how often in the past six months they had given someone sex for money, heroin, other drugs, and shelter, food, or clothing, and they were asked how often they had used a condom during these exchanges.
Binary indicators were created for past six month behaviors: 1) any unprotected vaginal or anal sex, 2) unprotected vaginal or anal sex with main partner, 3) unprotected vaginal or anal sex with non-main partner, 4) anal sex with any partner, 5) unprotected anal sex with any partner, 6) male unprotected anal sex with a male partner, 7) providing sex in exchange for money, drugs, shelter, food or clothing (trading sex), 8) unprotected trade sex, 9) giving someone money, drugs, etc. in exchange for sex (buying sex), 10) sex with a partner who ever injected drugs, and 11) sex with a current injection drug user.
Analyses
Baseline analysis
We conducted logistic regression analyses on baseline sexual risk behaviors to examine differences between participants who transitioned to injection during the study period and those who did not. Analyses were stratified by gender, and age, race/ethnicity, education, homelessness, and baseline injection history were included as covariates.
Longitudinal analysis
We conducted logistic regression analyses using generalized estimating equations (GEE), regressing sexual risk outcomes on injection drug use, adjusting for baseline injection history, sociodemographic variables, days of heavy drinking, and the lagged effect of injection drug use. The lagged value of the sexual risk outcome was also included. Lagged variables were the past 6-months behaviors reported in the previous (or last available) reporting period. By adjusting for previous sexual behavior, we obtain the effects of current and prior injection on change in sexual risk behavior. Analyses were conducted in Stata 11 using the -xtlogit- procedure, with the population-averaged model option and the Huber-White Sandwich estimate of standard errors, adjusting for clustering within subject. Analyses were repeated with the addition of non-injection drug use variables in a step-wise manner.
Results
Sample
Baseline sociodemographic characteristics of the sample are shown on Table 1. Fourteen percent (n = 78) of the baseline sample reported a prior history of injection drug use. During follow-up, 154 participants (27.5%) transitioned to injecting drugs. Of these, 42 (27%) had a prior history of injection drug use.
Table 1.
Baseline sociodemographic characteristics (N = 561)
| Frequency | Proportion | |
|---|---|---|
| Sex | ||
| Male | 352 | 62.7 |
| Female | 209 | 37.3 |
| Age (years) | ||
| 16–20 | 116 | 20.7 |
| 21–25 | 168 | 29.9 |
| 26–30 | 277 | 49.4 |
| Mean (sd), Median | 24.8 (4.1), 25 | |
| Race/Ethnicity | ||
| NH Black | 305 | 54.4 |
| NH White | 117 | 20.9 |
| Hispanic | 129 | 23.0 |
| Other | 10 | 1.8 |
| High school graduate | ||
| Not applicable (<18 yrs) | 15 | 2.7 |
| No | 325 | 57.9 |
| Yes | 221 | 39.4 |
| Cohabitation | ||
| No | 408 | 72.7 |
| Yes | 153 | 27.3 |
| Homeless past 6 months | ||
| No | 455 | 81.1 |
| Yes | 106 | 18.9 |
| Resided outside of Chicago a (past 6 months) | ||
| Yes | 157 | 28.0 |
| No | 404 | 72.0 |
| Ever injected drugs | ||
| Yes | 78 | 14.0 |
| No | 481 | 86.0 |
Primarily Chicago metropolitan area; 4 lived in other cities in Illinois.
Baseline sexual behavior
Prevalence rates of sexual risk behaviors in the last six months prior to baseline, and adjusted odds ratios for associations with injection during follow-up are reported on Table 2. Baseline sexual risk behaviors were significantly associated with cohabitation, race/ethnicity, education, and homelessness (not shown). Most unprotected sex occurred in the context of main partner relationships, and men and women who were cohabiting were more likely to engage in unprotected sex with a main partner (men: AOR=5.43, 95% CI 2.63–11.21; women: AOR=1.98, 95% CI 0.95–4.12). White women were more likely than Black women to report unprotected sex with a main partner (AOR=3.99, 95% CI 1.22–13.01), and were more likely than Black women to have a sex partner who ever injected drugs (AOR = 5.18, 95% CI 1.09–24.64).
Table 2.
Baseline sexual risk behaviors among young non-injecting heroin users and associations with injection drug use during follow-up
| Past six months: | Males | Females | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| N | % | AORa | 95% | Conf. Int. | N | % | AORa | 95% | Conf. Int. | |
| Any unprotected sexb | 330 | 73% | 1.38 | 0.76 | 2.49 | 199 | 73% | 1.34 | 0.54 | 3.3 |
| Unprotected sexb with main partner | 331 | 65% | 1.43 | 0.81 | 2.53 | 199 | 66% | 1.38 | 0.59 | 3.23 |
| Unprotected sexb with other partner | 333 | 23% | 1.91 | 0.99 | 3.67 | 201 | 19% | 2.07 | 0.85 | 5.03 |
| Any anal sex | 333 | 38% | 1.65 | 0.96 | 2.84 | 195 | 29% | 0.90 | 0.39 | 2.09 |
| Unprotected anal sex | 331 | 33% | 1.67 | 0.96 | 2.91 | 196 | 27% | 1.04 | 0.45 | 2.38 |
| Traded sex for money, drugs, other | 346 | 10% | 3.66 | 1.50 | 8.96 | 202 | 20% | 2.35 | 0.74 | 7.44 |
| Traded sex, unprotected | 335 | 5% | 6.68 | 2.04 | 21.87 | 185 | 8% | 0.79 | 0.16 | 3.97 |
| Bought sex | 348 | 8% | 2.00 | 0.83 | 4.80 | 205 | 6% | 1.39 | 0.32 | 6.00 |
| Current IDU sex partner | 343 | 3% | 16.01 | 3.25 | 78.87 | 204 | 5% | 1.26 | 0.39 | 4.07 |
| Ever IDU sex partner | 344 | 5% | 4.05 | 1.24 | 13.28 | 204 | 8% | 2.68 | 0.91 | 7.91 |
| More than 1 sex partner | 338 | 41% | 1.45 | 0.84 | 2.48 | 203 | 39% | 0.92 | 0.44 | 1.93 |
| MSM anal sex | 352 | 3% | 0.14 | 0.02 | 0.92 | Not applicable | ||||
odds ratio for injection drug use during follow-up, adjusted for age, race, education, cohabitation, homelessness, and prior injection drug use
vaginal or anal intercourse
Unprotected sex with a non-main partner was more likely among homeless men (AOR=2.07, 95% CI 1.07–4.00), and less likely among White men than Black men (AOR=0.37, 95% CI 0.16–0.84). Homeless men were also more likely to report trading sex for money, drugs, or goods (AOR=3.40, 95% CI 1.39–8.35), and more likely to report buying sex as well (AOR=4.29, 95% CI 1.65–11.17). White men were less likely than Black men to trade sex (AOR=0.13, 95% CI 0.03–0.56), to have unprotected trade sex (AOR=0.07, 95% CI 0.01–0.53), to have anal sex (AOR=0.31, 95% CI 0.15–0.65), and unprotected anal sex (AOR=0.42, 95% CI 0.20 – 0.88), and to have more than one sex partner (AOR=0.49, 95% CI 0.25–0.98).
Black women were more likely to report trading sex compared to non-Black women (AOR = 13.65, 95% CI 2.39 – 78.13). Among women, trading sex increased with age (AOR = 1.18, 95% CI 1.05–1.32) and was less likely among high school graduates (AOR 0.40, 95% CI 0.17–0.91). Unprotected trade sex and buying sex were reported only by Black women. Women who were cohabiting were less likely to have more than one sex partner (AOR = 0.42, 95% CI 0.21–0.84), and more likely to have anal sex (AOR = 2.61, 95% CI 1.31 – 5.22) and unprotected anal sex (AOR = 2.34, 95% CI 1.17 – 4.68).
Among men, transition to injection during the follow-up period was associated with baseline sexual behaviors (see Table 2), including trading sex (p = .004), unprotected trade sex (p = .002), and having an IDU sex partner (p = .001). Among women, transition to injection during the follow-up period was not significantly associated with baseline sexual risk behavior.
Longitudinal analysis
Tables 3 and 4 present the adjusted odds ratios for the effect of injection on change in sexual risk behaviors during follow-up for men and women, and the predicted probabilities of sexual risk behaviors by injection drug use. Due to the low prevalence of trading sex among White and Hispanic men, and zero prevalence of sex trading reported by White women, it was necessary to combine race/ethnicity categories in those analyses so that non-Hispanic Black race/ethnicity was contrasted with all others.
Table 3.
Estimated effect of injection drug use on sexual risk behaviors during 36-month follow-up period (GEE), Male Participants
| N | AORb | 95% CI | Pr(y|x=0)c | Pr(y|x=1)d | |
|---|---|---|---|---|---|
| Any unprotected sexa | 330 | 2.07 | (1.23–3.48) | 0.592 | 0.721 |
| Unprotected sexa with main partner | 331 | 1.30 | (0.81–2.10) | 0.501 | 0.555 |
| Unprotected sexa with non-main partner | 332 | 3.12 | (1.89–5.13) | 0.145 | 0.328 |
| Any anal sex | 327 | 2.25 | (1.31–3.85) | 0.184 | 0.313 |
| Unprotected anal sex | 329 | 2.60 | (1.47–4.61) | 0.149 | 0.291 |
| Traded/sold sex for money, drugs, goods | 341 | 5.90 | (2.66–13.10) | 0.028 | 0.128 |
| Traded/sold sex, unprotected † | 332 | 14.04 | (2.09–94.38) | 0.003 | 0.041 |
| Bought sex | 344 | 4.13 | (1.80–9.48) | 0.037 | 0.122 |
| Current IDU sex partner | 338 | 11.41 | (5.30–24.56) | 0.016 | 0.117 |
| Ever IDU sex partner | 339 | 5.50 | (2.55–11.86) | 0.046 | 0.153 |
| More than 1 sex partner | 342 | 1.40 | (0.92–2.11) | 0.270 | 0.336 |
| MSM anal sex | 345 | 0.96 | (0.10–9.04) | 0.027 | 0.026 |
vaginal or anal intercourse
adjusted for age, cohabitation, race/ethnicity, education, homelessness, heavy drinking, and lagged effects of injection and sexual risk outcome
Predicted probability of outcome when injection = “no”
Predicted probability of outcome when injection = “yes”
significant lagged effect of injection drug use (p<.001)
Table 4.
Estimated effect of injection drug use on sexual risk behaviors during 36-month follow-up period (GEE), Female Participants
| N | AORb | 95% CI | Pr(y|x=0)c | Pr(y|x=1)d | |
|---|---|---|---|---|---|
| Any unprotected sexa | 199 | 1.25 | (0.62–2.53) | 0.667 | 0.705 |
| Unprotected sexa with main partner | 202 | 1.36 | (0.71–2.63) | 0.594 | 0.650 |
| Unprotected sexa with non-main partner | 199 | 1.62 | (0.69–3.82) | 0.154 | 0.221 |
| Any anal sex | 203 | 1.10 | (0.54–2.27) | 0.163 | 0.174 |
| Unprotected anal sex | 203 | 0.90 | (0.40–2.00) | 0.153 | 0.142 |
| Traded/sold sex for money, drugs, goods | 203 | 2.95 | (1.31–6.67) | 0.111 | 0.247 |
| Traded/sold sex, unprotected | 191 | 0.78 | (0.12–5.13) | 0.019 | 0.015 |
| Bought sex | 205 | 1.88 | (0.56–6.28) | 0.050 | 0.089 |
| Current IDU sex partner | 204 | 19.95 | (7.67–51.91) | 0.031 | 0.272 |
| Ever IDU sex partner | 204 | 9.12 | (3.68–22.56) | 0.080 | 0.276 |
| More than 1 sex partner | 206 | 1.40 | (0.76–2.56) | 0.281 | 0.349 |
vaginal or anal intercourse
adjusted for age, cohabitation, race/ethnicity, education, homelessness, heavy drinking, and lagged effects of injection and sexual risk outcome
Predicted probability of outcome when injection = “no”
Predicted probability of outcome when injection = “yes”
Among men, injection drug use during the follow-up period was associated with increased likelihood of any unprotected vaginal or anal sex (p = .006), unprotected sex with non-main partners (p < .001), any anal sex (p = .004), unprotected anal sex (p = .001), trading sex (p < .001), buying sex (p = .001), and having an IDU sex partner (ever or current. p < .001). Among women, injection during follow-up was associated with increased likelihood of trading sex (p = .025), and having an IDU sex partner (ever or current, p < .001). In all models, the lagged effect of the sexual risk outcome variable was significant (p<.02). The lagged effect of injection drug use was significant only for unprotected trade sex among men (p<.001). The addition of non-injection drug use variables, including crack cocaine, did not have a substantive effect on the estimates for injection drug use (data not shown).
Additional analyses (not shown) were conducted to explore race/ethnicity differences for significant effects. A marginal interaction between injection and race/ethnicity was found for men on unprotected sex with a non-main partner (p = .07) such that the effect of injection was greatest for Hispanic men (OR = 7.79, 95% CI 3.29–18.48). Since trading sex was not reported by any White women we repeated the analysis for non-White women only; the effect of injection on trading sex was significant for non-White women (AOR = 2.27, 95% CI 1.03–5.01). Other outcomes did not vary by race/ethnicity.
Discussion
Transition to injection drug use was associated concurrently with increased likelihood of several risky sexual behaviors. In all the analyses, sexual behavior during the previous reporting period predicted current sexual behavior, while prior injection drug use (the lagged effect) for the most part did not predict changes in sexual behavior.
Among male non-injecting heroin users, trading sex, unprotected trade sex, and having an IDU sex partner at baseline were significantly associated with later injection. There were also borderline effects for unprotected sex with a non-main partner (p = .053), anal sex (p = .072), and unprotected anal sex (p = .069). During follow-up, transition to injection was associated with increased likelihood of unprotected sex with a non-main partner, anal sex and unprotected anal sex, and buying sex, as well as trading sex, unprotected trade sex, and having an IDU sex partner. The results suggest that the relationship between injecting and risky sexual behavior among young men who use heroin is such that men who engage in risky sexual behaviors (especially trading sex) are more likely to initiate or resume injecting, and that transitions from non-injection to injection drug use are also associated with an increased likelihood of risky sexual behavior. With the exception of having an IDU sex partner, the longitudinal associations were stronger than the baseline associations. Men who began injecting drugs were at increased risk for HIV through unprotected sex, including anal sex and trading sex, and through their partnerships with IDU sex partners.
Among female non-injecting heroin users, baseline sexual risk behaviors were not associated with later injection. During follow-up, transition to injection was associated with increased likelihood having an IDU sex partner. Transition to injection, for women, was not associated with unprotected sex. However, because unprotected sex with a main partner is the norm, having an IDU sex partner is likely to increase sexual risk. Injection drug use during follow-up was associated with increased likelihood of trading sex among minority women. Most minority women in the study resided in low-income urban neighborhoods with elevated levels of poverty and unemployment, and where sex work often was visible. In contrast, the majority of NH-White participants lived either in the suburbs or urban neighborhoods not marked by high rates of poverty and where visible sex work was rare.
For women who inject drugs, HIV risk is largely connected to sexual relationships with men who inject drugs; female IDUs who are sex partners of male IDUs are at dual risk for HIV infection through both injection and sexual risk. Although minority women were less likely than White women to transition from non-injection to injection heroin use (25), those who did tended to increasingly engage in high-risk sexual behavior.
The question of why sexual risk behavior increases among heroin users who transition to injection, particularly males, is not addressed in this study, and requires further research. One direction we would like to suggest, is to look at how the social networks of drug users change as they transition from non-injection to injection drug use.
Limitations
As with most studies of drug users, our sample is not necessarily representative of the population, in this case non-injecting heroin users. However, using multiple methods of recruitment increases the variability of the sample, and our sample is demographically mixed.
For low-prevalence outcomes, some cell sizes were small, resulting in wide confidence intervals for some estimates. This is particularly problematic when looking at race/ethnicity effects.
Although socially desirable responding regarding sexual and injection behaviors is probable, the use of computerized self-interviews instead of a face-to-face interview has been shown to minimize this occurrence (26, 27). The extent to which our findings are generalizable to other young NIHU is unknown. However, our use of multiple recruiting methods and the relatively large sample size augment confidence that our findings may be applicable to other young NIHUs.
Conclusion
Harm reduction efforts that focus on preventing initiation or return to injection among non-injecting drug users may also ameliorate HIV sexual risk behaviors. Moreover, interventions targeting young, recent onset IDUs for the prevention of HIV, HCV and STIs should address both injection and sexual risk behaviors at the individual level and the overlapping injection and sexual relationships within social networks. Such programs need to incorporate strategies that account for differences among men and women, as well as variations in risk contexts experienced by different racial or ethnic groups.
Acknowledgments
This study was supported by a grant from the National Institute on Drug Abuse #R01DA012068. The authors thank Maggie Parker for data analysis, the study participants for the time and effort they contributed to this study, and the project staff who administered the coupon referral system, collected data, and otherwise operated field sites in a manner welcoming to potential participants. We also wish to recognize the following people for their contributions to the development and/or implementation of the Chicago NIHU-HIT study: Angus Atkins-Trimnell, James Crues, David Cosey, Jaime Delgado, Julio Garcia, Michelle Giles, Erin Kubalanza, Floyd McGee, and Michael Phillips.
References
- 1.Santibanez S, Garfein R, Swartzendruber A, Purcell D, Paxton L, Greenberg A. Update and overview of practical epidemiologic aspects of HIV/AIDS among injection drug users in the United States. J Urban Health. 2006;83(1):86–100. doi: 10.1007/s11524-005-9009-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Booth RE, Kwiatkowski CF, Chitwood DD. Sex related HIV risk behaviors: Differential risks among injection drug users, crack smokers, and injection drug users who smoke crack. Drug Alcohol Depend. 2000;58(3):219–26. doi: 10.1016/s0376-8716(99)00094-0. [DOI] [PubMed] [Google Scholar]
- 3.Huo D, Ouellet LJ. Needle exchange and sexual risk behaviors among a cohort of injection drug users in Chicago, Illinois. Sex Transm Dis. 2009;36(1):35–40. doi: 10.1097/OLQ.0b013e318186dee3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kapadia F, Latka MH, Wu Y, Strathdee SA, Mackesy-Amiti ME, Hudson SM, et al. Longitudinal determinants of consistent condom use by partner type among young injection drug users: The role of personal and partner characteristics. AIDS Behav. 2011;15(7):1309–18. doi: 10.1007/s10461-009-9569-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Hagan H, Perlman DC, Des Jarlais DC. Sexual risk and HIV infection among drug users in New York City: A pilot study. Subst Use Misuse. 2011;46(2/3):201–7. doi: 10.3109/10826084.2011.521470. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Arasteh K, Des Jarlais DC, Perlis TE. Alcohol and HIV sexual risk behaviors among injection drug users. Drug Alcohol Depend. 2008;95(1–2):54–61. doi: 10.1016/j.drugalcdep.2007.12.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Neaigus A, Gyarmathy VA, Miller M, Frajzyngier V, Zhao M, Friedman SR, et al. Injecting and sexual risk correlates of HBV and HCV seroprevalence among new drug injectors. Drug Alcohol Depend. 2007;89(2–3):234–43. doi: 10.1016/j.drugalcdep.2007.01.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Des Jarlais DC, Arasteh K, McKnight C, Hagan H, Perlman DC, Semaan S. Associations between herpes simplex virus type 2 and HCV with HIV among injecting drug users in New York City: The current importance of sexual transmission of HIV. Am J Public Health. 2011;101(7):1277–83. doi: 10.2105/AJPH.2011.300130. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Armstrong GL, Wasley A, Simard EP, McQuillan GM, Kuhnert WL, Alter MJ. The prevalence of hepatitis C virus infection in the United States, 1999 through 2002. Ann Intern Med. 2006;144(10):705–14. doi: 10.7326/0003-4819-144-10-200605160-00004. [DOI] [PubMed] [Google Scholar]
- 10.Strathdee SA, Galai N, Safaiean M, Celentano DD, Vlahov D, Johnson L, et al. Sex differences in risk factors for HIV seroconversion among injection drug users: A 10-Year perspective. Arch Intern Med. 2001;161(10):1281–8. doi: 10.1001/archinte.161.10.1281. [DOI] [PubMed] [Google Scholar]
- 11.Strathdee SA. Sexual HIV transmission in the context of injection drug use: implications for interventions. Int J Drug Policy. 2003;14(1):79–81. [Google Scholar]
- 12.Kral AH, Bluthenthal RN, Lorvick J, Gee L, Bacchetti P, Edlin BR. Sexual transmission of HIV-1 among injection drug users in San Francisco, USA: Risk-factor analysis. Lancet. 2001;357(9266):1397–401. doi: 10.1016/S0140-6736(00)04562-1. [DOI] [PubMed] [Google Scholar]
- 13.Evans JL, Hahn JA, Page-Shafer K, Lum PJ, Stein ES, Davidson PJ, et al. Gender differences in sexual and injection risk behavior among active young injection drug users in San Francisco (the UFO Study) J Urban Health. 2003;80(1):137–46. doi: 10.1093/jurban/jtg137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Fuller CM, Vlahov D, Ompad DC, Shah N, Arria A, Strathdee SA. High-risk behaviors associated with transition from illicit non-injection to injection drug use among adolescent and young adult drug users: a case-control study. Drug Alcohol Depend. 2002;66(2):189–98. doi: 10.1016/s0376-8716(01)00200-9. [DOI] [PubMed] [Google Scholar]
- 15.Miller CL, Pearce ME, Moniruzzaman A, Thomas V, Christian W, Schechter MT, et al. The Cedar Project: Risk factors for transition to injection drug use among young, urban Aboriginal people. Can Med Assoc J. 2011;183(10):1147–54. doi: 10.1503/cmaj.101257. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Griffiths P, Gossop M, Powis B, Strang J. Transitions in patterns of heroin administration: A study of heroin chasers and heroin injectors. Addiction. 1994;89(3):301–9. doi: 10.1111/j.1360-0443.1994.tb00896.x. [DOI] [PubMed] [Google Scholar]
- 17.Grund J-PC. From the straw to the needle? Determinants of heroin administration routes. In: Inciardi JA, Harrison LD, editors. Heroin in the Age of Crack Cocaine. Thousand Oaks, CA: Sage; 1998. pp. 215–58. [Google Scholar]
- 18.Neaigus A, Miller M, Friedman SR, Hagen DL, Sifaneck SJ, Ildefonso G, et al. Potential risk factors for the transition to injecting among non-injecting heroin users: A comparison of former injectors and never injectors. Addiction. 2001;96(6):847–60. doi: 10.1046/j.1360-0443.2001.9668476.x. [DOI] [PubMed] [Google Scholar]
- 19.Neaigus A, Gyarmathy VA, Miller M, Frajzyngier VM, Friedman SR, Des Jarlais DC. Transitions to injecting drug use among noninjecting heroin users: Social network influence and individual susceptibility. J Acquir Immune Defic Syndr. 2006;41(4):493–503. doi: 10.1097/01.qai.0000186391.49205.3b. [DOI] [PubMed] [Google Scholar]
- 20.Roy É, Haley N, Leclerc P, Cédras L, Blais L, Boivin J-F. Drug injection among street youths in Montreal: Predictors of initiation. J Urban Health. 2003;80(1):92–105. doi: 10.1093/jurban/jtg092. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Sherman SG, Smith L, Laney G, Strathdee SA. Social influences on the transition to injection drug use among young heroin sniffers: A qualitative analysis. Int J Drug Policy. 2002;13(2):113–20. [Google Scholar]
- 22.Valdez A, Cepeda A, Neaigus A, Russell A. Heroin transition risk among daily and non-daily cannabis users who are non-injectors of heroin. Int J Drug Policy. 2008;19(6):442–9. doi: 10.1016/j.drugpo.2007.06.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Broz D, Ouellet LJ. Prevalence and correlates of former injection drug use among young noninjecting heroin users in Chicago. Subst Use Misuse. 2010;45(12):2000–25. doi: 10.3109/10826081003682875. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Garfein RS, Swartzendruber A, Ouellet LJ, Kapadia F, Hudson SM, Thiede H, et al. Methods to recruit and retain a cohort of young-adult injection drug users for the Third Collaborative Injection Drug Users Study/Drug Users Intervention Trial (CIDUS III/DUIT) Drug Alcohol Depend. 2007;91(Supplement 1):S4–S17. doi: 10.1016/j.drugalcdep.2007.05.007. [DOI] [PubMed] [Google Scholar]
- 25.Broz D. PhD dissertation. Chicago: University of Illinois at Chicago, United States; 2009. Transitions to injection and risk of HIV, HBV and HCV among young non-injecting heroin users in Chicago. [Google Scholar]
- 26.Des Jarlais DC, Paone D, Milliken J, Turner CF, Miller H, Gribble J, et al. Audio-computer interviewing to measure risk behaviour for HIV among injecting drug users: a quasi-randomised trial. Lancet. 1999;353(9165):1657–61. doi: 10.1016/s0140-6736(98)07026-3. [DOI] [PubMed] [Google Scholar]
- 27.Turner CF, Ku L, Rogers SM, Lindberg LD, Pleck JH, Sonenstein FL. Adolescent sexual behavior, drug use, and violence: Increased reporting with computer survey technology. Science. 1998;280(5365):867–73. doi: 10.1126/science.280.5365.867. [DOI] [PubMed] [Google Scholar]