Share this article on:

Correlates of HIV infection among young adult short-term injection drug users

Doherty, Meg C.a; Garfein, Richard S.a; Monterroso, Edgarb; Brown, Donalda; Vlahov, Davida

Epidemiology & Social

Objectives: To identify risks associated with HIV infection among young adult short-term injection drug users.

Methods: Current injection drug users, between 18 and 29 years of age, were recruited through street outreach to participate in a cross-sectional survey of HIV prevalence by circumstances of drug injection initiation, HIV-related risk behaviors, and a follow-up to estimate HIV incidence.

Results: At enrollment, 33 (14.4%) of 229 participants were HIV-seropositive. Significant bivariate associations with HIV at the time injection drug use was initiated included age less than or equal to 18 years, having receptive anal sex with the person who assisted with initiation, and having two or more `trainers' before being able to self-inject. Injecting risks positively associated with HIV included cocaine or speedball (heroin and cocaine together) injection versus heroin or amphetamine injection, injecting five or more times per day, daily crack smoking, backloading, sharing needles at peak drug use, and not using a new needle for every injection. Sexual practices associated with HIV included reporting > 100 lifetime sex partners, a history of sexual assault, being gay or bisexual, and trading sex for money or drugs after starting to inject. In a multivariate model, trading anal sex for money or drugs after initiating injection drug use [odds ratio (OR), 14.2; 95% confidence interval (CI) 3.2–62.3], cocaine/speedball injection (OR, 10.3; 95% CI, 2.2–47.9), daily crack smoking (OR, 4.2; 95% CI, 1.7–10.5), and having two or more trainers (OR, 2.6; 95% CI, 1.1–5.9) were independently associated with HIV. During 12 months of follow-up, four persons seroconverted for HIV (annual incidence: 2.6%; 95% CI, 1.1–5.9%)

Conclusions: Among short-term injectors, both sexual and injecting practices were important predictors of HIV infection, indicating that a proportion of HIV infections among young injection drug users can be attributed to sexual transmission. The incidence rate for HIV infection suggests that immediate steps should be taken to prevent new infections among young injection drug users.

From the aInfectious Disease Program, Department of Epidemiology, The Johns Hopkins School of Hygiene and Public Health, Baltimore, Maryland and the bDivision of HIV/AIDS Prevention – Surveillance and Epidemiology, National Center for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta Georgia, USA.

Sponsorship: This study was supported by cooperative agreement 309690 from the Centers for Disease Control and Prevention and by grant DA04334 and National Research Scientist Award grant F31 DA05556-02 both from National Institute of Drug Abuse.

Correspondence to Dr. David Vlahov, Room E-6008, Department of Epidemiology, The Johns Hopkins University, School of Hygiene and Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA. Tel: +1 410 955 1848; fax: +1 410 955 1383; e-mail:

Received: 7 May 1999;

revised: 16 July 1999; accepted: 2 December 1999.

Back to Top | Article Outline


Data from cohort studies of injection drug users (IDUs) indicate that younger IDUs and those who had more recently initiated injection drug use are at increased risk for the acquisition of HIV, hepatitis B virus, and hepatitis C virus [1–6]. Results from these studies show that the younger IDUs had an increased risk ratio of HIV (range, 2.2–3.3) when compared with older IDUs. Additionally, those reporting less than 3 years from onset of injection had an increased risk of seroconverting for HIV [1,2,7–10]. Although these studies noted higher risks of HIV infection for younger short-term IDUs, data on risk factors for these younger IDUs are sparse. In particular, these earlier studies did not investigate the circumstances surrounding the initiation of injection that might have contributed to or that might be a marker of early seroconversion for HIV.

Several studies [5,7,11] also found that younger female IDUs were at greater risk for prevalent and incident HIV infection. Some of the excess risk for women could be attributed to sexual behaviors other than injection risks [12,13]. Results from a natural history study of HIV infection in IDUs, found that sexual behaviors rather than injection behaviors were predominately associated with HIV; while infections with hepatitis B and C viruses were more strongly associated with injecting behaviors [5–7,13]. However, these data were collected primarily from older IDUs who had been injecting drugs for an average of 19 years [14].

In one study that examined HIV prevalence exclusively among young IDUs, Marrero Rodriquez and colleagues enrolled a cohort of IDUs aged 16 to 24 years in Puerto Rico [15]. With an HIV prevalence of 23.5%, factors significantly associated with HIV included age older than 20 years, initiating injection drug use when younger than 17 years, less than 12 years of education, having a history of incarceration, and reporting a history of sexually transmitted diseases (STDs); having children at home was inversely associated with HIV infection [15]. This study did not assess injection practices such as sharing injection equipment, types of drug injected or frequency of injection, nor did it assess sexual behaviors associated with drug use, such as trading sex for money or drugs.

To characterize the risks of HIV infection among young, short-term IDUs, we enrolled young adult IDUs in a community-based research study of HIV. The first objective was to measure HIV prevalence and risk correlates, emphasizing behaviors at the initiation of drug use and the sexual behaviors linked to drug use. Because some studies have shown higher HIV rates among women than men [5,7,11–13], a secondary objective was to assess gender differences in the risks of HIV to ascertain whether a sex-specific risk profile might account for the excess risk for HIV infection among young women. A third objective was to estimate HIV seroincidence in this population.

Back to Top | Article Outline

Materials and methods

Study design and population

In Baltimore, Maryland the REACH project enrolled 250 IDUs through street outreach from August 1994 through May 1996. A cohort of 50 persons who did not inject was simultaneously enrolled to eliminate an incentive among non-IDUs to falsify an injection history to obtain study entry. Follow-up visits were conducted at 6 months and 12 months, and the last participant was seen in September 1996. Project outreach workers approached young IDUs on the street, placed advertisements in shops and handed out information cards to interested persons. Advertisements were placed in a local free paper, in a newsletter for IDUs, at local clinics and departments of social services, and on bus placards. Participants also were recruited by word-of-mouth from enrolled participants.

Inclusion criteria included age 18 to 29 years, verified by photo identification, and having injected within the year preceding enrollment (`current' injector). The mean age was 22.8 years and six persons (2.6% of the cohort) who were 26 to 29 years old were enrolled. The inclusion of these persons did not significantly alter the findings and thus their data were retained. Although time since onset of injection was not an inclusion criteria, we sought to enroll persons with short injection histories. The median duration of injection was 3 years. Final analyses were conducted on 229 IDUs for whom we had complete data.

An active community advisory board consisting of leaders from local youth organizations, drug treatment centers, shelters, job placement programs, and the city health department, was formed prior to recruitment to provide feedback on the study protocol and interview instrument. The board recommended services appropriate for young IDUs and facilitated the development of referral protocols for HIV case-management, clinical treatment, and drug treatment programs. The Institutional Review Board of the Johns Hopkins School of Hygiene and Public Health approved this study

Back to Top | Article Outline

Data collection

Structured, confidential interviews were conducted at two sites in Baltimore City: a rowhouse on the east side and the Baltimore City Health Department Clinic on the west side. During the initial visit, participants underwent a face-to-face screening interview. Once a person had been screened and found to be eligible for the study, the study protocol was explained in detail and informed consent was obtained. A longer baseline interview covered the initiation of injecting drug use, lifetime drug use, and sexual behaviors. After the interview, participants underwent HIV pretest counseling and venipuncture by a trained counselor. At that time, the participant could also ask about and receive drug treatment counseling and referrals to other social services. The participant was given an appointment to return to the study site within 2 weeks for the HIV test results and to receive HIV post-test counseling in person. Any person who tested positive for HIV was referred for immediate medical evaluation. Participants received a small remuneration at the end of each visit.

Back to Top | Article Outline

Laboratory methods

HIV seropositivity was measured by enzyme linked immunosorbent assay (ELISA) (Genetic Systems, Seattle, WA, USA) and confirmed by Western blot (DuPont, Wilmington, DE, USA) according to standard criteria.

Back to Top | Article Outline

Study variables

Variables included demographic characteristics such as age, gender, and race. Variables specific for the time of first injection included circumstances before initiation, time to first injection, age at first injection, characteristics of the person who helped the initiate during the first injection (`helper'), the number of people who injected the drug for the new injector before he or she learned how to self-inject (`trainers'), and the time until a person was able to self-inject. Injection drug use practices were asked for two periods: over the lifetime and during the 6 months before the most recent injection. Lifetime behaviors included choice of drugs injected (cocaine or speedball versus heroin or amphetamine) and use of used needles (`sharing'). Behaviors at 6 months included frequency of injection, sharing needles, `backloading', and frequency of crack cocaine smoking. Sexual behaviors were measured over the lifetime and from first injection to interview. The specific variables included: sexual preference, number of sex partners, number of partners with whom one traded penile-vaginal, anal or oral sex for money or drugs, history of sexual assault (`rape'), and ever having a sex partner who was an IDU or who tested positive for HIV.

Back to Top | Article Outline

Statistical analysis

Univariate and exploratory data analyses were conducted for all variables. For normally distributed continuous variables, means and standard deviations were assessed. When appropriate, continuous variables were dichotomized or factored according to the mean or median, in response to a natural cut in the data or based on biologically meaningful levels reported in the literature. Categorical data were analyzed by using the Mantel–Haenzel χ2 test for differences in proportions. Fisher's exact test was used for comparisons of small numbers. The Mantel–Haenzel odds ratio (OR) and 95% confidence intervals (CI) [16] measured the strength of the association. Gender differences were assessed through a stratified analysis of the predictors of HIV prevalence for men and women separately. Adjusted rates were not reported because probable effect modification by gender was apparent; however, the small sample size limited our ability to measure the magnitude of the interaction.

Classification tree analysis with recursive partitioning was used to develop a method for examining risk factors, due to the limited number of outcomes and many potential interacting correlates. Recursive partitioning occurs as the data set is divided into two or more subsets based on the categories of the predictor variables. Each subset is further partitioned into other subsets until a priori defined stopping criteria are met. The final subsets are called the tree nodes. The SAS macro `%treedisc' was used for the computation [17]. This macro employs the theory of classification and regression tree (CART), by Breiman et al. [18] but uses the χ2 automatic interaction detection algorithm (CHAID), developed by Kass [17]. The predictor variable used to form the partition is the variable most significantly associated with the outcome based on the χ2 test of independence in a contingency table. The P- value from the χ2 test is used as the main stopping criterion; the smaller the P-value, the more likely the association is not due to chance alone. The %treedisc macro uses the Bonferroni adjustment for the P-value and Gabriel's adjustment to increase power for multiple comparisons [17].

In addition, multivariate logistic regression models were developed to assess the independent effect of each factor as it related to HIV while controlling for other confounding factors. Separate models were built for women and men because of concern that several variables interacted by gender on bivariate analysis. Person–year analysis was conducted for a point estimate of HIV seroconversion among the REACH participants [19]. Seroconversion was estimated to occur at the midpoint between the last seronegative and the first seropositive visit.

Back to Top | Article Outline



As shown in Table 1, the study cohort was fairly evenly split between women (54%) and men (46%). The median age at enrollment was 23 years (range: 18–29 years). Most of the population (79%) was African-American. The remainder was composed of Caucasians, Native Americans, Hispanic/Latino(a)s, and persons of mixed race. Almost two-thirds had less than a high school education. In the 6 months before the interview, 22% had been employed; one-third had received most of their money from illegal sources, such as theft, selling drugs or trading sex for money. In terms of social circumstances, the cohort showed signs of instability and poverty. In the year preceding enrollment, 21% had been runaways, 47% had been homeless, 38% had been in drug treatment, and almost 70% had spent time in jail. At baseline, 33 (14.4%) persons were HIV-seropositive, but none of their demographic factors were statistically associated with HIV prevalence.

Back to Top | Article Outline

HIV seroprevalence by calendar time

Figure 1 presents HIV seroprevalence by time since onset of injection. There was a gradually increasing rate of HIV infection with longer duration of injection; rates reached 15.2% by 3 years of injecting. This rate is similar to the rate reported for the entire cohort.

Back to Top | Article Outline

Drug use practices

Table 1 also summarizes several circumstances at initiation of injection drug use, by HIV serostatus. Young age (≤ 18 years) at initiation was significantly associated with HIV infection. However, taking less than 1 year to move from first illicit drug use to injection drug use and having initiated injection drug use 3 or more years before enrollment were positively, but not significantly, associated with HIV infection. The 22 persons who self-initiated by injecting themselves the very first time were less likely than the 207 who were initiated by others to be infected with HIV (OR, 0.57). After initiation of injection, persons who reported at least two trainers had increased odds for HIV infection (OR, 3.08); and likewise, needing more than 60 days to learn how to self- inject also showed a trend toward increased odds for HIV infection. These behaviors did not differ by the gender of participants.

Table 2 shows drug use practices significantly associated with HIV serostatus. Ever injecting cocaine or speedball (OR, 8.08) and ever sharing needles with an HIV-infected partner (OR, 5.66) were strongly correlated with HIV. Within the 6 months before the most recent injection, high-frequency drug use, such as injecting at least five times a day and daily crack smoking, was associated with HIV infection. Always using a new needle was protective for HIV (OR, 0.20). Sharing a needle and backloading were positively associated with HIV infection (OR, 1.79 and 2.72, respectively).

Back to Top | Article Outline

Sexual behaviors

Table 3 shows lifetime sexual behaviors, by HIV serostatus. HIV seropositivity was significantly associated with being gay, lesbian, or bisexual (OR, 3.79), reporting more than 100 lifetime sex partners (OR, 5.59), ever having traded anal sex for money or drugs (OR, 10.67), ever traded oral sex (OR, 3.97) or ever traded penile-vaginal sex (OR, 2.30). HIV infection also was associated with a history of sexual assault (OR, 2.61), forced receptive anal intercourse during rape (OR, 4.82), and receptive anal intercourse with a helper. Ever having had an HIV-positive sex partner (OR, 22.5) was strongly associated with HIV serostatus; therefore, we stratified this variable by those who had known that they were HIV-positive and those who had never previously tested positive. For persons with a prior HIV-positive test result, 17 of 18 were HIV-positive by REACH testing; therefore, the odds for HIV infection could not be calculated because of the small numbers. Three of 17 (17.6%) with previous HIV infection learned of their infection prior to the initiation of injection drug use. However, among persons who had never previously tested positive for HIV, ever having had an HIV-positive sex partner was non-significantly associated with current HIV infection (OR, 4.50). Prevalent HIV infection did not differ by age at first sex, being a lesbian or bisexual female, being a heterosexual female, or having a sex partner who was an IDU.

Back to Top | Article Outline

Classification tree

Figure 2 shows a classification tree analysis with recursive partitioning that illustrates HIV risks for this sample. The analysis started with the cohort of 229; recursive partitioning occurred with the most strongly associated factor as measured by the significance of the P-value. For example, trading anal sex after initiation of injection drug use was the strongest predictor of HIV infection (P  < 0.0001). The 10 persons who traded anal sex (60% of whom were HIV infected) became a terminal node at the base of the tree. Recursive partitioning continued for the 219 persons who did not trade anal sex after they began to inject drugs.

The final tree displays three groups with different risk profiles and HIV infection rates. Group I consists of end nodes with HIV rates of more than 57%. Among this group are the 10 persons who traded anal sex after they started injecting drugs. Thirteen persons, who did not trade anal sex but who injected cocaine or speedball, smoked crack at least daily, and had two or more trainers make up the next end node (69% seroprevalence). The third end node consists of seven persons (57% seroprevalence) who did not trade anal sex, did inject cocaine, did not smoke crack daily but did report that they were gay or bisexual.

Group II (medium HIV prevalence) consists of end nodes with HIV rates ranging from 8 to 14%. The end node of 14 persons (HIV rate = 14%) reported that they did not trade anal sex, did inject cocaine, did not smoke crack daily, and had fewer than two trainers. The next end node of 114 persons (HIV rate = 10%) did not trade anal sex, did inject cocaine, did not smoke crack daily, and were heterosexual. The final end node in this middle group consisted of 12 persons (HIV rate = 8%) who did not trade anal sex, and did not inject cocaine but began to inject drugs within one year of first illicit drug use. Group III is made up of 59 persons, none of whom were HIV infected. They did not trade anal sex, did not inject cocaine, and began to inject drugs more than a year after first drug use.

Each branch of the tree represents a predictor of HIV and each point at which the branches cross represent an interaction. For each unique end-node, we looked at the HIV infection rate and prevalence of high-risk behaviors. Overall, persons in group I reported higher levels of risky behavior. For example, the proportions of groups I, II, and III who had traded oral sex in the past 6 months were 53, 17, and 14%, respectively. Likewise, the proportions with more than 100 lifetime sex partners for the three groups were 23, 5, and 3%, respectively. There was a trend for the higher HIV prevalence groups to display a greater proportion of injection risk, as well. The proportions who had shared needles in the past 6 months were 60, 41, and 25%, respectively; the proportion who reported always using a new needle increased across the three groups, from 7 to 17 to 39%. Correlational analyses of these behaviors indicated a low level of correlation (mean r  = 0.29, 0.20, 0.26) when calculated for each group.

Back to Top | Article Outline

Logistic regression

Logistic regression models were built to assess independent correlates of HIV seroprevalence; the results mirror the regression tree analysis. Table 4 shows the final, most parsimonious model identified through the significance of the log-likelihood statistic. Trading anal sex after initiating injection drug use is the strongest correlate of HIV (adjusted OR, 14.16; 95% CI, 3.17–62.28). Injecting cocaine or speedball, smoking crack daily, and having two or more trainers before self-injection remain significant predictors in the model (adjusted OR, 10.27, 4.15, and 2.55, respectively). All two-way interaction terms were non-significant.

Because of the concern of possible interaction by gender, separate logistic models for women and men are shown. For women, trading anal sex after the initiation of injection drug use, injecting cocaine or speedball, and daily crack smoking remained significantly associated with HIV infection. Trading anal sex, smoking crack, and sharing needles were significant predictors of HIV infection among the men in the study. Although sharing in the past 6 months was not significantly associated with HIV for the entire population, it was borderline significant in the model for men and contributed to the best fit model. Possibly this variable has greater predictive value for HIV infection in male IDUs than in female IDUs.

Four persons seroconverted for HIV over 12 months and 112.9 person–years of follow-up, yielding an annual seroconversion of 3.5% per year (95% CI, 0.9–5.5). HIV seroconversion rates tended to be higher for women than men (4.9%; 95% CI, 0.9–11.9 versus 2.0%; 95% CI, 0.0–7.7) and greater for those older than 23 years old versus 23 years or younger (4.8%; 95% CI, 0.9–11.7 versus 2.0%; 95% CI, 0.0–7.9).

Back to Top | Article Outline


A major finding of this study is that the circumstances of initiation into injection drug use contributed to the risk for HIV infection. Specific markers included having two or more trainers, less than 1 year from starting any illicit drug to injection drug use, and trading anal sex for drugs or money after initiating injection drug use. These factors were important even after taking into account conventionally accepted risk factors for HIV infection such as injecting cocaine, smoking crack, and sexual orientation [20–26]. Another major finding was that sexual behaviors were strongly associated with HIV infection among both men and women. These findings suggest that the higher risk of HIV infection among younger, recently initiated injection drug users compared with older, more experienced drug users may include specific practices influenced by initiation into injection drug use.

Disentangling the risk for HIV infection among young adult, short-term IDUs is a complex task. As noted in this analysis, both drug use and sexual risks contributed to HIV infection. In addition, risk factors tended to cluster within individuals. For example, among group I of Figure 2 (characterized by persons who engaged in anal sex, injected cocaine, had a history of more than one trainer, and were gay, lesbian, or bisexual), the proportion who had histories of trading any type of sex, more than 100 sex partners, sharing needles, and a helper who was 5 or more years older than the index IDU tended to be larger than for the lower risk groups (groups II and III). These data suggest that those who acquired HIV infection were more likely to demonstrate a broad array of risky behaviors. The variables that identify the groups represent risky practices but could just as well be markers for other associated risky practices. Put another way, several risk factors may be prominent in a single person, and it makes sense to consider a broad profile of risk rather than restricting descriptions of HIV acquisition to isolated practices.

Early studies have noted that although the prevalence of HIV among IDUs is usually similar by gender, incidence is usually higher for women than for men [1,2,27,28]. Our data are consistent with these earlier reports. Although some reports have suggested that the differences by gender are due to higher drug-risk behaviors [27,29–31], others have suggested higher levels of sexual risk [1,12,13,32], and recently, one study suggests increased HIV among male new injectors who engage in sex with men [33], our ability to evaluate this issue was limited. However, when we extended our analysis to logistic regression analyses for predictors of the two major risk factors – cocaine injection and daily crack use – we noted that cocaine injection was significantly more common among men and daily crack use more common among women (data not shown). Moreover, cocaine injection was associated with other risky injection practices (i.e., injecting five or more times a day, not always using a new needle, needing more than 60 days before being able to self-inject, and being younger than 20 years at the first injection). Daily crack use was associated primarily with sexual practices (i.e., having more than 100 lifetime sex partners and having HIV-infected sex partners). The sexual transmission of HIV may take place in the context of many unprotected sex acts to get money or drugs to feed a crack addiction.

Our results suggest that among young adult, short-term IDUs, men and women tend to have somewhat different risk profiles. We had hypothesized that the behaviors at initiation might help to explain the differential risk for HIV among women. However, the data show no gender difference at the time of initiation (data not shown), but as the women and men become more involved with drug-use, gender differences in lifetime and 6 month behaviors emerge. For example, HIV infection among men is associated with sharing needles, whereas this behavior does not explain HIV infection among women. Trading anal sex seems more strongly predictive for women. Additional studies with larger sample sizes will be better suited to examine this important issue more closely.

The context for these findings is important. Despite the fact that socio-demographic characteristics were not associated with HIV infection, the high level of homelessness, lack of high school education, and dependence on public and medical assistance indicates that these groups of young IDUs live in poverty. Traumatic events, such as previous forced sex, sexual abuse in the home, and incarceration are prevalent among this cohort. The mechanisms by which these early life traumas might affect later drug misuse, injection initiation, and high-risk sexual behaviors remains to be clarified.

Before firm conclusions are drawn, several study limitations should be noted. There is a possibility of selection bias. Although we noted that HIV prevalence was similar to the 10% seroprevalence for adolescent and young adult gay and bisexual men in Baltimore in 1997 (J. Hylton, personal communication), the absence of a true sampling frame from which to choose a population sample, limits our ability to fully evaluate this potential bias. Another issue is that our analyses primarily are cross-sectional, so there is a potential for prevalence-incidence bias. To partially offset this concern, we collected all interview data before venipuncture and HIV testing. Lifetime factors often were more significant than were behaviors reported for the 6 months before the interview. Although data for the 6 months period allowed us to probe in greater detail, these data may reflect activities after infection. (Capturing information for different time frames, which has been used in other studies of HIV among IDUs [34], helped to clarify this issue.)

Similarly, whether circumstances of initiation reflect the risk of HIV infection or whether those behaviors are simply markers for subsequent behaviors that lead to infection cannot be definitively distinguished in this study. For example, having two or more trainers before self-injection may be a marker for less control over the injection environment and for sharing syringes or injection equipment. Those who self-inject at initiation may be more likely to have greater control over their injections, because the self-initiators in our study reported less sharing of needles and were more likely to always use a new needle. At best, this study suggests that some circumstances at initiation into injection drug use should be recognized as a warning sign for HIV infection. Other results identify the persons who may be at particularly great risk for HIV. For example, anal sex traders, cocaine and speedball injectors, and daily crack smokers might benefit from more intensive interventions to help reduce their risks.

Young adult IDUs have a substantial risk for HIV acquisition. Within this subgroup of IDUs is a subset who even early in their injection careers assume a wide array of risk behaviors that translate into disturbingly high rates of HIV infection. The classification tree analysis demonstrates that risky sexual behaviors combined with risky injection behaviors are particularly hazardous. Simple recommendations, such as using a new needle for each injection, are likely to be helpful, but prevention efforts should not stop there.

Identifying people during this early stage of their injection careers in order to facilitate prevention efforts may be difficult; nevertheless; it should be given high priority. Interventions for young IDUs should be comprehensive, targeting both sexual and injecting risks. Programs should seek ways to help young IDUs recognize their risk for HIV. Three of the seroconverters said they thought their chances of having HIV were `none'. Harm reduction and needle exchange programs run by youth for youth would be an excellent place to begin creative, peer-oriented programs to reduce HIV acquisition. Interventions among leaders in the injection community, aimed at reducing initiation, might also be an approach to curbing new infections.

To reduce the sexual transmission of HIV among this group, drug treatment for cocaine injection and crack smoking might reduce the need for young IDUs to trade sex for drugs or money to buy drugs. However, if reducing consumption of the drug and eliminating sex trade are not possible, interventions must help young IDUs learn how to introduce condoms into their commercial and non-commercial sex acts. Young IDUs may recognize the risk for HIV infection from their injection practices but may fail to recognize the risk from their sexual behaviors. Several of the young IDUs in this cohort initiated injection drug use after becoming infected with HIV; three participants reported that they were sexually abused by persons who were infected with the virus. Interventions to help identify and intervene with adolescents and young adults at risk for HIV infection through sexual abuse or sex trade are imperative. To date, studies of young adult IDUs have been rare; we have provided useful information for reaching this vulnerable population and focusing prevention efforts.

Back to Top | Article Outline


The authors gratefully acknowledge the contributions of Alvaro Muñoz, the staff of the REACH Project, including Bertha Queen, William Gray, Hahn Huang, Susan Patania and Margaret Park, and the REACH Community Advisory Board. We thank Hazel Hamond-Terry for manuscript preparation.

Back to Top | Article Outline


1. Nicolosi A, Leite MLC, Musicco M, Molinari S, Lazzarin A. Parenteral and sexual transmission of human immunodeficiency virus in intravenous drug users: a study of seroconversion. Am J Epidemiol 1992, 135: 225–233.
2. Nelson KE, Vlahov D, Solomon L, Cohn S, Muñoz A. Temporal trends of incident HIV infection in a cohort of injection drug users in Baltimore, Maryland. Arch Intern Med 1995, 155: 1305–1311.
3. Vlahov D, Anthony JC, Celentano DD, Solomon L, Chowdhury N. Trends in HIV-1 risk reduction among initiates into intravenous drug use 1982–1987. Am J Drug Alcohol Abuse 1991, 17: 39–48.
4. van Ameijden EJC, van den Hoek JAR, Mientjes GHC, Coutinho RA. A longitudinal study on the incidence and transmission patterns of HIV, HBV, and HCV infection among drug users in Amsterdam. Eur J Epidemiol 1993, 9: 255–262.
5. Levine OS, Vlahov D, Brookmeyer R, Cohn S, Nelson KE. Differences in the incidence of hepatitis B and human immunodeficiency virus infection among injecting drug users. J Infect Dis 1996, 173: 579–583.
6. Garfein RS, Vlahov D, Galai N, Doherty MC, Nelson KE. Viral infection in short-term injection drug users: The prevalence of hepatitis C, hepatitis B, human immunodeficiency, and human T-lymphotropic viruses. Am J Public Health 1996, 86: 655–661.
7. Zaccarelli M, Gattari P, Spizzichino L, Portaleone A, Venzia S, Rezza G. Understanding the dynamics of HIV infection among injecting drug users in Rome in the 1990's: the combined use of cross-sectional, longitudinal and behavioral data. XI International Conference on AIDS. Vancouver, July 1996 [abstract Mo.C.461].
8. Curtis SP, Edwards A. HIV in UK prison: a review of seroprevalence, transmission and patterns of risk. Int J STD & AIDS 1995, 6: 387–391.
9. van Ameijden EJC, van den Hoek JAR, van Haastrecht HJA, Coutinho RA. The harm reduction approach and risk factors for human immunodeficiency virus (HIV) seroconversion in injecting drug users, Amsterdam. Am J Epidemiol 1992, 136: 236–243.
10. Fennema JSA, van Ameijden EJC, van den Hoek A, Coutinho RA. Young and recent-onset injection drug users are at higher risk for HIV. Addiction 1997, 92: 1457–1465.
11. Zaccarelli M, Rezza G, Girardi E, Puro V, Pezzotti P, Lelli V. et al. Monitoring HIV trends in injecting drug users: an Italian experience. AIDS 1990, 4: 1007–1010.
12. Schoenbaum EE, Hartel D, Selwyn PA. et al. Risk factors for human immunodeficiency virus infection in intravenous drug users. N Engl J Med 1989, 321: 874–879.
13. Solomon L, Astemborski J, Warren D. et al. Difference in risk factors for human immunodeficiency virus type 1 seroconversion among male and female intravenous drug users. Am J Epidemiol 1993, 137: 892–898.
14. Vlahov D, Anthony JC, Muñoz A. et al. The ALIVE Study: a longitudinal study of HIV-1 infection in intravenous drug users: description of methods. J Drug Issues 1991, 21: 759–776.
15. Marrero Rodriquez CA, Robles RA, Colon HM, Freeman DH, Matos TD, Reyes JC. HIV risk behavior and HIV seropositivity among young injection drug users. P R Health Sci J 1993, 12: 7–12.
16. Breslow NE, Day NE. Statistical Methods in Cancer Research. Vol. I: The Analysis of Case–control Studies. Lyon: International Agency for Research on Cancer, 1980.
17. %Treedisc Macro for CHAID (Chi-squared Automatic Interaction Detection) Algorithm. Cary, NC: SAS Institute, 1997.
18. Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and Regression Trees. Belmont, CA: Wadsworth International Group, 1984.
19. Breslow NE, Day NE. Statistical Methods in Cancer Research. Vol. II: The Analysis of Cohort Studies. Lyon: International Agency for Research on Cancer, 1980.
20. Anthony JC, Vlahov D, Nelson KE, Cohn S, Astemborski J, Solomon L. New evidence on intravenous cocaine use and the risk of infection with human immunodeficiency virus type 1. Am J Epidemiol 1991, 134: 1175–1189.
21. Chaisson RE, Bacchetti P, Osmond D, Brodie B, Sande MA, Moss AR. Cocaine use and HIV infection in intravenous drug users in San Francisco. JAMA 1989, 261: 561–565.
22. Murphey S, Rosenbaum M. Women who use cocaine too much: smoking crack vs. snorting cocaine. J Psychoactive Drugs 1992, 24: 381–388.
23. Chiasson MA, Stoneburner RL, Hildebrandt DS, Ewing WE, Telzak EE, Jaffe HW. Heterosexual transmission of HIV-1 associated with the use of smokable freebase cocaine (crack). AIDS 1991, 5: 1121–1126.
24. Des Jarlais DC, Abdul-Quader A, Minkoff H, Hoegsberg B, Landesman S, Tross S. Crack use and multiple AIDS risk behaviors. J Acquir Immune Defic Syndr 1991, 4: 446–447.
25. Edlin BR, Irwin KL, Faruque S. et al. Intersecting epidemics – crack cocaine use and HIV infection among inner-city young adults. N Engl J Med 1994, 331: 1422–1427.
26. Edlin BR, Irwin KL, Ludwig DD. et al. High-risk sex behavior among young street-recruited crack cocaine smokers in three American cities: An interim report. J Psychoactive Drugs 1992, 24: 363–371.
27. Friedman SR, Neaigus A, Jose B, et al. Female injecting drug users get infected sooner than males. IX International Conference on AIDS. Berlin, June 1993 [abstract PO-D03-3512].
28. Nicolosi A, Leite MLC, Molinari S, Musicco M, Saracco A, Lazzarin A. Incidence and prevalence trends of HIV infection in intravenous drug users attending treatment centers in Milan and Northern Italy, 1986–1990. J Acquir Immune Defic Syndr 1992, 5: 365–373.
29. Sotheran JL, Wenston JA, Rockwell R, Des Jarlais DC, Friedman SR. Gender differences in the social context of syringe sharing among New York IDUs. VIII International Conference on AIDS. Amsterdam, 1992 [abstract PoD 5093].
30. Sotheran JL, Wenston JA, Rockwell R, Des Jarlais DC, Friedman SR. Injecting drug users: why do women share syringes more often then men? Presented at the Annual Meeting of American Public Health Association. Washington, DC, 1992.
31. Friedman SR, Jose B, Neaigus A, Curtis R, Des Jarlais DC. Female injecting drug users get infected with HIV sooner than males. Annual Meeting of American Public Health Association. San Francisco, 1993. [abstract 334].
32. Astemborski J, Vlahov D, Warren D, Solomon L, Nelson KE. The association between trading sex for drugs or money and HIV seropositivity among female intravenous drug users. Am J Public Health 1994, 84: 382–387.
33. Des Jarlais DC, Friedman SR, Perlis T. et al. Risk behavior and HIV infection among new drug injectors in the era of AIDS in New York City. J Acquir Immune Defic Syndr 1999, 20: 67–72.
34. Marmor M, Des Jarlais DC,Des Jarlais DC, Cohen H. et al. Risk factors for infection with human immunodeficiency virus among intravenous drug abusers in New York City. AIDS 1987, 1: 39–44.

Cited By:

This article has been cited 3 time(s).

HIV incidence and associated risk factors among young injection drug users
Miller, CL; Tyndall, M; Spittal, P; Li, K; LaLiberte, N; Schechter, MT
AIDS, 16(3): 491-493.

HIV incidence among street youth in Montreal, Canada
Boivin, J; Roy, É; Haley, N; Leclerc, P; Cédras, L; Weber, AE; Claessens, C
AIDS, 17(7): 1071-1075.

PDF (79)
JAIDS Journal of Acquired Immune Deficiency Syndromes
Requiring Help Injecting Independently Predicts Incident HIV Infection Among Injection Drug Users
O'Connell, JM; Kerr, T; Li, K; Tyndall, MW; Hogg, RS; Montaner, JS; Wood, E
JAIDS Journal of Acquired Immune Deficiency Syndromes, 40(1): 83-88.

PDF (94)
Back to Top | Article Outline

HIV; injection drug users; intravenous; substance abuse; prevention; epidemiology

© 2000 Lippincott Williams & Wilkins, Inc.