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The Impact of Engagement in Street-based Income Generation Activities on Stimulant Drug Use Cessation… Ti, Lianping; Richardson, Lindsey; DeBeck, Kora; Nguyen, Paul; Montaner, Julio; Wood, Evan; Kerr, Thomas Mar 17, 2014

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The Impact of Engagement in Street-based Income GenerationActivities on Stimulant Drug Use Cessation among People whoInject DrugsLianping Ti1,2, Lindsey Richardson1, Kora DeBeck1,3, Paul Nguyen1, Julio Montaner1,4,Evan Wood1,4, and Thomas Kerr1,41British Columbia Centre for Excellence in HIV/AIDS, St. Paul's Hospital, 1081 Burrard Street,Vancouver, BC, Canada V6Z 1Y62School of Population and Public Health, University of British Columbia, 2206 East Mall,Vancouver, BC, Canada V6T 1Z33School of Public Policy, Simon Fraser University, 8888 University Drive, Burnaby, BC, CanadaV5A 1S64Department of Medicine, University of British Columbia, 2775 Laurel Street, Vancouver, BC,Canada V5Z 1M9AbstractBackground—Despite the growing prevalence of illicit stimulant drug use internationally, andthe widespread involvement of people who inject drugs (IDU) within street-based drug markets,little is known about the impact of different types of street-based income generation activities onthe cessation of stimulant use among IDU.Methods—Data were derived from an open prospective cohort of IDU in Vancouver, Canada.We used Kaplan-Meier methods and Cox proportional hazards regression to examine the effect ofdifferent types of street-based income generation activities (e.g., sex work, drug dealing, andscavenging) on time to cessation of stimulant use.Results—Between December, 2005 and November, 2012, 887 IDU who use stimulant drugs(cocaine, crack cocaine, or crystal methamphetamine) were prospectively followed-up for amedian duration of 47 months. In Kaplan-Meier analyses, compared to those who did not engagein street-based income generation activities, participants who reported sex work, drug dealing,© 2014 Elsevier Ireland Ltd. All rights reserved.Send correspondence to: Thomas Kerr, Director, Urban Health Research Initiative, BC Centre for Excellence in HIV/AIDS, 608 -1081 Burrard Street, Vancouver BC V6Z 1Y6,Canada, Tel: 604-806-9116, Fax: 604-806-9044, uhri-tk@cfenet.ubc.ca.Authors' Contributions: The specific contributions of each author are as follows: LT and TK were responsible for study design; PNconducted the statistical analyses; LT prepared the first draft of the analysis; All authors provided critical comments on the first draftof the manuscript and approved the final version to be submitted.Conflict of Interest: No conflict declared.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to ourcustomers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review ofthe resulting proof before it is published in its final citable form. Please note that during the production process errors may bediscovered which could affect the content, and all legal disclaimers that apply to the journal pertain.NIH Public AccessAuthor ManuscriptDrug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.Published in final edited form as:Drug Alcohol Depend. 2014 August 1; 141: 58–64. doi:10.1016/j.drugalcdep.2014.05.003.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptscavenging, or more than one of these activities were significantly less likely to report stimulantdrug use cessation (all p<0.001). When considered as time-updated variables and adjusted forpotential confounders in a multivariable model, each type of street-based income generationactivity remained significantly associated with a slower time to stimulant drug cessation (allp<0.005).Conclusions—Our findings highlight the urgent need for strategies to address stimulantdependence, including novel pharmacotherapies. Also important, structural interventions, such aslow-threshold employment opportunities, availability of supportive housing, legal reformsregarding drug use, and evidence-based approaches that reduce harm among IDU are urgentlyrequired.Keywordspeople who inject drugs; stimulants; crack cocaine; crystal methamphetamine; drug cessation;street economy1. IntroductionStimulant misuse has been associated with various health and social harms, including thetransmission of infectious diseases and violence. For instance, syringe sharing, a well-known risk for HIV transmission, is common among people who inject cocaine and crystalmethamphetamine (Fairbairn et al., 2007; Lloyd-Smith et al., 2009; Tyndall et al., 2003).Crack cocaine smoking has also been shown to be an independent risk factor for HIVinfection (DeBeck et al., 2009; Edlin et al., 1994; Strathdee and Stockman, 2010).Furthermore, prior studies have demonstrated that the relationship between crack cocaineand sex work increases the likelihood of exploitation and violence among sex workers,including being pressured into unprotected sexual intercourse (Shannon and Csete, 2010;Shannon et al., 2009). There is also a growing body of research that has found aninterdependent relationship between crack cocaine markets, drug dealing and violent crimes(e.g., homicide) in North American settings (Baumer et al., 1998; Blumstein and Rosenfeld,1998).Many individuals who use illicit drugs engage in various street-based income generatingactivities to support their ongoing drug use and basic living needs (DeBeck et al., 2007).These activities often include sex work, drug dealing, street-based scavenging and otheractivities that carry significant risk for severe violence and other health-related harms(Booth et al., 1993; Braitstein et al., 2003; Parker and Bottomley, 1996; Schneider, 2013;Shannon and Csete, 2010). It is well known that illicit drug dependence plays an importantrole in contributing to an increased reliance on various street-based income generationactivities as a means of generating money to buy drugs (Deering et al., 2013; Maher andCurtis, 1992). However, there is also evidence to suggest that some individuals engaged inthe street-based economy become increasingly dependent on illicit drugs as a way to copewith the difficulties and demands of their work (Draus et al., 2010; Erickson et al., 2000;Yahne et al., 2002).Ti et al. Page 2Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDespite the extensive literature documenting the various harms associated with stimulantdrug use among people who inject drugs (IDU) engaged in street-based income generationactivities (Baumer et al., 1998; Fairbairn et al., 2008; Maher and Curtis, 1992), and theincreasing prevalence of stimulant drug use among these individuals (DeBeck et al., 2011a;Fischer et al., 2006; Werb et al., 2010), the conditions surrounding stimulant drug usecessation are not yet fully understood. Given the growing calls for the identification of socialand structural drivers of drug-related harms (Rhodes, 2009, 2002; Strathdee et al., 2010), thepresent study was conducted to investigate the impact of different types of street-basedincome generation activities (e.g., sex work, drug dealing, and scavenging) on stimulantdrug use cessation in Vancouver, Canada.2. MethodsData for this study were obtained from the Vancouver Injection Drug Users Study (VIDUS),which is an open prospective cohort that began enrolling IDU through street outreach andself-referral in May, 1996. This study has been described in detail previously (Wood et al.,2001). Briefly, participants are eligible to enroll in the study if they meet the following entrycriteria at recruitment: 1) reside in the Greater Vancouver Regional District; 2) have injectedillicit drugs in the previous month; and 3) provide written informed consent. At enrollmentand on a semi-annual basis, participants complete an interviewer-administered questionnaireand provide a blood sample for serologic testing. Participants received a stipend ($20 CDN)for each study visit. The study has received ethics approval from St. Paul's Hospital/University of British Columbia's Research Ethics Board. The present study was conductedbetween December, 2005 and November, 2012.For the present analysis, we restricted our sample to participants who reported recentinjection or non-injection illicit stimulant drugs (in the last six months) at the time of thebaseline interview, and who had at least one subsequent study visit to assess for stimulantdrug use cessation. Individuals who initiated stimulant drug use during follow-up wereincluded from the point of initiation of stimulant use and followed forward. Only periods ofactive use were included in the analyses. Illicit stimulant drugs included: cocaine, crackcocaine, and crystal methamphetamine. Individuals who did not use stimulant drugs atbaseline but who initiated stimulant drug use during follow-up were included from the nextfollow-up interview forward. Consistent with previous analyses focused on the cessation ofdrug use (DeBeck et al., 2011b), the primary outcome of interest was time to first stimulantdrug use cessation during the study period, defined as the first instance of a period of at leastsix months without any episodes of self-reported stimulant drug use administered by eitherinjection or non-injection. The primary independent variable of interest, engagement instreet-based income generation activities, was categorically defined as: 1) none; 2) sex workonly; 3) drug dealing only; 4) scavenging only; and 5) engagement in more than one of theseactivities. ‘Sex work’ was defined as having exchanged sex for any of the following: money,gifts, food, shelter, clothes, drugs, and favours. ‘Drug dealing’ was defined as having soldillicit drugs. ‘Scavenging’ was defined as reporting either recycling (i.e., binning or buying/selling recycled products), squeegeeing (i.e., washing car windows), or panhandling (i.e.,soliciting donations on the street) as a source of income. These activities all referred to thesix-month period prior to the follow-up interview and therefore, income generationTi et al. Page 3Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptcategories are dynamic and can change over time. This categorical variable was measuredlongitudinally at each follow-up and was included in analyses as a time-updated measure.To estimate the independent relationship between engagement in street-based incomegeneration activities and time to first stimulant drug use cessation, we considered secondaryexplanatory variables that may potentially confound this relationship. Variables included:age (dichotomized at the median) (Evans et al., 2009); gender (female vs. male; Lejuez etal., 2007); White race (yes vs. no; Falck et al., 2007); year of enrolment (per year increase);HCV serostatus (positive vs. negative); homelessness, defined as living on the street orhaving no fixed address (yes vs. no; Cox et al., 2014; Mehta et al., 2012); binge drug use,defined as having used injection or non-injection drugs more than usual (yes vs. no; Whiteand Bates, 1995); daily injection or non-injection heroin use (yes vs. no; Werb et al., 2013);daily injection or non-injection prescription opioid use, including Dilaudid(hydromorphone), morphine, oxycodone, illicit methadone (yes vs. no; Evans et al., 2009);incarceration, defined as having been in detention, prison, or jail overnight or longer (yes vs.no; Mehta et al., 2012); drug addiction treatment (detoxification programs and/orbehavioural therapies [e.g., a detoxification program, recovery house, residential addictiontreatment centre, or engaging with an addiction counselor or participating in peer supportprograms] vs. methadone maintenance therapy (MMT) vs. both vs. none; DeBeck et al.,2011b; Werb et al., 2013). All non-invariant variables are time-updated and refer to the six-month period prior to the follow-up interview unless otherwise indicated.As an initial step, we compared selected characteristics among participants who reported noengagement in any street-based income generating activity; those who reported one of sexwork, drug dealing, or scavenging; and those who reported engaging in more than one ofthese activities. Using Kaplan-Meier methods, we estimated the cumulative incidence ofstimulant drug use cessation separately for each type of street-based income generationactivity at baseline. Cumulative incidence of cessation among participants reporting noengagement in street-based income generation activities; those reporting sex work, drugdealing, or scavenging; and those engaging in more than one of these activities werecompared using the log-rank test. As a next step, using Cox proportional hazards regressionanalyses, unadjusted and adjusted hazard ratios were calculated to assess the independenteffect of engagement in different types of street-based income generation activities on timeto stimulant drug use cessation. To fit the multivariable confounding model, we employed aconservative stepwise variable selection approach (Maldonado and Greenland, 1993).Specifically, we included all variables (where p <0.05 in bivariable analyses) in amultivariable model and used a stepwise approach to fit a series of reduced models. Aftercomparing the value of the coefficient associated with the main independent variable ofinterest in the full model to the value of this coefficient in each of the reduced models, wedropped the secondary covariate associated with the smallest relative change in the mainindependent variable. We continued this iterative process until the minimum changeexceeded 5%. Remaining variables were included as confounders in our final model. Allstatistical analyses were performed using SAS software version 9.2 (SAS Institute, Inc.,Cary, NC).Ti et al. Page 4Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscript3. ResultsOf the 887 participants who met the inclusion criteria, 294 (33.1%) were female and themedian age at baseline was 41 years (interquartile range [IQR] = 35 – 47 years). Over thestudy period, the participants contributed 39393 person-months of follow-up, and themedian duration of follow-up among the study sample was 47 months (IQR = 19 – 69months). Over the study period, 377 (42.5%) participants reported a stimulant drug usecessation event. In total, 566 (63.8%) and 810 (91.3%) reported using injection and non-injection stimulant drugs in the 6 months prior to their baseline interview, respectively.Table 1 provides baseline descriptive characteristics stratified by type of street-based incomegeneration activity. Among the study participants at baseline, 75 (8.5%) reported sex workonly, 201 (22.7%) reported drug dealing only, 152 (17.1%) reported scavenging only, 136(15.3%) reported more than one of these activities, and 323 (36.4%) reported none of theseactivities.The Kaplan-Meier analysis of time to first stimulant drug use cessation stratified by type ofstreet-based income generation activity at baseline is shown in Figure 1. By the end of thestudy period, there was a significant difference in cumulative incidence of first stimulantdrug cessation among the different types of street-based income generation activities (log-rank: p < 0.001). At four years of follow-up, the cumulative incidence of first stimulant drugcessation was 39.9% among IDU who reported no engagement in street-based incomegeneration activities (95% confidence interval [CI]: 34.5 – 45.8%), 26.5% among those whoreported sex work only (95%CI: 17.1 – 39.7%), 39.7% among those who reported drugdealing only (95%CI: 32.6 – 47.7%), 29.9% among those who reported scavenging only(95%CI: 22.8 – 38.5%), and 19.4% among those who were engaged in more than oneactivity type (95%CI: 13.2 – 28.0%).The results of the Cox proportional hazards regression analyses examining the associationsbetween the various types of street-based income generation activities and time to firststimulant drug use cessation are shown in Table 2. In multivariable Cox proportionalhazards regression analyses, after adjusting for various confounders, engagement in any typeof street-based income generation activity remained inversely associated with time tostimulant drug use cessation. Specifically, IDU reporting sex work (adjusted hazard ratio[AHR] = 0.30; 95%CI: 0.14 – 0.65), drug dealing (AHR = 0.32; 95%CI: 0.21 – 0.49),scavenging (AHR = 0.40; 95%CI: 0.29 – 0.56), and engagement in more than one of theseactivities (AHR = 0.13; 95%CI: 0.05 – 0.33) were all significantly less likely to reportstimulant drug use cessation compared to IDU who did not report engaging in any of theseactivities.4. DiscussionIn the present study, we found that a large proportion of IDU in Vancouver reportedstimulant drug use cessation during a seven-year period, with 43% reporting such an event.However, we also found that many IDU (63.6%) reported engagement in at least one street-based income generating activity, and when compared to IDU who were not engaged in anystreet-based income generation activity, those who reported sex work, drug dealing, and/orTi et al. Page 5Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptscavenging were significantly less likely to report stimulant drug use cessation. Thesignificantly lower likelihood of stimulant drug use cessation among individuals reportingstreet-based income generation activity persisted even after adjustment for variousconfounders, including homelessness and intensity of drug use.Consistent with previous studies demonstrating a strong association between street-basedincome generation activities and stimulant drug use (Booth et al., 1993; DeBeck et al.,2011a; Maher and Curtis, 1992), our findings suggest that individuals engaged in theseactivities were less likely to report cessation from stimulant use. This could be due to thefact that more severe stimulant drug addiction may perpetuate the need to generate incomethrough illegal means. However, it may also be that engagement in the street-based economyitself serves to exacerbate stimulant use through enhanced access to drugs, integration indrug use scenes, or as a result of the stress associated with these activities. Given thegrowing body of evidence supporting the latter interpretation (Erickson et al., 2000; Kerr etal., 2007), efforts to scale up interventions that address poverty among this population arewarranted.Our findings should be considered alongside the growing body of evidence indicating thatdrug dependence is a chronic and relapsing condition; thus, cessation is not alwayssustainable among this population. The present study only explored time to first stimulantdrug use cessation, and therefore there is a possibility that the participants may havecontinued use of other drugs other than stimulants, or relapsed into stimulant use followingtheir first cessation event. It is therefore necessary to further investigate transitions betweenthe use of different illicit drugs as well as sustained drug use cessation among thispopulation. Additionally, it may be important to explore whether the transitions betweeninjection and non-injection routes of administration differ.It is noteworthy that binge drug use was the strongest factor negatively associated withstimulant drug use cessation among our study sample. This may reflect the additionalchallenges individuals with higher intensity addiction face in ceasing drug use. Our findingsare consistent with a study demonstrating that cocaine “users” report more dependencysymptoms, including binge use, compared to “stoppers” (White and Bates, 1995). Otherstudies conducted on other illicit drugs also present similar findings (Cheng et al., 2010).However, since little is known about binge drug use and its impact on stimulant drug usecessation, future research should seek to explore this relationship further.Our study also found gender to be a strong predictor of stimulant drug use cessation, withfemales reporting a longer time to stimulant drug use cessation than males. This finding isinconsistent with previous studies that suggest that males have longer addiction careers thanfemales (Dennis et al., 2005). Past research has also shown that females have higher rates ofaccess to drug addiction treatment compared to males (Wood et al., 2005); however, thisfinding may be specific to opioid dependence. Given that less is known about stimulantdependence, future research should seek to explore gender-based differences and access toaddiction treatment for those dependent on stimulant drugs.Ti et al. Page 6Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptOur findings have implications for interventions that aim to maximize stimulant drug usecessation among IDU engaged in various street-based income generation activities. Anextensive body of research has identified effective substitution therapies for the treatment ofsome substance use disorders, including opioid and nicotine dependence (Cahill et al., 2012;Comer et al., 2006; Mattick et al., 2009), which have shown to have a positive impact onpublic health and public order in various settings. For instance, studies have shown thatMMT is linked to an increase in formal employment and reduction in engagement incriminal activities (Bell et al., 1992; Corsi et al., 2009; French et al., 1993; Shi et al., 2007),although these positive impacts may be conditioned by the degree to which MMT enrolmentand regulation is compatible with mainstream economic activities (Richardson et al., 2012).The present study demonstrated that while detoxification programs and behaviouraltherapies may be effective in promoting stimulant cessation, MMT did not appear to havethe same beneficial impact for stimulant users. Unfortunately, there are currently no provenpharmacotherapies for the treatment of cocaine or crystal methamphetamine addiction so wewere unable to assess the impact of these stimulant-specific types of therapies on stimulantdependence. While individual studies have indicated the modest effectiveness of potentialmedications for the treatment of cocaine dependence (Grabowski et al., 2001; Kampman etal., 2004; Mariani et al., 2012; Shearer et al., 2003), at present, scientific evidence pertainingto pharmacotherapies to treat stimulant drug dependence remains inconclusive given that themajority of studies are limited by high attrition rates and small sample sizes (Castells et al.,2010; Minozzi et al., 2008). Due to the differences in pharmaceutical properties betweenopioid and stimulant drugs, future randomized controlled trials investigating novelpharmacotherapies for the treatment of stimulant drug dependence should be prioritized. Inthe meantime, contingency management for stimulant drug cessation may be beneficial, as ithas shown some success in studies conducted among MMT patients (Weinstock et al.,2010). Concurrently, prevention efforts that aim to minimize the occurrence of drug useinitiation may be an important public health endeavor.Interventions designed to increase the availability of low-threshold employmentopportunities for IDU may reduce engagement in street-based income generation activitiesthat have shown to be associated with stimulant drug use (DeBeck et al., 2011a; Maher andCurtis, 1992). Prior research conducted in Vancouver suggest that if provided with theopportunity, IDU who generate income through sex work and drug dealing were willing tocease these illegal activities and would opt for low-threshold employment opportunities if itwere available (DeBeck et al., 2011c). Unfortunately, legitimate and less risky incomegeneration opportunities for IDU remain limited, and a number of barriers to more formalemployment among these individuals have been noted in the literature (Braveman et al.,2006; Hoffman, 1997; Richardson et al., 2012, 2010; Rusch et al., 2004).It is well known that various social, structural, and environmental characteristics operatingwithin the broader risk environment of IDU increase their vulnerability to social instabilityand poor health (Pauly et al., 2011; Pinkham et al., 2012; Richardson et al., 2013). A largebody of evidence has documented links between unstable housing, drug addiction, and riskbehaviours (Baumer et al., 1998; Deering et al., 2013; Fairbairn et al., 2007; Maher andCurtis, 1992; Palepu et al., 2010). Given this, as well as findings from the present analysisthat point to homelessness as a significant confounder in the relationship betweenTi et al. Page 7Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptengagement in the street-based economy and persistent stimulant use, the provision ofsupportive housing environments for IDU may also serve to promote disengagement fromthe street economy and ultimately cessation from stimulant use.Lastly, research undertaken in North America and elsewhere internationally has documentedthat prices of illicit drugs remain stable and low even with the roll-out of anti-drug strategiesthat heavily rely on law enforcement efforts (Office of National Drug Control Policy, 2007;United Nations Office on Drugs and Crime, 2009). Thus, the potential for drug law reformto reduce risky behaviours associated with high intensity addiction should be considered,particularly in settings that criminalize vulnerable drug using populations at significantpublic health, social, and economic cost. Indeed, reports on the experiences of Portugal'sdecriminalization efforts suggest that this type of policy reform has potential to reduce drugdependence and crime among this population (Domoslawski, 2011; Kain, 2011). Ofparticular relevance to the present study, it is likely that illicit drug prices will drop as aresult of decriminalization efforts (Bretteville-Jensen, 2006), and thus reduce the need forIDU to engage in various street-based income generation activities as a means of survival.This study has several limitations. Firstly, VIDUS is not a random sample of IDU andtherefore these findings may not be generalizable to other drug using populations. Secondly,many of our measures relied on self-reported information concerning illegal and/orstigmatizing practices and behaviours, including sex work and drug dealing, and aretherefore vulnerable to social desirability reporting. This could have resulted in an under-reporting of engagement in street-based income generation activities and therefore, estimatesof these activities in the present study may have been conservatively reported. Thirdly, as ageneral limitation of observational studies, the relationship between engagement in street-based income generation activities and achieving stimulant drug use cessation may be underthe influence of unobserved or unmeasured confounding. Future research on street-basedincome generation activities and stimulant drug use cessation should seek to collect data ona broader range of potential confounders, including mental illness and availability of illicitdrugs. Lastly, the covariates were not time lagged in the multivariable Cox regressionanalyses and therefore we were unable to determine a causal relationship betweenengagement in street-based income generation activities and stimulant drug use cessation.In summary, we found an independent association between engagement in different street-based income generation activities and slower time to stimulant drug use cessation amongIDU in Vancouver. Our findings suggest that future research should focus on novelpharmacotherapies for the treatment of stimulant drug dependence. As well, efforts topromote stimulant drug use cessation among IDU should include consideration of the social,structural, and environmental contexts that may be influencing IDUs' engagement in street-based income generation activities. Accordingly, structural interventions that aim to increaseopportunities for low-threshold employment and supportive housing among this population,in addition to legal reforms, are urgently needed in this setting.Ti et al. Page 8Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptAcknowledgmentsThe authors thank the study participants for their contribution to the research, as well as current and pastresearchers and staff. We would specifically like to thank Deborah Graham, Peter Vann, Jennifer Matthews, SteveKain, and Tricia Collingham for their research and administrative assistance.Role of funding: The study was supported by the US National Institutes of Health (R01DA011591). This researchwas undertaken, in part, thanks to funding from the Canada Research Chairs program through a Tier 1 CanadaResearch Chair in Inner city Medicine which supports Dr. Evan Wood. 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Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptFigure 1.Kaplan Meier estimates of cumulative incidence of first stimulant drug use cessation amongstudy participants, stratified by type of street-based income generation activity (n=887)Ti et al. Page 13Drug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptTi et al. Page 14Table 1Characteristics of study sample at baseline, stratified by type of street-based income generation activity in the last six months (n=887)CharacteristicStreet-based income generation activities*No engagement 323(36.4%)Sex work only 75 (8.5%)Drug dealing only 201(22.7%)Scavenging only 152(17.1%)More than one 136 (15.3%)≥ 42 years old195 (60.4)24 (32.0)99 (49.3)91 (59.9)58 (42.7)Female gender82 (25.4)74 (98.7)41 (20.4)33 (21.7)64 (47.1)White race208 (64.4)37 (49.3)127 (63.2)109 (71.7)81 (59.6)Year of enrolment (med, IQR)2006 (2006-2006)2006 (2006-2006)2006 (2006-2006)2006 (2006-2006)2006 (2006-2007)HCV-positive serostatus277 (85.8)68 (90.7)170 (84.6)137 (90.1)120 (88.2)Homelessness*76 (23.5)30 (40.0)105 (52.2)56 (36.8)76 (55.9)Any crack cocaine use*280 (86.7)73 (97.3)187 (93.0)128 (84.2)127 (93.4)Any cocaine use*175 (54.2)39 (52.0)129 (64.2)86 (56.6)93 (68.4)Any crystal methamphetamine use*60 (18.6)13 (17.3)36 (17.9)47 (30.9)60 (44.1)Any heroin use*162 (50.2)55 (73.3)159 (79.1)85 (55.9)112 (82.4)Any prescription opioid use*66 (20.4)23 (30.7)98 (48.8)41 (27.0)69 (50.7)Binge drug use*154 (47.7)49 (65.3)116 (57.7)80 (52.6)82 (60.3)Incarceration*47 (14.6)11 (14.7)62 (30.9)23 (15.1)38 (27.9)Any drug addiction treatment(including MMT)*151 (46.7)40 (53.3)98 (48.8)73 (48.0)64 (47.1)HCV; hepatitis C virus; MMT: methadone maintenance therapy*Activities in the previous six months‡ Any cocaine use refers to injection and non-injection (e.g., powder, snorted) cocaine use excluding crack cocaine useDrug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptTi et al. Page 15Table 2Cox proportional hazard analyses of factors associated with time to drug use cessation ofstimulant drugs† among study participants (n=887)Unadjusted AdjustedCharacteristic Hazard Ratio (95% CI) p – value Hazard Ratio (95% CI) p – valueStreet-based income generation activities* None Reference Reference Reference Reference Sex work only 0.16 (0.08 – 0.35) <0.001 0.32 (0.15 – 0.69) 0.004 Drug dealing only 0.20 (0.13 – 0.31) <0.001 0.32 (0.21 – 0.50) <0.001 Scavenging only 0.33 (0.24 – 0.46) <0.001 0.42 (0.30 – 0.58) <0.001 More than one 0.07 (0.02 – 0.17) <0.001 0.13 (0.05 – 0.35) <0.001Age (≥ median vs. < median) 0.94 (0.77 – 1.15) 0.525Gender (female vs. male) 0.65 (0.52 – 0.81) <0.001 0.76 (0.61 – 0.96) 0.019White race (yes vs. no) 0.93 (0.76 – 1.14) 0.489Year of enrolment (per year increase) 1.08 (0.92 – 1.27) 0.357HCV serostatus (positive vs. negative) 0.73 (0.54 – 0.98) 0.036Homelessness* (yes vs. no) 0.52 (0.40 – 0.69) <0.001 0.73 (0.56 – 0.94) 0.017Daily heroin use* (yes vs. no) 0.54 (0.40 – 0.73) <0.001Daily prescription opioid use* (yes vs. no) 0.74 (0.45 – 1.23) 0.251Binge drug use* (yes vs. no) 0.05 (0.03 – 0.08) <0.001 0.07 (0.04 – 0.11) <0.001Incarceration* (yes vs. no) 0.79 (0.58 – 1.08) 0.141Drug addiction treatment* None Reference Reference Reference Reference Detoxification programs/behavioural 1.86 (1.39 – 2.48) <0.001 1.55 (1.19 – 2.02) 0.001 therapies MMT 0.71 (0.56 – 0.91) 0.007 0.80 (0.63 – 1.02) 0.071 Both 1.29 (0.93 – 1.77) 0.124 1.20 (0.88 – 1.62) 0.255CI: confidence interval; HCV; hepatitis C virus; MMT: methadone maintenance therapy*Activities in the previous six monthsDrug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptTi et al. Page 16†Stimulant drugs refer to the following illicit drugs: crack cocaine, cocaine, and crystal methamphetamineDrug Alcohol Depend. Author manuscript; available in PMC 2015 August 01.


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