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Major depressive disorder and access to health services among people who use illicit drugs in Vancouver,… Beaulieu, Tara; Ti, Lianping; Milloy, M.-J.; Nosova, Ekaterina; Wood, Evan; Hayashi, Kanna Jan 19, 2018

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RESEARCH Open AccessMajor depressive disorder and access tohealth services among people who useillicit drugs in Vancouver, CanadaTara Beaulieu1, Lianping Ti1,4, M.-J. Milloy1,2,4, Ekaterina Nosova1,2, Evan Wood1,2,4 and Kanna Hayashi1,2,3*AbstractBackground: People who use illicit drugs (PWUD) are commonly diagnosed with major depressive disorder (MDD).However, little is known about whether PWUD living with MDD experience additional barriers to accessing healthservices compared to those without MDD. We sought to identify whether MDD symptoms were associated withperceived barriers to accessing health services among people who use illicit drugs (PWUD) in Vancouver, Canada.Methods: Data were collected through prospective cohorts of PWUD in Vancouver, Canada between 2005 and2016. Using multiple logistic regression, we examined the relationship between MDD symptoms, defined as aCentre for Epidemiologic Studies Depression (CES-D) scale total score of ≥16, and barriers to access health services.We also used descriptive statistics to examine common barriers among participants who reported any barriers.Results: Among a total of 1529 PWUD, including 521 (34.1%) females, 415 (27.1%) reported barriers to accessinghealth services, and 956 (62.5%) reported MDD symptoms at baseline. In multiple logistic regression analyses, afteradjusting for a range of potential confounders, MDD symptoms (adjusted odds ratio [AOR] = 1.40; 95% confidenceinterval [CI]: 1.03–1.92) were positively and significantly associated with barriers to accessing health services. Amongthose who reported MDD symptoms and barriers to access, commonly reported barriers included: long wait lists/times (38.1%); and treated poorly by health care professionals (30.0%).Conclusion: These findings show that the likelihood of experiencing barriers to accessing health services washigher among PWUD with MDD symptoms compared to their counterparts. Policies and interventions tailored toaddress these barriers are urgently needed for this subpopulation of PWUD.Keywords: Depression, Access to care, People who use illicit drugs, CanadaBackgroundThe extent of overlap between major depressive disorder(MDD) and substance use disorder (SUD) is compelling,with an estimated lifetime prevalence of co-occurrenceranging from 27 to 40% in persons with MDD [1]. Thereexists notable empirical evidence to shed light on the pos-sible mechanisms underlying SUD-MDD co-occurrence,with the simplest explanation being a bidirectional causalrelationship (whether direct or indirect). Other explana-tions tend to reflect two paths of derivation: genetic,developmental and environmental factors (e.g., socio-economic marginalization, early life trauma and a dis-ruptive family environment); or the self-medicationhypotheses (i.e., use of illicit drugs to alleviate MDDsymptoms) [1–4]. No single or consistent pattern ap-pears to underlie co-occurrence, which lends evidenceto suggest that multiple pathways of association maybe acting simultaneously.A growing body of literature has indicated that SUD-MDD co-occurrence causes a significant burden to theindividual, their families, and society. For instance, thiscomorbidity is often associated with a greater severity ofsymptoms, poorer treatment response and enhanced riskfor SUD and MDD recurrence [5, 6]. SUD-MDD co-occurrence also yields greater social and personal* Correspondence: bccsu-kh@cfenet.ubc.ca1British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital,608-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada2British Columbia Centre on Substance Use, St. Paul’s Hospital, 1081 BurrardStreet, Vancouver, BC V6Z 1Y6, CanadaFull list of author information is available at the end of the article© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Beaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 DOI 10.1186/s13011-018-0142-9impairments (e.g., interpersonal concerns and reduced oc-cupational functioning), and enhanced risk for comorbidpsychiatric conditions, particularly posttraumatic stressdisorder (PTSD) and generalized anxiety disorder (GAD)[1]. Moreover, a much higher risk of suicidal ideation andattempt has been evident among this subpopulation [1, 7].Finally, evidence suggests that there are broader implica-tions in the context of public health and healthcare costs.For example, SUD-MDD co-occurrence often leads tohigher rates of acute service utilization (e.g., emergencydepartment and inpatient healthcare utilization) - contrib-uting to higher costs [8, 9].Although there are effective pharmacological andpsychotherapeutic options to treat MDD, their effica-ciousness is sometimes not well understood amongpersons with SUD (e.g., when administered concur-rently with opioid agonist therapy medications suchas methadone or buprenorphine) [10]. Moreover,some prescription drugs have been found to signifi-cantly increase harms (e.g., completed suicide) [11].Additionally, while well-designed psychotherapiesand pharmacological treatments for SUD exist,therapeutic efficacy and safety may differ in thepresence of MDD co-occurrence [12]. Studies whichexamine effective treatments for SUD-MDD co-occurrence are sparse and sometimes methodologic-ally, open to doubt. What is clear is that access tocare remains disproportionately low among individ-uals with SUD-MDD co-occurrence [13]. A growingbody of literature has explored barriers to SUD andMDD care separately [14–18], and treatment barriersamong individuals with SUD and co-occurring men-tal illness in a broader sense [19]. However, there isa dearth of literature on barriers to care among indi-viduals with SUD-MDD co-occurrence [20]. There-fore, we sought to identify whether MDD symptomswere associated with perceived barriers to accessinghealth services among people who use illicit drugs(PWUD) in Vancouver, Canada.MethodsStudy design and populationData for this study were drawn from the VancouverInjection Drug Users Study (VIDUS), and the AIDS CareCohort to evaluate Exposure to Survival Services(ACCESS), two prospective cohorts involving PWUD inVancouver, Canada. The methods for these studies havebeen described elsewhere [21, 22]. To be eligible forVIDUS, participants must be ≥18 years of age, HIV-seronegative and report injection drug use at least onemonth prior to enrollment. ACCESS participants mustbe ≥18 years of age, HIV-seropositive and report usingan illicit drug (other than or in addition to cannabis) inthe month prior to enrollment. Recruitment was con-ducted through self-referral and street outreach.The data collection instruments and procedures wereharmonized across the two cohorts to allow for pooledanalyses. At baseline and semi-annually, participantscompleted an interviewer-administered questionnairethat elicited information on socio-demographic charac-teristics, drug use patterns, access to healthcare, andother relevant exposures and outcomes. Additionally, ateach visit, participants provided blood samples for HIVand HCV serologic tests and HIV disease monitoring asappropriate. A $30 (CAD) honorarium was offered toparticipants upon completion of each study visit. Thecohorts have received ethical approval by the Universityof British Columbia/Providence Health Care ResearchEthics Board.Study sampleFor the present analysis, the sample was restricted tothose who: 1) completed a baseline between December2005 and May 2016; and 2) completed at least onefollow-up visit directly after baseline to allow for laggedanalyses. For those that did not have a Centre for Epide-miologic Studies Depression (CES-D) score at baselinebut had one during follow-up, the follow-up was in-cluded as the baseline (if at least one subsequent follow-up visit occurred).Variable selectionThe primary outcome of interest was having experiencedbarriers to accessing health services in the last sixmonths, dichotomized as any barriers vs. none. Possiblebarriers included: 1) Limited hours of operation; 2) Longwait lists/times; 3) Didn’t know where to go; 4)Language barrier; 5) Jail/detention/prison; 6) Wastreated poorly by health care professionals; 7) Difficultykeeping appointments; 8) Restricted to one physician; 9)No Personal Health Number (PHN); 10) Other (barriersunaccounted for were grouped together for analysis); 11)No barriers, at baseline. The primary explanatory vari-able was having depressive symptoms, defined as aCentre for Epidemiologic Studies Depression (CES-D)summed score of ≥16. Our analysis utilized this cut-point as MDD has been typically classified based on asummed score of ≥16 [23–25].We also considered a selection of possible con-founders in the relationship between MDD symptomsand barriers to care, including: age at baseline (per 10-year increase); sex (male vs. female); white ethnicity (yesvs. no); calendar year (per one-year increase); HIV seros-tatus (positive vs. negative); homelessness (yes vs. no);any injection drug use (yes vs. no); daily heroin use (yesvs. no); daily cocaine use (yes vs. no); daily crystal meth-amphetamine use (yes vs. no); daily prescription opioidBeaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 Page 2 of 8use (yes vs. no); incarceration (yes vs. no); enrollment inopioid agonist therapy (yes vs. no); hospitalized (yes vs.no); sex work (yes vs. no); stable employment (yes vs.no); history of childhood physical abuse (yes vs. no);history of childhood sexual abuse (yes vs. no); and victimof violence (yes vs. no). With the exception of age, sex,calendar year, HIV serostatus, and history of childhoodphysical or sexual abuse, all variables were considered astime-updated variables of events reported in the sixmonths prior to interview.Statistical analysesAs a first step, we examined descriptive and socio-demographic characteristics of the sample, stratified byhaving had recently experienced barriers to accessinghealth services at baseline. Comparisons were madeusing the Pearson’s χ2 test for binary variables and theMann-Whitney U test for continuous variables. Next, weused bivariate logistic regression to estimate the relation-ship between the outcome (i.e., barriers to accessinghealth services in the last six months) and all explana-tory variables, including CES-D summed score. Then, amultiple logistic regression model was constructedwhere all secondary variables significant at p < 0.10 in bi-variate analyses were included. Of note, the explanatoryvariable and the primary outcome of interest coveredthe previous two weeks and six months, respectively;thus, the CES-D variable was lagged in response to po-tential temporal concerns.In a stepwise manner, we compared the value ofthe coefficient in the full model to the value of thecoefficient for the main relationship in each of the re-duced models, the variable associated with the smal-lest relative change was dropped. We continued thisiterative process until the maximum change exceeded5%. Multicollinearity was assessed using the varianceinflation factor. Finally, the following variables wereforced back into the final model as these variables areknown confounders in the main relationship: sex;homelessness; and injection drug use in the last sixmonths.As a secondary analysis, we accessed frequencies todetermine common barriers to accessing health ser-vices among participants who reported ‘yes’ to themain outcome: in total and stratified by CES-Dsummed score (≥ 16 vs. < 16). All analyses were per-formed in R version 3.2.4 (Foundation for StatisticalComputing, Vienna, Austria).ResultsBaseline descriptive and socio-demographic characteris-tics, stratified by the outcome are presented in Table 1.Among a total of 1529 PWUD, 801 (87.3%) of VIDUSparticipants and 481 (79.1%) of ACCESS participantsreported injecting drug use in the past six months. 415(27.1%) reported barriers to accessing health servicesand 956 (62.5%) had a CES-D total score ≥ 16 at base-line. Among those with a CES-D total score ≥ 16 at base-line, 297 (71.6%) reported barriers to accessing healthservices whereas 650 (59.1%) reported no barriers toaccessing health services, resulting in a difference of12.5%. Five hundred twenty-one (34.1%) were female,878 (57.4%) had white ancestry, and the median age atbaseline was 43 years (quartile [Q]1 - Q3: 36–49 years).The median difference between the lagged date for theexplanatory variable and current date for the outcomevariable was 6 months (Q1 - Q3: 6-6).As presented in Table 2, in a multiple logistic regres-sion analyses after adjusting for a range of confounders,lagged CES-D total score ≥ 16 remained independentlyassociated with barriers to accessing health services (ad-justed odds ratio [AOR] = 1.40; 95% confidence interval[CI]: 1.03–1.92). The relative risk (RR) was 1.20 (95% CI,1.12–1.29). Suffered physical violence also remainedindependently associated with barriers to accessinghealth services (AOR = 1.38; 95% CI: 1.01–1.86). Amongthose who reported a CES-D total score of ≥16 and bar-riers to accessing health services, the most commonlyreported barriers included: long wait lists/times (38.1%);treated poorly by health care professionals (30.0%); anddifficulty keeping appointments (18.5%). Among thosewho reported a CES-D total score < 16 and barriers toaccessing health services, the most commonly reportedbarriers included: long wait lists/times (30.3%); treatedpoorly by health care professionals (27.0%); and difficultykeeping appointments (14.6%).DiscussionIn the present study, more than half of PWUDshowed MDD symptoms. We observed a high propor-tion of participants who reported barriers to accessinghealth services. We also found a positive and inde-pendent relationship between MDD and barriers toaccessing health services among PWUD, after adjust-ing for various confounders.While these results corroborate the findings fromprevious research in that we found a high prevalenceof barriers to care among PWUD [19, 20, 26], thereare some inconsistencies between our results andprevious findings, which are likely attributable to dif-ferences in study environments. For example, in astudy conducted in the United States (US), the sam-ple was comprised of 393 patients who met criteriafor both MDD and SUD (i.e., 100% prevalence ofMDD-SUD co-occurrence) [20]. Our study samplewas comprised of 1529 PWUD, 573 (37.5%) of whichreported no MDD symptoms. Furthermore, thisUS-based study focused primarily on the role ofBeaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 Page 3 of 8Table 1 Baseline characteristics stratified by having had recently experienced barriers to accessing health services among peoplewho use illicit drugs in Vancouver, Canada (N = 1529)Totaln = 1529, N (%)Barriers to accessing health services in the last six months p – valueYesn = 415, N (%)Non = 1099, N (%)CharacteristicCES-D total score≥ 16 956 (62.5) 297 (71.6) 650 (59.1) < 0.001< 16 459 (30) 89 (21.4) 364 (33.1)Ageamedian 43.0 42.4 43.1 0.119IQR (36.2–48.6) (35.0–47.8) (36.6–49.0)Gendermale 1008 (65.9) 258 (62.2) 739 (67.2) 0.063female 521 (34.1) 157 (37.8) 360 (32.8)Caucasian ethnicityyes 878 (57.4) 248 (59.8) 624 (56.8) 0.295no 651 (42.6) 167 (40.2) 475 (43.2)Calendar yearmedian 2007 2007 2007 0.776IQR (2006–2009) (2006–2009) (2006–2009)HIV serostatuspositive 600 (39.2) 147 (35.4) 445 (40.5) 0.071negative 929 (60.8) 268 (64.6) 654 (59.5)Homelessnessbyes 481 (31.5) 164 (39.5) 311 (28.3) < 0.001no 1041 (68.1) 246 (59.3) 786 (71.5)Any injection drug usebyes 1282 (83.8) 378 (91.1) 891 (81.1) < 0.001no 244 (16) 37 (8.9) 206 (18.7)Daily heroin usebyes 346 (22.6) 107 (25.8) 234 (21.3) 0.066no 1179 (77.1) 308 (74.2) 862 (78.4)Daily cocaine usebyes 130 (8.5) 49 (11.8) 81 (7.4) 0.006no 1393 (91.1) 365 (88.0) 1014 (92.3)Daily crystal methamphetamine usebyes 74 (4.8) 28 (6.7) 44 (4.0) 0.026no 1450 (94.8) 387 (93.3) 1051 (95.6)Daily prescription opioid usebyes 97 (6.3) 39 (9.4) 58 (5.3) 0.004no 1429 (93.5) 376 (90.6) 1039 (94.5)Incarcerationbyes 228 (14.9) 72 (17.3) 153 (13.9) 0.084no 1298 (84.9) 340 (81.9) 946 (86.1)Beaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 Page 4 of 8financial barriers to accessing SUD and evidence-based MDD care. Our study provides new insightinto client perspectives in a setting where there areless financial barriers to SUD or evidence-basedMDD care due to universal health care. That beingsaid, it is important to consider that British Columbia’sprovincial health insurance program covers limited mentalhealth care.In line with previous findings, we found a relationshipbetween MDD and barriers to care among PWUD [20].Encouragingly, MDD symptoms in PWUD often im-prove following SUD treatment initiation [5, 27]. Giventhe central role of primary care physicians in SUD carein Canada, and abroad [13, 28], it is likely that the inte-gration of SUD care into primary care settings wouldlead to improved depressive symptoms for many. In cir-cumstances where MDD is not a self-limited condition,integration of evidence-based MDD care with primarycare could also potentially reduce wait times, improvecontinuity of care, and increase patient satisfaction [29,30]. Research data suggest scaling-up collaborative andintegrated care pathways as another potential approachto reduce wait times while improving continuity and sat-isfaction with care among individuals with SUD-MDDco-occurrence [31, 32].The perception of being ‘treated poorly by health careprofessionals’ may be a consequence of mental illness-related stigma, substance use-related stigma, and/orabstinence-only based policies within healthcare settings.Our findings underscore a widely prevalent perceptionof poor treatment by health care professionals amongPWUD, regardless of the presence of MDD symptoms[33]. Empirical evidence suggests that a certain level of“mutual mistrust” can exist between providers andPWUD. This may be partially attributable to the factthat providers who are not specialized in addictionmedicine lack confidence in providing care for those liv-ing with SUD. This can lead to inconsistency in care oravoidance by the provider, which could be interpreted asa sign of maltreatment by PWUD [34]. Provider trainingsuch as addiction medicine programs which have soughtto integrate substance use care with the rest of medicine,anti-stigma interventions, contact-based educationapproaches which enhance provider comfort and skillsTable 1 Baseline characteristics stratified by having had recently experienced barriers to accessing health services among peoplewho use illicit drugs in Vancouver, Canada (N = 1529) (Continued)Totaln = 1529, N (%)Barriers to accessing health services in the last six months p – valueYesn = 415, N (%)Non = 1099, N (%)Enrollment in opioid agonist therapybyes 667 (43.6) 181 (43.6) 481 (43.8) 0.994no 858 (56.1) 232 (55.9) 616 (56.1)Hospitalizedbyes 302 (19.8) 91 (21.9) 208 (18.9) 0.191no 1227 (80.2) 324 (78.1) 891 (81.1)Sex workbyes 222 (14.5) 71 (17.1) 148 (13.5) 0.064no 1300 (85.0) 340 (81.9) 948 (86.3)Stable employmentbyes 371 (24.3) 94 (22.7) 275 (25.0) 0.338no 1158 (75.7) 321 (77.3) 824 (75.0)History of childhood physical abuseyes 1061 (69.4) 296 (71.3) 757 (68.9) 0.076no 410 (26.8) 95 (22.9) 309 (28.1)History of childhood sexual abuseyes 655 (42.8) 207 (49.9) 444 (40.4) < 0.001no 824 (53.9) 192 (46.3) 621 (56.5)Victim of violencebyes 324 (21.2) 125 (30.1) 195 (17.7) < 0.001no 1200 (78.5) 288 (69.4) 901 (82.0)aPer 10-year increasebActivities reported in the six months prior to interviewBeaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 Page 5 of 8Table 2 Multiple logistic regression model to determine the relationship between CES-D score and barriers to accessing healthservices among people who use illicit drugs in Vancouver, Canada (n = 1529)Unadjusted AdjustedCharacteristic Odds ratio (95% CI) p - value Odds ratio (95% CI) p - valueCES-D total scorea(≥ 16 vs. < 16) 1.63 (1.23–2.18) 0.001 1.40 (1.03–1.92) 0.035Age(per 10-year increase) 0.81 (0.70–0.93) 0.002 0.88 (0.76–1.02) 0.096Gender(male vs. female) 0.85 (0.66–1.10) 0.214 0.99 (0.74–1.31) 0.927Caucasian ethnicity(yes vs. no) 1.02 (0.80–1.31) 0.869Calendar year(per 1-year increase) 0.99 (0.94–1.03) 0.564HIV serostatus(positive vs. negative) 0.82 (0.64–1.06) 0.139Homelessnessb(yes vs. no) 1.31 (1.00–1.72) 0.049 1.11 (0.83–1.49) 0.467Any injection drug useb(yes vs. no) 1.37 (1.03–1.84) 0.032 1.21 (0.89–1.65) 0.224Daily heroin useb(yes vs. no) 1.13 (0.84–1.52) 0.419Daily cocaine useb(yes vs. no) 0.87 (0.53–1.35) 0.543Daily crystal methamphetamine useb(yes vs. no) 1.80 (1.05–3.01) 0.027Daily prescription opioid useb(yes vs. no) 1.44 (0.87–2.32) 0.140Incarcerationb(yes vs. no) 1.72 (1.22–2.41) 0.002Enrollment in opioid agonist therapyb(yes vs. no) 0.92 (0.72–1.18) 0.511Hospitalizedb(yes vs. no) 1.67 (1.22–2.27) 0.001Sex workb(yes vs. no) 1.08 (0.74–1.54) 0.689Stable employmentb(yes vs. no) 0.81 (0.59–1.10) 0.190History of childhood physical abuse(yes vs. no) 1.47 (1.09–1.99) 0.012History of childhood sexual abuse(yes vs. no) 1.44 (1.12–1.86) 0.004 1.30 (0.99–1.70) 0.060Victim of violenceb(yes vs. no) 1.55 (1.16–2.07) 0.003 1.38 (1.01–1.86) 0.039CES-D Center for Epidemiological Studies Depression Scale, CI Confidence IntervalaCES-D variable is laggedbActivities reported in the six months prior to interviewBeaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 Page 6 of 8in treating those with MDD and/or SUD, and efforts toabolish abstinence-only based policies in healthcare set-tings may help to address this barrier [30, 35]. Future re-search should explore the impact of these diverse andinnovative strategies to improve MDD and SUD diagno-sis, uptake and continuity of care among PWUD.Our findings should be viewed in the context ofseveral limitations. First, measurement of the pri-mary explanatory variable and the outcome were re-liant on self-reported data, which is susceptible tosocial desirability and recall bias. Second, as with allMDD screening measures, there are psychometriclimitations of the CES-D [36, 37]. However, theCES-D has demonstrated validity and reliability innumerous populations (including among PWUD),and has been used extensively in epidemiologicresearch [38–40]. Third, we relied on a laggedexplanatory variable; therefore, there may have beena time gap between when the explanatory and out-come variables were measured. However, we foundthat the median time between these variables was6 months. Given that the median duration of anMDD episode is approximately 20 weeks, we decidedto use a lagged explanatory variable in our analyses.Forth, despite adjusting models for known con-founders, results may be subject to underlying re-sidual and unmeasured confounding. Fifth, thesedata are observational, thus we were unable to drawconclusions regarding causality. Finally, participantswere not randomly selected and therefore, the extentto which these results may be generalized beyondour setting is unclear.ConclusionOverall, our findings demonstrate an essential need forscaling-up access to evidence-based SUD and MDD careamong PWUD populations. The integration of evidence-based SUD and MDD care with primary care, scaling-upcollaborative and integrated care pathways (to diminishlong wait lists/times), provider education, anti-stigma in-terventions, and efforts to extinguish abstinence-onlybased policies in healthcare settings (to diminishperceived stigma by health care professionals) may helpto alleviate MDD and/or SUD symptoms among PWUDpopulations. Although future studies are required tofully elucidate the impact of SUD-MDD co-occurrenceand to provide guidance for healthcare providers facingthe challenge of treating SUD-MDD co-occurrence, theresults of this analysis clearly indicate that policies andinterventions tailored to address these barriers areurgently needed to mitigate the alarming rates ofmorbidity and mortality experienced among individualswith SUD-MDD co-occurrence.AbbreviationsACCESS: AIDS Care Cohort to evaluate Exposure to Survival Services;AOR: Adjusted odds ratio; CES-D: Centre for Epidemiologic StudiesDepression; CI: Confidence interval; GAD: Generalized anxiety disorder;MDD: Major depressive disorder; PHN: Personal Health Number;PTSD: Posttraumatic stress disorder; PWUD: People who use illicit drugs;Q: Quartile; US: United States; VIDUS: Vancouver Injection Drug Users StudyAcknowledgementsThe authors thank the study participants for their contribution to theresearch, as well as current and past researchers and staff.FundingThis work was supported by the US National Institutes of Health(VIDUS: U01DA038886; ACCESS: U01DA021525) This research wasundertaken, in part, thanks to funding from the Canada ResearchChairs program through a Tier 1 Canada Research Chair in Inner CityMedicine which supports Dr. Evan Wood. Dr. Lianping Ti is supportedby a Michael Smith Foundation for Health Research (MSFHR) ScholarAward. Dr. Kanna Hayashi is supported by a Canadian Institutes ofHealth Research (CIHR) New Investigator Award (MSH-141971) andMSFHR Scholar Award. Dr. M-J Milloy is supported by a CIHR NewInvestigator Award, an MSFHR Scholar Award and the US NIH(U01DA0251525). His institution has received an unstructured gift fromNG Biomed, Ltd., to support his research.Availability of data and materialsThe cohort data is not publicly available. For further information regardingthe data and materials used please contact the corresponding author.Authors’ contributionsLT, KH, and TB designed the study and the present analysis plan. ENconducted the statistical analyses. TB drafted the manuscript, andincorporated suggestions from all co-authors. All authors made significantcontributions to drafting of the manuscript. All authors read and approvedthe final manuscript.Ethics approval and consent to participateParticipants from VIDUS and ACCESS cohorts have provided informedconsent. The cohorts have received ethical approval by the University ofBritish Columbia/Providence Health Care Research Ethics Board.Consent for publicationNot applicableCompeting interestsThe authors declare that they have no competing interests.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Author details1British Columbia Centre for Excellence in HIV/AIDS, St. Paul’s Hospital,608-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada. 2British ColumbiaCentre on Substance Use, St. Paul’s Hospital, 1081 Burrard Street, Vancouver,BC V6Z 1Y6, Canada. 3Faculty of Health Sciences, Simon Fraser University,Blusson Hall, 8888 University Drive, Burnaby, BC V5A 1S6, Canada.4Department of Medicine, University of British Columbia, 2775 Laurel Street,Vancouver, BC V5Z 1M9, Canada.Received: 14 November 2017 Accepted: 12 January 2018References1. Davis L, Uezato A, Newell JM, Frazier E. 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J Psychosom Res. 1999;46(5):437–43.•  We accept pre-submission inquiries •  Our selector tool helps you to find the most relevant journal•  We provide round the clock customer support •  Convenient online submission•  Thorough peer review•  Inclusion in PubMed and all major indexing services •  Maximum visibility for your researchSubmit your manuscript atwww.biomedcentral.com/submitSubmit your next manuscript to BioMed Central and we will help you at every step:Beaulieu et al. Substance Abuse Treatment, Prevention, and Policy  (2018) 13:3 Page 8 of 8

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