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RESEARCH ARTICLE
Supervised injection facility use and all-cause
mortality among people who inject drugs in
Vancouver, Canada: A cohort study
Mary Clare Kennedy
1,2
*, Kanna HayashiID
1,3
, M-J MilloyID
1,2
, Evan Wood
1,2
,
Thomas KerrID
1,2
1British Columbia Centre on Substance Use, St. Paul’s Hospital, Vancouver, British Columbia, Canada,
2Department of Medicine, University of British Columbia, St. Paul’s Hospital, Vancouver, British Columbia,
Canada, 3Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
*bccsu-mck@bccsu.ubc.ca
Abstract
Background
People who inject drugs (PWID) experience elevated rates of premature mortality. Although
previous studies have demonstrated the role of supervised injection facilities (SIFs) in
reducing various harms associated with injection drug use, including accidental overdose
death, the possible impact of SIF use on all-cause mortality is unknown. Therefore, we
examined the relationship between frequent SIF use and all-cause mortality among PWID
in Vancouver, Canada.
Methods and findings
Data were derived from 2 prospective cohort studies of PWID in Vancouver, Canada,
between December 2006 and June 2017. Every 6 months, participants completed question-
naires that elicited information regarding sociodemographic characteristics, substance use
patterns, social-structural exposures, and use of health services including SIFs. These data
were confidentially linked to the provincial vital statistics database to ascertain mortality
rates and causes of death. We used multivariable extended Cox regression analyses to esti-
mate the independent association between frequent (i.e., at least weekly) SIF use and all-
cause mortality. Of 811 participants, 278 (34.3%) were women, and the median age was 39
years (IQR 33–46) at baseline. In total, 432 (53.3%) participants reported frequent SIF use
at baseline, and 379 (46.7%) did not. At baseline, frequent SIF users were on average youn-
ger than nonfrequent users, and a higher proportion of frequent SIF users than nonfrequent
users were unstably housed, resided in the Downtown Eastside neighbourhood, injected in
public, had a recent non-fatal overdose, used prescription opioids at least daily, injected her-
oin at least daily, injected cocaine at least daily, and injected crystal methamphetamine at
least daily. A lower proportion of frequent SIF users than nonfrequent users were HIV posi-
tive and enrolled in addiction treatment at baseline. The median duration of follow-up among
study participants was 72 months (IQR 24–123). In total, 112 participants (13.8%) died dur-
ing the study period, yielding a crude mortality rate of 22.7 (95% CI 18.7–27.4) deaths per
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 1 / 20
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OPEN ACCESS
Citation: Kennedy MC, Hayashi K, Milloy MJ,
Wood E, Kerr T (2019) Supervised injection facility
use and all-cause mortality among people who
inject drugs in Vancouver, Canada: A cohort study.
PLoS Med 16(11): e1002964. https://doi.org/
10.1371/journal.pmed.1002964
Academic Editor: Alexander C. Tsai,
Massachusetts General Hospital, UNITED STATES
Received: June 14, 2019
Accepted: October 18, 2019
Published: November 26, 2019
Copyright: ©2019 Kennedy et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data cannot be
shared publicly as this is not permitted under the
parameters of our research ethics approval.
However, anonymized data will be made available
to researchers who meet specific criteria set in the
relevant ethics approval. To enquire about access,
contact the University of British Columbia/
Providence Health Care Research Ethics Board via
the research administration office of the British
Columbia Centre on Substance Use:
inquiries@bccsu.ubc.ca.
1,000 person-years. The median years of potential life lost per death was 34 (IQR 27–42)
years. In a time-updated multivariable model, frequent SIF use was inversely associated
with risk of all-cause mortality after adjusting for potential confounders, including age, sex,
HIV seropositivity, unstable housing, at least daily cocaine injection, public injection, incar-
ceration, enrolment in addiction treatment, and calendar year of interview (adjusted hazard
ratio 0.46, 95% CI 0.26–0.80, p= 0.006). The main study limitations are the limited gener-
alizability of findings due to non-random sampling, the potential for reporting biases due to
reliance on some self-reported information, and the possibility that residual confounding
influenced findings.
Conclusions
We observed a high burden of premature mortality among a community-recruited cohort of
PWID. Frequent SIF use was associated with a lower risk of death, independent of relevant
confounders. These findings support efforts to enhance access to SIFs as a strategy to
reduce mortality among PWID. Further analyses of individual-level data are needed to
determine estimates of, and potential causal pathways underlying, associations between
SIF use and specific causes of death.
Author summary
Why was this study done?
• Previous studies have indicated that supervised injection facilities contribute to reduc-
tions in overdose-related deaths. However, it is not known if supervised injection facility
use may shape risk of all-cause mortality.
• From a public health perspective, this is an important topic to investigate given the
urgent need for evidence-based interventions to address the disproportionately high
rates of premature mortality experienced by people who inject drugs in many settings
internationally.
What did the researchers do and find?
• In this study, we prospectively followed a community-recruited cohort of 811 people
who inject drugs in Vancouver, Canada, for a median follow-up duration of 6 years.
• We longitudinally assessed the association between frequent supervised injection facility
use and all-cause mortality using extended Cox regression with time-updated
covariates.
• We found that this cohort of people who inject drugs experienced a high burden of pre-
mature mortality. A total of 112 participants (13.8%) died during follow-up, yielding a
crude mortality rate of 22.7 (95% confidence interval 18.7–27.4) deaths per 1,000 per-
son-years and a median of 34 years of potential life lost (interquartile range 27–42) per
death.
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 2 / 20
Funding: This study was supported by the US
National Institutes of Health (U01DA038886,
U01DA021525). This research was undertaken, in
part, thanks to funding from the Canada Research
Chairs program through a Tier 1 Canada Research
Chair in Addiction Medicine, which supports EW.
MCK is supported by a Canadian Institutes of
Health Research (CIHR) Fellowship Award. TK is
supported by a CIHR Foundation grant
(20R74326). KH is supported by a CIHR New
Investigator Award (MSH-141971), a Michael
Smith Foundation for Health Research (MSFHR)
Scholar Award, and the St. Paul’s Hospital
Foundation. MJM is supported by a CIHR New
Investigator Award, a MSFHR Scholar Award, and
the National Institutes of Drug Abuse
(U01DA0251525). The funders had no role in study
design, data collection and analysis, decision to
publish, or preparation of the manuscript.
Competing interests: I have read the journal’s
policy and the authors of this manuscript have the
following competing interests: MJM’s institution
has received an unstructured gift to support his
research from NG Biomed, Ltd, an applicant to the
Canadian federal government for a license to
produce medical cannabis. He is the Canopy
Growth Professor of cannabis science at the
University of British Columbia, a position created
by an unstructured gift to the university from
Canopy Growth, a licensed producer of cannabis,
and the Government of British Columbia’s Ministry
of Mental Health and Addictions. KH has an unpaid
appointment as a member of the Scientific and
Research Staff at the Department of Family and
Community Practice of the Vancouver Coastal
Health Authority, which runs supervised injection
facilities that were examined in the present study.
However, neither the health authority nor the
aforementioned funders had a role in the study
design; collection, analysis and interpretation of
data; writing of the paper; or decision to submit for
publication. All other authors have declared that
they have no competing interests.
Abbreviations: ACCESS, AIDS Care Cohort to
evaluate Exposure to Survival Services; PWID,
people who inject drugs; SIF, supervised injection
facility; VIDUS, Vancouver Injection Drug Users
Study; YPLL, years of potential life lost.
• We also found that individuals who reported using supervised injection facilities on an
at least weekly basis had a reduced risk of dying compared to those who reported less
than weekly or no use of this health service. This association held after statistical adjust-
ment for potential confounders including age, sex, HIV seropositivity, unstable housing,
at least daily cocaine injection, public injection, incarceration, enrolment in addiction
treatment, and calendar year of interview (adjusted hazard ratio 0.46, 95% confidence
interval 0.26–0.80, p= 0.006).
What do these findings mean?
• These findings suggest that increasing access to supervised injection facilities may help
to prevent premature mortality among people who inject drugs.
• Additional studies should be conducted to determine individual-level estimates of the
impact of supervised injection facility use on specific causes of death, and to discern
possible underlying mechanisms that may account for these potential associations.
Introduction
People who inject drugs (PWID) are known to be at heightened risk of premature mortality. A
2013 systematic review and meta-analysis of 67 cohort studies estimated that PWID worldwide
have a crude all-cause mortality rate of 2.4 deaths per 100 person-years, a rate 14.7 times that
of the general population [1]. Globally, the leading causes of death among PWID are accidental
drug overdose and HIV-related disease [1], and in the US and Canada in particular, overdose
deaths have increased dramatically in recent years to become a leading cause of accidental
death at the general population level [2,3]. As a result of this rise in overdose deaths, average
life expectancy of the general population has recently declined in the US, and has failed to
increase in Canada for the first time in over 4 decades [3,4]. In addition, previous studies
undertaken in diverse settings internationally have found that other underlying causes of
death, including suicide, liver-related conditions, and other non-accidental causes (e.g., circu-
latory and respiratory infections or diseases), are also common among PWID [5–9].
As part of efforts to address the health and social harms stemming from injection drug use,
including mortality and morbidity related to overdose and infectious diseases, an increasing
number of cities worldwide have opened supervised injection facilities (SIFs) [10,11]. SIFs pro-
vide regulated spaces in which individuals can inject previously acquired illicit drugs under
the supervision of health professionals or trained staff [11]. Within SIFs, clients are typically
provided with sterile drug use equipment, education on safer drug consumption practices,
emergency intervention in the event of overdose, and referrals to co-located and external
addiction treatment and health services [11]. At present, more than 140 SIFs are in operation
internationally, including in Canada, Australia, and Europe [10–15].
In 2003, North America’s first government-sanctioned SIF, Insite, was established in the
Downtown Eastside of Vancouver, Canada, a neighbourhood characterized by a large open
drug scene and high levels of marginalization and criminalization [16]. This facility remained
the only sanctioned SIF in North America until 2016, when additional SIFs began to be estab-
lished and legally authorized in Canada in response to the overdose crisis [16]. Since then, a
total of 39 SIFs have been federally sanctioned and are now operating in cities across the
Supervised injection facility use and all-cause mortality
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country, 3 of which are located in Vancouver [12]. In addition, more than 30 provincially sanc-
tioned low-threshold SIFs, known as overdose prevention sites, have been implemented in
Canada since 2016, 6 of which are presently operating in Vancouver [13,14,16,17]. In the US,
no SIFs have received formal legal sanctions to operate to date, although several major cities
are currently considering authorizing such facilities, and an unsanctioned SIF has been operat-
ing in an undisclosed urban area in the country since 2014 [18].
Evaluations of SIFs in Canada and international settings have provided extensive evidence
of the effectiveness of this form of health intervention [11,19,20]. For instance, past studies
have consistently shown that SIFs effectively attract and retain their target client population,
including PWID who contend with structural vulnerabilities (e.g., homelessness) and engage
in drug use practices associated with heightened risk of morbidity and mortality (e.g., public
injection, binge injection, frequent injection) [6,21–31]. Additionally, studies have identified
associations between SIF use and various positive changes in health-related outcomes among
PWID, including reduced likelihood of engaging in injection practices associated with infec-
tious disease transmission (e.g., syringe sharing), as well as increased uptake of addiction treat-
ment and other health and social services [21,32–43]. Past research has also found that SIFs
contribute to reductions in overdose-related morbidity and mortality [13,44–49]. For example,
a geospatial analysis of death records demonstrated that the establishment of Insite in Vancou-
ver was associated with a 35% population-level decrease in the fatal overdose rate in the area
surrounding the SIF, compared to a 9% decrease in the rest of the city [44]. Further, a recent
mathematical modelling study estimated that between 160 and 350 overdose deaths were
averted by SIFs operating in Vancouver and other municipalities in British Columbia between
April 2016 and December 2017 [13].
Although these latter analyses indicate a protective role of SIFs against overdose mortality,
we know of no studies that have examined the potential impact of SIF use on all-cause mortal-
ity. Information concerning the relationship between SIF use and mortality may be of public
health importance given that evidence-based interventions to mitigate premature death
among PWID are urgently needed at present, and that many jurisdictions in Canada and else-
where are currently debating the merits of implementing SIFs as a strategy to address drug-
related harms [12,16,18]. We therefore undertook the present study to examine the association
between frequent SIF use and all-cause mortality among a community-recruited cohort of
PWID in Vancouver, Canada, between 2006 and 2017. We also sought to examine the fre-
quency and distribution of premature mortality in this cohort by estimating the years of poten-
tial life lost (YPLL) among individuals who died during follow-up.
Methods
Study sample
The Vancouver Injection Drug Users Study (VIDUS) and the AIDS Care Cohort to evaluate
Exposure to Survival Services (ACCESS) are 2 concurrent community-recruited prospective
cohort studies of people who use drugs in Vancouver, Canada. Participants have been
recruited through self-referral, snowball sampling, and street outreach since May 1996. These
cohorts have been described in detail previously [50,51]. In brief, persons are eligible for
VIDUS if they report having injected illicit drugs at least once in the previous month at enrol-
ment. Persons are eligible for ACCESS if they are HIV-infected and report having used illicit
drugs in the previous month at enrolment. Individuals who seroconvert following recruitment
are transferred from VIDUS into ACCESS, although ACCESS also includes individuals not
previously followed in VIDUS who meet the ACCESS study eligibility criteria. All enrolled
study participants provide written informed consent. The VIDUS and ACCESS studies have
Supervised injection facility use and all-cause mortality
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been approved by the University of British Columbia/Providence Health Care Research Ethics
Board (H05-50234; H05-50233; H14-01396).
At baseline and every 6 months thereafter, study participants in both cohorts complete a
harmonized interviewer-administered questionnaire that elicits information regarding socio-
demographic characteristics, drug use and other behavioural patterns, social-structural expo-
sures, and use of health services including SIFs. In addition, participants provide blood
samples for HIV testing or disease monitoring, as appropriate, and hepatitis C testing. At the
conclusion of each study visit, participants receive a Can$40 honorarium.
We restricted the present analyses to participants who completed at least 1 baseline or fol-
low-up interview between December 1, 2006, and June 30, 2017 (the time period during which
all variables of interest were available) in which they reported having injected drugs in the pre-
vious 6 months. As previously mentioned, SIF use has been associated with a number of nota-
ble health benefits for PWID [11,19,20]. However, existing literature also indicates that PWID
who engage with this health service tend to be more likely than non-users to possess various
markers of structural vulnerability and drug-related risk and therefore may have an inherently
greater risk of death [6,21–31]. We expected that such selection effects would preclude individ-
uals who had never used SIFs from being an appropriate comparison population when exam-
ining the association between frequent SIF use and mortality, as has been described in studies
of frequent needle exchange use [52]. Thus, in effort to mitigate potential bias due to lack of
comparability of exposure variable groups (with respect to balance of potential confounding
factors) when estimating this association [53–56], we further restricted our analyses to partici-
pants who reported having used a SIF use at least once in the past 6 months in 50% of their
available study visits. The 50% of available study visits cutoff point was employed for this
restriction criterion given that participants who reported having used a SIF at least once during
follow-up reported past-6-month SIF use in a median of 53.8% of their available study visits.
Thus, applying this sample restriction was intended to exclude individuals who rarely or never
used SIFs during follow-up and who therefore may have systematically differed in terms of
their overall mortality risk profile in comparison to those who used this health service more
consistently during follow-up. We expected that this approach would allow us to minimize the
potential for bias due to selection effects and confounding when estimating the association of
interest by reducing variation in the values of confounders, including unknown and unmea-
sured confounders, in the study sample [53,55,56].
Measures
The primary outcome for this analysis was all-cause mortality. This variable and specific
underlying causes of death were ascertained through confidential record linkages with the
British Columbia Vital Statistics Agency, the centralized mortality registry for the province,
using government-issued personal health numbers. The Vital Statistics Agency database
recorded causes of death during the study period in accordance with the International Classifi-
cation of Diseases and Related Health Problems–10th Revision (ICD-10) codes used in medi-
cal records. To avoid potential bias due to long durations between study visits and death [6],
individuals who died more than 24 months after their last recorded follow-up visit were cen-
sored on the date of their last study visit. Consistent with previous studies of PWID [1,6–8],
causes of death were classified into the following 8 categories: HIV-related, overdose, liver-
related, homicide, suicide, other accidental, other non-accidental, and ill-defined/unknown
causes. The primary exposure of interest was frequent SIF use. This was defined in response to
one of the following questions: “In the last 6 months, how often have you used Insite to inject?”
(December 2006 to November 2016) or “In the last 6 months, how often have you used
Supervised injection facility use and all-cause mortality
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supervised injection facilities to inject?” (December 2016 to June 2017, as additional SIFs and
overdose prevention sites began operating in Vancouver in December 2016 [16]). Consistent
with our past work [33,35], responses were classified as at least once a week versus less than
once a week (including no use).
To examine the independent association between frequent SIF use and all-cause mortality,
we assessed the following as potential confounding variables on the basis of previous literature
concerning mortality and SIF use among PWID [1,6,8,21–26,29]: age (per year older), sex
(male versus female), ancestry (white versus non-white), HIV status (positive versus negative
serological test); hepatitis C virus status (positive versus negative serological test), and heavy
alcohol use (average of >3 alcoholic drinks per occasion at least once per week or >7 drinks in
total per week in the previous 6 months for women, and average of >4 alcoholic drinks per
occasion at least once per week or >14 drinks in total per week in the previous 6 months for
men [57]). Other potential confounders examined included Downtown Eastside residence,
unstable housing, binge injection drug use, public injection drug use, non-fatal overdose,
enrolment in addiction treatment, exposure to violence, incarceration, involvement in sex
work, and benzodiazepine use (all yes versus no). Finally, we assessed as confounders frequent
use of injection heroin, injection cocaine, injection crystal methamphetamine, non-injection
crack cocaine, injection or non-injection prescription opioids, and cannabis (all at least daily
versus less than daily). Variable definitions were consistent with those used in our previous
work [6,35,58,59]. Unless otherwise indicated, all variables refer to activities and experiences
that occurred in the 6-month period preceding the date of the interview, and were treated as
time-updated based on each semi-annual follow-up visit.
Analysis
First, we examined descriptive statistics and estimated odds ratios to compare the baseline
characteristics of cohort participants who were included in the study with those who were not.
Next, we calculated the crude mortality rates and 95% confidence intervals [CIs] for all-cause
mortality and each specific cause of death using the Poisson distribution. To investigate pre-
mature mortality among the study sample, we calculated the YPLL for each decedent using the
method described by Arago
´n and colleagues [60]. As previously [61,62], we used conservative
life expectancy estimates based on data for the province of British Columbia from Statistics
Canada (84.6 years for females and 80.1 years for males) [4] and calculated the median YPLL
per death and rate of YPLL per 100,000 population. We then examined descriptive statistics
and estimated odds ratios to compare baseline characteristics of those who reported frequent
SIF use at baseline with those who did not. Next, we used bivariable extended Cox regression
analyses with time-updated covariates to examine the association between each explanatory
variable (i.e., frequent SIF use and all hypothesized potential confounders) and all-cause mor-
tality. We then applied an a priori–defined statistical protocol to estimate the independent
association between frequent SIF use and all-cause mortality. First, we fit a multivariable
model that included frequent SIF use and all hypothesized potential confounders as explana-
tory variables. Next, we removed the hypothesized confounding variable corresponding to the
smallest relative change in the frequent SIF use coefficient. We continued this iterative process
until the minimum change in the value of the coefficient for frequent SIF use exceeded 5%.
Lastly, age, sex, and unstable housing were forced into the model to account for the established
associations between these variables and the primary exposure and outcome variables of inter-
est [6,21–26,29,58]. For all participants, time 0 was defined as the date of first report of past-
6-month injection drug use during the study period given that only active injectors are eligible
to use SIFs. Participants who did not die during follow-up were right censored at the date of
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PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 6 / 20
their latest interview, their first report of having not injected drugs in the previous 6 months,
or June 30, 2017, whichever came first. We also conducted sensitivity analyses to determine
whether using an alternative measure of SIF use or broadening our study sample inclusion cri-
teria would significantly alter our results (see S1 Text). We conducted all statistical analyses
with SAS version 9.4 (SAS Institute, Cary, NC), and all reported p-values are 2-sided. The
study analysis plan is included as S2 Text. The study is reported in accordance with the
Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines
for cohort studies (see S1 STROBE Checklist).
Results
Between December 2006 and June 2017, 2,139 participants were recruited into the cohorts. As
shown in Fig 1, 1,328 individuals were excluded from the present study because they either did
not report past-6-month injection drug use in any study interviews during the study period
(n= 262) or did not report past-6-month SIF use in at least 50% of their available interviews
(n= 1,066). Compared with participants included in the analytic sample (n= 811), those
excluded (n= 1,328) were more likely to be older, be HIV seropositive, and report heavy alco-
hol use at baseline (all p<0.05). Additionally, participants excluded from the analytic sample
were less likely than those included to reside in the Downtown Eastside, be unstably housed,
be hepatitis C seropositive, inject heroin at least daily, inject cocaine at least daily, inject crystal
methamphetamine at least daily, use prescription opioids at least daily, use crack cocaine at
least daily, inject in public, binge inject, have had a recent non-fatal overdose, have recently
experienced violence, have recently engaged in sex work, and have been recently incarcerated
at baseline (all p<0.05). S3 Text reports the results of analyses comparing the baseline charac-
teristics of individuals who reported past-6-month SIF use in at least 50% of their available
study visits and were therefore included in the analytic sample (n= 811) versus those who did
not and were therefore excluded from the analytic sample (n= 1,066) among cohort partici-
pants who completed at least 1 interview during the study period in which they reported hav-
ing injected drugs in the previous 6 months (n= 1,877).
Fig 1. Flowchart showing how the analytical sample (n= 811) was determined. ACCESS, AIDS Care Cohort to
evaluate Exposure to Survival Services; VIDUS, Vancouver Injection Drug Users Study.
https://doi.org/10.1371/journal.pmed.1002964.g001
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The 811 PWID included in present study were followed for a median duration of 72
months (interquartile range [IQR] 24–123) and collectively contributed a total of 4,928.1 per-
son-years of observation. At baseline, 278 (34.3%) study participants were women, and the
median age was 39 years (IQR 33–46). A total of 432 (53.3%) participants reported frequent
(i.e., at least weekly) SIF use at baseline. Table 1 reports the baseline characteristics of the study
participants stratified by frequent SIF use. As shown, at baseline, persons who reported fre-
quent SIF use were more likely than those who did not to be younger (median age = 38 versus
40 years), reside in the Downtown Eastside (84.7% versus 75.9%), be unstably housed (85.4%
versus 78.1%), inject heroin at least daily (52.9% versus 30.1%), inject cocaine at least daily
(17.4% versus 6.3%), inject crystal methamphetamine at least daily (12.8% versus 7.4%), use
prescription opioids at least daily (14.2% versus 5.8%), inject in public (64.4% versus 52.4%),
have had a recent non-fatal overdose (14.0% versus 9.5%), and have been recently incarcerated
(31.5% versus 16.6%). Those who reported frequent SIF use at baseline were less likely to be
HIV seropositive (25.3% versus 36.2%) and to be enrolled in addiction treatment (48.8% ver-
sus 56.7%) at baseline.
A total of 112 participants (13.8%) died during the 10.5-year study period, corresponding
to a crude mortality rate of 22.7 deaths (95% CI 18.7–27.4) per 1,000 person-years. The under-
lying causes of death are presented in Table 2. The leading observed causes of death were as
follows: other non-accidental (n= 30; 26.8%), ill-defined/unknown causes (n= 27; 24.1%),
overdose (n= 19; 16.7%), and HIV-related causes (n= 15; 13.4%). The median YPLL per death
was 33.6 (IQR 26.9–41.7) years, and the estimated rate was 3,431,827 (95% CI 3,231,297–
3,632,356) YPLL per 100,000 population.
Table 3 presents the crude and adjusted hazard ratios (HRs) for the associations between
the explanatory variables and all-cause mortality. In bivariable extended Cox regression analy-
ses, frequent SIF use was significantly and inversely associated with all-cause mortality (HR
0.57, 95% CI 0.34–0.94, p= 0.029). In the final multivariable Cox regression model, frequent
SIF use remained significantly associated with decreased risk of all-cause mortality after adjust-
ing for age, sex, HIV seropositivity, unstable housing, at least daily cocaine injection, public
injection, incarceration, enrolment in addiction treatment, and calendar year of interview
(adjusted HR 0.46, 95% CI 0.26–0.80, p= 0.006).
Discussion
In this 10.5-year study of a community-recruited cohort of more than 800 PWID in Vancou-
ver, Canada, we observed a high burden of premature death, with an estimated crude mortality
rate of 22.7 deaths per 1,000 person-years and a median of 34 YPLL per death. The primary
causes of death were other non-accidental, ill-defined or unknown factors, accidental over-
dose, and HIV-related causes. We found that frequent SIF use was associated with lower risk
of all-cause mortality, independent of potential confounders including sociodemographic
characteristics, unstable housing, HIV seropositivity, at least daily cocaine injection, public
injection, incarceration, enrolment in addiction treatment, and calendar year of interview.
Existing modelling and simulation studies indicate that SIFs avert numerous overdose
deaths per year [13,48,49]. Moreover, past research relying on aggregate data has demonstrated
the role of SIFs in reducing local population-based rates of fatal overdose [44,47]. However, we
believe that ours is the first study to identify an individual-level association between frequent
SIF use and decreased risk of all-cause mortality among a community-recruited cohort of
PWID.
There are likely multiple explanations for the protective association between frequent SIF
use and death observed in the present study. For instance, SIF use has been associated with
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Table 1. Characteristics of 811 people who inject drugs in Vancouver, Canada, stratified by at least weekly supervised injection facility (SIF) use at baseline, 2006–
2017.
Characteristic Total
(n= 811)
At least weekly SIF useOdds ratio (95% CI)
Yes
(n= 432)
No
(n= 379)
Age
Median [IQR] 39 [33–46] 38 [32–45] 40 [33–48] 0.98 (0.96–0.99)
Sex
Male 532 (65.7) 281 (65.4) 250 (66.0) 0.97 (0.73–1.30)
Female 278 (34.3) 149 (34.7) 129 (34.0)
Ancestry
White 526 (64.9) 282 (65.6) 244 (64.4) 1.05 (0.79–1.41)
Non-white 284 (35.1) 148 (34.4) 135 (35.6)
Downtown Eastside residence
Yes 653 (80.5) 366 (84.7) 287 (75.9) 1.76 (1.24–2.50)
No 158 (19.5) 66 (15.3) 91 (24.1)
Unstable housing
Yes 663 (81.9) 367 (85.4) 296 (78.1) 1.63 (1.14–2.35)
No 147 (18.2) 63 (14.7) 83 (21.9)
HIV seropositive
Yes 246 (30.3) 109 (25.3) 137 (36.2) 0.60 (0.44–0.81)
No 566 (69.7) 322 (74.7) 242 (63.9)
Hepatitis C seropositive
Yes 691 (85.3) 375 (87.0) 315 (83.3) 1.34 (0.91–1.98)
No 119 (14.7) 56 (13.0) 63 (16.7)
Heroin injection
At least daily 342 (42.2) 228 (52.9) 114 (30.1) 2.61 (1.95–3.49)
Less than daily 469 (57.8) 203 (47.1) 265 (69.9)
Cocaine injection
At least daily 99 (12.2) 75 (17.4) 24 (6.3) 3.13 (1.93–5.06)
Less than daily 711 (87.8) 355 (82.6) 355 (93.7)
Crystal methamphetamine injection
At least daily 83 (10.3) 55 (12.8) 28 (7.4) 1.84 (1.14–2.97)
Less than daily 726 (89.7) 374 (87.2) 351 (92.6)
Non-injection crack cocaine use
At least daily 314 (38.8) 177 (41.1) 137 (36.2) 1.23 (0.92–1.63)
Less than daily 496 (61.2) 254 (58.9) 241 (63.8)
Prescription opioid use
At least daily 83 (10.2) 61 (14.2) 22 (5.8) 2.68 (1.61–4.45)
Less than daily 728 (89.8) 370 (85.9) 357 (94.2)
Cannabis use
At least daily 174 (21.5) 86 (20.0) 88 (23.3) 0.82 (0.59–1.15)
Less than daily 635 (78.5) 345 (80.1) 289 (76.7)
Benzodiazepine use
Yes 28 (3.5) 12 (2.8) 15 (4.0) 0.70 (0.32–1.50)
No 783 (96.6) 419 (97.2) 364 (96.0)
Heavy alcohol use
†
Yes 96 (11.8) 51 (11.8) 45 (11.9) 0.99 (0.65–1.52)
No 715 (88.2) 381 (88.2) 333 (88.1)
Public injection
(Continued)
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 9 / 20
positive changes in various injecting practices, including declines in syringe sharing, syringe
reuse, outdoor injecting, and rushed injecting, thereby reducing the risk of acquiring HIV and
other common viral and bacterial infections that may contribute to premature mortality
[21,32,43,63]. In addition, the provision of rapid, well-equipped emergency response in the
event of overdose within SIFs (e.g., oxygen and naloxone administration) has served to prevent
the occurrence of on-site overdose deaths [11,19]. Indeed, no overdose deaths have ever
occurred within any SIF in operation in Canada or internationally to date [11,19]. Further,
regular SIF use and contact with addiction counsellors within SIFs have been associated with
increased engagement with addiction treatment, including residential treatment and opioid
agonist therapy [33–36,39], which may help to prevent deaths related to ongoing high-risk
drug use [6,35,64–66]. SIFs may also mitigate mortality related to diverse causes by enhancing
connections to other internal and external health and social services [37,38,40–42,67–72]. For
example, studies of SIF clients in Vancouver have found that SIF nurses facilitate early inter-
vention for the treatment of cutaneous injection-related infections, including by providing
care for these conditions and referrals to hospital, which may prevent these from advancing to
more severe forms of infection that could lead to death [37,38,70,71]. However, interpretations
of the underlying explanations for the observed association between frequent SIF use and
Table 1. (Continued)
Characteristic Total
(n= 811)
At least weekly SIF useOdds ratio (95% CI)
Yes
(n= 432)
No
(n= 379)
Yes 476 (58.8) 277 (64.4) 198 (52.4) 1.65 (1.24–2.18)
No 333 (41.2) 153 (35.6) 180 (47.6)
Binge injection
Yes 264 (32.6) 140 (32.4) 123 (32.7) 0.99 (0.73–1.33)
No 545 (67.4) 292 (67.6) 253 (67.3)
Non-fatal overdose
Yes 96 (11.9) 60 (14.0) 36 (9.5) 1.55 (1.00–2.40)
No 714 (88.2) 370 (86.0) 343 (90.5)
Enrolled in addiction treatment
Yes 426 (52.6) 210 (48.8) 215 (56.7) 0.73 (0.55–0.96)
No 384 (47.4) 220 (51.2) 164 (43.3)
Exposure to violence
Yes 242 (30.1) 140 (32.8) 102 (27.0) 1.32 (0.97–1.79)
No 563 (69.9) 287 (67.2) 276 (73.0)
Sex work involvement
Yes 148 (18.3) 78 (18.2) 70 (18.5) 0.98 (0.68–1.40)
No 659 (81.7) 351 (81.8) 308 (81.5)
Incarceration
Yes 198 (24.5) 135 (31.5) 63 (16.6) 2.30 (1.64–3.23)
No 610 (75.5) 294 (68.5) 316 (83.4)
Data are provided as n(percentage) unless otherwise indicated. Column counts may not necessarily sum to column totals due to missing baseline data, and column
percentages may not necessarily sum to 100% due to rounding error.
Refers to the 6-month period prior to the baseline study visit.
†
Average of >3 alcoholic drinks on at least 1 day per week or >7 drinks in total per week for women, or >4 alcoholic drinks on at least 1 day per week or >14 drinks in
total per week for men.
SIF, supervised injection facility.
https://doi.org/10.1371/journal.pmed.1002964.t001
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 10 / 20
reduced risk of all-cause mortality cannot be confirmed based on the present analyses, and fur-
ther investigation of these issues is warranted. In particular, future studies should seek to deter-
mine individual-level estimates of the impact of SIF use on specific causes of death, and to
discern any mediating factors underlying these potential associations. This is especially impor-
tant given that almost a quarter of the deaths included in the present study were listed in the
Vital Statistics Agency database as being due to ill-defined or unknown causes, and therefore
important questions remain about the pathways and mechanisms that may explain the
observed protective relationship between SIF use and mortality among PWID in this setting.
Together with the findings of previous research [13,44,47,48], our findings underscore the
need for continued efforts to enhance access to SIFs as a strategy to reduce mortality among
PWID. In particular, given that SIFs have limited geographic coverage and that PWID have
been found to often encounter long wait times in accessing SIF services in this setting, the
broader expansion of SIFs may serve to improve service accessibility and thereby reduce the
potential for mortality and other harms among this population [13,16,73–75]. The recent
scale-up of SIFs in Vancouver and other settings in Canada provides an opportunity for future
research to further examine these issues, including the potential impacts of this expansion on
service utilization patterns and related health and social outcomes among PWID. As well, fur-
ther efforts should be undertaken to mitigate other barriers to engagement with SIFs. For
example, increasing SIF operating hours may promote more frequent use of this service, and
amending SIF regulations that have been shown to constrain access to SIFs (e.g., rules prohib-
iting the provision of manual assistance with injections within most federally sanctioned SIFs
in Canada) may help to engage vulnerable and underserved populations of PWID
[25,74,76,77].
Our findings also point to the need for further research to better understand how varying
levels of supplementary services offered within SIFs may shape risk of mortality among PWID.
For example, studies should seek to determine if the association between service use and mor-
tality differs between users of overdose prevention sites and users of conventional SIFs given
that overdose prevention sites typically offer a lower level of ancillary services and supports
Table 2. Causes of death in a study of 811 people who inject drugs in Vancouver, Canada, 2006–2017.
Cause of death nPercent Rate95% CI
All causes 112 100.0 22.7 18.7–27.4
HIV-related 15 13.4 3.0 1.7–5.0
Overdose 19 17.0 3.9 2.3–6.0
Liver-related 11 9.8 2.2 1.1–4.0
Suicide 3 2.7 0.6 0.1–1.8
Homicide 2 1.8 0.4 0.1–1.5
Other accidental 5 4.5 1.0 0.3–2.4
Substance-related 4 3.6
Other causes 1 0.9
Other non-accidental 30 26.8 6.1 4.1–8.7
Neoplasms 10 8.9
Circulatory disease 8 7.1
Respiratory disease 6 5.4
Other causes 6 5.4
Ill-defined or unknown 27 24.1 5.5 3.6–8.0
Per 1,000 person-years.
https://doi.org/10.1371/journal.pmed.1002964.t002
Supervised injection facility use and all-cause mortality
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Table 3. Unadjusted and adjusted Cox regression analyses of factors associated with all-cause mortality among people who inject drugs (n= 811) in Vancouver,
Canada, 2006–2017.
Characteristic Unadjusted Adjusted
Hazard ratio (95% CI) p-Value Hazard ratio (95% CI) p-Value
Age
Per year older 1.04 (1.01–1.07) 0.006 1.05 (1.01–1.09) 0.012
Sex
Male versus female 1.54 (0.88–2.68) 0.128 1.62 (0.89–2.96) 0.114
Ancestry
White versus non-white 0.80 (0.49–1.28) 0.345
Downtown Eastside residence
Yes versus no 1.07 (0.65–1.76) 0.788
Unstable housing
Yes versus no 1.16 (0.65–2.08) 0.614 1.39 (0.79–2.42) 0.250
HIV seropositive
Yes versus no 3.23 (2.00–5.24) <0.001 4.28 (2.63–6.96) <0.001
Hepatitis C seropositive
Yes versus no 0.99 (0.40–2.45) 0.978
At least weekly supervised injection facility use
Yes versus no 0.57 (0.34–0.94) 0.029 0.46 (0.26–0.80) 0.006
At least daily heroin injection
Yes versus no 0.58 (0.34–0.99) 0.045
At least daily cocaine injection
Yes versus no 1.67 (0.90–3.08) 0.101 1.47 (0.78–2.76) 0.232
At least daily crystal methamphetamine injection
Yes versus no 0.69 (0.28–1.72) 0.431
At least daily non-injection crack cocaine use
Yes versus no 1.32 (0.80–2.21) 0.289
At least daily prescription opioid use
Yes versus no 0.71 (0.29–1.73) 0.446
At least daily cannabis use
Yes versus no 1.26 (0.71–2.26) 0.429
Benzodiazepine use
Yes versus no 0.64 (0.16–2.55) 0.527
Heavy alcohol use
†
Yes versus no 1.30 (0.66–2.57) 0.453
Public injection
Yes versus no 0.79 (0.49–1.28) 0.341 1.48 (0.93–2.37) 0.100
Binge injection
Yes versus no 0.88 (0.54–1.43) 0.591
Non-fatal overdose
Yes versus no 0.76 (0.33–1.75) 0.518
Enrolled in addiction treatment
Yes versus no 0.63 (0.40–1.01) 0.632 0.66 (0.41–1.08) 0.102
Exposure to violence
Yes versus no 0.63 (0.31–1.32) 0.221
Sex work involvement
Yes versus no 0.97 (0.46–2.05) 0.941
Incarceration
(Continued)
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 12 / 20
(e.g., referrals, clinical care) [16]. Additionally, studies should continue to examine if specific
programming co-delivered with SIF services (e.g., naloxone distribution programs, safer drug
supply interventions, drug checking services, initiatives to support linkages to HIV care) may
extend the health impacts of this intervention [68,69,78–80].
We should note that our sensitivity analyses involving an alternative 3-level measure of SIF
use suggested an independent protective association between at least biweekly to less than
daily SIF use (versus no SIF use to once monthly SIF use) and all-cause mortality, but did not
suggest a significant association between at least daily SIF use (versus no SIF use to once
monthly SIF use) and mortality (see S1 Text). While the latter finding may seem counterintui-
tive given the main findings of the present study, this finding likely reflects the extremely high-
risk profile of daily SIF attendees [25], which may mask the protective benefits of SIF use when
comparing these individuals to PWID who rarely or never use this health service, as has been
found in studies of needle exchange use [52]. Although we sought to control for a range of
potential confounders through sample restriction and statistical adjustment, and this shifted
estimates of the association between at least daily SIF use and mortality in the direction of a
protective association, there is significant potential for residual confounding due to failure to
measure or imprecise measurement of notable potential confounders (e.g., socioeconomic
marginalization) given the observational nature of this study, which may explain why this asso-
ciation did not achieve statistical significance.
This study has a number of additional limitations. Of note, the VIDUS and ACCESS
cohorts are community-recruited, non-randomized samples of PWID, and therefore our find-
ings may not be generalizable to PWID in Vancouver or other settings. Moreover, the main
analyses presented in this study were restricted to PWID in the cohorts who reported recent
SIF use in at least half of their available study visits, which likely further reduced the generaliz-
ability of our findings and decreased the precision of estimates of association. However, con-
sistent with existing research [6,21–29,31], our findings indicate that many established risk
factors for mortality were more prevalent among this group compared to individuals who
were excluded from the study sample because they rarely or never used SIFs during the study
period (see S3 Text). As such, we believe that our approach of restricting our analyses to this
sample provided a more appropriate comparison population when examining the relationship
between frequent SIF use and mortality by promoting balance across exposure variable groups
with respect to known, unknown, and unmeasured confounders, thereby enhancing the inter-
nal validity of the study by reducing the potential for biased measures of association
[53,55,56]. We should also note that although the main study sample was restricted to individ-
uals who had used SIFs, we included observations in our analyses that captured heterogeneity
in service use over time among these individuals, including periods in which SIFs were not
used. In light of these strengths, future studies should continue to explore the application of
Table 3. (Continued)
Characteristic Unadjusted Adjusted
Hazard ratio (95% CI) p-Value Hazard ratio (95% CI) p-Value
Yes versus no 0.37 (0.14–1.02) 0.055 0.43 (0.18–1.04) 0.060
Calendar year of interview
Per year increase 0.60 (0.48–0.76) <0.001 0.52 (0.40–0.69) <0.001
Refers to the 6-month period prior to a study visit.
†
Average of >3 alcoholic drinks on at least 1 day per week or >7 drinks in total per week for women, or >4 alcoholic drinks on at least 1 day per week or >14 drinks in
total per week for men.
https://doi.org/10.1371/journal.pmed.1002964.t003
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 13 / 20
this approach when evaluating potential impacts of SIF use. Another limitation is that this
study relied on self-reported information for many measures, including SIF use given that ser-
vice use was not recorded in administrative databases at some SIFs during the study period.
Thus, our findings are susceptible to reporting biases, including social desirability bias. How-
ever, it is noteworthy that our primary outcome of mortality was based on objective measures
derived from linkages to an external administrative database. As previously noted, a further
limitation is that just under a quarter of all deaths observed in the present study were listed in
the Vital Statistics Agency database as being due to ill-defined or unknown causes, which com-
plicates interpretations of the observed protective association between SIF use and mortality.
The observed excess of deaths of unknown causes is likely largely explained by delays in updat-
ing causes of death in the database in recent years as a result of a backlog in post-death toxicol-
ogy testing due to the present overdose crisis [81]. Indeed, 55.6% of deaths of ill-defined or
unknown causes observed in the present study occurred in the last 3 years of the study period.
As such, the true prevalence of overdose-related deaths may have been underestimated in the
present study, as may have been deaths of other specific causes. However, given that our pri-
mary study aim was to examine the independent association between SIF use and all-cause
mortality (rather than distinct causes of death), we believe that the improvements in statistical
power resulting from including recent deaths in our analyses offset the potential benefits con-
cerning interpretations if we had instead restricted the study period to reduce the number of
deaths of unknown causes. As mentioned previously, an additional limitation is that the
observed relationship between frequent SIF use and decreased risk of mortality might be influ-
enced by residual confounding. Although we sought to reduce the potential for this bias by
restricting our study sample based on SIF utilization patterns and by adjusting multivariable
analyses for key confounding factors, an e-value analysis [82] indicated that an unmeasured
confounder associated with frequent SIF use and mortality by a HR equivalent to a magnitude
of at least 1.81 each could explain away the upper confidence limit (i.e., the limit closest to the
null value) for the observed adjusted HR for the association between frequent SIF use and all-
cause mortality. For example, it is possible that we did not adequately adjust for social chal-
lenges associated with mortality risk that may be less prevalent among frequent SIF users com-
pared to nonfrequent users, which could have biased our estimate of the association of interest
away from the null. In particular, past qualitative research has documented how factors such
as drug debts, street-level policing, and area restrictions (i.e., court-ordered restrictions pro-
hibiting individuals from entering areas where they have been arrested) may deter some
PWID from accessing health services concentrated within the local drug scene, including SIFs,
and increase their susceptibility to harms [83–85]. However, as discussed above, existing evi-
dence indicates that frequent SIF attendees are a particularly marginalized subpopulation of
PWID who tend to be more likely than nonfrequent attendees to contend with various charac-
teristics, behaviours, and exposures associated with heightened mortality risk [22,25]. As we
likely imprecisely measured or neglected to measure some of such risk factors (e.g., markers of
structural vulnerability and drug-related risk, comorbid conditions), we suspect that it is more
probable that our observed estimate of the association between frequent SIF use and mortality
is biased towards rather than away from the null.
In conclusion, this study of a cohort of PWID in Vancouver, Canada, reports a previously
unidentified independent association between frequent SIF use and decreased risk of all-cause
mortality. This relationship warrants further investigation. In particular, future studies should
seek to examine the individual-level association between SIF use and distinct causes of death
among PWID. Nonetheless, the findings of the present study suggest that efforts to scale up
access to SIFs may serve to reduce preventable deaths among this population.
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 14 / 20
Supporting information
S1 STROBE Checklist. STROBE checklist.
(DOCX)
S1 Text. Sensitivity analyses. ACCESS, AIDS Care Cohort to evaluate Exposure to Survival
Services; SIF, supervised injection facility; VIDUS, Vancouver Injection Drug Users Study.
(DOCX)
S2 Text. Analysis plan. ACCESS, AIDS Care Cohort to evaluate Exposure to Survival Services;
VIDUS, Vancouver Injection Drug Users Study.
(DOCX)
S3 Text. Baseline characteristics of participants included versus excluded from the analytic
sample on the basis of SIF use. ACCESS, AIDS Care Cohort to evaluate Exposure to Survival
Services; PWID, people who inject drugs; SIF, supervised injection facility; VIDUS, Vancouver
Injection Drug Users Study.
(DOCX)
Acknowledgments
The authors thank the study participants for their contribution to the research, as well as cur-
rent and past researchers and staff. We would specifically like to thank Yuko Endo, Julie
Sagram, Christine Fei, Ana Prado, Peter Vann, Jennifer Matthews, Steve Kain, Ekaterina
Nosova, Janet Mok, and Huiru Dong for their research and administrative assistance. The
authors also gratefully acknowledge that this research took place on the unceded traditional
territories of the xʷməθkwəy̓əm (Musqueam), Skwxwu
´7mesh (Squamish), and sel
´ı
´ll
´witulh
(Tsleil-waututh) Nations.
Author Contributions
Conceptualization: Mary Clare Kennedy, Thomas Kerr.
Formal analysis: Mary Clare Kennedy.
Funding acquisition: Mary Clare Kennedy, Kanna Hayashi, MJ Milloy, Evan Wood, Thomas
Kerr.
Investigation: Mary Clare Kennedy, Kanna Hayashi, MJ Milloy, Evan Wood, Thomas Kerr.
Methodology: Mary Clare Kennedy, Thomas Kerr.
Writing – original draft: Mary Clare Kennedy.
Writing – review & editing: Mary Clare Kennedy, Kanna Hayashi, MJ Milloy, Evan Wood,
Thomas Kerr.
References
1. Mathers BM, Degenhardt L, Bucello C, Lemon J, Wiessing L, Hickman M. Mortality among people who
inject drugs: a systematic review and meta-analysis. Bull World Health Organ. 2013; 91(2):102–23.
https://doi.org/10.2471/BLT.12.108282 PMID: 23554523
2. Health Canada. National report: apparent opioid-related deaths in Canada (September 2019). Ottawa:
Government of Canada; 2019 [cited 2019 Oct 21]. Available from: https://health-infobase.canada.ca/
datalab/national-surveillance-opioid-mortality.html.
3. National Institute on Drug Abuse. Overdose death rates. North Bethesda (MD): National Institute on
Drug Abuse; 2019 [cited 2019 May 29]. Available from: https://www.drugabuse.gov/related-topics/
trends-statistics/overdose-death-rates.
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 15 / 20
4. Statistics Canada. Changes in life expectancy by selected causes of death, 2017. Ottawa: Statistics
Canada; 2019 [cited 2019 Jun 4]. Available from: https://www150.statcan.gc.ca/n1/daily-quotidien/
190530/dq190530d-eng.htm.
5. Darke S, Degenhardt L, Mattick R. Mortality amongst illicit drug users: epidemiology, causes and inter-
vention. Cambridge: Cambridge University Press; 2006. 145 p.
6. Hayashi K, Dong H, Marshall BDL, Milloy M-J, Montaner JSG, Wood E, et al. Sex-based differences in
rates, causes, and predictors of death among injection drug users in Vancouver, Canada. Am J Epide-
miol. 2016; 183(6):544–52. https://doi.org/10.1093/aje/kwv207 PMID: 26865265
7. Copeland L, Budd J, Robertson JR, Elton RA. Changing patterns in causes of death in a cohort of inject-
ing drug users, 1980–2001. Arch Intern Med. 2004; 164(11):1214. https://doi.org/10.1001/archinte.164.
11.1214 PMID: 15197047
8. Miller CL, Kerr T, Strathdee SA, Li K, Wood E. Factors associated with premature mortality among
young injection drug users in Vancouver. Harm Reduct J. 2007; 4:1. https://doi.org/10.1186/1477-7517-
4-1 PMID: 17201933
9. Vanichseni S, Martin M, Suntharasamai P, Sangkum U, Mock PA, Gvetadze RJ, et al. High mortality
among non-HIV-infected people who inject drugs in Bangkok, Thailand, 2005–2012. Am J Public
Health. 2015; 105(6):1136–41. https://doi.org/10.2105/AJPH.2014.302473 PMID: 25880964
10. European Monitoring Centre for Drugs and Drug Addiction. Drug consumption rooms: an overview of
provision and evidence. Lisbon: European Monitoring Centre for Drugs and Drug Addiction; 2018
[cited 2019 Jun 8]. Available from: http://www.emcdda.europa.eu/topics/pods/drug-consumption-
rooms.
11. Kennedy MC, Karamouzian M, Kerr T. Public health and public order outcomes associated with super-
vised drug consumption facilities: a systematic review. Curr HIV/AIDS Rep. 2017; 14(5):161–83. https://
doi.org/10.1007/s11904-017-0363-y PMID: 28875422
12. Health Canada. Supervised consumption sites: status of applications. Ottawa: Government of Can-
ada; 2019 [cited 2019 Jun 1]. Available from: https://www.canada.ca/en/health-canada/services/
substance-abuse/supervised-consumption-sites/status-application.html.
13. Irvine MA, Kuo M, Buxton J, Balshaw R, Otterstatter M, Macdougall L, et al. Modelling the combined
impact of interventions in averting deaths during a synthetic-opioid overdose epidemic. Addiction. 2019;
114(9): 1602–13. https://doi.org/10.1111/add.14664 PMID: 31166621
14. Perkel C. Ontario announces 15 overdose prevention sites across the province. National Post. 2019
Mar 29 [cited 2019 Jun 14]. Available from: https://nationalpost.com/pmn/news-pmn/canada-news-
pmn/ontario-announces-15-overdose-prevention-sites-across-the-province.
15. Belackova V, Salmon AM, Schatz E, Jauncey M. Drug consumption rooms (DCRs) as a setting to
address hepatitis C—findings from an international online survey. Hepatol Med Policy. 2018; 3:9.
https://doi.org/10.1186/s41124-018-0035-6 PMID: 30288332
16. Kerr T, Mitra S, Kennedy MC, McNeil R. Supervised injection facilities in Canada: past, present, and
future. Harm Reduct J. 2017; 14:28. https://doi.org/10.1186/s12954-017-0154-1 PMID: 28521829
17. Vancouver Coastal Health. Overdose prevention & response. Vancouver: Vancouver Coastal Health;
2019 [cited 2019 May 20]. Available from: http://www.vch.ca/public-health/harm-reduction/overdose-
prevention-response.
18. Davidson PJ, Lopez AM, Kral AH. Using drugs in un/safe spaces: impact of perceived illegality on an
underground supervised injecting facility in the United States. Int J Drug Policy. 2018; 53:37–44. https://
doi.org/10.1016/j.drugpo.2017.12.005 PMID: 29278831
19. Potier C, Lapre
´vote V, Dubois-Arber F, Cottencin O, Rolland B. Supervised injection services: what has
been demonstrated? A systematic literature review. Drug Alcohol Depend. 2014; 145:48–68. https://
doi.org/10.1016/j.drugalcdep.2014.10.012 PMID: 25456324
20. McNeil R, Small W. ‘Safer environment interventions’: a qualitative synthesis of the experiences and
perceptions of people who inject drugs. Soc Sci Med. 2014; 106:151–8. https://doi.org/10.1016/j.
socscimed.2014.01.051 PMID: 24561777
21. Bravo MJ, Royuela L, De la Fuente L, Brugal MT, Barrio G, Domingo-Salvany A, et al. Use of super-
vised injection facilities and injection risk behaviours among young drug injectors. Addiction. 2009; 104
(4):614–9. https://doi.org/10.1111/j.1360-0443.2008.02474.x PMID: 19215603
22. Kimber J, MacDonald M, van Beek I, Kaldor J, Weatherburn D, Lapsley H, et al. The Sydney Medically
Supervised Injecting Centre: client characteristics and predictors of frequent attendance during the first
12 months of operation. J Drug Issues. 2003; 33(3):639–48.
23. Scherbaum N, Specka M, Bombeck J, Marrziniak B. Drug consumption facility as part of a primary
health care centre for problem drug users—which clients are attracted? Int J Drug Policy. 2009; 20
(5):447–9. https://doi.org/10.1016/j.drugpo.2009.01.001 PMID: 19269803
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 16 / 20
24. Kennedy MC, Klassen DC, Dong H, Milloy M-JS, Hayashi K, Kerr TH. Supervised injection facility utili-
zation patterns: a prospective cohort study in Vancouver, Canada. Am J Prev Med. 2019; 57(3):330–7.
https://doi.org/10.1016/j.amepre.2019.04.024 PMID: 31377091
25. Wood E, Tyndall MW, Qui Z, Zhang R, Montaner JSG, Kerr T. Service uptake and characteristics of
injection drug users utilizing North America’s first medically supervised safer injecting facility. Am J Pub-
lic Health. 2006; 96(5):770–3. https://doi.org/10.2105/AJPH.2004.057828 PMID: 16571703
26. Wood E, Tyndall MW, Li K, Lloyd-Smith E, Small W, Montaner JSG, et al. Do supervised injecting facili-
ties attract higher-risk injection drug users? Am J Prev Med. 2005; 29(2):126–30. https://doi.org/10.
1016/j.amepre.2005.04.011 PMID: 16005809
27. Strathdee SA, Galai N, Safaiean M, Celentano DD, Vlahov D, Johnson L, et al. Sex differences in risk
factors for HIV seroconversion among injection drug users: a 10-year perspective. Arch Intern Med.
2001; 161(10):1281. https://doi.org/10.1001/archinte.161.10.1281 PMID: 11371255
28. Tyndall MW, Currie S, Spittal P, Li K, Wood E, O’Shaughnessy MV, et al. Intensive injection cocaine
use as the primary risk factor in the Vancouver HIV-1 epidemic. AIDS. 2003; 17(6):887. https://doi.org/
10.1097/00002030-200304110-00014 PMID: 12660536
29. Piggott DA, Muzaale AD, Mehta SH, Brown TT, Patel KV, Leng SX, et al. Frailty, HIV infection, and mor-
tality in an aging cohort of injection drug users. PLoS ONE. 2013; 8(1):e54910. https://doi.org/10.1371/
journal.pone.0054910 PMID: 23382997
30. Linton SL, Celentano DD, Kirk GD, Mehta SH. The longitudinal association between homelessness,
injection drug use, and injection-related risk behavior among persons with a history of injection drug use
in Baltimore, MD. Drug Alcohol Depend. 2013; 132(3):457–65. https://doi.org/10.1016/j.drugalcdep.
2013.03.009 PMID: 23578590
31. Galea S, Vlahov D. Social determinants and the health of drug users: socioeconomic status, homeless-
ness, and incarceration. Public Health Rep. 2002; 117:S135–45. PMID: 12435837
32. Kerr T, Tyndall M, Li K, Montaner J, Wood E. Safer injection facility use and syringe sharing in injection
drug users. Lancet. 2005; 366(9482):316–8. https://doi.org/10.1016/S0140-6736(05)66475-6 PMID:
16039335
33. Wood E, Tyndall MW, Zhang R, Stoltz J -A, Lai C, Montaner JSG, et al. Attendance at supervised inject-
ing facilities and use of detoxification services. N Engl J Med. 2006; 354(23):2512–4. https://doi.org/10.
1056/NEJMc052939 PMID: 16760459
34. Wood E, Tyndall MW, Zhang R, Montaner JSG, Kerr T. Rate of detoxification service use and its impact
among a cohort of supervised injecting facility users. Addiction. 2007; 102(6):916–9. https://doi.org/10.
1111/j.1360-0443.2007.01818.x PMID: 17523986
35. DeBeck K, Kerr T, Bird L, Zhang R, Marsh D, Tyndall M, et al. Injection drug use cessation and use of
North America’s first medically supervised safer injecting facility. Drug Alcohol Depend. 2011; 113(2–
3):172–6. https://doi.org/10.1016/j.drugalcdep.2010.07.023 PMID: 20800976
36. Gaddis A, Kennedy MC, Nosova E, Milloy M-J, Hayashi K, Wood E, et al. Use of on-site detoxification
services co-located with a supervised injection facility. J Subst Abuse Treat. 2017; 82:1–6. https://doi.
org/10.1016/j.jsat.2017.08.003 PMID: 29021106
37. Lloyd-Smith E, Wood E, Zhang R, Tyndall MW, Sheps S, Montaner JS, et al. Determinants of hospitali-
zation for a cutaneous injection-related infection among injection drug users: a cohort study. BMC Pub-
lic Health. 2010; 10(1):327.
38. Lloyd-Smith E, Tyndall M, Zhang R, Grafstein E, Sheps S, Wood E, et al. Determinants of cutaneous
injection-related infections among injection drug users at an emergency department. Open Infect Dis J.
2012; 6:5–11.
39. Kimber J, Mattick RP, Kaldor J, Van Beek I, Gilmour S, Rance J. Process and predictors of drug treat-
ment referral and referral uptake at the Sydney Medically Supervised Injecting Centre. Drug Alcohol
Rev. 2008; 27(6):602–12. https://doi.org/10.1080/09595230801995668 PMID: 19378444
40. van der Poel A, Barendregt C, van de Mheen D. Drug consumption rooms in Rotterdam: an explorative
description. Eur Addict Res. 2003; 9:94–100. https://doi.org/10.1159/000068807 PMID: 12644736
41. Zurhold H, Degkwitz P, Verthein U, Haasen C. Drug consumption rooms in Hamburg, Germany: evalua-
tion of the effects on harm reduction and the reduction of public nuisance. J Drug Issues. 2003; 33
(3):663–88.
42. Toth EC, Tegner J, Lauridsen S, Kappel N. A cross-sectional national survey assessing self-reported
drug intake behavior, contact with the primary sector and drug treatment among service users of Danish
drug consumption rooms. Harm Reduct J. 2016; 13:27. https://doi.org/10.1186/s12954-016-0115-0
PMID: 27717366
43. Kinnard EN, Howe CJ, Kerr T, Skjødt Hass V, Marshall BDL. Self-reported changes in drug use behav-
iors and syringe disposal methods following the opening of a supervised injecting facility in
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 17 / 20
Copenhagen, Denmark. Harm Reduct J. 2014; 11:29. https://doi.org/10.1186/1477-7517-11-29 PMID:
25352296
44. Marshall BDL, Milloy M-J, Wood E, Montaner JS, Kerr T. Reduction in overdose mortality after the open-
ing of North America’s first medically supervised safer injecting facility: a retrospective population-
based study. Lancet. 2011; 377(9775):1429–37. https://doi.org/10.1016/S0140-6736(10)62353-7
PMID: 21497898
45. Salmon AM, Van Beek I, Amin J, Kaldor J, Maher L. The impact of a supervised injecting facility on
ambulance call-outs in Sydney, Australia. Addiction. 2010; 105(4):676–83. https://doi.org/10.1111/j.
1360-0443.2009.02837.x PMID: 20148794
46. National Centre in HIV Epidemiology and Clinical Research. Sydney Medically Supervised Injecting
Centre evaluation report no. 4: evaluation of service operation and overdose-related events. Sydney:
University of New South Wales; 2007 [cited 2019 Oct 21]. Available from: https://kirby.unsw.edu.au/
sites/default/files/kirby/report/EvalRep4SMSIC.pdf.
47. Poschadel S, Ho
¨ger R, Schnitzler J, Schreckenberger J. Evaluation der Arbeit der Drogenkonsum-
ra
¨ume in der Bundesrepublik Deutschland: Endbericht im Auftrag des Bundesministeriums fu¨r Gesund-
heit, das Bundesministerium fu¨r Gesundheit und Soziale Sicherung. Band 149. Baden-Baden: Nomos
Verlagsgesellschaft; 2003.
48. Milloy M-J, Kerr T, Tyndall M, Montaner J, Wood E. Estimated drug overdose deaths averted by North
America’s first medically-supervised safer injection facility. PLoS ONE. 2008; 3(10):e3351. https://doi.
org/10.1371/journal.pone.0003351 PMID: 18839040
49. Hedrich D. European report on drug consumption rooms. Lisbon: European Monitoring Centre for
Drugs and Drug Addiction; 2004 [cited 2019 Oct 21]. Available from: http://www.emcdda.europa.eu/
system/files/publications/339/Consumption_rooms_101741.pdf.
50. Strathdee SA, Palepu A, Cornelisse PGA, Yip B, O’Shaughnessy MV, Montaner JSG, et al. Barriers to
use of free antiretroviral therapy in injection drug users. JAMA. 1998; 280(6):547–9. https://doi.org/10.
1001/jama.280.6.547 PMID: 9707146
51. Wood E, Tyndall MW, Spittal PM, Li K, Kerr T, Hogg RS, et al. Unsafe injection practices in a cohort of
injection drug users in Vancouver: could safer injecting rooms help? Can Med Assoc J. 2001; 165
(4):405–10.
52. Wood E, Lloyd-Smith E, Li K, Strathdee SA, Small W, Tyndall MW, et al. Frequent needle exchange
use and HIV incidence in Vancouver, Canada. Am J Med. 2007; 120(2):172–9. https://doi.org/10.1016/
j.amjmed.2006.02.030 PMID: 17275459
53. Psaty BM, Siscovick DS. Minimizing bias due to confounding by indication in comparative effectiveness
research: the importance of restriction. JAMA. 2010; 304(8):897–8. https://doi.org/10.1001/jama.2010.
1205 PMID: 20736474
54. Rothman KJ, Gallacher JE, Hatch EE. Why representativeness should be avoided. Int J Epidemiol.
2013; 42(4):1012–4. https://doi.org/10.1093/ije/dys223 PMID: 24062287
55. McGrath LJ, Ellis AR, Brookhart MA. Controlling time-dependent confounding by health status and
frailty: restriction versus statistical adjustment. Am J Epidemiol. 2015; 182(1):17–25. https://doi.org/10.
1093/aje/kwu485 PMID: 25868551
56. Secrest MH, Platt RW, Dormuth CR, Chateau D, Targownik L, Nie R, et al. Extreme restriction design
as a method for reducing confounding by indication in pharmacoepidemiologic research. Pharmacoepi-
demiol Drug Saf. 2019 Jan 9. https://doi.org/10.1002/pds.4708 PMID: 30628152
57. National Institute on Alcohol Abuse and Alcoholism. Rethinking drinking: alcohol and your health. NIH
Publication No. 15–3770. Bethesda (MD): National Institute on Alcohol Abuse and Alcoholism; 2016
[cited 2019 May 24]. Available from: https://www.niaaa.nih.gov/sites/default/files/publications/
Rethinking_Drinking.pdf.
58. Zivanovic R, Milloy M, Hayashi K, Dong H, Sutherland C, Kerr T, et al. Impact of unstable housing on
all-cause mortality among persons who inject drugs. BMC Public Health. 2015; 15:106. https://doi.org/
10.1186/s12889-015-1479-x PMID: 25884182
59. Hayden A, Hayashi K, Dong H, Milloy M-J, Kerr T, Montaner JS, et al. The impact of drug use patterns
on mortality among polysubstance users in a Canadian setting: a prospective cohort study. BMC Public
Health. 2014; 14:1153. https://doi.org/10.1186/1471-2458-14-1153 PMID: 25377274
60. Arago
´n TJ, Lichtensztajn DY, Katcher BS, Reiter R, Katz MH. Calculating expected years of life lost for
assessing local ethnic disparities in causes of premature death. BMC Public Health. 2008; 8:116.
https://doi.org/10.1186/1471-2458-8-116 PMID: 18402698
61. Milloy M-J, Wood E, Reading C, Kane D, Montaner J, Kerr T. Elevated overdose mortality rates among
First Nations individuals in a Canadian setting: a population-based analysis. Addiction. 2010; 105
(11):1962–70. https://doi.org/10.1111/j.1360-0443.2010.03077.x PMID: 20825372
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 18 / 20
62. Lloyd-Smith E, Brodkin E, Wood E, Kerr T, Tyndall MW, Montaner JS, et al. Impact of HAART and injec-
tion drug use on life expectancy of two HIV-positive cohorts in British Columbia. AIDS. 2006; 20(3):445.
https://doi.org/10.1097/01.aids.0000206508.32030.92 PMID: 16439879
63. Stoltz J-A, Wood E, Small W, Li K, Tyndall M, Montaner J, et al. Changes in injecting practices associ-
ated with the use of a medically supervised safer injection facility. J Public Health. 2007; 29(1):35–9.
64. Sordo L, Barrio G, Bravo MJ, Indave BI, Degenhardt L, Wiessing L, et al. Mortality risk during and after
opioid substitution treatment: systematic review and meta-analysis of cohort studies. BMJ. 2017; 357:
j1550. https://doi.org/10.1136/bmj.j1550 PMID: 28446428
65. Scott CK, Dennis ML, Laudet A, Funk RR, Simeone RS. Surviving drug addiction: the effect of treatment
and abstinence on mortality. Am J Public Health. 2011; 101(4):737–44. https://doi.org/10.2105/AJPH.
2010.197038 PMID: 21330586
66. Bahji A, Cheng B, Gray S, Stuart H. Reduction in mortality risk with opioid agonist therapy: a systematic
review and meta-analysis. Acta Psychiatr Scand. 2019; 140(4):313–39. https://doi.org/10.1111/acps.
13088 PMID: 31419306
67. Tyndall MW, Kerr T, Zhang R, King E, Montaner JG, Wood E. Attendance, drug use patterns, and refer-
rals made from North America’s first supervised injection facility. Drug Alcohol Depend. 2006; 83
(3):193–8. https://doi.org/10.1016/j.drugalcdep.2005.11.011 PMID: 16356659
68. Karamouzian M, Dohoo C, Forsting S, McNeil R, Kerr T, Lysyshyn M. Evaluation of a fentanyl drug
checking service for clients of a supervised injection facility, Vancouver, Canada. Harm Reduct J. 2018;
15:46. https://doi.org/10.1186/s12954-018-0252-8 PMID: 30200991
69. McNeil R, Dilley LB, Guirguis-Younger M, Hwang SW, Small W. Impact of supervised drug consumption
services on access to and engagement with care at a palliative and supportive care facility for people liv-
ing with HIV/AIDS: a qualitative study. J Int AIDS Soc. 2014; 17:18855. https://doi.org/10.7448/IAS.17.
1.18855 PMID: 24629844
70. Small W, Wood E, Lloyd-Smith E, Tyndall M, Kerr T. Accessing care for injection-related infections
through a medically supervised injecting facility: a qualitative study. Drug Alcohol Depend. 2008; 98(1–
2):159–62. https://doi.org/10.1016/j.drugalcdep.2008.05.014 PMID: 18650034
71. Lloyd-Smith E, Wood E, Zhang R, Tyndall MW, Montaner JS, Kerr T. Determinants of cutaneous injec-
tion-related infection care at a supervised injecting facility. Ann Epidemiol. 2009; 19(6):404–9. https://
doi.org/10.1016/j.annepidem.2009.03.007 PMID: 19364660
72. Small W, Van Borek N, Fairbairn N, Wood E, Kerr T. Access to health and social services for IDU: the
impact of a medically supervised injection facility. Drug Alcohol Rev. 2009; 28(4):341–6. https://doi.org/
10.1111/j.1465-3362.2009.00025.x PMID: 19594786
73. Petrar S, Kerr T, Tyndall MW, Zhang R, Montaner JSG, Wood E. Injection drug users’ perceptions
regarding use of a medically supervised safer injecting facility. Addict Behav. 2007; 32(5):1088–93.
https://doi.org/10.1016/j.addbeh.2006.07.013 PMID: 16930849
74. Small W, Shoveller J, Moore D, Tyndall M, Wood E, Kerr T. Injection drug users’ access to a supervised
injection facility in Vancouver, Canada: the influence of operating policies and local drug culture. Qual
Health Res. 2011; 21(6):743–56. https://doi.org/10.1177/1049732311400919 PMID: 21378259
75. Wood E, Tyndall MW, Montaner JS, Kerr T. Summary of findings from the evaluation of a pilot medically
supervised safer injecting facility. Can Med Assoc J. 2006; 175(11):1399–404.
76. Fairbairn N, Small W, Van Borek N, Wood E, Kerr T. Social structural factors that shape assisted inject-
ing practices among injection drug users in Vancouver, Canada: a qualitative study. Harm Reduct J.
2010; 7:20. https://doi.org/10.1186/1477-7517-7-20 PMID: 20807442
77. Gagnon M. It’s time to allow assisted injection in supervised injection sites. CMAJ. 2017; 189(34):
E1083–4. https://doi.org/10.1503/cmaj.170659 PMID: 28847779
78. Ti L, Dong H, Kerr T, Turje R, Parashar S, Min J, et al. The effect of engagement in an HIV/AIDS inte-
grated health programme on plasma HIV-1 RNA suppression among HIV-positive people who use illicit
drugs: a marginal structural modelling analysis. HIV Med. 2017; 18(8):580–6. https://doi.org/10.1111/
hiv.12493 PMID: 28317290
79. Collins AB, Parashar S, Hogg RS, Fernando S, Worthington C, McDougall P, et al. Integrated HIV care
and service engagement among people living with HIV who use drugs in a setting with a community-
wide treatment as prevention initiative: a qualitative study in Vancouver, Canada. J Int AIDS Soc. 2017;
20(1):21407. https://doi.org/10.7448/IAS.20.1.21407 PMID: 28426185
80. Wood W. Distributing “take home” naloxone via Sydney medically supervised injecting centre: where to
from here? Drug Alcohol Rev. 2015; 34(S1):67.
81. Wilson D. Toxicology backlog delaying drug overdose test results. CBC News. 2017 Mar 14 [cited 2019
May 23]; Available from: https://www.cbc.ca/news/canada/british-columbia/drugs-overdose-fentanyl-
toxicology-backlog-1.4024621.
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 19 / 20
82. VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the e-value. Ann
Intern Med. 2017; 167(4):268. https://doi.org/10.7326/M16-2607 PMID: 28693043
83. Collins AB, Boyd J, Mayer S, Fowler A, Kennedy MC, Bluthenthal RN, et al. Policing space in the over-
dose crisis: a rapid ethnographic study of the impact of law enforcement practices on the effectiveness
of overdose prevention sites. Int J Drug Policy. 2019 Sep 6. https://doi.org/10.1016/j.drugpo.2019.08.
002 PMID: 31542327
84. McNeil R, Shannon K, Shaver L, Kerr T, Small W. Negotiating place and gendered violence in Canada’s
largest open drug scene. Int J Drug Policy. 2014; 25(3):608–15. https://doi.org/10.1016/j.drugpo.2013.
11.006 PMID: 24332972
85. McNeil R, Cooper H, Small W, Kerr T. Area restrictions, risk, harm, and health care access among peo-
ple who use drugs in Vancouver, Canada: a spatially oriented qualitative study. Health Place. 2015;
35:70–8. https://doi.org/10.1016/j.healthplace.2015.07.006 PMID: 26241893
Supervised injection facility use and all-cause mortality
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002964 November 26, 2019 20 / 20
