SystematicSystematic reviews reviews

Mortality among people who inject drugs: a systematic review and meta-analysis Bradley M Mathers,a Louisa Degenhardt,b Chiara Bucello,b James Lemon,b Lucas Wiessing c & Mathew Hickman d

Objective To systematically review cohort studies of mortality among people who inject drugs, examine mortality rates and causes of death in this group, and identify participant- and study-level variables associated with a higher risk of death. Methods Tailored search strings were used to search EMBASE, Medline and PsycINFO. The grey literature was identified through online grey literature databases. Experts were consulted to obtain additional studies and data. Random effects meta-analyses were performed to estimate pooled crude mortality rates (CMRs) and standardized mortality ratios (SMRs). Findings Sixty-seven cohorts of people who inject drugs were identified, 14 of them from low- and middle-income countries. The pooled CMR was 2.35 deaths per 100 person–years (95% confidence interval, CI: 2.12–2.58). SMRs were reported for 32 cohorts; the pooled SMR was 14.68 (95% CI: 13.01–16.35). Comparison of CMRs and the calculation of CMR ratios revealed mortality to be higher in low- and middle-income country cohorts, males and people who injected drugs that were positive for human immunodeficiency virus (HIV). It was also higher during off-treatment periods. Drug overdose and acquired immunodeficiency syndrome (AIDS) were the primary causes of death across cohorts. Conclusion Compared with the general population, people who inject drugs have an elevated risk of death, although mortality rates vary across different settings. Any comprehensive approach to improving health outcomes in this group must include efforts to reduce HIV infection as well as other causes of death, particularly drug overdose.

Introduction death.3–5 Findings from other reviews have also suggested that rates of death among people who are dependent on opioids are People who use drugs, especially by injection, are at higher different from the rates of death observed in people who are risk of dying from both acute and chronic diseases, many of dependent on stimulants such as cocaine and amphetamine which are related to their drug use, than people who do not type stimulants.3–5 use these drugs. Fatal overdose and infection with human im- In recent years the number of studies reporting on mor- munodeficiency virus (HIV) and other blood-borne viruses tality among people who inject drugs has increased. Hence, transmitted through shared needles and syringes are the most the objective of this review was to determine the following: common causes of death in this group.1 Understanding causes • overall crude mortality rates (CMRs) and excess deaths of death is important when setting priorities for programmes across cohorts of people who inject drugs, by sex; designed to reduce deaths from the use of drugs. Longitudinal • causes of death across studies, particularly from drug over- studies of people who inject drugs are critical for assessing dose and acquired immunodeficiency syndrome (AIDS); the magnitude, nature and correlates of the risk of death in differences in mortality rates and causes of death among this population. HIV-positive (HIV+) and HIV-negative (HIV−) people A systematic review conducted in 2004 identified 30 pro- who inject drugs; spective studies published between 1967 and 2004 that dealt • differences in mortality rates across cohorts by geographi- with “problematic drug users” or people who inject drugs.2 cal location and country income level; These reviews have consistently shown that the practice of • mortality rates by type of drug injected (e.g. opioids versus injecting drugs is associated with an elevated risk of death, stimulants); particularly from the complications of HIV infection, drug • mortality rates during in-treatment and off-treatment overdose and suicide. Since these reviews were conducted, periods. the number of studies examining mortality among cohorts of people who inject drugs has risen substantially. This has made it possible to perform fine-grained analyses that were not feasible in earlier reviews. Furthermore, those earlier reviews Methods did not examine the potential impact of study-level variables, Identifying studies variation across countries, or of participant-level variables that could affect both mortality rates and differences in causes of A recent series of reviews identified cohort studies among opi- death, yet study-level evidence suggests that males who inject oid, amphetamine and cocaine users to examine mortality.3–5 In drugs may be at higher risk of dying than females and that these reviews tailored search strings were used to search three different types of drugs are associated with different risks of electronic databases for studies published between 1980 and

a The Kirby Institute, University of New South Wales, Sydney, NSW 2052, Australia. b National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia. c Scientific Division, European Monitoring Centre for Drugs and Drug Addiction, Lisbon, Portugal. d School of Social and Community Medicine, University of Bristol, Bristol, England. Correspondence to Bradley M Mathers (e-mail: [email protected]). (Submitted: 31 May 2012 – Revised version received: 26 November 2012 – Accepted: 28 November 2012 )

102 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

2012: Medline, EMBASE and PsycINFO. cohorts. We included in the analysis in the analyses (Fig. 1). These studies The search strings contained keywords only studies of drug users that included were further assessed using STROBE and database-specific terms (MeSH mortality data disaggregated by partici- reporting guidelines.7 headings, EMTREE terms and explode pants’ injecting drug use; studies were Data extraction terms; Box 1). All results were limited included only if more than 70% of the to human subjects. We identified grey cohort was composed of people who Once we had identified all studies, one literature sources reporting on mortality injected drugs. of the authors (JL) extracted the data by searching online grey literature data- The searches yielded a total of 5981 into an Excel database (Microsoft, Red- bases, library databases and the web sites studies of mortality related to the use of mond, United States of America) and listed in a published technical report.6 To opioids, amphetamines and cocaine. We two others rechecked them (BM, CB). make sure that no relevant papers had identified another 79 articles by search- This yielded the basic data set for the been missed, we sent the draft lists of the ing the reference lists of reviews on mor- statistical analyses. We extracted infor- papers identified through these searches tality related to drug use. Experts pro- mation on the location of each study, the to experts for their review. vided additional studies for 16 cohorts. period of recruitment and duration of For the current study we exam- From these 5981 articles we excluded a follow-up, the number of people in the ined all papers found in the reviews of total of 5762: 4999 did not focus on drug cohort, the percentage of people in the drug-related mortality but selected only dependence or mortality, 118 did not cohort who injected drugs, the number cohorts composed of people who in- include raw data, 292 were case series, of person–years (PY) of follow-up and jected opioids and other drugs. We used and 600 had insufficient mortality data the number of deaths. the strategy outlined in the preceding on people who inject drugs. In total, we We extracted CMRs and standard- paragraph to further search for these selected 67 cohort studies for inclusion ized mortality ratios (SMRs). We ex-

Box 1. Strategy for search of the peer-reviewed literature Database specific search terms were developed and combined using Boolean operators as follows: ( < opioids > OR < cocaine > OR < amphetamine type stimulants > ) AND < drug use > AND < mortality > AND < longitudinal studies > All results were limited to human subjects and publication years between 1980 and 2012. The full search strings used for each database were as follows: Medline: ((heroin or opiate$ OR opium OR opioid$ OR Exp Opium/ OR exp Narcotics/ OR exp Heroin Dependence/ OR exp Heroin/ OR exp Morphine/ OR exp Opioid-Related Disorders/ OR exp Opiate Alkaloids/ OR exp Methadone/ OR exp Analgesics, Opioid/) OR (Cocaine exp Cocaine- Related Disorders/ or exp Cocaine/ or exp Crack Cocaine/) OR (ATS OR amphetamine type stimulant$ OR amphetamine$ OR methamphetamine OR deoxyephedrine OR desoxyephedrine OR Desoxyn OR madrine OR metamfetamine OR methamphetamine hydrochloride OR methylamphetamine OR n-methylamphetamine OR d-amphetamine OR dextroamphetamine sulfate OR dexamphetamine OR dexedrine OR dextro-amphetamine sulfate OR dextroamphetamine sulfate OR d-amphetamine sulfate OR stimulant$ exp amphetamines/ or exp amphetamine/ or exp dextroamphetamine/ or exp p-chloroamphetamine/ or exp 2,5-dimethoxy-4-methylamphetamine/ or exp p-hydroxyamphetamine/ or exp iofetamine/ or exp methamphetamine/ or exp benzphetamine/ or exp phentermine/ or exp chlorphentermine/ or exp mephentermine/ or exp amphetamine-related disorders/)) AND (drug abuse$ OR drug use$ OR drug misuse$ OR drug dependenc$ OR substance abuse$ OR substance use$ OR substance misuse$ OR substance dependenc$ OR addict$ OR Exp Substance-related disorders/) AND (Mortal$ OR fatal$ OR death$ OR exp “death and dying”/ OR exp mortality/ OR exp hospitalization) AND (“cohort” OR “longitudinal” OR “incidence” OR “prospective” OR “follow-up” OR exp cohort studies/ OR exp longitudinal studies/ OR exp follow-up studies/ OR exp prospective studies/) EMBASE: ((heroin OR opioid$ OR opiate$ OR opium OR exp Diamorphine/ OR exp Opiate/ OR exp Methadone treatment/ OR exp Methadone/) OR (Cocaine exp Cocaine-Related Disorders/ or exp Cocaine/ or exp Crack Cocaine/) OR (ATS OR amphetamine type stimulant$ OR amphetamine$ OR methamphetamine OR deoxyephedrine OR desoxyephedrine OR Desoxyn OR madrine OR metamfetamine OR methamphetamine hydrochloride OR methylamphetamine OR n-methylamphetamine OR d-amphetamine OR dextroamphetamine sulfate OR dexamphetamine OR dexedrine OR dextro-amphetamine sulfate OR dextroamphetamine sulfate OR d-amphetamine sulfate OR stimulant$ exp amphetamines/ or exp amphetamine/ or exp dextroamphetamine/ or exp p-chloroamphetamine/ or exp 2,5-dimethoxy-4-methylamphetamine/ or exp p-hydroxyamphetamine/ or exp iofetamine/ or exp methamphetamine/ or exp benzphetamine/ or exp phentermine/ or exp chlorphentermine/ or exp mephentermine/ or exp amphetamine-related disorders/)) AND (Drug abuse OR drug use$ OR drug misuse OR drug dependenc$ OR substance abuse OR substance use$ OR substance misuse OR substance dependenc$ OR addict$ OR exp substance abuse/ OR exp drug abuse/ OR exp analgesic agent abuse/ OR exp drug abuse pattern/ OR exp drug misuse/ OR exp drug traffic/ OR exp multiple drug abuse/ OR exp addiction/ OR exp drug dependence/ OR exp cocaine dependence/ OR narcotic dependence/ OR exp heroin dependence/ OR exp morphine addiction/ OR exp opiate addiction/) AND (Mortal$ OR fatal$ OR death$ OR exp death/ OR exp “cause of death”/ OR exp accidental death/ OR exp sudden death/ OR exp fatality/ OR exp mortality/ OR exp hospitalization/) AND (“cohort” OR “longitudinal” OR “incidence” OR “prospective” OR “follow-up” OR exp cohort analysis/ OR exp longitudinal study/ OR exp prospective study/ OR exp follow up/) PsychINFO: ((“heroin” OR “opium” OR “opiate$” OR “methadone” OR exp Opiates/ OR exp METHADONE/ OR exp HEROIN ADDICTION/ OR exp HEROIN) OR (Cocaine exp Cocaine-Related Disorders/ or exp Cocaine/ or exp Crack Cocaine/) OR (ATS OR amphetamine type stimulant$ OR amphetamine$ OR methamphetamine OR deoxyephedrine OR desoxyephedrine OR Desoxyn OR madrine OR metamfetamine OR methamphetamine hydrochloride OR methylamphetamine OR n-methylamphetamine OR d-amphetamine OR dextroamphetamine sulfate OR dexamphetamine OR dexedrine OR dextro-amphetamine sulfate OR dextroamphetamine sulfate OR d-amphetamine sulfate OR stimulant$ exp amphetamines/ or exp amphetamine/ or exp dextroamphetamine/ or exp p-chloroamphetamine/ or exp 2,5-dimethoxy-4-methylamphetamine/ or exp p-hydroxyamphetamine/ or exp iofetamine/ or exp methamphetamine/ or exp benzphetamine/ or exp phentermine/ or exp chlorphentermine/ or exp mephentermine/ or exp amphetamine-related disorders/)) AND (Drug abuse OR drug use$ OR drug misuse OR drug dependenc$ OR substance abuse OR substance use$ OR substance misuse OR substance dependenc$ OR addict$ OR Exp drug abuse/ OR exp drug addiction/ OR exp addiction/ OR exp drug usage) AND (Mortal$ OR fatal$ OR death$ OR exp “death and dying”/ OR exp mortality/ OR exp hospitalization) AND (“cohort” OR “longitudinal” OR “incidence” OR “prospective” OR “follow-up” OR Exp age differences/ OR exp cohort analysis/ OR exp human sex differences)

Note: $ indicates wildcard.

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 103 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 1. Flowchart showing study selection process for systematic review of studies on levels of heterogeneity between stud- mortality in people who inject drugs ies because of the marked differences between the samples of people inject- ing drugs; accordingly, we applied a Total from random effects model to all analyses. 5981 initial search The appropriateness of this a priori decision was confirmed by the resultant χ2 and the I-squared statistic. To further Hand search: investigate this heterogeneity, when the 79 data permitted we divided the cohorts into subgroups and used CMR ratios to compare differences in mortality.11 We 6060 made comparisons between subgroups as follows: sex (male versus female); pri- From experts: mary drug injected at baseline (opioids 16 versus stimulants); HIV status (HIV+ versus HIV−); and treatment for drug 6076 dependence (in-treatment period versus off-treatment period). Not drug/mortality focused: We examined the following as po- 4999 tential sources of heterogeneity in CMRs or SMRs using random effects univariate 1077 meta-regressions in STATA: geographic region, country income group (based on World Bank categories), percentage of No raw data: sample that injected drugs, were male 118 or were HIV+ at baseline; presence of opioid users in the cohort; and the year 959 in which the follow-up period ended.12,13

Case series studies: Results 292 We included 67 cohorts in the analysis; 14 were from low- and middle-income 667 countries (Table 1). Studies from Eu- rope, North America and Australasia Insufficient mortality data on people were the most common; nine studies who inject drugs: 600 were from Asia and one was from South America. The pooled CMR across the 65 67 cohorts for which a CMR was provided was 2.35 deaths per 100 PY (Fig. 2). Co- horts from Asia had the highest pooled CMRs (5.25), followed by the cohorts pressed CMRs as the number of deaths number of PYs, the number of deaths from North America (2.64) and western per 100 PY of follow-up. We reported and mortality rates. Europe (2.31); cohorts from Australasia SMRs as calculated in the source pa- Statistical analysis had the lowest pooled CMR (0.71). pers. In several cases standard errors, SMRs were reported for 31 cohorts; confidence intervals (CIs) and CMRs We performed meta-analyses to estimate their pooled SMR was 14.68 (Fig. 3). were not reported, so we estimated them pooled all-cause CMRs and all-cause Since the heterogeneities (I2) of the using standard calculations. We also put SMRs, and pooled estimates of deaths pooled CMR and SMR were both very into the database CMRs and SMRs that from specific causes, as in previous re- high (98.6% and 98.3%, respectively), we were reported according to sex, HIV views.8 To perform the meta-analyses we stratified estimates by subgroups. status, treatment status and type of drug used the “metan” command in STATA Sex differences in mortality injected, as well as data on deaths from version 10.1 (StataCorp LP, College Sta- drug overdose or AIDs-related causes. tion, USA). The “metan” command uses Thirty-seven studies presented CMRs We included in the analyses studies inverse-variance weighting to calculate by sex.14,17–19,21–24,26,28,30–32,34,36–38,43, that specified treatment status if they random effects pooled summary esti- 45–50,52,54,57,58,62,66–72,74 The pooled CMR classified the data by mutually exclusive mates and their confidence limits, true ratio for males versus females was 1.32 treatment groups or periods. We only effect differences between studies and (Fig. 4), which suggests that crude mor- included studies in which the exact dates study heterogeneity.9,10 Random effects tality was higher among males. Nineteen of entry into and exit from the study had models allow for heterogeneity between studies reported SMRs by sex;14,17,21,24, been recorded and used to calculate the and within studies. We expected high 26,28,30,32,34,38,43,46,52,54,58,66,67,70,74 the pooled

104 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs . .) – – – – – – – – – – – – – – 95% CI 8.9–12 6.2–6.6 5.4–7.7 8.0–10.0 6.7–8.95 ( continues 16.5–18.2 17.3–44.0 24.9–30.7 24.6–37.4 16.5–28.8 14.59–20.3 12.11–13.91 19.27–44.04 – – – – – – – – – – – – – – 31 22 6.4 9.0 6.5 17.3 30.7 10.3 27.6 7.77 SMR 13.01 17.45 29.13 – 95% CI 1.7–2.23 0.4–2.29 2.46–4.59 2.94–4.76 0.91–1.46 1.80–2.16 2.05–2.25 2.08–2.43 0.86–1.15 0.59–0.88 0.86–0.92 0.93–1.25 1.43–1.77 0.47–0.68 2.98–3.68 1.72–2.25 5.22–9.06 1.26–2.83 3.11–4.25 0.62–1.20 4.68–7.96 2.06–2.84 2.22–3.42 1.52–2.64 3.45–7.40 1.45–4.09 5.54–10.58 – 3.52 3.85 1.18 2.01 2.15 2.26 1.95 1.00 0.74 0.89 1.09 1.60 0.57 3.33 1.99 7.14 2.04 3.68 0.91 6.32 2.45 2.77 2.08 7.76 5.42 1.27 2.77 CMR 998

667 787 424 934 968 294 188 307 369 772

731.5 538.2

394 612 1793 6011 1272 4352 4167 6244 2547 742.5 901.6 515.3 534.8 PYs of PYs 39 80 28 10 15 21 20 10 15 10 1191.7 3136.4 425 17 13 follow-up c years 2007 2007 2003 1990 1993 1997 2001 2001 2004 2002 2008 2007 2009 2010 1992 2005 2006 2007 2001 1994 1997 2007 2001 1991 1994 1999 1995

End of period 5 follow-up follow-up 1998 1999 1985 period 1994–1998 2002–2004 2005–2007 1997–2003 1986–1988 1986–1990 1998–2001 1980–1995 1998–2001 1998–1999 2000–2006 2000–2009 2001–2006 1981–1988 1990–2005 1985–2006 1981–1988 2000–2001 1997–2007 1990–1997 1980–2001 1985–1991 1982–1993 1975–1999 1975–1995 Recruitment S – – O O O O O O O O O O O O O O O O O O O O, S O, S O, S O, S O, S O, S used Drug(s) – – – – 80 69 (%) 100 100 68.1 55.4 82.2 85.6 58.8 65.0 81.6 78.0 80.0 30.8 69.2 78.7 76.8 68.3 67.4 64.0 99.4 79.1 78.0 Males a b b b a 80 73 98 94 72 70

70 70 70

84 72 72 85 99 (%) 100 100 100 100 100 100 100 100 100 100 100 100 100 > > > > > ≥ ≥ ≥ ≥ 90–95 People who People inject drugs 432 454 676 376 n

552 675 652 114 678 472 101 478 138 175 644 660 459 3644 2707 3789 1009 3059 1640 5577 1244 4644 4260 1487 11 10 42 10 OR HC DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS T&C NSP frame Sampling DTS, other DTS, Low Low High High High High High High High High High High High High High High High High High High High High High Middle Middle Middle Middle Middle income Country Italy Italy Italy Italy Italy Italy USA USA Brazil Spain Latvia United United United United United Austria Croatia Norway Norway Country Sweden Sweden Sweden Sweden Bulgaria Australia Australia Romania Kingdom Kingdom Kingdom Bangladesh Bangladesh 35 36 37 24 21 19 27 20 17 29 22 14 34 23 25 18 28 15 16 32 30 30 30 30 30 31 Studies included in this systematic review of studies on mortality review among people who injectStudies drugs included in this systematic

26 33 Table 1. Table Azim (2008) et al. (2010) et al. Cornish (2004) et al. DiGiusto (2011) EMCDDA Study (2006) et al. Antolini Bargagli et al. (2001) et al. Bargagli Fugelstad et al. (1997) et al. Fugelstad EMCDDA (2011) EMCDDA Brancato et al. (1995) et al. Brancato Eskild (1993) et al. Copeland et al. (2004) et al. Copeland et al. Degenhardt (2009) (2011) EMCDDA (1998) et al. Fugelstad Bauer et al. (2008) Bauer et al. (2008) et al. Clausen (2011) EMCDDA (2012) Evans Fingerhood et al. et al. Fingerhood (2006) Frischer et al. (1997) et al. Frischer Cardoso et al. (2006) et al. Cardoso (2011) EMCDDA (2007) et al. Ferri Azim (2009) et al. Davoli et al. (2007) et al. Davoli Esteban et al. (2003) et al. Esteban (1995) et al. Fugelstad Ciccolallo et al. (2000) et al. Ciccolallo

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 105 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al. . .) – – – – – – – – – – – – – – 95% CI 5.5–6.8 9.6–15.0 9.1–27.1 ( continues 7.28–9.09 11.4–15.3 8.71–21.04 8.64–16.09 5.71–11.66 20.02–24.34 12.28–16.56 – – – – – – – – – – – – – – 8.3 20.5 8.15 5.94 13.4 16.4 13.9 11.9 SMR 12.06 14.28 95% CI 1.8–2.3 0–14.30 5.79–7.98 1.81–2.83 1.13–2.23 2.28–2.77 1.41–1.75 4.42–4.92 1.92–2.12 0.75–0.93 2.00–2.36 2.16–2.69 3.38–4.14 1.12–1.48 4.60–8.50 0.80–1.94 2.42–5.83 2.80–5.64 0.95–3.44 1.28–2.38 0.36–0.65 2.48–3.33 0.69–1.41 1.22–1.96 1.25–6.91 6.85 2.28 1.59 2.52 1.57 4.67 2.02 0.84 2.18 2.04 2.43 3.74 1.30 6.30 1.37 3.85 4.22 1.92 1.83 0.50 4.83 2.91 1.05 1.59 4.08 CMR 415 130 901 826 069 116

900.2 131.2 280.3 203.1

805 574 196 20.7 3594 2075 1608 3149 4591 710.1 571.4 PYs of PYs 16 21 73 26 13 10 2192.9 2349.7 9362.4 6158.5 28 38 13 15 follow-up – 2007 2011 2002 2000 2006 1992 2001 2006 2002 1990 2004 2004 1991 2007 2007 1991 1998 2002 1991 2004 2002 1992 1989 1997 End of period follow-up follow-up – 2005 1999 1969 2007 1991 period 2005–2011 1996–2000 1997–2006 1983–1992 1997–1999 1970–1978 1997–2002 1980–1990 1966–2004 1987–1996 2000–2007 1980–1998 1987–1991 1977–1996 1987–2004 1990–1996 1989–1991 1981–1988 1994–1997 Recruitment – – – – – – O O O O O O O O O O O O O O O, S O, S O, S O, S O, S used Drug(s) – – – – – 68 (%) 100 96.1 93.1 58.0 70.0 74.2 74.5 67.5 53.1 77.2 72.7 72.8 78.3 66.0 75.5 79.5 77.4 73.3 63.9 Males d 76 79 80 99 (%) 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 95.2 People who People inject drugs 207 n

66 79 894 860 346 178 146 881 656 561 572 128 6575 2773 2432 4962 6570 1214 6248 2279 1181 3247 1769 2849 12 PR SIF DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS DTS frame OR, HC Sampling DTS, other DTS, other DTS, High High High High High High High High High High High High High High High High High High High Middle Middle Middle Middle Middle Middle income Country Iran Iran Italy Italy Italy Italy Italy USA USA USA Spain Spain Spain China Czech Czech United United United Islamic Islamic Poland Canada Norway Country Sweden Thailand Australia Republic Viet Nam Viet Germany Kingdom Kingdom Republic of Republic of 51 38 50 57 49 43 46 42 39 40 53 55 52 59 60 45 44 41 47 ) 56 62 48 54 58 61 Lumbreras et al. et al. Lumbreras (2006) Study (1994) Galli & Musicco Muga et al. (2007) Muga et al. Jafari et al. (2010) Jafari et al. Goedert (2001) et al. (2001) Golz et al. (2007) et al. Lejckova (2006) et al. Manfredi Moskalewicz et al. (1996) Nyhlén (2011) (2001) O’Driscoll et al. Goedert (1995) et al. (2011) Liu et al. McAnulty (1995) et al. Rahimi-Movaghar et al. Rahimi-Movaghar et al. (2009) Quan et al. (2010) Quan et al. Miller (2007) et al. (1991) et al. Moroni Haarr & Nessa (2007) Hickman (2003) et al. Quan et al. (2007) Quan et al. Reece (2010) Mezzelani et al. (1998) et al. Mezzelani Oppenheimer et al. (1994) Jarrin et al. (2007) Jarrin et al. (. . continued

106 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs vised – – – – – super

95% CI 11.4–21.2 3.99–4.78 8.85–13.7 9.31–19.49 31.63–68.71 14.65–42.65 19.41–31.23 27.44–36.93 wballing; SIF, sno

– – – – – 24.8 14.4 4.38 11.1 SMR 15.75 47.62 28.58 31.92 ts; SB, stimulan

95% CI 1.6–3.27 2.44–4.53 2.56–4.07 0.15–0.81 0.28–0.72 1.93–2.31 4.24–4.76 0.56–1.21 4.87–10.6 0.54–0.88 2.36–4.44 3.35–5.16 1.96–2.63 3.4 3.49 3.23 0.48 2.33 0.54 2.12 4.50 0.83 7.73 0.71 4.25 2.30 CMR 736

468.2

2229 3151 1998 382.4 PYs of PYs 25 1232.3 1659.7 1416.9 4166.9 1205.9 8629.3 7872.2 22 follow-up evention service; PY, person–years; S, person–years; service;evention PY, HIV pr

2003 1999 1993 2008 1994 2003 2005 2006 1995 2005 2002 2008 1991 End of period follow-up follow-up each; PR, outr

2002 1967 1985 1988 period 1980–1984 1985–1992 1996–1998 1983–1994 2001–2001 1990–1995 1997–1999 2005–2006 1985–1991 Recruitment opioids; OR,

– O O O O O O O, S O, S O, S O, S O, S O, S used Drug(s) inge programme; O, inge programme; 43 (%) 100 100 82.8 67.3 61.9 79.2 59.6 56.4 71.0 77.3 62.3 75.5 Males b needle and syr

, 70

83 88 (%) 100 100 100 100 100 100 100 100 100 100 ≥ People who People inject drugs n health clinic; NSP

376 101 509 151 316 817 894 220 135 3593 2089 1158 2029 OR DTS DTS DTS DTS DTS DTS frame OR, SB OR, SB OR, SB Multiple Sampling DTS, other DTS, DTS, other DTS, eatment service;eatment HC, esting and counselling; USA, United States of America. States USA, United esting and counselling; HIV t

drug tr

High High High High High High High High High High High Middle Middle income Country Italy USA USA India Spain China Czech Czech United United Country Sweden Australia Australia Republic Denmark Kingdom years after the date of enrolment. after the date years Netherlands

67 73 74 66 65 64 71 72 75 68 ted, but implied in the paper. ted, 69 ) 63 70 Da T Subjec Not explicitly sta among opioid-dependent of administration people in this country. of injectinghe proportion as a route of subjects least 70% because of the predominance be at who injectednot reported assumed to drugs was but was 99% had a history and of these, 62% of the subjects, ta on history for of injecting available drugs. of drug use was

5 for followed ts were a b c d CI, confidence interval, CMR, crude mortality rate; DTS, interval, CMR, crude mortalityCI, confidence rate; injectingT&C, facility; mortality SMR, standardized ratio; author). the corresponding from available (formulae calculated were of follow-up Some CMRs and PYs Note: Stenbacka et al. (2007) Stenbacka et al. Solomon et al. (2009) Solomon et al. Seaman et al. (1998) Seaman et al. Study Sánchez-Carbonell et (2000) al. Vlahov et al. (2005) et al. Vlahov Zaccarelli et al. (1994) et al. Zaccarelli van Haastrecht et al. et al. Haastrecht van (1996) Vlahov et al. (2008) et al. Vlahov Stoov et al. (2008) et al. Stoov Tait et al. (2008) et al. Tait Zabranksy et al. (2011) et al. Zabranksy (2005) Zhang et al. Sørensen et al. (2005) et al. Sørensen (. . continued

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 107 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 2. Crude mortality rates for people who inject drugs, by region

% Cohort CMR (95% CI) Weight

Western Europe Antolini 2006 (Italy) 2.01 (1.79, 2.16) 1.83 Bargagli 2001 (Italy) 2.15 (2.05, 2.25) 1.84 Bauer 2008 (Austria) 5.42 (3.45, 7.40) 0.77 Brancato 1995 (Italy) 2.04 (1.26, 2.83) 1.51 Ciccolallo 2000 (Italy) 2.26 (2.08, 2.43) 1.83 Clausen 2008 (Norway) 1.95 (1.70, 2.23) 1.80 Copeland 2004 (UK) 2.45 (2.06, 2.84) 1.75 Cornish 2010 (UK) 1.00 (0.86, 1.15) 1.83 Davoli 2007 (Italy) 0.74 (0.59, 0.88) 1.83 EMCDDA 2011 (Sweden) 3.33 (2.98, 3.68) 1.77 Eskild 1993 (Norway) 2.77 (2.22, 3.42) 1.64 Esteban 2003 (Spain) 3.68 (3.11, 4.25) 1.66 Frischer 1997 (UK) 2.08 (1.52, 2.64) 1.66 Fugelstad 1995 (Sweden) 3.85 (2.94, 4.76) 1.43 Fugelstad 1997 (Sweden) 1.99 (1.72, 2.25) 1.80 Fugelstad 1998 (Sweden) 7.76 (5.54, 10.58) 0.57 Galli 1994 (Italy) 2.52 (2.28, 2.77) 1.81 Goedert 1995 (Italy) 1.57 (1.41, 1.75) 1.83 Golz 2001 (Germany) 4.22 (2.80, 5.64) 1.08 Haarr 2007 (Norway) 1.92 (0.95, 3.44) 1.19 Hickman 2003 (UK) 1.61 (1.13, 2.23) 1.67 Jarrin 2007 (Spain) 2.02 (1.92, 2.12) 1.84 Lejckova 2007 (Czech Republic) 0.84 (0.75, 0.93) 1.84 Lumbreras 2006 (Spain) 2.18 (2.00, 2.36) 1.83 Manfredi 2006 (Italy) 2.04 (1.80, 2.30) 1.81 Mezzelani 1998 (Italy) 2.91 (2.48, 3.33) 1.74 Moroni 1991 (Italy) 2.43 (2.16, 2.69) 1.80 Muga 2007 (Spain) 3.74 (3.38, 4.14) 1.76 Nyhlen 2011 (Sweden) 1.30 (1.12, 1.48) 1.83 Oppenheimer 1994 (UK) 1.83 (1.28, 2.38) 1.67 Sanchez−Carbonell 2000 (Spain) 3.40 (2.36, 4.44) 1.33 Seaman 1998 (UK) 2.33 (1.60, 3.27) 1.48 Sorensen 2005 (Denmark) 3.49 (2.45, 4.53) 1.33 Stenbacka 2007 (Sweden) 2.12 (1.93, 2.31) 1.82 VanHaastrecht 1996 (Netherlands) 3.23 (2.56, 4.07) 1.54 Zabransky 2011 (Czech Republic) 0.48 (0.15, 0.81) 1.78 Zaccarelli 1994 (Italy) 2.30 (1.96, 2.63) 1.78 Subtotal (I−squared = 97.4%, p = 0.000) 2.31 (2.06, 2.56) 60.26 . Asia Azim 2008 (Bangladesh) 6.32 (4.68, 7.96) 0.94 Azim 2009 (Bangladesh) 3.52 (2.46, 4.59) 1.31 Jafan 2010 (Islamic Republic of Iran) 4.08 (1.25, 6.91) 0.48 Liu 2011 (China) 6.89 (5.79, 7.98) 1.29 Quan 2007 (Thailand) 3.85 (2.42, 5.83) 0.91 Quan 2010 (Viet Nam) 6.30 (4.60, 8.50) 0.78 Rahimi-Movahgar 2009 (Islamic Republic of Iran) 4.83 (0.00, 14.30) 0.10 Solomon 2009 (India) 4.25 (3.35, 5.16) 1.43 Zhang 2005 (China) 7.73 (4.87, 10.60) 0.47 Subtotal (I−squared = 74.3%, p = 0.000) 5.25 (4.16, 6.35) 7.71 . Latin America Cardoso 2006 (Brazil) 2.77 (1.45, 4.09) 1.14 Subtotal (I−squared = .%, p = .) 2.77 (1.45, 4.09) 1.14 . Australasia Degenhardt 2009 (Australia) 0.89 (0.86, 0.92) 1.85 Digusto 2004 (Australia) 1.27 (0.40, 2.29) 1.40 Reece 2010 (Australia) 0.50 (0.36, 0.65) 1.83 Stoove 2008 (Australia) 0.83 (0.56, 1.21) 1.78 Tait 2008 (Australia) 0.50 (0.29, 0.72) 1.82 Subtotal (I−squared = 89.7%, p = 0.000) 0.71 (0.46, 0.96) 8.68 . Eastern Europe EMCDDA 2011 (Romania) 0.57 (0.47, 0.68) 1.84 EMCDDA 2011 (Croatia) 1.09 (0.93, 1.25) 1.83 EMCDDA 2011 (Bulgaria) 1.18 (0.91, 1.46) 1.80 EMCDDA 2011 (Latvia) 1.60 (1.43, 1.77) 1.83 Moskalewicz 1996 (Poland) 2.28 (1.81, 2.83) 1.69 Subtotal (I−squared = 97.1%, p = 0.000) 1.31 (0.82, 1.80) 8.99 . North America Evans 2012 (USA) 0.91 (0.62, 1.20) 1.79 Fingerhood 2006 (USA) 7.14 (5.22, 9.06) 0.80 Goedert 2001 (USA) 4.67 (4.42, 4.92) 1.81 McAnulty 1995 (USA) 1.05 (0.69, 1.41) 1.77 Miller 2007 (Canada) 1.37 (0.80, 1.94) 1.65 O’Driscoll 2001 (USA) 1.59 (1.22, 1.96) 1.76 Vlahov 2005 (USA) 4.50 (4.24, 4.76) 1.80 Vlahov 2008 (USA) 0.71 (0.54, 0.88) 1.83 Subtotal (I−squared = 99.4%, p = 0.000) 2.64 (1.25, 4.02) 13.22 . Overall (I−squared = 98.6%, p = 0.000) 2.35 (2.12, 2.58) 100.00

NOTE: Weights are from random effects analysis

−10 −5 0 5 10 15

Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; CMR, crude mortality rate.

108 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

Fig. 3. Standardized mortality ratios for people who inject drugs, by region

% Cohort SMR (95% CI)) Weight

Western Europe Antolini 2006 (Italy) 13.01 (11.38, 13.09) 4.08 Bargagli 2001 (Italy) 17.30 (16.50, 18.20) 4.08 Bauer 2008 (Austria) 29.13 (19.27, 44.04) 1.26 Ciccolallo 2000 (Italy) 30.70 (17.30, 44.00) 1.13 Copeland 2004 (UK) 17.45 (14.59, 20.30) 3.68 EMCDDA 2011 (Sweden) 27.60 (24.90, 30.70) 3.67 Eskild 1993 (Norway) 31.00 (24.60, 37.40) 2.57 Ferri 2007 (Italy) 7.77 (6.70, 8.95) 4.05 Frischer 1997 (UK) 22.00 (16.50, 28.80) 2.65 Galli 1994 (Italy) 20.50 (20.02, 24.33) 3.86 Lejckova 2007 (Czech Republic) 8.15 (7.28, 9.09) 4.08 Mezzelani 1998 (Italy) 14.28 (12.28, 16.56) 3.86 Nyhlen 2011 (Sweden) 5.94 (5.50, 6.80) 4.10 Oppenheimer 1994 (UK) 11.90 (8.64, 16.09) 3.42 Sanchez−Carbonell 2000 (Spain) 28.58 (14.65, 42.65) 1.06 Sorensen 2005 (Denmark) 15.75 (11.40, 21.20) 3.04 Stenbacka 2007 (Sweden) 4.38 (3.99, 4.78) 4.12 VanHaastrecht 1996 (Netherlands) 24.80 (19.41, 31.23) 2.72 Zabransky 2011 (Czech Republic) 14.40 (9.31, 19.49) 2.98 Zaccarelli 1994 (Italy) 31.92 (27.44, 36.93) 3.09 Subtotal (I−squared = 98.8%, p = 0.000) 17.52 (14.62, 20.43) 63.51 . Asia Quan 2007 (Thailand) 13.90 (8.71, 21.04) 2.64 Quan 2010 (Viet Nam) 13.40 (11.40, 15.30) 3.91 Solomon 2009 (India) 11.10 (8.85, 13.70) 3.80 Zhang 2005 (China) 47.62 (31.63, 68.71) 0.68 Subtotal (I−squared = 81.2%, p = 0.001) 14.47 (9.95, 19.00) 11.02 . Australasia Degenhardt 2009 (Australia) 6.40 (6.20, 6.60) 4.12 Subtotal (I−squared = .%, p = .) 6.40 (6.20, 6.60) 4.12 . Eastern Europe EMCDDA 2011 (Romania) 6.50 (5.40, 7.70) 4.05 EMCDDA 2011 (Croatia) 10.30 (8.90, 12.00) 3.98 EMCDDA 2011 (Latvia) 9.00 (8.00, 10.00) 4.07 Moskalewicz 1996 (Poland) 12.06 (9.60, 15.00) 3.72 Subtotal (I−squared = 87.7%, p = 0.000) 9.25 (7.22, 11.28) 15.82 . North America McAnulty 1995 (USA) 8.30 (5.71, 11.66) 3.65 Miller 2007 (Canada) 16.40 (9.10, 27.10) 1.88 Subtotal (I−squared = 64.4%, p = 0.094) 11.19 (3.58, 18.80) 5.53 . Overall (I−squared = 98.3%, p = 0.000) 14.68 (13.01, 16.35) 100.00

NOTE: Weights are from random effects analysis

−68.7 0 68.7 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; SMR, standardized mortality ratio.

CMR ratio suggests that females had 1.38 times higher (Fig. 7) among males (Fig. 9).28,33–36,38–41,48,49,60,65,70,72,74 When significantly greater excess mortality than among females.14,17,19,21,24,32,38,49,52,57,58 we examined mortality from causes than males in similar age groups in the In 20 studies CMRs were pro- other than AIDS, we found it to be general population (Fig. 5). Only two vided separately for people who inject 1.63 times higher among HIV+ than of the nineteen studies presented SMRs drugs according to their HIV sta- among HIV− people who inject drugs for males that were greater than those tus.15,16,18,28,34,36–40,45,48,49,55,57,60,65,70,72,74 All- (Fig. 10).28,34,36,38–40,48,49,60,65,70,72,74 for females.30,74 cause mortality was three times higher Mortality from drug overdose was Causes of death among HIV+ than among HIV− sub- presented by HIV status in 9 stud- jects (CMR ratio: 3.15) (Fig. 8). Much ies.28,34,36,38,39,49,65,70,74 Pooled estimates Several studies reported specific causes of this elevated mortality appeared showed mortality to be twice as high of death. The pooled CMR for death to result from AIDS deaths among among HIV+ than among HIV− people from drug overdose was 0.62 per 100 PY HIV+ users of injecting drugs. The who inject drugs (CMR ratio: 1.99) across 43 studies (Fig. 6). Eleven stud- pooled estimate of AIDS-related mor- (Fig. 11). Further analyses across 13 ies reported CMRs for death from drug tality for the 16 studies for which data studies conducted on HIV+ people overdose by sex: overall the CMR was were available was 2.55 per 100 PY who inject drugs showed no significant

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 109 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 4. Ratios of crude mortality rates in males versus females who inject drugs

% Cohort RR (95% CI) Weight

Antolini 2006 (Italy) 1.30 (1.09, 1.55) 4.98 Bargagli 2001 (Italy) 0.97 (0.86, 1.09) 5.63 Bauer 2008 (Austria) 2.62 (1.18, 5.81) 1.01 Brancato 1995 (Italy) 1.14 (0.44, 3.01) 0.72 Ciccolallo 2000 (Italy) 1.32 (1.09, 1.61) 4.76 Clausen 2008 (Norway) 1.14 (0.85, 1.53) 3.68 Copeland 2004 (UK) 1.23 (0.87, 1.74) 3.13 Cornish 2010 (UK) 1.67 (1.16, 2.40) 2.99 Degenhardt 2009 (Australia) 1.58 (1.47, 1.70) 6.03 EMCDDA 2011 (Croatia) 2.57 (1.56, 4.24) 2.05 Eskild 1993 (Norway) 1.08 (0.70, 1.67) 2.44 Evans 2012 (USA) 1.60 (0.76, 3.37) 1.12 Ferri 2007 (Italy) 1.51 (1.06, 2.16) 3.06 Frischer 1997 (UK) 0.99 (0.57, 1.72) 1.77 Fugelstad 1997 (Sweden) 1.35 (0.99, 1.84) 3.52 Fugelstad 1998 (Sweden) 1.74 (0.93, 3.26) 1.48 Galli 1994 (Italy) 1.14 (0.89, 1.45) 4.19 Hickman 2003 (UK) 2.01 (0.78, 5.18) 0.75 Jarrin 2007 (Spain) 1.36 (1.19, 1.55) 5.50 Lejckova 2007 (Czech Republic) 1.88 (1.44, 2.45) 3.95 Liu 2011 (China) 0.80 (0.39, 1.66) 1.17 Lumbreras 2006 (Spain) 1.50 (1.21, 1.86) 4.56 Manfredi 2006 (Italy) 1.14 (0.86, 1.51) 3.77 McAnulty 1995 (USA) 1.59 (0.66, 3.84) 0.85 Miller 2007 (Canada) 0.64 (0.27, 1.53) 0.88 Moskalewicz 1996 (Poland) 1.80 (1.00, 3.23) 1.63 O’Driscoll 2001 (USA) 1.10 (0.68, 1.78) 2.15 Oppenheimer 1994 (UK) 0.86 (0.45, 1.64) 1.41 Reece 2010 (Australia) 3.31 (1.31, 8.36) 0.77 Sorensen 2005 (Denmark) 0.68 (0.37, 1.24) 1.58 Stenbacka 2007 (Sweden) 1.24 (0.98, 1.56) 4.35 Stoove 2008 (Australia) 3.49 (1.32, 9.22) 0.71 Tait 2008 (Australia) 1.09 (0.43, 2.76) 0.77 VanHaastrecht 1996 (Netherlands) 1.42 (0.87, 2.32) 2.11 Vlahov 2005 (USA) 1.20 (1.04, 1.38) 5.39 Vlahov 2008 (USA) 1.21 (0.73, 1.99) 2.04 Zaccarelli 1994 (Italy) 1.22 (0.86, 1.74) 3.09 Overall (I−squared = 63.9%, p = 0.000) 1.32 (1.21, 1.44) 100.00 NOTE: Weights are from random effects analysis

.5 1 2 3 4 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; RR, relative risk. difference in deaths from drug overdose stimulants) (Table 2). Pooled estimates Mortality according to treatment and from AIDS in this group (CMR of all-cause mortality by primary type ratio: 1.35; P = 0.554) (Fig. 12).28,33–36,38, of drug injected showed no overall dif- Six studies provided information on 39,41,49,65,70,71,74 ference across studies (CMR ratio: 1.25; mortality during in-treatment and Only four studies presented data by 95% CI: 0.60–2.61; P = 0.553).36,46,57,70,71 off-treatment periods at follow-up: the sex and HIV status.37,47,49,74 They showed The same was true of studies of mortal- meta-analysis suggested that mortality no significant difference in CMRs be- ity resulting from drug overdose (CMR was 2.52 times higher during off-treat- tween HIV+ males and HIV+ females ratio: 1.85; 95% CI: 0.75–4.56; P = 0.18). ment periods than during in-treatment who inject drugs (CMR ratio: 1.13; In three of the four studies mortality as- periods (Fig. 15).22,23,25,26,35,37 Fig. 13), but HIV– males had a pooled sociated with drug overdose was higher Heterogeneity in mortality CMR 1.81 times greater than that of among people injecting opioids than HIV– females who inject drugs (Fig. 14). among those injecting stimulants.36,46,71 We performed univariate analyses to Mortality by primary drug In the fourth study, people who injected determine if the heterogeneity in overall injected at baseline primarily stimulants had higher rates of CMRs and SMRs could be explained by drug overdose; however, the deaths from participant characteristics and method- Five studies estimated mortality by overdose in this group were later shown to ological variables. The results showed primary drug injected (opioids versus have been caused by opioid use.57 that high-income countries had lower

110 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

Fig. 5. Ratios of standardized mortality ratios for males versus females who inject drugs

%

Cohort RR (95% CI) Weight

Antolini 2006 (Italy) 0.60 (0.50, 0.71) 6.94

Bargagli 2001 (Italy) 0.41 (0.36, 0.46) 7.24

Ciccolallo 2000 (Italy) 0.50 (0.41, 0.61) 6.83

Copeland 2004 (UK) 0.67 (0.47, 0.95) 5.74

Degenhardt 2009 (Australia) 0.68 (0.63, 0.73) 7.40

EMCDDA 2011 (Croatia) 1.05 (0.64, 1.73) 4.60

Eskild 1993 (Norway) 0.43 (0.28, 0.67) 5.06

Ferri 2007 (Italy) 0.29 (0.21, 0.42) 5.68

Frischer 1997 (UK) 0.43 (0.25, 0.74) 4.21

Galli 1994 (Italy) 0.36 (0.28, 0.46) 6.50

Hickman 2003 (UK) 0.95 (0.37, 2.45) 2.30

Lejckova 2007 (Czech Republic) 0.99 (0.76, 1.29) 6.35

Miller 2007 (Canada) 0.24 (0.10, 0.57) 2.60

Moskalewicz 1996 (Poland) 0.55 (0.31, 0.99) 4.00

Oppenheimer 1994 (UK) 0.81 (0.42, 1.53) 3.66

Sorensen 2005 (Denmark) 0.37 (0.20, 0.67) 3.93

Stenbacka 2007 (Sweden) 0.60 (0.47, 0.75) 6.60

VanHaastrecht 1996 (Netherlands) 0.79 (0.49, 1.29) 4.68

Zaccarelli 1994 (Italy) 1.44 (1.01, 2.05) 5.70

Overall (I−squared = 87.3%, p = 0.000) 0.58 (0.49, 0.69) 100.00

NOTE: Weights are from random effects analysis

.5 1 1.5 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; RR, relative risk.

CMRs than low- and middle-income high mortality associated with injecting observed no significant difference in countries (Fig. 16). Cohorts with greater drug use. The pooled SMR of 14.68 also pooled SMRs. This suggests that the proportions of males and HIV+ partici- shows that mortality is much higher higher CMRs may reflect higher over- pants at baseline also had higher CMRs. in those who inject drugs than in the all mortality in the general population Cohorts whose follow-up periods ended general population. Differences by sex in low- and middle-income countries in more recent years had lower SMRs were evident: across all studies that than in high-income countries. The (Table 3). Study data were not sufficient reported mortality by sex, males had lowest and highest mortality rates were to allow for multivariate analyses. higher CMRs, yet females who inject documented in cohorts in Australasia drugs had a much higher elevation in and Asia, respectively. Differences across Discussion mortality relative to their age-matched high-income countries probably reflect peers in the general population than did differences in HIV infection prevalence, Although previous reviews have exam- males who inject drugs. coverage of HIV prevention and cov- ined mortality among people who inject Most of the cohorts identified were erage of opioid agonist maintenance drugs, to our knowledge this is the most from 14 high-income countries; togeth- treatment.76,77 comprehensive systematic review of er these 14 counties represent 78% of Drug overdose and AIDS-related the topic and the first to employ novel the total estimated population of people mortality were by far the most com- approaches to search for the available who inject drugs in such countries.76 mon causes of death. The pooled CMR evidence. These approaches ranged from Studies from only 11 low or middle for death from drug overdose was 0.62 standard searches of the peer-reviewed income countries were identified; these per 100 PY, higher among males than literature to comprehensive searches of countries account for only 40% of the females who inject drugs, and higher the non-peer reviewed literature and estimated number of people inject- among HIV+ people who inject drugs multiple expert consultations, as well ing drugs in low- or middle-income than among those who were HIV−. as examination of both participant- and countries.76 In three of the four studies comparing study-level factors potentially associated Although pooled CMRs were drug overdose among people injecting with the risk of death. higher among people injecting drugs opioids compared to those injecting The pooled CMR of 2.35 deaths in low- and middle-income countries stimulants, CMRs were higher among per 100 PY provides evidence of the rather than high-income countries, we the former group, as expected.36,46,71 In

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 111 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 6. Crude mortality rates for death from drug overdose in people who inject drugs

% Cohort CMR (95% CI) Weight

Antolini 2006 (Italy) 0.61 (0.53, 0.69) 3.27 Bargagli 2001 (Italy) 0.52 (0.47, 0.57) 3.32 Bauer 2008 (Austria) 2.06 (0.84, 3.27) 0.40 Brancato 1995 (Italy) 0.80 (0.30, 1.30) 1.50 Ciccolallo 2000 (Italy) 0.69 (0.60, 0.80) 3.21 Clausen 2008 (Norway) 1.03 (0.84, 1.22) 2.85 Copeland 2004 (UK) 0.61 (0.43, 0.83) 2.79 Davoli 2007 (Italy) 0.40 (0.09, 0.72) 2.24 Degenhardt 2009 (Australia) 0.43 (0.41, 0.45) 3.36 Digusto 2004 (Australia) 0.76 (−0.10, 1.62) 0.71 Eskild 1993 (Norway) 1.85 (1.37, 2.33) 1.57 Ferri 2007 (Italy) 0.46 (0.39, 0.56) 3.24 Fingerhood 2006 (USA) 0.81 (0.30, 1.76) 0.91 Frischer 1997 (UK) 0.98 (0.63, 1.45) 1.83 Fugelstad 1995 (Sweden) 2.30 (1.64, 3.10) 0.91 Fugelstad 1997 (Sweden) 0.97 (0.78, 1.15) 2.88 Galli 1994 (Italy) 0.92 (0.77, 1.07) 3.04 Goedert 1995 (Italy) 0.30 (0.23, 0.37) 3.28 Goedert 2001 (USA) 0.64 (0.55, 0.74) 3.22 Haarr 2007 (Norway) 1.22 (0.32, 2.12) 0.66 Hickman 2003 (UK) 1.01 (0.58, 1.44) 1.73 Jarrin 2007 (Spain) 0.32 (0.28, 0.36) 3.34 Lejckova 2007 (Czech Republic) 0.18 (0.14, 0.23) 3.33 Manfredi 2006 (Italy) 0.45 (0.34, 0.56) 3.16 McAnulty 1995 (USA) 0.41 (0.22, 0.71) 2.58 Miller 2007 (Canada) 0.25 (0.07, 0.64) 2.39 Moroni 1991 (Italy) 0.93 (0.77, 1.12) 2.94 O’Driscoll 2001 (USA) 0.70 (0.48, 0.98) 2.54 Oppenheimer 1994 (UK) 0.77 (0.46, 1.22) 1.95 Quan 2007 (Thailand) 0.89 (0.11, 1.67) 0.83 Seaman 1998 (UK) 1.41 (0.86, 2.18) 1.06 Solomon 2009 (India) 1.10 (0.64, 1.56) 1.63 Stenbacka 2007 (Sweden) 0.05 (0.02, 0.08) 3.35 Stoove 2008 (Australia) 0.44 (0.26, 0.75) 2.58 Tait 2008 (Australia) 0.14 (0.03, 0.26) 3.15 van Haastrecht 1996 (Netherlands) 0.72 (0.41, 1.17) 1.96 Vlahov 2005 (USA) 0.71 (0.61, 0.82) 3.19 Vlahov 2008 (USA) 0.31 (0.21, 0.46) 3.12 Zaccarelli 1994 (Italy) 0.55 (0.40, 0.74) 2.94 Zhang 2005 (China) 4.71 (2.53, 6.88) 0.14 Nyhlen 2011 (Sweden) 0.30 (0.22, 0.39) 3.25 Zabransky 2011 (Czech Republic) 0.12 (0.00, 0.29) 3.04 Quan 2010 (Viet Nam) 1.69 (0.73, 2.65) 0.60 Overall (I−squared = 96.2%, p = 0.000) 0.62 (0.53, 0.70) 100.00 NOTE: Weights are from random effects analysis

−2 0 2 4 6 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; CMR, crude mortality rate. a fourth study, however, drug overdose mortality from causes other than AIDS were around 2.5 times higher in off- was higher among people who injected was also higher among those who were treatment periods than in in-treatment stimulants,57 although further inves- HIV+. Overdose-related mortality was periods. Variation in exposure to treat- tigation revealed that the deaths from also higher among HIV+ people who ment could also explain differences overdose in this group were more often inject drugs in many cohorts. These between cohorts in mortality from drug linked to the injection of opioids than differences in mortality may reflect dif- overdose, although this variation was to the injection of stimulants. This find- ferences in risky behaviour, physical not explicitly measured across cohorts. ing highlights the fact that people who health and social disadvantage. The prevention of HIV transmis- inject drugs often use more than one The observational evidence exam- sion among people who inject drugs is drug type, even if they have a particular ined in this review is consistent with the clearly a public health priority.79,80 There drug of choice. evidence from randomized controlled is growing evidence that opioid agonist The prevalence of HIV infection trials that opioid agonist maintenance maintenance treatment, antiretrovi- varied widely. As expected, overall mor- treatment is associated with a reduced ral treatment and needle and syringe tality was much higher among HIV+ risk of death.78 Among cohorts for which programmes reduce HIV transmis- than among HIV− people who inject in-treatment and off-treatment periods sion.81–83 These interventions have been drugs (pooled CMR ratio: 3.15), but were carefully tracked, mortality rates implemented in many countries, but

112 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

77 often on a limited scale only. Clearly, Fig. 7. Ratios of crude mortality rates for death from drug overdose in males versus however, AIDS is only one of several females who inject drugs common causes of death in this group: a comprehensive approach to improving % health outcomes among people who Cohort RR (95% CI) Weight inject drugs must also include efforts to Antolini 2006 (Italy) 1.83 (1.27, 2.64) 15.22 reduce other causes of death frequently Bargagli 2001 (Italy) 1.41 (1.07, 1.85) 17.94 found among them, particularly drug Brancato 1995 (Italy) 0.63 (0.16, 2.40) 2.82 overdose.84 Ciccolallo 2000 (Italy) 1.84 (1.23, 2.74) 14.29 Limitations of the evidence Copeland 2004 (UK) 1.05 (0.53, 2.08) 8.16 Evidence on mortality rates among users Ferri 2007 (Italy) 0.65 (0.36, 1.17) 9.88 of injecting drugs is still predominantly Galli 1994 (Italy) 1.03 (0.70, 1.54) 14.32 from high-income countries, particu- Manfredi 2006 (Italy) 3.00 (1.29, 6.97) 6.07 larly in western Europe. Interestingly, Miller 2007 (Canada) 3.36 (0.35, 32.19) 1.08 however, this review has shown that O’Driscoll 2001 (USA) 1.49 (0.69, 3.22) 6.94 despite marked differences in CMRs Oppenheimer 1994 (UK) 1.91 (0.56, 6.59) 3.27 across countries, the extent to which Overall (I−squared = 46.5%, p = 0.044) 1.38 (1.08, 1.76) 100.00 this mortality exceeds that of the general NOTE: Weights are from random effects analysis population may show less pronounced differences. It would be inappropriate .5 1 5 to assume that mortality is equally high Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval, RR, relative risk. among all people who inject drugs. New research in this area is needed, especially

Fig. 8. Ratios of crude mortality rates in HIV-positive versus HIV-negative people who inject drugs

% Cohort RR (95% CI) Weight

Azim 2008 (Bangladesh) 4.08 (2.26, 7.38) 3.23

Azim 2009 (Bangladesh) 0.42 (0.06, 3.02) 0.40

Bauer 2008 (Austria) 3.31 (1.63, 6.70) 2.50

Eskild 1993 (Norway) 2.24 (1.46, 3.43) 4.86

Frischer 1997 (UK) 3.53 (1.55, 8.05) 1.96

Fugelstad 1997 (Sweden) 3.75 (2.84, 4.95) 7.08

Fugelstad 1998 (Sweden) 1.38 (0.74, 2.57) 3.00

Galli 1994 (Italy) 2.41 (1.98, 2.94) 8.50

Goedert 1995 (Italy) 10.00 (5.59, 17.88) 3.32

Goedert 2001 (USA) 3.47 (3.11, 3.86) 9.92

Jarrin 2007 (Spain) 3.35 (3.00, 3.75) 9.85

Lumbreras 2006 (Spain) 3.02 (2.54, 3.60) 8.89

Manfredi 2006 (Italy) 2.18 (1.58, 2.99) 6.42

Muga 2007 (Spain) 2.91 (2.24, 3.77) 7.41

O’Driscoll 2001 (USA) 2.48 (0.92, 6.67) 1.44

Quan 2010 (Viet Nam) 3.56 (2.04, 6.21) 3.52

Solomon 2009 (India) 2.93 (1.94, 4.44) 5.01

VanHaastrecht 1996 (Netherlands) 3.62 (2.27, 5.79) 4.37

Vlahov 2008 (USA) 2.46 (1.18, 5.12) 2.36

Zaccarelli 1994 (Italy) 5.31 (3.75, 7.53) 5.95

Overall (I−squared = 66.8%, p = 0.000) 3.15 (2.78, 3.58) 100.00

NOTE: Weights are from random effects analysis

.5 1 2 4 6

Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; HIV, human immunodeficiency virus; RR, relative risk.

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 113 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 9. Crude mortality rates for AIDS-related deaths in people injecting drugs who were HIV-positive at baseline

% Cohort CMR (95% CI) Weight

Eskild 1993 (Norway) 0.62 (0.01, 1.23) 7.11

Fingerhood 2006 (USA) 3.91 (2.48, 5.33) 5.84

Frischer 1997 (UK) 3.41 (−0.45, 7.27) 2.44

Fugelstad 1995 (Sweden) 0.39 (0.10, 0.68) 7.38

Fugelstad 1997 (Sweden) 0.48 (0.26, 0.70) 7.42

Galli 1994 (Italy) 2.97 (2.36, 3.58) 7.10

Goedert 1995 (Italy) 1.73 (1.43, 2.02) 7.38

Goedert 2001 (USA) 9.12 (8.13, 10.10) 6.59

Golz 2001 (Germany) 1.74 (0.83, 2.65) 6.70

Lumbreras 2006 (Spain) 1.94 (1.69, 2.20) 7.40

Manfredi 2006 (Italy) 2.73 (2.28, 3.17) 7.27

Solomon 2009 (India) 3.37 (1.61, 5.14) 5.22

van Haastrecht 1996 (Netherlands) 1.71 (0.74, 2.68) 6.61

Vlahov 2008 (USA) 1.24 (0.25, 2.23) 6.57

Zaccarelli 1994 (Italy) 2.83 (2.25, 3.42) 7.13

Quan 2010 (Viet Nam) 8.64 (3.94, 13.34) 1.84

Overall (I−squared = 96.9%, p = 0.000) 2.55 (1.81, 3.28) 100.00

NOTE: Weights are from random effects analysis

−5 0 5 10 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). AIDS, acquired immunodeficiency syndrome; CI, confidence interval; CMR, crude mortality rate; HIV, human immunodeficiency virus.

Fig. 10. Ratios of crude mortality rates for non-AIDS-related deaths in HIV-positive versus HIV-negative people who inject drugs

% Cohort RR (95% CI) Weight

Eskild 1993 (Norway) 1.96 (1.28, 3.01) 7.65 Frischer 1997 (UK) 1.77 (0.78, 4.02) 4.68 Fugelstad 1997 (Sweden) 2.80 (2.12, 3.70) 8.85 Galli 1994 (Italy) 1.15 (0.94, 1.40) 9.38 Goedert 1995 (Italy) 3.77 (2.11, 6.74) 6.38 Goedert 2001 (USA) 1.31 (1.18, 1.46) 9.81 Lumbreras 2006 (Spain) 1.98 (1.67, 2.36) 9.51 Manfredi 2006 (Italy) 0.57 (0.42, 0.79) 8.55 Quan 2010 (Viet Nam) 1.52 (0.87, 2.65) 6.58 Solomon 2009 (India) 1.83 (1.21, 2.77) 7.75 VanHaastrecht 1996 (Netherlands) 2.66 (1.66, 4.25) 7.30 Vlahov 2008 (USA) 0.62 (0.30, 1.29) 5.26 Zaccarelli 1994 (Italy) 1.96 (1.38, 2.78) 8.31 Overall (I−squared = 88.4%, p = 0.000) 1.63 (1.28, 2.08) 100.00

NOTE: Weights are from random effects analysis

.5 1 2 3 4

Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). AIDS, acquired immunodeficiency syndrome; CI, confidence interval; HIV, human immunodeficiency virus; RR, relative risk.

114 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

Fig. 11. Ratios of crude mortality rates for death from drug overdose in HIV-positive versus HIV-negative people who inject drugs

% Cohort RR (95% CI) Weight

Eskild 1993 (Norway) 2.02 (1.18, 3.45) 13.24

Frischer 1997 (UK) 2.41 (0.58, 10.05) 5.74

Fugelstad 1997 (Sweden) 3.51 (2.33, 5.28) 14.52

Galli 1994 (Italy) 1.04 (0.70, 1.56) 14.57

Goedert 1995 (Italy) 3.90 (1.36, 11.18) 8.22

Manfredi 2006 (Italy) 0.77 (0.43, 1.38) 12.75

Solomon 2009 (India) 2.18 (0.92, 5.16) 9.88

VanHaastrecht 1996 (Netherlands) 3.63 (1.32, 9.94) 8.58

Zaccarelli 1994 (Italy) 2.09 (1.14, 3.83) 12.50

Overall (I−squared = 73.4%, p = 0.000) 1.99 (1.31, 3.04) 100.00

NOTE: Weights are from random effects analysis

.5 1 2 4 6 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; HIV, human immunodeficiency virus; RR, relative risk.

Fig. 12. Ratios of crude mortality rates for AIDS-related death versus death from drug overdose in HIV-positive people who inject drugs

% Cohort RR (95% CI) Weight

Eskild 1993 (Norway) 0.20 (0.07, 0.56) 6.84

Fingerhood 2006 (USA) 4.83 (2.02, 11.57) 7.34

Frischer 1997 (UK) 1.50 (0.26, 8.76) 4.60

Fugelstad 1995 (Sweden) 0.17 (0.08, 0.38) 7.57

Fugelstad 1997 (Sweden) 0.18 (0.10, 0.32) 8.25

Galli 1994 (Italy) 3.13 (2.06, 4.73) 8.62

Goedert 1995 (Italy) 5.08 (3.34, 7.72) 8.61

Golz 2001 (Germany) 2.00 (0.81, 4.93) 7.24

Manfredi 2006 (Italy) 1.81 (1.13, 2.88) 8.51

Solomon 2009 (India) 1.75 (0.74, 4.13) 7.39

van Haastrecht 1996 (Netherlands) 1.20 (0.52, 2.76) 7.47

Vlahov 2005 (USA) 1.70 (1.42, 2.04) 8.99

Zaccarelli 1994 (Italy) 3.56 (2.29, 5.53) 8.56

Overall (I−squared = 92.5%, p = 0.000) 1.35 (0.79, 2.31) 100.00

NOTE: Weights are from random effects analysis

.0719 1 13.9 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). AIDS, acquired immunodeficiency syndrome; CI, confidence interval; HIV, human immunodeficiency virus; RR, relative risk.

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 115 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 13. Ratios of crude mortality rates in HIV-positive males versus HIV-positive females who inject drugs

% Cohort RR (95% CI) Weight

Fugelstad 1998 (Sweden) 1.45 (0.65, 3.23) 3.99

Liu 2011 (China) 1.01 (0.81, 1.26) 52.62

Manfredi 2006 (Italy) 1.22 (0.89, 1.68) 25.88

Zaccarelli 1994 (Italy) 1.30 (0.89, 1.91) 17.50

Overall (I−squared = 0.0%, p = 0.537) 1.13 (0.96, 1.32) 100.00

NOTE: Weights are from random effects analysis

.5 1 3 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; HIV, human immunodeficiency virus; RR, relative risk.

Fig. 14. Ratios of crude mortality rates in HIV-negative males versus HIV-negative females who inject drugs

% Cohort RR (95% CI Weight

Fugelstad 1998 (Sweden) 2.14 (0.77, 5.93) 27.67

Manfredi 2006 (Italy) 1.46 (0.62, 3.44) 39.31

Zaccarelli 1994 (Italy) 2.02 (0.79, 5.15) 33.02

Overall (I−squared = 0.0%, p = 0.820) 1.81 (1.06, 3.09) 100.00

NOTE: Weights are from random effects analysis

.5 1 2 4 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; HIV, human immunodeficiency virus; RR, relative risk. in countries where drug injecting is explanation for this discrepancy might The ability to detect differences in taking place but little research has been lie in the extent of drug injection among mortality in cohort studies according to conducted about it. the groups examined, whether people HIV status is subject to limitations. HIV In this review we found no signifi- used multiple drugs (polydrug use be- status was typically measured at baseline cant differences in the risk of death by ing the norm), or the possibility, seldom only, and some subjects who contracted type of primary drug injected. This con- examined, that some people in the co- HIV infection during follow-up would trasts with the findings of other reviews horts switched from one primary drug remain assigned to the HIV− group for of people dependent on different drug to another during the follow-up period. the entire follow-up period. Nonethe- types, which, despite their own limita- All of these factors would have reduced less, this would only serve to underesti- tions, have suggested differences in our capacity to detect any differences in mate the relative differences in mortality mortality among opioid-, amphetamine- mortality among people injecting differ- between HIV+ and HIV− people who and cocaine-dependent persons.3–5 An ent types of drugs. inject drugs. The markedly higher all-

116 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs nition Stimulant use defi - Primary drug – or speed cocaine or crack cocaine Any ICD-10 code F15 – stimulant dependence Hospital records Hospital records – if had no heroin dependence and at diagnosis had a least once of ATS diagnosis dependence – Main drug injected or ATS – cocaine tion Opioid use defini - Primary drug – heroin Heroin ICD-10 F11 code opioid dependence Hospital records – at – at Hospital records had a least once of heroin diagnosis –opioiddependence user – Main drug injected – heroin – 95% CI 0.20–1.24 1.12–1.86 2.35–4.61 3.46–5.53 0.75–4.56 b d Overdose CMR ratio Overdose Ratio 0.50 1.44 3.29 4.39 1.85 – 95% CI 0.29–0.95 0.69–1.14 1.24–2.44 3.12–6.33 0.33–1.64 0.60–2.61 b c All-cause CMR ratio Ratio 0.88 0.52 1.74 4.44 0.73 1.25 a – – OD 0.54 1.29 0.08 0.38 CMR years; S, stimulant. years; 7 8 – – OD 20 15 person–

(No.) from from Deaths Deaths 94.1%.

85.1%.

=

= a 2

I 2 I – 4.70 0.99 2.57 0.49 4.60 All- CMR verdose; PY, verdose; cause o

0.0005;

0.0005;

<

<

P P – 14 48 39 15 All- (No.) Users of stimulants Users cause 175 deaths deaths 67.99;

20.10;

=

= )

2 ) 2 χ χ – PY 326 3938 3727 544.6 9748.4 a – – 0.78 0.64 0.27 1.67 OD CMR 0.18; heterogeneity (

0.553; heterogeneity (

=

=

P P 1:

1;

=

=

– – OD 16 19 36 72 values were derived from other available data. other available from derived were values italicized (No.) from from Deaths Deaths a – 4.15 4.40 1.34 3.36 0.86 All- CMR cause tality rate; ICD-10, of Diseases; OD, tality Classification International rate; Users of opioids Users 9 – All- 40 85 (No.) cause 114 133 crude mor

deaths deaths – PY 323.9

268 3022.7 2984.9 2047 13 Comparison of risk of dying from all causes and from drug overdose among people injecting all causes opioids and those injecting of risk dying from Comparison drug overdose and from stimulants

46 71 36 57 70 M R M D people injecting (denominator). versus stimulants people injecting for opioids (numerator) the CMR ratio epresents of estimate Test CMR ratio: eta-analysis of overdose of follow-up. per 100 PY eaths of estimate Test eta-analysis of all-cause CMR ratio: a b c d CI, confidence interval;CI, confidence CMR, Note: Values reported in papers appear plain text; Values Note: Table 2. Table Study van van Haastrecht et al. (1996) Pooled estimate O’Driscoll et al. (2001) Lejckova et Lejckova (2007) al. Fugelstad Fugelstad et al. (1997) Vlahov et Vlahov (2005) al.

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 117 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Fig. 15. Ratios of crude mortality rates in people who inject drugs during in-treatment period versus off-treatment period

% Cohort RR (95% CI) Weight

Clausen 2008 (Norway) 1.96 (1.50, 2.56) 18.67

Cornish 2010 (UK) 1.90 (1.40, 2.59) 18.32

Davoli 2007 (Italy) 10.86 (7.25, 16.26) 17.30

Degenhardt 2009 (Australia) 1.92 (1.79, 2.05) 19.85

Fugelstad 1995 (Sweden) 1.19 (0.58, 2.45) 13.37

Fugelstad 1998 (Sweden) 2.55 (1.15, 5.66) 12.49

Overall (I−squared = 93.0%, p = 0.000) 2.52 (1.59, 4.00) 100.00

NOTE: Weights are from random effects analysis

1 5 10 15 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; RR, relative risk.

Table 3. Univariate associations between study-level variables and all-cause crude ported in various forms, including odds mortality rates (CMRs) and standardized mortality ratios (SMRs) ratios, relative risks, hazard ratios and CMRs. Most studies did not report Characteristic CMR SMR SMRs and many failed to report standard parameters such as PY, or were seldom n t P n t P easy to calculate, particularly for disag- Geographic region 53 −1.05 0.298 23 0.74 0.466 gregated mortality estimates. As a result, Country income 67 3.03 0.004 33 0.65 0.519 only a subset of studies could be included Percentage of cohort who inject drugs 60 1.49 0.141 26 2.04 0.052 in many of the analyses. Percentage of males 57 3.40 0.001 31 0.29 0.771 Causes of death were not uniformly Percentage of cohort HIV+ at baseline 30 2.42 0.022 9 1.00 0.349 or consistently coded. Deaths from drug overdose might have been missed Presence of people using opioids 67 −0.07 0.945 33 −1.28 0.209 (alone or with other drugs) in cohort in countries with limited capacity to Year in which follow-up ceased 59 0.26 0.795 32 −2.80 0.009 conduct toxicological tests or where recording a death as being from a drug overdose is surrounded by stigma. As cause mortality that we observed among HAART.55 Unfortunately, we were un- a result, we may have underestimated HIV+ people who inject drugs is there- able to examine the impact of treatment CMRs and SMRs for death from drug fore probably a conservative estimate of for HIV infection across studies because overdose. Misattribution of deaths by the elevation in mortality in that group. mortality was rarely reported separately HIV status may have occurred, since Misattribution of cause of death as either for the periods before and after the in- most cohorts were assessed for HIV AIDS- or non-AIDS-related could have troduction of HAART.77 However, the status at the beginning of the study only occurred as well. observed association between cohorts and people infected during follow-up Treatment for HIV infection has with more recent follow-up periods and could have been missed. Again, this may improved greatly and has become more lower SMRs might have to do with the have resulted in conservative estimates widely available. In some cohorts, mor- greater availability in recent years of ef- of mortality among HIV+ people who tality was examined for the periods be- fective interventions for the prevention inject drugs and in lower effect sizes. In fore and after highly active antiretroviral and treatment of HIV infection. future research, assessing individuals’ therapy (HAART) was introduced. The Reporting quality was poor. Few HIV status at several time points during findings suggest that mortality among studies met criteria in consensus state- the follow-up period would allow a more HIV+ people who inject drugs decreased ments for the reporting of observational accurate measurement of mortality in after the widespread introduction of studies.7 Mortality estimates were re- relation to HIV status.

118 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

Fig. 16. Crude mortality rates for people who inject drugs, by country income group

% Cohort CMR (95% CI) Weight high income Antolini 2006 (Italy) 2.01 (1.79, 2.16) 1.83 Bargagli 2001 (Italy) 2.15 (2.05, 2.25) 1.84 Bauer 2008 (Austria) 5.42 (3.45, 7.40) 0.77 Brancato 1995 (Italy) 2.04 (1.26, 2.83) 1.51 Ciccolallo 2000 (Italy) 2.26 (2.08, 2.43) 1.83 Clausen 2008 (Norway) 1.95 (1.70, 2.23) 1.80 Copeland 2004 (UK) 2.45 (2.06, 2.84) 1.75 Cornish 2010 (UK) 1.00 (0.86, 1.15) 1.83 Davoli 2007 (Italy) 0.74 (0.59, 0.88) 1.83 Degenhardt 2009 (Australia) 0.89 (0.86, 0.92) 1.85 Digusto 2004 (Australia) 1.27 (0.40, 2.29) 1.40 EMCDDA 2011 (Sweden) 3.33 (2.98, 3.68) 1.77 EMCDDA 2011 (Croatia) 1.09 (0.93, 1.25) 1.83 Eskild 1993 (Norway) 2.77 (2.22, 3.42) 1.64 Esteban 2003 (Spain) 3.68 (3.11, 4.25) 1.66 Evans 2012 (USA) 0.91 (0.62, 1.20) 1.79 Fingerhood 2006 (USA) 7.14 (5.22, 9.06) 0.80 Frischer 1997 (UK) 2.08 (1.52, 2.64) 1.66 Fugelstad 1995 (Sweden) 3.85 (2.94, 4.76) 1.43 Fugelstad 1997 (Sweden) 1.99 (1.72, 2.25) 1.80 Fugelstad 1998 (Sweden) 7.76 (5.54, 10.58) 0.57 Galli 1994 (Italy) 2.52 (2.28, 2.77) 1.81 Goedert 1995 (Italy) 1.57 (1.41, 1.75) 1.83 Goedert 2001 (USA) 4.67 (4.42, 4.92) 1.81 Golz 2001 (Germany) 4.22 (2.80, 5.64) 1.08 Haarr 2007 (Norway) 1.92 (0.95, 3.44) 1.19 Hickman 2003 (UK) 1.61 (1.13, 2.23) 1.67 Jarrin 2007 (Spain) 2.02 (1.92, 2.12) 1.84 Lejckova 2007 (Czech Republic) 0.84 (0.75, 0.93) 1.84 Lumbreras 2006 (Spain) 2.18 (2.00, 2.36) 1.83 Manfredi 2006 (Italy) 2.04 (1.80, 2.30) 1.81 McAnulty 1995 (USA) 1.05 (0.69, 1.41) 1.77 Mezzelani 1998 (Italy) 2.91 (2.48, 3.33) 1.74 Miller 2007 (Canada) 1.37 (0.80, 1.94) 1.65 Moroni 1991 (Italy) 2.43 (2.16, 2.69) 1.80 Muga 2007 (Spain) 3.74 (3.38, 4.14) 1.76 Nyhlen 2011 (Sweden) 1.30 (1.12, 1.48) 1.83 O’Driscoll 2001 (USA) 1.59 (1.22, 1.96) 1.76 Oppenheimer 1994 (UK) 1.83 (1.28, 2.38) 1.67 Reece 2010 (Australia) 0.50 (0.36, 0.65) 1.83 Sanchez−Carbonell 2000 (Spain) 3.40 (2.36, 4.44) 1.33 Seaman 1998 (UK) 2.33 (1.60, 3.27) 1.48 Sorensen 2005 (Denmark) 3.49 (2.45, 4.53) 1.33 Stenbacka 2007 (Sweden) 2.12 (1.93, 2.31) 1.82 Stoove 2008 (Australia) 0.83 (0.56, 1.21) 1.78 Tait 2008 (Australia) 0.50 (0.29, 0.72) 1.82 VanHaastrecht 1996 (Netherlands) 3.23 (2.56, 4.07) 1.54 Vlahov 2005 (USA) 4.50 (4.24, 4.76) 1.80 Vlahov 2008 (USA) 0.71 (0.54, 0.88) 1.83 Zabransky 2011 (Czech Republic) 0.48 (0.15, 0.81) 1.78 Zaccarelli 1994 (Italy) 2.30 (1.96, 2.63) 1.78 Subtotal (I−squared = 98.8%, p = 0.000) 2.17 (1.92, 2.42) 83.99 . low and middle income Azim 2008 (Bangladesh) 6.32 (4.68, 7.96) 0.94 Azim 2009 (Bangladesh) 3.52 (2.46, 4.59) 1.31 Cardoso 2006 (Brazil) 2.77 (1.45, 4.09) 1.14 EMCDDA 2011 (Romania) 0.57 (0.47, 0.68) 1.84 EMCDDA 2011 (Bulgaria) 1.18 (0.91, 1.46) 1.80 EMCDDA 2011 (Latvia) 1.60 (1.43, 1.77) 1.83 Jafan 2010 (Islamic Republic of Iran) 4.08 (1.25, 6.91) 0.48 Liu 2011 (China) 6.89 (5.79, 7.98) 1.29 Moskalewicz 1996 (Poland) 2.28 (1.81, 2.83) 1.69 Quan 2007 (Thailand) 3.85 (2.42, 5.83) 0.91 Quan 2010 (Viet Nam) 6.30 (4.60, 8.50) 0.78 Rahimi-Movahgar 2009 (Islamic Republic of Iran) 4.83 (0.00, 14.30) 0.10 Solomon 2009 (India) 4.25 (3.35, 5.16) 1.43 Zhang 2005 (China) 7.73 (4.87, 10.60) 0.47 Subtotal (I−squared = 97.0%, p = 0.000) 3.53 (2.81, 4.24) 16.01 . Overall (I−squared = 98.6%, p = 0.000) 2.35 (2.12, 2.58) 100.00 NOTE: Weights are from random effects analysis

−10 −5 0 5 10 15 Image produced using Stata (StataCorp. LP, College Station, TX, United States of America). CI, confidence interval; CMR, crude mortality rate.

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 119 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

Limitations of the review and reference lists. Meta-analytical methods AIDS-related mortality in settings with a meta-analysis were originally developed to aggregate high prevalence of HIV infection. HIV+ the findings of randomized controlled people who inject drugs have higher Our review has limitations. The lag trials,85 which have the advantage of mortality not just from HIV-related time between the date when the studies allowing for control or adjustment of causes but also from drug overdose. were conducted and when they were pre-conditions and sample-related fac- Mortality varies by participant- and published in peer-reviewed journals was tors that could influence the outcomes study-level characteristics, which sug- generally long. In light of this we used of interest. Controlling for such factors gests that multiple factors contribute several methods to search for published is not possible in observational studies, to the higher risk of death observed in and unpublished studies. We reviewed like the ones included in our review. people who inject drugs. Many of these primarily English-language papers, factors are probably modifiable, since although we also reviewed the abstracts Conclusion certain predominant causes of death ac- of non-English-language peer-reviewed count for most of the mortality observed articles when they were available in People who inject drugs have a much in this group. ■ English. When studies seemed relevant, higher risk of death than those who do we had them translated; we engaged ex- not. Major causes of death in this group Competing interests: None declared. perts from a range of different countries are often poorly specified, but death and language groups to review these from drug overdose is common, as is

ملخص معدل الوفيات بني األشخاص الذين يتعاطون املخدرات عن طريق احلقن: استعراض منهجي وحتليل وصفي الغرضاستعراض الدراسات األترابية املعنية بمعدل الوفيات بني الثنتني وثالثني جمموعة؛ وكانت نسبة الوفيات املوحدة 14.68 األشخاص الذين يتعاطون املخدرات عن طريق احلقن عىل نحو )فاصل الثقة 95 %: 13.01 إىل 16.35(. وأظهرت مقارنة منهجي، ودراسة معدالت الوفيات وأسباب الوفاة يف هذه الفئة، معدالت الوفيات األولية وحساب نسب معدالت الوفيات وحتديد متغريات مستوى املشاركني والدراسة املرتبطة بارتفاع األولية ارتفاع معدل الوفيات يف البلدان املنخفضة واملتوسطة خطر الوفاة. الدخل بني املجموعات والذكور واألشخاص اإلجيابيني لفريوس تم الطريقةاستخدام عبارات بحث خمصصة للبحث يف قواعد العوز املناعي البرشي )HIV( الذين تعاطوا املخدرات عن طريق بيانات EMBASE وMedline و . PsycINFOوتم حتديد احلقن. وكان املعدل ً مرتفعاكذلك خالل فرتات وقف العالج. الكتابات غري الرسمية من خالل قواعد بيانات الكتابات غري وكانفرط جرعة املخدرات ومتالزمة العوز املناعي املكتسب الرسمية عىل شبكة اإلنرتنت. وتم استشارة اخلرباء للحصول )األيدز( السببني الرئيسيني للوفاة بني املجموعات. عىل دراسات وبيانات إضافية. وتم إجراء التحليالت الوصفية االستنتاجمقارنة بعامة السكان، يتعرض األشخاص الذين للتأثريات العشوائية لتقييم معدالت الوفيات األولية املجمعة يتعاطون املخدرات عن طريق احلقن خلطر وفاة مرتفع، عىل الرغم )CMRs( ونسب الوفيات املوحدة )SMRs(. منتفاوت معدالت الوفيات بني البيئات املختلفة. وجيب أن تم حتديدالنتائج سبع وستني جمموعة من األشخاص الذين يتضمن أي هنج شامل لتحسني حصائل الصحة يف هذه الفئة ًجهودا يتعاطون املخدرات عن طريق احلقن، أربع عرشة منها من البلدان خلفض عدوى اإلصابة بفريوس العوز املناعي البرشي باإلضافة املنخفضة واملتوسطة الدخل. وكان معدل الوفيات األويل املجمع إىل غريها من أسباب الوفاة، والسيام فرط جرعة املخدرات. 2.35 وفاة لكل 100 شخص-سنة )فاصل الثقة 95 %، فاصل الثقة: 2.12 إىل (. 2.58وتم اإلبالغ عن نسب الوفيات املوحدة

摘要 药物注射人群的死亡率：系统回顾和荟萃分析 目的 系统回顾药物注射人群死亡率的队列研究，检查该群 集的SMR为14.68（95% CI：13.01-16.35）。CMR的比 体的死亡率和死亡原因，并确定与较高死亡风险相关的参 较和CMR比率的计算表明，中低收入国家的队列、男性 与水平和研究水平变量。 以及艾滋病毒（HIV）呈阳性的药物注射人群中的死亡率 方法 使用定制的搜索字符串搜索EMBASE、Medline和 较高。治疗结束期间死亡率也较高。药物过量和艾滋病 PsycINFO。通过网上灰色文献数据库识别灰色文献。咨询 （AIDS）是各个队列的主要死亡原因。 专家以获取更多的研究和数据。执行随机效果荟萃分析来 结论 尽管不同环境中的死亡率各异，与普通人群相比，药 估计汇集的粗死亡率（CMR）和标准化死亡率（SMR）。 物注射人群的死亡风险更高。任何改善该群体的健康疗效 结果 确定67 个药物注射人群队列，其中14 个来自中低 的综合方案都必须包括减少艾滋病毒感染以及其他死亡致 收入国家。汇集的CMR为每100 人年2.35 例死亡（95% 因（尤其是药物过量）的努力。 置信区间，CI：2.12-2.58）。报告32 个队列的SMR；汇

120 Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 Systematic reviews Bradley M Mathers et al. Mortality among people who inject drugs

Résumé Mortalité chez les personnes qui s’injectent des drogues : revue systématique et méta-analyse Objectif Examiner systématiquement les études de cohortes de la Les TMS étaient indiqués pour 32 cohortes, avec un TMS groupé de 14,68 mortalité chez les toxicomanes par injection, étudier les taux de mortalité (IC de 95%: 13,01 – 16,35). La comparaison des TBM et le calcul des taux et les causes de décès dans ce groupe, et identifier les variables, au niveau de TMS ont révélé une mortalité plus élevée parmi les cohortes des pays des participants et des études, associées à un risque accru de décès. à revenu faible et intermédiaire, les sujets masculins et les toxicomanes Méthodes Des critères de recherche spécifiquement adaptés ont été par injection séropositifs. Elle était également plus élevée pendant utilisés pour les recherches réalisées sur EMBASE, Medline et PsycINFO. les périodes d’interruption thérapeutique. L’overdose et le syndrome La littérature grise a été identifiée par le biais de bases de données de d’immunodéficience acquise (SIDA) étaient les causes principales des littérature grise disponibles en ligne. Des experts ont été consultés pour décès parmi ces cohortes. obtenir des données et des études supplémentaires. Des méta-analyses Conclusion Si l’on compare avec la population globale, les personnes des effets aléatoires ont été réalisées afin d’estimer les taux bruts de qui s’injectent des drogues ont un risque élevé de décès, bien que les mortalité (TBM) groupés et les taux de mortalité standardisés (TMS). taux de mortalité varient selon les contextes. Toute approche exhaustive Résultats Soixante-sept cohortes de personnes qui s’injectent des visant à améliorer les résultats de ce groupe en matière de santé doit drogues ont été identifiées, dont 14 appartenant à des pays à revenu comprendre des efforts en vue de diminuer l’infection par le VIH, ainsi faible et intermédiaire. Le TBM groupé était de 2,35 décès pour que d’autres causes de décès, notamment l’overdose. 100 personnes-années (intervalle de confiance de 95%, IC: 2,12 – 2,58).

Резюме Смертность среди лиц, вводящих наркотики внутривенно: систематический обзор и мета-анализ Цель Провести систематический обзор когортных исследований интервал, ДИ: 2,12–2,58). СКС фиксировался для 32 когорт; смертности среди лиц, вводящих наркотики внутривенно, суммарный СКС составлял 14,68 (95% ДИ: 13,01-16,35). Сравнение изучить уровни смертности и причины смерти в данной группе и ОПС и расчет коэффициентов ОПС выявил высокий уровень определить переменные на уровне участников и исследований, смертности в когортах, относящихся к странам с низким и связанные с высоким риском смерти. средним уровнями доходов, среди мужчин и лиц, вводивших Методы Поиск исследований осуществлялся по базам данных наркотики внутривенно, которые имели положительные EMBASE, Medline и PsycINFO по специализированным критериям результаты на вирус иммунодефицита человека (ВИЧ). Высокий поиска. Поиск литературы для служебного пользования уровень также отмечен вне периодов лечения. Передозировка осуществлялся по онлайновым базам данных литературы для наркотиков и синдром приобретенного иммунодефицита (СПИД) служебного пользования. С целью получения дополнительных являлись основными причинами смерти в когортах. данных и исследований проводились консультации с экспертами. Вывод По сравнению с населением в целом, лица, вводящие Для определения суммарных общих показателей смертности наркотики внутривенно, подвержены повышенному риску (ОПС) и стандартизированных коэффициентов смертности (СКС) смерти несмотря на то, что уровни смертности варьируются выполнялся мета-анализ случайных эффектов. в зависимости от условий. Любой комплексный подход к Результаты Были выявлены шестьдесят семь когорт лиц, улучшению результатов мероприятий по охране здоровья в вводящих наркотики внутривенно, 14 из которых относятся к данной группе должен включать в себя меры по сокращению странам с низким и средним уровнями доходов. Суммарный ОПС уровня ВИЧ-инфекции, а также других причин смерти, в составлял 2,35 смертей на 100 человеко-лет (95% доверительный особенности, передозировки наркотиков.

Resumen La mortalidad entre consumidores de drogas inyectables: una revisión sistemática y meta-análisis Objetivo Revisar de forma sistemática los estudios de cohortes sobre la para 32 cohortes; la tasa bruta combinada de mortalidad fue de 14,68 mortalidad entre los consumidores de drogas inyectables, examinar las (IC 95%: 13,01-16,35). La comparación de las tasas brutas combinadas tasas de mortalidad y las causas de muerte en este grupo e identificar de mortalidad y el cálculo de las proporciones de la mortalidad las variables relacionadas con el estudio y los participantes asociadas a bruta combinada revelaron que la mortalidad fue superior en las un mayor riesgo de muerte. cohortes de países con ingresos bajos y medios, en varones y entre Métodos Se emplearon cadenas de búsqueda adaptadas para registrar consumidores de drogas inyectables que dieron positivo para el virus EMBASE, Medline y PsycINFO. La literatura gris se identificó por medio de de la inmunodeficiencia humana (VIH), así como durante los periodos bases de datos de literatura gris en línea. Se consultaron expertos a fin sin tratamiento. Las sobredosis y el síndrome de la inmunodeficiencia de obtener datos y estudios adicionales y se llevaron a cabo metaanálisis adquirida (SIDA) fueron las causas principales de muerte en las cohortes. de efectos aleatorios para calcular las tasas brutas combinadas de Conclusión En comparación con la población general, los consumidores mortalidad y las tasas de mortalidad estandarizadas. de drogas inyectables presentan un riesgo elevado de muerte, si bien Resultados Se identificaron diecisiete cohortes de consumidores las tasas de mortalidad varían en los distintos lugares. Cualquier enfoque de drogas inyectables, 14 de las cuales en países con ingresos completo para mejorar los resultados sanitarios en este grupo deberá bajos y medios. La tasa bruta combinada de mortalidad fue de 2,35 esforzarse por reducir la infección por VIH, así como las otras causas de fallecimientos por cada 100 años-persona (intervalo de confianza del muerte, en especial, la sobredosis. 95%, IC: 2,12-2,58). Se declararon las tasas de mortalidad estandarizadas

Bull World Health Organ 2013;91:102–123 | doi:10.2471/BLT.12.108282 121 Systematic reviews Mortality among people who inject drugs Bradley M Mathers et al.

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