Mortality risk factors and excess mortality in a cohort of cocaine users admitted to drug treatment in Spain

Journal of Substance Abuse Treatment 46 (2014) 219–226

Contents lists available at ScienceDirect

Journal of Substance Abuse Treatment

Mortality risk factors and excess mortality in a cohort of cocaine users admitted to drug treatment in Spain☆,☆☆,★ Luis de la Fuente, M.D., Ph.D. a, b, Gemma Molist, MSc a, b, Albert Espelt, M.P.H., Ph.D. c, d, Gregorio Barrio, M.D., Ph.D. e,⁎, Anna Guitart, MSc c, d, Maria J. Bravo, M.D., Ph.D. a, b, M. Teresa Brugal c, d Spanish Working Group for the Study of Mortality among Drug Users 1 a

National Epidemiology Center, Carlos III Health Institute, Madrid, Spain Consortium for Biomedical Research in Epidemiology & Public Health (CIBERESP), Madrid, Spain c Public Health Agency, Barcelona, Spain d Biomedical Research Institute Sant Pau (IIB-Sant Pau), Barcelona, Spain e National School of Public Health, Carlos III Health Institute, Madrid, Spain b

a r t i c l e

i n f o

Article history: Received 27 February 2013 Received in revised form 1 July 2013 Accepted 1 July 2013 Keywords: Cocaine Cohort Drug treatment Excess mortality Mortality Risk factors

a b s t r a c t We assessed mortality risk factors and excess mortality compared to the general population in two Spanish sub-cohorts of 8,825 cocaine and heroin users (CHUs) and 11,905 only cocaine users (OCUs) aged 15–49 admitted to drug treatment. Heroin use (among all cocaine users), no-regular employment and drug injection (among CHUs and OCUs), daily cocaine use and previous drug treatment (among CUs), and death before 2005 and N10 years of heroin use (among CHUs) were clearly associated with higher mortality in Cox regression. Excess mortality was assessed by the directly standardized mortality rate ratio, which was higher in CHUs (14.3; 95% CI: 12.6–16.2) than CUs (5.1; 95% CI: 4.3–6.0) and in women than men, especially among OCUs (8.6; 95% CI: 7.5–10.0 vs. 3.5; 95% CI: 3.3–3.8); it decreased with age among CHUs, but did not decrease overall during 1997–2008. OCUs excess mortality was considerable and showed no signs of decline, suggesting the need for improved treatment and prevention interventions. © 2013 Elsevier Inc. All rights reserved.

1. Introduction Cocaine use is widespread in many countries, mainly among young adults. In most countries cocaine is usually administered by sniffing, with smoking and injection generally restricted to heroin users and marginalized groups (United Nations Office on Drugs and Crime (UNODC), 2011; European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2012; Substance Abuse & Mental Health Services Administration (SAMHSA), 2012a; Substance Abuse and Mental Health Services Administration (SAMHSA) (2012b)). Cocaine use has been associated with increased risk of cardiovascular, neurological, and psychiatric disorders, as well as unintentional ☆ Funding: This work was supported by the Spanish Network on Addictive Disorders grant number RD06/0001/1018 and RD12/0028/0018 and The Spanish Fund for Health Research (FIS) grants, numbers PI070661 and PI061807. ☆☆ Ethics approval: This study was conducted with the approval of the Clinical Research Ethical Committee of the Municipal Institute of Health Care (CEIC-IMAS), Barcelona. ★ Conflict of interest: None. ⁎ Corresponding author. Instituto de Salud Carlos III, Escuela Nacional de Sanidad, Avenida Monforte de Lemos 5, 28029 Madrid, Spain. E-mail address: [email protected] (G. Barrio). 1 The Working Group for this study includes the following people: Francisco Babín, Montserrat Bartroli, Yolanda Castellano, Antonia Domingo-Salvany, Teresa Hernández, Blanca Indave, Beatriz Mesías, Carmen Puerta, Sara Santos, Ana Sarasa y Luis Sordo). 0740-5472/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jsat.2013.07.001

injuries, violent behaviours, and other health problems (European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2007; Kaye & Darke, 2004a; Kuhns, Wilson, Maguire, Ainsworth, & Clodfelter, 2009; Macdonald et al., 2003; Maraj, Figueredo, & Lynn, 2010; Marzuk et al., 1995; Qureshi, Suri, Guterman, & Hopkins, 2001; Ryb et al., 2009; Santos et al., 2012; Schnitzer et al., 2010). Cocaine accounts for a significant proportion of treatment admissions for illicit drugs in some countries. In addition, in the US and Spain it is the illicit drug related to the highest proportion of emergency room visits (United Nations Office on Drugs and Crime (UNODC), 2011; Delegación del Gobierno para el Plan Nacional sobre Drogas (DGPNSD), 2011; Substance Abuse and Mental Health Services Administration (SAMHSA) (2012b); European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), 2012). Thus, cocaine can be expected to contribute to a certain number of deaths in countries where it is used. The role of cocaine in mortality can be assessed by quantifying the drug-induced deaths in which cocaine use is mentioned using special or general mortality registers (Bernstein et al., 2007; Coffin et al., 2003; Darke, Kaye, & Duflou, 2005; Delegación del Gobierno para el Plan Nacional sobre Drogas (DGPNSD), 2011; Sanchez et al., 1995; Substance Abuse and Mental Health Services Administration, 2012), by investigating the presence of cocaine through toxicological analysis in some violent or sudden deaths (Kuhns et al., 2009; Lucena et al., 2010), or by studying mortality in cohorts of cocaine users over time

220

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

(Arendt, Munk-Jorgensen, Sher, & Jensen, 2011; Barrio et al., 2013; Degenhardt et al., 2011b; Dias, Ribeiro, Dunn, Sesso, & Laranjeira, 2008; Pavarin, 2008; Ribeiro, Dunn, Laranjeira, & Sesso, 2004). All these have advantages and limitations, but this last approach makes it possible to quantify excess mortality in cocaine users compared to their age-sex peers in the general population, as well as to identify factors associated with a higher mortality risk (mortality risk factors). Excess mortality is an indicator of the health needs of cocaine users in relation to the general population, and its time trends may reflect the influence of various factors, including changes in drug use patterns or the effectiveness of harm reduction interventions aimed at cocaine users (for example, drug abuse treatment). The excess mortality for all causes among cohorts of cocaine users has been estimated as 4–12 times greater than in the general population (Arendt et al., 2011; Barrio et al., 2013; Degenhardt et al., 2011b; Dias et al., 2011). Most published estimates come from cohorts with over-representation of heroin users, drug injectors or crack/ cocaine smokers, which are known or suspected to be associated with a higher risk of mortality (Barrio et al., 2013; Degenhardt et al., 2011a; Muhuri & Gfroerer, 2011). Thus, extrapolation of these estimates to all cocaine users in the general population could overestimate excess mortality. Moreover, most such estimates are based on standardized mortality ratios (SMRs); which allow comparison of the mortality risk of the cohort or cohort sub-groups with their age-sex peers in the general population, but not the excess mortality between different sub-groups, for example men and women. However, the latter comparisons would be possible using the direct method of standardization (Rothman, Greenland, & Lash, 2008). Published data on mortality risk factors among cocaine users is scarce, due to limited cohort size or the difficulty of collecting information on relevant variables. Heroin or opioid use is suspected to be one of the main mortality risk factors, although its effect has not been quantified. This higher risk can be explained by the negative effects of the opioids themselves or a possible heightening of the negative effects of cocaine, especially on the cardiovascular system, when used concurrently with opioids, although this last remains a subject of debate (Bandettini et al., 2006; Goletiani, Mendelson, Sholar, Siegel, & Mello, 2009; Krantz, Baker, & Schmittner, 2006; Leri, Bruneau, & Stewart, 2003; Mello et al., 2005; Molina & Hargrove, 2011; Saland, Hillis, Lange, & Cigarroa, 2002; Schindler et al., 2007; United Nations Office on Drugs and Crime (UNODC), 2011). There is also a higher extent of crack/cocaine smoking and drug injection among cocaine users who also use heroin than among those who do not, which probably increases the risk of cardiovascular, respiratory, infectious, overdose and mental health problems (Baum et al., 2009; Cook et al., 2008; Devlin & Henry, 2008; Gossop, Manning, & Ridge, 2006; Hatsukami & Fischman, 1996; Shearer et al., 2007). In addition to opioid use and older age, other mortality risk factors are history of intravenous drug use (Arendt et al., 2011; Ribeiro et al., 2004), unemployment at baseline (Ribeiro et al., 2004), premature discharge from treatment or short time in treatment (Ribeiro et al., 2004; Yang, Huang, & Hser, 2006), early initiation of cocaine use (Yang et al., 2006), white ethnicity (Yang et al., 2006) or psychiatric comorbidity (Arendt et al., 2011). There are also some indications that the risk of death could be higher in males (Bernstein et al., 2007; Pavarin, 2008) and alcohol drinkers (Santos et al., 2012). Finally, excess mortality of cocaine users in comparison with the general population seems to be higher in females than males (Arendt et al., 2011; López, Martineau, & Palle, 2004), although the published results are not entirely conclusive. In most mortality studies, cohorts of cocaine users are recruited in drug treatment facilities. In Spain in 1997–2009, an average of some 15,000 treatment admissions per year were reported for cocaine and 8,000 for heroin (in most of which the patient had also used cocaine in the 30 days prior to treatment). Thus, it is possible to recruit large cohorts of cocaine users for these studies. Treatment for cocaine abuse or dependence in Spain is generally based on individual or group therapy

with cognitive-behavioural orientation, with possible pharmacological support in case of psychiatric comorbidity (depression, anxiety, psychosis, etc.). Currently the most widespread treatment for heroin abuse or dependence is methadone maintenance, with buprenorphine maintenance used only rarely. It has been estimated that the coverage of heroin users by opioid substitution treatment (OST) in the whole country increased from 29% in 1997 to 61.9% in 2008, and that the increase occurred earlier in Barcelona than Madrid (Barrio et al., 2012). The objectives of this study were: a) to estimate the mortality risk in a Spanish cohort of cocaine users, and to identify factors associated with a higher mortality risk, assessing especially the effect of heroin use, and b) to estimate excess mortality of two sub-cohorts defined by heroin use at baseline in comparison with the general population by sex and calendar-year of death. 2. Methods 2.1. Participants A dynamic cohort of 20,730 cocaine users aged 15–49 was recruited in the cities of Madrid and Barcelona, Spain. Cocaine users who started drug treatment in 1997–2007 in publicly owned or funded centres in the two cities were included in the cohort regardless of whether they had been treated for drugs prior to 1997. Repeated admissions of the same subject were eliminated. All the treatment centres were outpatient centres that reported to the national drug information system and provided free care. Participants were initially separated in two subgroups, those who at baseline were cocaine and heroin users (CHUs), and those who were only cocaine users (OCUs). The criterion for cocaine use at baseline was being admitted for treatment to quit or reduce cocaine use or evidence in the clinical record of having used such drug within 30 days prior to treatment admission. The criterion for heroin use at baseline was similar, but obviously referring to heroin. 2.2. Baseline and follow up assessments At the time of treatment admission an individual record was completed for each patient, including date of recruitment (which coincides with the date of treatment admission), existence of previous drug treatment, personal identifiers (first name, surname, date of birth and sex), socio-demographic variables (age, education, and employment), and drug use variables (lifetime drug injection, and frequency and length of cocaine and heroin use). Baseline measurements of socio-demographic variables and frequency of drug use referred to time of treatment admission or the previous 30 days. The proportion of missing values was less than 4% for all variables. Participants were followed until 31 December 2008. Vital status and date of death were obtained through record linkage with the Spanish National Mortality Register, which is virtually exhaustive, using the identifiers mentioned above. All individuals who were not identified as dead were considered to be alive at the end of follow-up. The rate of emigration abroad of the general population of the same age was estimated at 0.2% (Instituto Nacional de Estadística (INE), 2012), but this rate could be higher in cocaine users. Particular attention was paid to guaranteeing absolute confidentiality. In the cities of Madrid and Barcelona the data base with individual records from all drug treatment centres are centralized, registered in the Spanish Data Protection Agency, and subject to high security levels, as required by Spanish legislation on data protection for health data. The extraction of data for this study was performed in two different databases, one with personal identifiers and another with the epidemiological data. The record of the same patient in both bases included a meaningless identical code to link the information. In order to obtain mortality data, the database containing personal identifiers was sent to the Spanish National Mortality Register. The record linkage was performed in the register offices, obtaining a file without personal

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

identifiers, but containing vital status, date and cause of death and the aforementioned meaningless code that would later allow the linkage of mortality data with the rest of the epidemiological data. 2.3. Statistical analysis All-cause crude mortality rates (CRs) by age and sex were computed separately for OCUs and CHUs. CRs were expressed per thousand person-years of follow-up (py) using the dynamic method of allocation of py and deaths to the categories of age and length of cocaine and heroin use. Each subject contributes to py from the baseline date until the date of death or 31-12-2008. Rates were directly standardized (SRs) by age and sex using weights from the European standard population stratified into 5-year age groups. The mortality standardized rate ratio (SRR) was then calculated, allowing comparisons of mortality experience between subgroups, adjusted by age and sex. 95% Confidence intervals (CIs) of estimates were obtained, assuming a baseline Poisson distribution of deaths in each stratum of age-sex. For confidence intervals of the SRRs it was also assumed that the SR in the numerator varied independently of the SR in the denominator, applying the variance formula for the natural logarithm of the SRR (Rothman et al., 2008). To identify mortality risk factors, CRs were calculated by calendaryear of death, as well as the socio-demographic and drug use variables mentioned above. Additionally, bivariate and multivariate Cox regression models were fitted for OCUs, CHUs and all participants using age as the time-scale for the outcome variable. Participants entered the population at risk at their baseline age and exited at the age of death. The independent variables were year of death, sex, education, employment, lifetime drug injection, frequency of cocaine and heroin use, and length of cocaine and heroin use, with the latter two considered as varying over time. Variables found to be significant (P b 0.05) in the bivariate analysis were included in the multivariate model, along with those considered to be potential confounders, using the backward procedure to select the final set of covariates in the model. The proportional hazards assumption was checked by a test based on smoothed Schoenfeld residuals. Each variable fulfilled the assumption, except lengths of cocaine or heroin use, which were time-dependent, therefore extended Cox regression was used to fit the model. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for different mortality risk factors were obtained. Records with missing data were excluded from the models. To estimate the excess mortality in relation to the general population, SRRs were calculated for different subgroups, using the SRs of the general population of Madrid and Barcelona as the denominator. In order to consistently characterize the trends of annual SRs or SRRs by age or calendar-year, some join point regression models were fitted (National Cancer Institute, 2013). This methodology uses joined linear segments on a logarithmic scale. Each join point indicates a statistically significant (p b 0.05) change in trend, either in direction or intensity. Standard errors of SRs and SRRs were entered in the models. The join points were identified by a permutation test, after which a linear regression was fitted for each segment, estimating the corresponding annual percent change (APC). A permutation test was used to select the optimal number of join points. Analyses were performed with STATA version 12.1 (Cleves, Gould, Gutierrez, & Marchenko, 2008), and Joinpoint software 4.0.1 (National Cancer Institute, 2013). 3. Results 3.1. Baseline characteristics At baseline most participants were men and were recruited in Madrid. Most of them had secondary or higher education, and had never injected drugs (never injectors). Only 42.9% had regular employment (Table 1). The mean age and length of cocaine use

221

was 31.0 (Standard deviation [SD]: 7.1) and 10.7 years (SD: 6.5), respectively. A total of 8,825 participants were CHUs and 11,905 were OCUs. CHUs had lower education and higher unemployment, and included a slightly lower proportion of men and a much higher proportion of ever drug injectors and persons previously admitted to drug treatment than OCUs (Table 1). The mean age was 32.4 years among CHUs vs. 30.0 years among OCUs, p b 0.001, and the mean length of cocaine use was 12.3 years among CHUs vs. 8.9 among OCUs, p b 0.001. OCUs recruited in Barcelona compared to Madrid included a significantly higher proportion of lifetime drug injectors (13.0% vs. 3.0%) and patients previously admitted to drug treatment (23.2% vs. 2.7%). They also showed other significant, but smaller, differences in socio-demographic or drug use variables. The CHUs recruited in Barcelona compared to Madrid included a significantly higher proportion of lifetime drug injectors (74.2% vs. 35.8%), patients previously admitted to drug treatment (64.7% vs. 33.4%) and daily cocaine users (42.3% vs. 33.7%). They also showed significantly lower length of heroin (11.1 vs. 13.0) and cocaine use (11.0 vs. 13.1), and significant, although smaller, differences in other variables. 3.2. Mortality rates Participants generated a total of 132,824 person-years of follow-up during 1997–2008. The mean length of follow-up in all participants was 6.4 (SD: 3.4) years. A total of 1,691 deaths from all causes were recorded, giving an average annual CR of 12.7/1000 py (95% CI: 12.1– 13.3). The SR was slightly higher among men than women (SRR = 1.2; 95% CI: 1.1–1.3). Table 1 Baseline characteristics of the participants by heroin use at baseline (%).

City of recruitment Madrid Barcelona Year of recruitment 1997–2000 2001–2004 2005–2007 Male Age 15–24 25–29 30–34 35–39 40–49 Secondary education or higher No regular employmenta Length of cocaine use (years) N15 10–14 5–9 b5 Daily cocaine usea Frequency of heroin usea Heroin use daily Heroin use less than daily No heroin use Length of heroin use (years) N 15 10–14 5–9 b5 Lifetime drug injector Previous admission to drug treatment

Only cocaine users (OCUs) (n = 11905)

Cocaine and heroin users (CHUs) (n = 8825)

Total (n = 20730)

55.8 44.2

78.1 21.9

65.3 34.7

25.1 38.4 36.5 83.0

62.9 25.1 12.0 81.0

41.2 32.8 26.1 82.1

14.4 22.7 24.2 18.8 19.9 76.3 43.5

3.8 12.5 23.2 28.1 32.4 62.3 75.5

9.9 18.3 23.8 22.8 25.2 70.4 57.1

19.2 23.2 29.9 27.7 25.2

38.5 27.8 20.5 13.2 35.6

27.4 25.2 25.9 21.5 29.6

0.0 0.0 100.0

42.0 58.0 0.0

17.9 24.7 57.4

_ _ _ _ 7.4 11.6

40.0 26.1 19.9 14.0 44.2 39.7

40.0 26.1 19.9 14.0 23.1 23.5

Note: All the above variables showed statistically significant differences between CHUs and OCUs (p b 0.001). a Last 30 days before treatment admission.

222

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

The mean length of follow-up was 7.6 years (SD: 3.4) for CHUs and 5.5 (SD: 3.0) for OCUs. Mortality rates by sex and age group for OCUs and CHUs are shown in Table 2. When age trends of mortality rates were modelled using join point regression, the CR increased significantly with age in both OCUs (APC = 6.5%; 95% CI: 4.3–8.6) and CHUs (APC = 3.9%; 95% CI: 3.2–4.7). The SR was considerably higher among CHUs than OCUs (SRR = 2.8; 95% CI: 2.3–3.4). Men had higher a SR than women among CHUs (SRR = 1.5; 95% CI:1.3–1.6), but not among OCUs (SRR = 0.9; 95% CI:0.8–1.1). The SRs by calendar-year of death for OCUs and CHUs are shown in Fig. 1. A statistically significant downward trend in the SR was observed by calendar-year of death among CHUs (APC = − 4.4%; 95% CI: − 7.8 to − 0.8), and a complex curve with a join point in 2000 among OCUs, although none of the segment trends (slopes) reached statistical significance. When the SR was modelled according to the number of years since treatment admission (which coincides with the number of years in the cohort), no significant trends were observed among OCUs, whereas among CHUs a significant linear downward trend was seen with increasing number of years (APC = − 8.6, 95% CI: − 5.9 to − 11.3). Fig. 1. Title: Time trends of mortality in two groups of cocaine users and the general population. Madrid and Barcelona, 1997–2008. Title X-axis: Calendar-year. Title Y-axis: Standardized rates per thousand person-years (py). Footnote: CHUs: Cocaine and heroin users. People aged 15–49 who were admitted to drug treatment and had used both cocaine and heroin in the 30 days prior to treatment admission. OCUs: Only cocaine users. People aged 15–49 who were admitted to drug treatment and had used cocaine but not heroin in the 30 days prior to treatment admission. General population: General population of Madrid and Barcelona aged 15–49. Standardized rates (95% CI): Direct age- and sex-standardized rate using weights of the European Standard Population stratified into 5-year age groups. The vertical lines represent the confidence intervals at 95% (95% CI).

3.3. Mortality risk factors In the bivariate analysis heroin use within 30 days of baseline was a strong mortality risk factor. Other significant mortality risk factors among OCUs and CHUs are shown in Table 3. Heroin use was also the strongest independent predictor of a higher mortality risk among all cocaine users in multivariate Cox regression (aHR = 2.1; 95% CI: 1.8– 2.4). Among OCUs, the main independent risk factors were not having

Table 2 Mortality indicators among two groups of cocaine users and the general population aged 15–49. Madrid and Barcelona, 1997–2008. Excess mortality (rate ratioa)

Mortality rate (deaths/1000 person-years) Only cocaine users (OCUs) Point estimate Males 15–24 25–29 30–34 35–39 40–44 45–49 15–49 15–49b Females 15–24 25–29 30–34 35–39 40–44 45–49 15–49 15–49b Both sexes 15–24 25–29 30–34 35–39 40–44 45–49 15–49 15-49b

95%

Cocaine and heroin users (CHUs)

General population

OCUs

CI

Point estimate

95%

CI

Point estimate

Point estimate

CHUs 95%

CI

Point estimate

95%

CI

2.7 3.8 4.1 6.1 5.7 14.3 5.3 5.5

1.4 2.7 3.1 4.6 3.9 10.7 4.7 5.1

3.9 4.9 5.2 7.6 7.5 17.9 5.9 5.8

14.1 14.0 17.1 20.8 22.2 32.1 20.8 18.8

7.9 11.0 14.8 18.6 19.5 27.9 19.5 17.1

20.4 17.1 19.3 23.1 24.8 36.4 22.0 20.5

0.5 0.7 1.1 1.7 2.4 3.8 1.5 1.5

4.9 5.2 3.8 3.6 2.4 3.8 3.5 3.5

3.1 3.9 2.9 2.8 1.7 3.0 3.1 3.3

7.8 7.0 4.9 4.6 3.2 4.9 3.9 3.8

25.9 19.2 15.5 12.2 9.1 8.6 13.8 12.2

16.7 15.3 13.5 10.9 8.1 7.5 13.0 11.2

40.3 23.9 17.7 13.6 10.3 9.8 14.6 13.3

1.0 3.8 4.6 7.1 11.8 10.2 5.6 5.8

−0.4 1.3 1.9 3.4 6.0 3.5 4.2 5.0

2.5 6.3 7.3 10.8 17.6 16.8 7.0 6.7

5.7 10.4 12.2 18.8 24.7 17.6 16.3 12.9

0.1 5.7 8.3 14.3 18.4 10.4 14.1 11.9

11.3 15.1 16.0 23.3 31.0 24.8 18.5 13.8

0.2 0.3 0.5 0.7 1.1 1.6 0.7 0.7

4.4 13.1 10.1 9.6 10.4 6.2 8.2 8.6

1.1 6.8 5.6 5.7 6.4 3.2 6.4 7.5

17.6 25.2 18.2 16.2 17.0 12.0 10.5 10.0

24.4 35.8 26.8 25.4 21.8 10.8 23.8 19.1

9.1 22.7 19.5 19.9 16.8 7.2 20.8 17.7

65.3 56.4 36.9 32.4 28.2 16.2 27.3 20.6

2.3 3.8 4.2 6.3 6.7 13.6 5.3 5.6

1.3 2.8 3.2 4.9 4.9 10.4 4.8 4.7

3.3 4.8 5.2 7.6 8.5 16.8 5.9 6.6

11.3 13.2 16.1 20.5 22.6 29.8 19.9 15.8

6.8 10.6 14.1 18.5 20.1 26.0 18.8 13.9

15.9 15.8 18.0 22.5 25.1 33.6 21.0 17.8

0.4 0.5 0.8 1.2 1.8 2.6 1.1 1.1

5.9 7.4 5.4 5.1 3.8 5.2 4.9 5.1

3.8 5.7 4.2 4.1 2.9 4.1 4.4 4.3

9.2 9.7 6.9 6.4 5.0 6.5 5.4 6.0

29.0 25.6 20.6 16.8 12.9 11.3 18.2 14.3

19.4 21.0 18.1 15.1 11.5 10.0 17.2 12.6

43.4 31.3 23.3 18.5 14.4 12.9 19.2 16.2

OCUs: People aged 15–49 who were admitted to drug treatment and had used cocaine but not heroin in the 30 days prior to treatment admission. CHUs: People aged 15–49 who were admitted to drug treatment and had used both cocaine and heroin in the 30 days prior to treatment admission. General population: General population of Madrid and Barcelona aged 15–49; 95% CI: 95% confidence interval. a Rate ratios are computed using the rate in the general population as the reference. b Direct age- and sex-standardized rate (and rate ratio) using weights of the European Standard Population stratified into 5-year age groups.

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

223

Table 3 Crude mortality rate (CR) and adjusted hazard ratio (aHR) among two subgroups of cocaine users aged 15–49, by year of death and baseline characteristics. Madrid and Barcelona, 1997–2008. Only cocaine users (OCUs) No. of deaths TOTAL Year of death 1997–2000 2001–2004 2005–2008 City of recruitment Madrid Barcelona Sex Male Female Secondary education or higher No Yes Regular Employmenta No Yes Length of cocaine use N10 years 5–10 years ≤5 years Daily cocaine usea Yes No Lifetime drug injection Yes No Frequency of heroin usea Heroin use dailyb Heroin use less than dailyb No heroin use Length of heroin use (nº of years)b N10 years 5–10 years ≤5 years Previous drug treatment Yes No

CR (×1000 py)

aHR

Cocaine and heroin users (CHUs) 95% CI

No. of deaths

CR (×1000 py)

aHR

All cocaine users 95% CI

No. of deaths

CR (×1000 py)

1691

12.7

313 608 770

16.7⁎ 13.7⁎ 11.1

1212 479

13.5⁎ 11.1

aHR

95% CI

1.6 1.2 1.0

1.4–1.8 1.1–1.4

349

5.3

1342

19.9

33 111 205

5.8 5.7 5.1

280 497 565

21.6⁎ 19.9 19.1

158 191

4.5⁎ 6.3

1054 288

19.4 21.8

288 61

5.3 5.6

1130 212

20.8⁎ 16.3

1.2 1.0

1.0–1.4

1418 273

13.0⁎ 11.4

1.1 1.0

1.0–1.3

104 245

6.9⁎ 4.9

588 754

23.5⁎ 17.8

1.2 1.0

1.1–1.4

692 999

17.2⁎ 10.8

1.2 1.0

1.1–1.4

211 138

7.5⁎ 3.7

2.0 1.6–2.5 1.0

1130 212

22.4⁎ 12.5

1.8 1.0

1.5–2.1

1341 350

17.0⁎ 6.5

1.9 1.0

1.6–2.1

237 86 26

6.2⁎ 4.4⁎ 3.3

1.1 0.8–1.5 1.3 1.0–1.7 1.0

1159 144 39

20.7⁎ 16.6⁎ 13.4

1396 230 65

6.0⁎ 8.2⁎ 6.0

1.3 1.3 1.0

1.0–1.7 1.0–1.7

119 230

7.1⁎ 4.7

1.4 1.1–1.7 1.0

442 900

19.1 20.3

1.1 1.0

1.0–1.3

561 1130

14.0⁎ 12.2

289 60

13.1⁎ 4.8

1.9 1.4–2.6 1.0

657 685

24.2⁎ 17.0

1.4 1.0

1.2–1.6

974 717

22.6⁎ 9.6

1.5 1.0

1.3–1.7

527 815 _

19.5 20.2 _

1.1 1.0

1.0–1.3

527 815 349

19.5⁎ 20.2⁎ 5.3

2.1 2.0 1.0

1.8–2.4 1.7–2.3

1167 123 52

21.1⁎ 14.0⁎ 16.1

1.4 1.0 1.0

1.1–1.7 0.8–1.2

589 729

21.1⁎ 19.0

665 992

18.4⁎ 10.5

349

76 263

5.3

9.2⁎ 4.7

1.4 1.1–1.9 1

1.5 1.2 1.0

1.3–1.7 1.1–1.4

OCUs: People aged 15–49 who were admitted to drug treatment and had used cocaine but not heroin in the 30 days prior to treatment admission. CHUs: People aged 15–49 who were admitted to drug treatment and had used both cocaine and heroin in the 30 days prior to treatment admission. CR (×1000 py): Crude mortality rate per 1000 person-years; aHR (95% CI): Adjusted hazard ratio wit h Cox regression (95% confidence interval). a Last 30 days before treatment admission. b Refers only to CHUs. ⁎ Statistical significance of CR ratios with reference to the last category (P b 0.05).

regular employment (aHR = 2.0; 95% CI: 1.6–2.5) and lifetime drug injection (aHR = 1.9; 95% CI: 1.4–2.6). Other significant risk factors were daily cocaine use and having been previously admitted to drug treatment. Gender was not a significant risk factor. Among CHUs, the main risk factors were not having regular employment (aHR = 1.8; 95% CI: 1.5–2.1), death in 1997–2000 (aHR = 1.5; 95% CI: 1.3–1.7), and lifetime drug injection (aHR = 1.4; 95% CI: 1.2–1.6). Other significant risk factors were being male, death in 2001–2004, less than secondary education, length of heroin use over 10 year, and daily cocaine use (Table 3). The city of recruitment was not a factor significantly associated with mortality risk among CUs or CHUs, after adjusting for other covariates. 3.4. Excess mortality compared to the general population Excess mortality was much lower for OCUs than CHUs (SRR = 5.1 vs. 14.3), and was higher in women than men in both OCUs (SRR = 8.6 vs. 3.5) and CHUs (SRR = 19.1 vs. 12.2) (Table 2). When the trends in excess mortality by age were modelled using join point regression, a significant downward trend with increasing age was found among CHUs (APC = −4.0), but not in OCUs. Significant trends by calendar-year

were not found among CHUs, whereas a significant upward trend was seen among OCUs between 1997 and 1999, followed by a relatively stable trend between 1999 and 2008. 4. Discussion We estimated the mortality risk in a large Spanish cohort of treated cocaine users aged 15–49 for a maximum of 12 years (1997– 2008), accounting for heroin use at baseline. We identified some mortality risk factors and estimated excess mortality compared to the general population. The main findings were the following: a) The crude mortality rate was 5.3/1000 py among OCUs and 19.9/1000 py among CHUs; b) Recent heroin use at baseline was a strong independent predictor of a higher mortality risk (aHR = 2.1) among all cocaine users. In addition to age, not having regular employment and lifetime drug injection were important independent mortality risk factors both among OCUs and CHUs. Daily cocaine use and previous drug treatment (among OCUs), and calendar-year of death prior to 2004 and more than ten years of heroin use (among CHUs) were also important predictors; c) Considerable excess mortality compared to the general population was found in both

224

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

OCUs (SRR = 5.1) and CHUs (SRR = 14.3), and was higher in women than men, especially among OCUs (SRR = 8.6 vs. 3.5). Excess mortality decreased with increasing age in CHUs, but not in OCUs. A significant decrease in excess mortality in more recent years was not found among either CHUs or OCUs. One of the strengths of this study is that we controlled for the effect of heroin use at baseline, which is essential to obtain valid estimates of excess mortality since, as shown in this and other studies, this behaviour is associated with a high risk of mortality (Barrio et al., 2013; Degenhardt et al., 2011a; Muhuri & Gfroerer, 2011). The sample size is quite large (perhaps greater than in any other published study), which leads to relatively precise estimates among subgroups (i.e. men-women, CHUs-OCUs, age-subgroups). Furthermore, excess mortality has been estimated using ratios of directly standardized rates, allowing comparisons among cohort subgroups. However, the study also has some limitations. The results refer to patients admitted to drug treatment, most of whom probably had a diagnosis of cocaine abuse or dependence. The main consequence of self-selection of cocaine users included in the cohort is that the results on mortality risk and excess mortality in this study probably represent an overestimation of these values among cocaine users in the general population. This is especially true in the case of OCUs, because the proportion of lifetime drug injectors or daily cocaine users among cocaine users in the general population is probably lower than in our cohort. Another potential limitation is that an unknown proportion of cocaine users may have migrated abroad during follow-up. These people may have died during their stay abroad, therefore they would not have been included in the Spanish general register of mortality (losses to follow-up). As participants who were not found on the mortality register were considered alive, losses to follow-up could lead to some underestimation of the mortality risk. However, the effect of this problem on the main results should be negligible, because during the study period the annual rate of migration abroad among the Spanish population of the same age was only 0.2%. As the proportion of unknown values for different covariates was less than 4%, is also very unlikely that this could have introduced significant bias affecting the main findings. There may also have been some misclassification by drug use patterns because of recall biases or socially desirable responses. Only a small number of confounding factors could be evaluated. Data on the duration and nature of the treatment were not available, so the effect of these variables on mortality risk cannot be estimated. Furthermore, changes in drug use patterns during follow-up could not be assessed. The probability of changes over time in patterns of drug use among Spanish cocaine users is relatively high, as suggested by a recently published study (Barrio et al., 2013). Some of such changes would increase the mortality risk (e.g. starting heroin use) and others would decrease it (e.g. quitting cocaine use). In any case, in the present study it is impossible to know the contribution of each specific change to the final net estimate of mortality risk. The CR among OCUs, who at baseline had not used heroin, used cocaine mainly by sniffing and who mostly (92.6%) had never injected drugs, was 5.6/1000 py. This rate is in the range of those found in other European cohorts of cocaine users (range 2.3–7.9/1000 py) (Arendt et al., 2011; Barrio et al., 2013; Degenhardt et al., 2011b; Pavarin, 2008), but much lower than that found among crack users in Brazil (35.1/1000 py) (Ribeiro et al., 2004) or in cocaine users who inject drugs (Degenhardt et al., 2011b). If cocaine users who had ever used heroin or injected drugs were excluded, the figures would probably be lower (Barrio et al., 2013). There are few published studies that identify mortality risk factors among cocaine users. Our results suggest that the concomitant use of heroin seems to be the most important predictor (aHR of heroin use vs. no use was 2.1). This effect has not been previously quantified, although it was already known that the CR of heroin users (20.9/1000

py (Degenhardt et al., 2011a)) was much higher than that of cocaine users. Among OCUs, besides age (whose effect was not estimated in the multivariate analysis because age was the time-scale for the outcome variable), the other identified mortality risk factors were not having regular employment, lifetime injection drug use, daily cocaine use and previous drug treatment. The first two factors have already been identified in previous studies (Arendt et al., 2011; Ribeiro et al., 2004). The last two had not been mentioned previously. An increased risk of mortality with increasing frequency of cocaine use is plausible, because frequent users are more likely than less frequent users to have a higher level of dependence, greater likelihood of negative health effects attributable to the effect of cocaine, and a greater probability of using other drugs whose effect has not been controlled. The risk of most acute and chronic health complications after cocaine use would be dose-dependent, and some evidence has been published in this regard (Kaye & Darke, 2004a; Kaye & Darke, 2004b; Santos et al., 2012). The increased risk of mortality among cocaine users who had previously been admitted to drug treatment suggests that cocaine users who relapse in drug use after treatment have a worse prognosis. Premature discharge from treatment or short time in treatment had already been identified as risk factors for an increased mortality risk (Ribeiro et al., 2004; Yang et al., 2006). Not having regular employment and lifetime injection drug use, calendar-year of death before 2004, and more than ten years of heroin use were identified as risk factors among CHUs. Drug injection had already been identified as a risk factor for a higher mortality risk among heroin users (Degenhardt et al., 2011a). The decrease in mortality risk in recent years could be due to the decrease in HIVrelated mortality and fatal opioid overdoses (Barrio et al., 2012; Ferreros, Lumbreras, Hurtado, Perez-Hoyos, & Hernandez-Aguado, 2008). However, no clear time trend was identified among OCUs, and the annual changes in mortality risk are difficult to interpret. Considerable excess mortality compared to the general population was found in both OCUs (SRR = 5.1) and CHUs (SRR = 14.3). This excess mortality cannot automatically be attributed to cocaine or heroin use, because participants and the general population may differ in other factors that were not assessed, such as mental disorders, personality factors, social conditions, etc. Moreover, as stated above, patterns of drug use (especially cocaine and heroin use, drug injection) were assessed only at baseline. In any case, excess mortality among OCUs is within the range of published results for cocaine users (SMR = 4–12) (Arendt et al., 2011; Barrio et al., 2013; Degenhardt et al., 2011b; Dias et al., 2011; López, Martineau, & Palle, 2004; Pavarin, 2008), and among CHUs is close to the published results for general cohorts of heroin users (Degenhardt et al., 2011a). However, there may be important differences between the cohorts regarding some relevant characteristics (age, drug dependence, other drug use, drug administration routes, etc.) that could affect the comparison. The excess mortality in OCUs was much higher among women than men, because mortality rates in men and women were very similar in this group, whereas in the general population aged 15–49 the rate for women is half that of men. Previous studies had been inconclusive in this respect because of their limited sample sizes Arendt et al., 2011; López, Martineau, & Palle, 2004, except for one study (Callaghan et al., 2012). It seems, therefore, that cocaine use (or lifestyle or living conditions associated with it) would be more harmful in women than men. In fact, in cocaine users women have been found to have a higher rate of non-fatal cocaine overdose than men (Kaye & Darke, 2004b; Mesquita et al., 2001; Santos et al., 2012). The mechanism to explain this excess risk is unknown. In the present work, we also found a higher excess mortality in women than men among CHUs, primarily because of the intersexual difference in general population mortality. These findings are consistent with those observed among regular heroin users in previous studies (Callaghan et al., 2012; Degenhardt et al., 2011a). One study has also found a higher risk of non-fatal opioid overdose in females than males (Powis et al., 1999).

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

There were no significant differences in excess mortality by age among OCUs, as seen in the fact that the increase of CRs with age was similar in both OCUs and the general population. The likely decline with age of mortality from external causes (unintentional injuries, etc.) would not be enough to balance the effect of other factors such as the greater probability of adverse effects of drugs (cardiovascular, neurological, etc.) with aging due to changes in pharmacokinetics, accumulation of organic and functional harm caused by past drug use, chronic health problems likely to worsen or be triggered by drug use, and interactions with medications (Beynon, 2009; Dowling, Weiss, & Condon, 2008; Gossop & Moos, 2008). However, in CHUs excess mortality clearly decreased with age, due to the fact that the increase of CR with age was lower in this subgroup than in the general population. The decline in CHUs is consistent with the results of some cohorts of heroin users (Degenhardt et al., 2011a) and could be partially explained by the decrease with age of the risk of fatal opioid overdoses, as a result of experience and learning, and by the survival bias (the most vulnerable die younger). Most studies have consistently reported a decrease in the risk of non-fatal opioid overdose with age (Bergenstrom et al., 2008; Coffin et al., 2007; Copeland, Budd, Robertson, & Elton, 2004; Kinner et al., 2012), although there are some studies in which this has not been observed (Kerr et al., 2007; Ochoa, Hahn, Seal, & Moss, 2001). Finally, it should be noted that a significant decrease of excess mortality in more recent years was not found in OCUs and CHUs, although a significant decrease in the risk of death was found in the latter group. This suggests that the potential positive effect of harm reduction interventions targeted to CHUs was overshadowed by a parallel decline in mortality in the general population. Our results are relevant for public health because they can be used to obtain better estimations of cocaine-attributable mortality. The OCU subcohort of this study is probably more representative of all cocaine users in the general population than in other published studies. However, all participants probably had a diagnosis of abuse/dependence, so that the excess mortality of cocaine users in general may be overestimated. Moreover, knowledge of time trends in mortality risk and excess mortality may allow assessment of the effectiveness of harm reduction policies targeted to cocaine users, including drug treatment. In this regard, the situation in Spain seems to be no worse than in other European countries. However, the fact that excess mortality did not decrease in 1997–2008 supports the hypothesis that no great advances in these policies were made in that period. New studies that collect data on changes in drug use during follow-up in the main subgroups of cocaine users in different geographical areas continue to be needed. Acknowledgments Grateful thanks are due to the people working in drug information systems and drug treatment centres in the cities of Madrid and Barcelona, as well as Francisco de Asís Babín and the Madrid Institute of Addictions. References Arendt, M., Munk-Jorgensen, P., Sher, L., & Jensen, S. O. (2011). Mortality among individuals with cannabis, cocaine, amphetamine, MDMA, and opioid use disorders: a nationwide follow-up study of Danish substance users in treatment. Drug and Alcohol Dependence, 114, 134–139. Bandettini, D. P., Fornai, F., Paparelli, A., Pacini, M., Perugi, G., & Maremmani, I. (2006). Comparison between heroin and heroin-cocaine polyabusers: a psychopathological study. Annals of the New York Academy of Sciences, 1074, 438–445. Barrio, G., Bravo, M. J., Brugal, M. T., Díez, M., Regidor, E., Belza, M. J., et al. (2012). Harm reduction interventions for drug injectors or heroin users in Spain: expanding coverage as the storm abates. Addiction, 107, 1111–1122. Barrio, G., Molist, G., de la Fuente, L., Fernández, F., Guitart, A., Bravo, M. J., et al. (2013). Mortality in a cohort of young primary cocaine users: controlling the effect of the riskiest drug-use behaviours. Addictive Behaviour, 38, 1601–1604.

225

Baum, M. K., Rafie, C., Lai, S., Sales, S., Page, B., & Campa, A. (2009). Crack-cocaine use accelerates HIV disease progression in a cohort of HIV-positive drug users. Journal of Acquired Immune Deficiency Syndromes, 50, 93–99. Bergenstrom, A., Quan, V. M., Van, N. L., McClausland, K., Thuoc, N. P., Celentano, D., et al. (2008). A cross-sectional study on prevalence of non-fatal drug overdose and associated risk characteristics among out-of-treatment injecting drug users in North Vietnam. Substance Use & Misuse, 43, 73–84. Bernstein, K. T., Bucciarelli, A., Piper, T. M., Gross, C., Tardiff, K., & Galea, S. (2007). Cocaine- and opiate-related fatal overdose in New York City, 1990–2000. BMC Public Health, 7, 31. Beynon, C. M. (2009). Drug use and ageing: Older people do take drugs! Age and Ageing, 38, 8–10. Callaghan, R. C., Cunningham, J. K., Verdichevski, M., Sykes, J., Jaffer, S. R., & Kish, S. J. (2012). All-cause mortality among individuals with disorders related to the use of methamphetamine: A comparative cohort study. Drug and Alcohol Dependence, 125, 290–294. Cleves, M., Gould, W., Gutierrez, R., & Marchenko, Y. (2008). An introduction to survival analysis using Stata. Texas: Stata Press. Coffin, P. O., Galea, S., Ahern, J., Leon, A. C., Vlahov, D., & Tardiff, K. (2003). Opiates, cocaine and alcohol combinations in accidental drug overdose deaths in New York City, 1990–98. Addiction, 98, 739–747. Coffin, P. O., Tracy, M., Bucciarelli, A., Ompad, D., Vlahov, D., & Galea, S. (2007). Identifying injection drug users at risk of nonfatal overdose. Academic Emergency Medicine, 14, 616–623. Cook, J. A., Burke-Miller, J. K., Cohen, M. H., Cook, R. L., Vlahov, D., Wilson, T. E., et al. (2008). Crack cocaine, disease progression, and mortality in a multicentre cohort of HIV-1 positive women. AIDS, 22, 1355–1363. Copeland, L., Budd, J., Robertson, J. R., & Elton, R. A. (2004). Changing patterns in causes of death in a cohort of injecting drug users, 1980–2001. Archives of Internal Medicine, 164, 1214–1220. Darke, S., Kaye, S., & Duflou, J. (2005). Cocaine-related fatalities in New South Wales, Australia 1993–2002. Drug and Alcohol Dependence, 77, 107–114. Degenhardt, L., Bucello, C., Mathers, B., Briegleb, C., Ali, H., Hickman, M., et al. (2011a). Mortality among regular or dependent users of heroin and other opioids: a systematic review and meta-analysis of cohort studies. Addiction, 106, 32–51. Degenhardt, L., Singleton, J., Calabria, B., McLaren, J., Kerr, T., Mehta, S., et al. (2011b). Mortality among cocaine users: a systematic review of cohort studies. Drug and Alcohol Dependence, 113, 88–95. Delegación del Gobierno para el Plan Nacional sobre Drogas (DGPNSD) (2011). Observatorio Español de la Droga y las Toxicomanías (OEDT). Informe 2011. Situación y tendencias de los problemas de drogas en España [Spanish Monitoring Centre for Drugs and Drug Addiction. 2011 Report. Status and trends of drug problems in Spain]. Madrid: DGPNSD. Ministerio de Sanidad, Política Social e Igualdad. Devlin, R. J., & Henry, J. A. (2008). Clinical review: Major consequences of illicit drug consumption. Critical Care, 12, 202. Dias, A. C., Araujo, M. R., Dunn, J., Sesso, R. C., de Castro, V., & Laranjeira, R. (2011). Mortality rate among crack/cocaine-dependent patients: a 12-year prospective cohort study conducted in Brazil. Journal of Substance Abuse Treatment, 41, 273–278. Dias, A. C., Ribeiro, M., Dunn, J., Sesso, R., & Laranjeira, R. (2008). Follow-up study of crack cocaine users: situation of the patients after 2, 5, and 12 years. Substance Abuse, 29, 71–79. Dowling, G. J., Weiss, S. R., & Condon, T. P. (2008). Drugs of abuse and the aging brain. Neuropsychopharmacology, 33, 209–218. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). (2007). EMCDDA 2007 selected issue – Cocaine and crack cocaine: a growing public health issue. Luxembourg: Office for Official Publications of the European Communities. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). (2012). Annual report 2012: the state of the drugs problem in Europe. Luxembourg: Publications Office of the European Union. Ferreros, I., Lumbreras, B., Hurtado, I., Perez-Hoyos, S., & Hernandez-Aguado, I. (2008). The shifting pattern of cause-specific mortality in a cohort of human immunodeficiency virus-infected and non-infected injecting drug users. Addiction, 103, 651–659. Goletiani, N. V., Mendelson, J. H., Sholar, M. B., Siegel, A. J., & Mello, N. K. (2009). Opioid and cocaine combined effect on cocaine-induced changes in HPA and HPG axes hormones in men. Pharmacology, Biochemistry, and Behavior, 91, 526–536. Gossop, M., Manning, V., & Ridge, G. (2006). Concurrent use of alcohol and cocaine: differences in patterns of use and problems among users of crack cocaine and cocaine powder. Alcohol and Alcoholism, 41, 121–125. Gossop, M., & Moos, R. (2008). Substance misuse among older adults: a neglected but treatable problem. Addiction, 103, 347–348. Hatsukami, D. K., & Fischman, M. W. (1996). Crack cocaine and cocaine hydrochloride. Are the differences myth or reality? Journal of the American Medical Association, 276, 1580–1588. Instituto Nacional de Estadística (INE). (2012). Estadística de variaciones residenciales. Serie 1998–2011. INE. Kaye, S., & Darke, S. (2004a). Injecting and non-injecting cocaine use in Sydney, Australia: physical and psychological morbidity. Drug and Alcohol Review, 23, 391–398. Kaye, S., & Darke, S. (2004b). Non-fatal cocaine overdose among injecting and noninjecting cocaine users in Sydney Australia. Addiction, 99, 1315–1322. Kerr, T., Fairbairn, N., Tyndall, M., Marsh, D., Li, K., Montaner, J., et al. (2007). Predictors of non-fatal overdose among a cohort of polysubstance-using injection drug users. Drug and Alcohol Dependence, 87, 39–45. Kinner, S. A., Milloy, M. J., Wood, E., Qi, J., Zhang, R., & Kerr, T. (2012). Incidence and risk factors for non-fatal overdose among a cohort of recently incarcerated illicit drug users. Addictive Behaviour, 37, 691–696.

226

L. de la Fuente et al. / Journal of Substance Abuse Treatment 46 (2014) 219–226

Krantz, M. J., Baker, W. A., & Schmittner, J. (2006). Cocaine and methadone: parallel effects on the QTc interval. The American Journal of Cardiology, 98, 1121. Kuhns, J. B., Wilson, D. B., Maguire, E. R., Ainsworth, S. A., & Clodfelter, T. A. (2009). A meta-analysis of marijuana, cocaine and opiate toxicology study findings among homicide victims. Addiction, 104, 1122–1131. Leri, F., Bruneau, J., & Stewart, J. (2003). Understanding polydrug use: review of heroin and cocaine co-use. Addiction, 98, 7–22. López D, Martineau H, Palle C. (2004). Mortality of individuals arrested for heroin, cocaine or crack use (Tendances No. 36). Paris: Observatoire Français des Drogues et des Toxicomanies. Lucena, J., Blanco, M., Jurado, C., Rico, A., Salguero, M., Vazquez, R., et al. (2010). Cocainerelated sudden death: a prospective investigation in south-west Spain. European Heart Journal, 31, 318–329. Macdonald, S., Anglin-Bodrug, K., Mann, R. E., Erickson, P., Hathaway, A., Chipman, M., et al. (2003). Injury risk associated with cannabis and cocaine use. Drug and Alcohol Dependence, 72, 99–115. Maraj, S., Figueredo, V. M., & Lynn, M. D. (2010). Cocaine and the heart. Clinical Cardiology, 33, 264–269. Marzuk, P. M., Tardiff, K., Leon, A. C., Hirsch, C. S., Stajic, M., Portera, L., et al. (1995). Fatal injuries after cocaine use as a leading cause of death among young adults in New York City. The New England Journal of Medicine, 332, 1753–1757. Mello, N. K., Mendelson, J. H., Sholar, M. B., Jaszyna-Gasior, M., Goletiani, N., & Siegel, A. J. (2005). Effects of the mixed mu/kappa opioid nalbuphine on cocaineinduced changes in subjective and cardiovascular responses in men. Neuropsychopharmacology, 30, 618–632. Mesquita, F., Kral, A., Reingold, A., Haddad, I., Sanches, M., Turienzo, G., et al. (2001). Overdoses among cocaine users in Brazil. Addiction, 96, 1809–1813. Molina, D. K., & Hargrove, V. M. (2011). Fatal cocaine interactions: a review of cocainerelated deaths in Bexar County, Texas. The American Journal of Forensic Medicine and Pathology, 32, 71–77. Muhuri, P. K., & Gfroerer, J. C. (2011). Mortality associated with illegal drug use among adults in the United States. The American Journal of Drug and Alcohol Abuse, 37, 155–164. National Cancer Institute. (2013). Joinpoint Regression Program, Version 4.0.1 - January 2013. Bethesda, MD: National Cancer Institute. [Available at: http://surveillance. cancer.gov/joinpoint/]. Ochoa, K. C., Hahn, J. A., Seal, K. H., & Moss, A. R. (2001). Overdosing among young injection drug users in San Francisco. Addictive Behaviour, 26, 453–460. Pavarin, R. M. (2008). Cocaine consumption and death risk: a follow-up study on 347 cocaine addicts in the metropolitan area of Bologna. Annali dell'Istituto Superiore di Sanità, 44, 91–98. Powis, B., Strang, J., Griffiths, P., Taylor, C., Williamson, S., Fountain, J., et al. (1999). Selfreported overdose among injecting drug users in London: extent and nature of the problem. Addiction, 94, 471–478. Qureshi, A. I., Suri, M. F., Guterman, L. R., & Hopkins, L. N. (2001). Cocaine use and the likelihood of nonfatal myocardial infarction and stroke: data from the Third National Health and Nutrition Examination Survey. Circulation, 103, 502–506.

Ribeiro, M., Dunn, J., Laranjeira, R., & Sesso, R. (2004). High mortality among young crack cocaine users in Brazil: a 5-year follow-up study. Addiction, 99, 1133–1135. Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern epidemiology. Philadelphia, PA: Lippincott Williams & Wilkins. Ryb, G. E., Cooper, C. C., Dischinger, P. C., Kufera, J. A., Auman, K. M., & Soderstrom, C. A. (2009). Suicides, homicides, and unintentional injury deaths after trauma centre discharge: cocaine use as a risk factor. The Journal of Trauma, 67, 490–496. Saland, K. E., Hillis, L. D., Lange, R. A., & Cigarroa, J. E. (2002). Influence of morphine sulfate on cocaine-induced coronary vasoconstriction. The American Journal of Cardiology, 90, 810–811. Sanchez, J., Rodriguez, B., de la Fuente, L., Barrio, G., Vicente, J., Roca, J., et al. (1995). Opiates or cocaine: mortality from acute reactions in six major Spanish cities. Journal of Epidemiology and Community Health, 49, 54–60. Santos, S., Brugal, M. T., Barrio, G., Castellano, Y., Domingo-Salvany, A., Espelt, A., et al. (2012). Assessing the effect of patterns of cocaine and alcohol use on the risk of adverse acute cocaine intoxication. Drug and Alcohol Review, 31, 439–446. Schindler, C. W., Graczyk, Z., Gilman, J. P., Negus, S. S., Bergman, J., Mello, N. K., et al. (2007). Effects of kappa opioid agonists alone and in combination with cocaine on heart rate and blood pressure in conscious squirrel monkeys. European Journal of Pharmacology, 576, 107–113. Schnitzer, S., Bellis, M. A., Anderson, Z., Hughes, K., Calafat, A., Juan, M., et al. (2010). Nightlife violence: a gender-specific view on risk factors for violence in nightlife settings: a cross-sectional study in nine European countries. Journal of Interpersonal Violence, 25, 1094–1112. Shearer, J., Johnston, J., Fry, C. L., Kaye, S., Dillon, P., Dietze, P., et al. (2007). Contemporary cocaine use patterns and associated harms in Melbourne and Sydney, Australia. Drug and Alcohol Review, 26, 537–543. Substance Abuse and Mental Health Services Administration (SAMHSA), Center for Behavioral Health Statistics and Quality (2012). The DAWN Report: Highlights of the 2010. Drug AbuseWarning Network (DAWN). Findings on drug-related emergency department visits. Rockville, MD: SAMHSA. [Available at: http:// www.samhsa.gov/data/2k12/DAWN096/SR096EDHighlights2010.pdf]. Substance Abuse and Mental Health Services Administration (SAMHSA) (2012a). Results from the 2010 National Survey on Drug Use and Health: Detailed Tables. Prevalence Estimates, Standard Errors, P Values, and Sample Sizes Rockville, MD: SAMHSA. Substance Abuse and Mental Health Services Administration (SAMHSA), Center for Behavioral Health Statistics and Quality (2012b). Treatment Episode Data Set (TEDS): 2000–2010. National Admissions to Substance Abuse Treatment Services. (Rep. No. HHS Publication No. (SMA) 12–4701). Rockville, MD: SAMHSA. [Available at: http://www.samhsa.gov/data/2k12/TEDS2010N/TEDS2010NWeb.pdf]. United Nations Office on Drugs and Crime (UNODC). (2011). World Drug Report 2011 Vienna. Yang, J. C., Huang, D., & Hser, Y. I. (2006). Long-term morbidity and mortality among a sample of cocaine-dependent black and white veterans. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 83, 926–940.