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Correlates of dependence and treatment for substance use among people withcomorbid severe mental and substance use disorders

Giuseppe Carra, Cristina Crocamo, Paola Borrelli, Ioana Popa, Alessan-dra Ornaghi, Cristina Montomoli, Massimo Clerici

PII: S0010-440X(14)00345-9DOI: doi: 10.1016/j.comppsych.2014.11.021Reference: YCOMP 51442

To appear in: Comprehensive Psychiatry

Received date: 27 October 2014Accepted date: 26 November 2014

Please cite this article as: Carra Giuseppe, Crocamo Cristina, Borrelli Paola, Popa Ioana,Ornaghi Alessandra, Montomoli Cristina, Clerici Massimo, Correlates of dependence andtreatment for substance use among people with comorbid severe mental and substanceuse disorders, Comprehensive Psychiatry (2014), doi: 10.1016/j.comppsych.2014.11.021

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Correlates of dependence and treatment for substance use among people with comorbid severe

mental and substance use disorders. Findings from the “Psychiatric and Addictive Dual Disorder in Italy (PADDI)” Study

Giuseppe Carràa, Cristina Crocamo

b,c,*, Paola Borrelli

b, Ioana Popa

b, Alessandra Ornaghi

c,

Cristina Montomolib, Massimo Clerici

c

Research paper submitted for publication to Comprehensive Psychiatry

a Division of Psychiatry, Faculty of Brain Sciences, University College London. Charles Bell

House, 67–73 Riding House Street, London W1W 7EJ, UK. b

Department of Public Health, Experimental and Forensic medicine, Unit of Biostatistics and

Clinical Epidemiology, University of Pavia. Via Forlanini, 2 - 27100 Pavia, Italy.

c Department of Surgery and Interdisciplinary Medicine, University of Milano Bicocca. Via Cadore,

48 - 20900 Monza, Italy.

Word count: Abstract 218; Text 3422; Tables: 3

*Address for correspondence:

Cristina Crocamo, MSc. University of Milano-Bicocca, Department of Surgery and Interdisciplinary

Medicine, Via Cadore 48, 20900 Monza (MB), Italy.

Tel. /Fax +390392332277. E-mail: c.crocamo1@campus.unimib.it; cristina.crocamo@hotmail.it

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Correlates of dependence and treatment for substance use among people with comorbid severe

mental and substance use disorders. Findings from the “Psychiatric and Addictive Dual Disorder in Italy (PADDI)” Study

Abstract

Objective People with severe mental illness (SMI) have often comorbid alcohol and other substance

disorders but substantial barriers to addiction care remain.

The study is aimed at describing correlates associated with dependence and with treatment for

substance use among people with SMI and comorbid substance disorders cared in community mental

health teams (CMHTs).

Methods This study capitalized on data from a national survey on comorbid severe mental and

substance use disorders, among 2,235 subjects in 42 CMHTs nationwide.

Results 26% of people with SMI and comorbid misuse suffered from dependence on alcohol and 21%

on any other substance. Use of opioids, liver diseases, involvement with criminal justice system, but

also area of residence, all were associated with dependence in people with SMI. As regards treatment

for substance use, only 50% of comorbid people with SMI were treated by specialist services in the

past 12 months. This was associated with opioids and cocaine use, as well as with liver diseases, and

involvement with criminal justice. People with schizophrenia and those living in Central and Southern

Italy, had the lowest chances to be treated for their comorbid substance use disorder.

Conclusions There are extensive unmet treatment needs among comorbid individuals with SMI.

Better integration of substance abuse and mental health care systems, and more effective reciprocal

referral procedures, are needed.

Keywords: correlation study; dual diagnosis; community mental health services; substance abuse

treatment centres.

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1. Introduction

People suffering from severe mental illnesses (SMI) have high rates of comorbid substance use, i.e.,

“dual diagnosis”1. The Epidemiologic Catchment Area (ECA) study found that 47% of people with

schizophrenia had a comorbid substance use disorder2. In Europe the lifetime rates for comorbid

schizophrenia and dependence on any substance are high for example in the UK (35 %), but

considerably lower in Germany (21%) and in France (19%) 3. Research in clinical populations with

this comorbidity is consistent in showing poor clinical and social outcomes4, 5

. Socio-demographic,

clinical, infectious diseases and legal adverse correlates are well documented 6-9

. However, a formal

diagnosis of dependence is often not reported, though its consequences may differ as compared with

simple abuse10

. DSM–IV diagnosis of dependence has been shown to be reliable and valid11

but

evidence in support of abuse was weaker12

. In fact, DSM 5 has combined DSM-IV substance abuse

and dependence into a single disorder, measured on a mild to severe continuum13

. Furthermore, for

people with dual diagnosis, not simply the use of substances but rather dependence predicts poor

outcomes14

. However, the bulk of evidence is about correlates of dual diagnosis in general15

, though

an early identification of factors specifically associated with dependence and only in people with SMI

can help clinicians in targeting clients who need to be in treatment for substance abuse.

As regards health care delivery, integrated treatment for people with dual diagnosis is still far from

standard practice worldwide and there are substantial barriers also to parallel treatment for substance

abuse for people with comorbid SMI16, 17

. Less than 10% of those in need receive separate treatment

for both their mental health and substance use problems18

. Community studies have examined patterns

of service use, generally combining mental health and substance abuse services, but less is known

about the use of each type of service separately19

. Although there are wide differences across

countries, individuals with dual diagnosis seem more likely to use mental health rather than substance

abuse services20

. However, risk of persistent drug and alcohol misuse is reduced if comorbid people

use also specialty substance abuse services21

. Unlike the USA, in many European countries including

Italy (see 5 for a review) mental health and substance abuse treatment delivered by different providers

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at the same time (parallel treatment) is standard practice for people with dual diagnosis because of the

separation of mental health and addiction services22

, even if a large evidence base supports integrated

treatment for dual diagnosis23

. Previous research has shown that among CMHT patients with

comorbid SMI and dependence, only a minority have contact with drug services24

. However, little is

known about factors associated to be referred to drug treatment programmes in countries with parallel

systems. In addition, findings from EU studies may be of general interest in relation to variations in

service use, since these are more likely to be reflections of the whole local mentally ill population than

those from the USA, where a variety of factors other than place of residence determines who uses

which service25

.

We capitalized on data from a national survey, the Psychiatric and Addictive Dual Disorders in Italy

(PADDI) project, providing the unmatched opportunity to study correlates of dependence and of

provision of interventions for substance abuse in a large, representative, sample of patients from

community mental health teams (CMHTs) with comorbid SMI and substance use disorders.

Particularly, this study will address two research questions: (1) which factors are associated to drug

and alcohol dependence in people with SMI undergoing treatment in CMHTs in Italy?; (2) which

factors are associated to be treated for substance abuse within programs of the National healthcare

system?

2. Material and methods

2.1 Setting and Sample

We conducted a cross-sectional survey exploring dual diagnosis within Italian Mental Health Care

Trusts (MHTs) in 2008. In Italy integrated programmes for dually diagnosed people are rare. MHTs,

serving the population living in a specific district, include psychiatric services that offer inpatient

(General Hospital Psychiatric Units), and outpatient (CMHTs) care, residential treatment and day-

centre activities. Substance misuse care is provided only by addicts’ outpatient clinics, with non-

statutory residential therapeutic communities playing an ancillary role5. CMHTs carry out most of

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outpatient mental health care, assigning each client with SMI a case manager26

. Thus they represent

the optimal setting to study the epidemiology of dual diagnosis in people with SMI. Tax-based

funding warrants universal access to all citizens across health care services, meaning that no selection

factors are in place determining whether individuals get care through the system.

The study population was defined as all people with SMI aged 18-65 years, allocated in the case-load

of a psychiatrist in participating CMHTs, and diagnosed also with an alcohol or a substance use

disorder. Participation of staff and data collection procedures were agreed by the ethic committee of

the University of Pavia and clients were approached for their informed, signed, consent.

2.2 Measures and procedures

CMHTs provide healthcare almost exclusively for people with SMI. However, in order to ensure

comparability between clients from different CMHTs, we adopted a clear, well established, definition

of SMI27

. Therefore, we included from administrative datasets only people who had diagnoses of

Schizophrenia and other psychotic disorders (Schizophrenia, Schizophreniform, Schizoaffective,

Delusional, Brief Psychotic, Shared Psychotic and NOS Psychotic disorders), Bipolar I–II disorders,

and 12-month depressive disorders (major depressive disorder and dysthymic disorder)28

. We also

considered people with clusters A and B personality disorders, since they are routinely in caseloads of

Italian CMHTs26

. At least one of the above mentioned DSM-IV diagnoses, along with a Global

Assessment of Functioning scale29

score of less than 60 during the worst month of the past year as

recorded in the clinical chart, was required to define SMI30

. All psychiatric diagnoses were then

checked, by fully trained consultant psychiatrists administering the 12-month patient version of the

SCID-I (Structured Clinical Interview for DSM-IV) and SCID-II (after screening self-report

questionnaire).

For substance use assessment, given self-report reduced reliability31

, and also the limited practical

gains of biological measures32

, we identified staff rating as an alternative, reasonably sensitive,

method (e.g.,24, 33

). Therefore, alcohol and substance disorders of people with SMI were screened by

their case managers using the Drake Clinician Rating Scales for Alcohol (AUS) and Drug (DUS)

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Use34

, which are based on DSM-IV. These instruments are not usually included in routine

documentation collection.

We defined a subject with SMI as suffering from dual diagnosis if at least one 12 month substance use

disorder could be detected using AUS and DUS.

2.3 Outcome definitions

Following our research questions, we defined two specific outcomes. The first was comorbid DSM-IV

12 month alcohol and other substances dependence (from now on dependence). Secondly, in order to

study the likelihood of comorbid SMI people from CMHTs of receiving treatment for substance use,

we adopted a broad definition. We explored any kind of treatment (including those of non-statutory

organizations, e.g., self-help groups) provided by specialty services in the past 12 months for

comorbid alcohol and/or other substances disorders. Long-term follow up for treatment received in

previous years was also considered.

2.4 Statistical analysis

Analyses were carried out using STATA 1035

. All statistical tests used the 5% level of significance,

and all p-values were two-tailed. Cohen's k coefficients were used to measure AUS/DUS inter-rater

reliability among case-managers. Mean (SD) and percentages were used for descriptive statistics,

provided also by gender. Univariate comparisons for categorical data were made between groups

using Pearson’s chi-square test and Student t test for continuous variables. In order to control for error

effects, Bonferroni multiple testing correction was used. We identified covariates significantly

associated with each outcome for inclusion in subsequent multivariate analyses, yielding odds ratios

(ORs) with 95% CIs. We then carried out logistic regressions of the effect of characteristics of

comorbid SMI patients independently on both outcomes, controlling for age, gender and other

variables significantly related in the univariate analyses. Likelihood Ratio Test was used to compare

nested models, exploring the contribution that different variables made to regression equations.

3. Results

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3.1 Socio-demographic, clinical and substance use characteristics

The caseloads of 257 case managers (88% response rate) from 42 MHTs across the country provided

individual data for 2,235 patients with dual diagnosis. SMI diagnoses comprised 681 (30.5%) subjects

with Schizophrenia and other psychotic disorders, 395 (17.7%) with Bipolar Disorders, 230 (10.3%)

with Depressive Disorders, and 929 (41.6%) suffering from Clusters A and B personality disorders.

AUS/DUS inter-rater reliability k coefficients ranged between 0.80 and 0.95 among different case-

managers rating the same patient. Women were 25% of the study sample, and they were significantly

older than men. Most subjects had just compulsory eight years education (74%), were unemployed

(58%), and often lived with their parents or relatives (80%). All socio-demographic characteristics

significantly differed by gender, apart from living conditions and employment status (Table 1). Men

more often had involvement with criminal justice and liver diseases and were more likely than women

to suffer from dependence on substances (in particular opioids) but not on alcohol. Women were more

likely to be dependent on prescription drugs.

Cumulative rates of simple use and abuse were 51% for Alcohol, and 48% for other substances

(Cannabis=28%; Opioids=10%; Cocaine=17%; Hallucinogens=5%; Prescription drugs=10%). In

terms of polysubstance use, just 9% in our sample misused no more than one substance (including

alcohol), and men (92%) were more likely than women (86%) to report polysubstance patterns

(p<0.001). Only 50% of comorbid people had received treatment in any substance use programme in

the past 12 months, and small proportions of them were on methadone/buprenorphine outpatient

maintenance programmes (9%) or else could benefit from inpatient detoxification (4%).

TABLE 1 about here

Table 2 shows rates of dependence and of substance use treatment by SMI diagnoses. We found

negligible differences as regards dependence in different diagnostic groups. People with schizophrenia

were less likely to suffer from alcohol dependence, as compared to people with bipolar disorders, and

from substance dependence, as compared to people with personality disorders. Furthermore, those

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with schizophrenia were also less likely to have received any kind of treatment for substance use in

the past year, apart from inpatient detoxification, compared to all the other groups.

TABLE 2 about here

3.2 Characteristics associated with 12 month dependence and treatment for substance use

disorders

3.2.1 Univariate analyses

Table 3 shows the influence of several variables at univariate level on dependence and on the

provision of any treatment for alcohol and other substances disorders with unadjusted, but significant,

ORs (95% CIs). Living in Central and Southern, as compared with Northern, Italy was associated with

a higher likelihood of dependence, but geographical area had no influence on being referred to

specialty treatment. Criminal justice sanctions were associated with high odds for both dependence

and referral to treatment. People who lived alone were less likely to access treatment. As regards

physical health conditions, HIV-positive serostatus and liver diseases were associated with both

dependence and substance abuse treatment. In relation to variables describing specific substances

misuse, comorbid people who used opioids were more likely to be dependent and to receive specialty

treatment, similarly to those who used cocaine. Assuming schizophrenia as reference category, people

with bipolar and cluster A and B personality disorders were more likely to be dependent.

3.2.2. Multivariate analyses

In order to explore factors associated with each outcome, we fitted several models (controlling for age

and gender) that included significant attributes from the univariate analyses, but retaining only

variables which made a statistically significant contribution to final regression models in terms of

goodness of fit. Adjusted ORs (95% CIs) are shown in table 3 for dependence and provision of

specialty treatment in the past 12 months.

TABLE 3 about here

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We focussed on variables which, along with statistical significance, carried substantial odds ratios and

differences that were large enough to be of clinical significance. Living in Central and Southern, as

compared to Northern, Italy influenced both outcomes at multivariate level, with higher odds of

suffering from dependence, and relatively lower odds of accessing specialty services. However, most

of results from univariate analyses were confirmed. Sanctions inflicted by criminal justice system and

liver diseases showed a moderate effect on both outcomes. As regards specific substances misuse,

odds of suffering from dependence were fourfold greater for opioids users, who were also to a similar

degree more likely to receive appropriate treatment. This was true, though to a lesser extent, also for

cocaine users. More importantly, people with schizophrenia were less likely to receive any kind of

treatment for substance use as compared to all the other diagnostic groups.

4. Discussion

We analysed with a structured diagnostic assessment a large sample of people with co-occurring

severe mental and substance use disorders in CMHTs nationwide. We were thus able to study a

number of correlates in relation to dependence syndromes and provision of treatment for substance

disorders by specialty services in the past 12 months. Data were collected in 2008 but no major

changes of the treatment system have been implemented meanwhile, allowing sufficient

generalization to the contemporary situation and also comparison to similar data from other nations

and health systems. The study documents areas where policy is falling short and improvements in

patient care are needed.

4.1 Dependence and specialist treatment rates

Among people with comorbid SMI and substance use disorders, 26% and 21% suffered from 12

month dependence on alcohol and on any other substance, respectively. However, the most salient

finding of this study is that only 50% of comorbid people in CMHTs had been cared also by drug and

alcohol specialty services in the past 12 months. A specific concern is about

methadone/buprenorphine maintenance programmes that were offered only to 207 out of 326 opiate

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dependent clients. These findings from a nationally representative sample reveal a largely

unrecognized and underserved population at risk. This is consistent with evidence for example from

the comparable UK COSMIC study showing that CMHTs’ dependent patients receive any alcohol or

drug abuse treatment even more rarely than those from our sample24

. Comparisons might be less

appropriate with countries like USA where a variety of factors other than place of residence

determines who uses which service36

. Indeed, the 2005 National Survey on Drug Use and Health

identified that among people with co-occurring mental and substance use disorders, just

approximately half (47%) received treatment at a specialty facility. Of these, 34% received treatment

only for their mental health problems and 4% received specialty substance abuse treatment only,

showing unmet treatment needs perhaps even more serious than those from our findings19

.

4.2 Correlates of 12 month dependence in people with SMI

Previous studies have suggested that the early identification of several correlates may assist clinicians

in managing dependence in DD people37, 38

. Our study adds important information on relatively new

correlates. Involvement in the criminal justice system often results from illegal drug-seeking

behaviour and participation in activities that reflect, in part, disrupted behaviour ensuing from

dependence39

. However there is the need for further research exploring if SMI condition may modify

the association between criminal justice sanctions and dependence as compared with non SMI people.

Furthermore, adverse health consequences such as liver diseases are associated with both drug

dependence40

and SMI41

. Thus it is not surprising that our findings show an important risk for liver

diseases in SMI people with dependence. As regards dependence potential of individual drugs, our

findings show that opioids and cocaine induce powerful dependence, confirming the general tendency

of these classes of substances42

. However the most striking feature is the role played by geographic

area of residence on the chances of suffering from dependence, since people with SMI living in

Central and Southern Italy were more likely to suffer from this condition as compared with those

living in Northern Italy. Higher availability of substances, along with relatively scarce preventive

programmes, are the most likely explanations, that are confirmed by figures showing that quantity of

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seizures of drugs by law enforcement agencies are mainly concentrated in Central and Southern Italy,

and that prevention is unevenly implemented across the country43

. Furthermore, studies of inequalities

in health between geographic areas have shown no significant association with urbanization for

substance use disorders, but this was the case for SMI (e.g.,44

). Additional research specifically

exploring the association with dual diagnosis is needed.

4.3 Correlates of provision of treatment for substance abuse by specialty services

The correlates of provision of treatment by specialty services matched up just in part those of

dependence, providing useful clues for the design of policy initiatives that can improve access to care

for comorbid people with SMI. Our findings show that “external” drivers such as legal issues and

comorbid physical conditions, but also area of residence and psychiatric diagnosis, may play a major

role in terms of provision of treatment for substance abuse. First, if treatment for drug dependence is

offered as an alternative to criminal justice sanctions, people with SMI are more likely to be treated by

specialty services. Indeed, substance abuse services have been traditionally more closely affiliated

with criminal justice system rather than with mental health care one21

. Our findings also confirm

previous evidence that if people with SMI suffer from liver diseases (Hepatitis B and C), this

increases their odds to be treated by drug and alcohol services45

.

Secondly, as regards geographic area of residence, our findings show that despite people with

comorbid SMI and living in Central and Southern Italy are more likely to suffer from dependence,

they have lower odds to get relevant treatment than those living in Northern regions. Possible

explanations for this puzzling result are the regional barriers to substance abuse treatment for people

with comorbid mental disorders living in Central and Southern regions, with possibly less efficient

regional health systems26

. A second possible explanation is that many individuals perceive substance

abuse services as more stigmatizing than those for mental health care. This may be more true for

social and cultural reasons in central and southern areas of the country46

, reflecting differences in

public attitudes.

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As regards individual classes of substances, subjects using drugs with the highest harm potential

(heroin and cocaine) were more likely to access specialty services, which is largely consistent with the

relevant literature, (e.g.,47

). However, our findings also show that different comorbid psychiatric

disorders are associated with different chances to be treated by addiction services48

. Overall, cluster A

and B personality disorders are the comorbid disorders that increase the chance to be treated. On the

other hand, comorbid people with schizophrenia have the lowest chances to use addiction services.

Ineffective referral from CMHTs, differential difficulties in engaging different clinical populations in

traditional addiction services, lack of competencies and skills among drug and alcohol services staff,

poor treatment-seeking behaviours in individuals with comorbid psychotic disorders, all are possible

explanations supporting the need for an integrated approach5.

4.4 Limitations

We acknowledge several limitations. First, alcohol and substance disorders of people with SMI were

screened by staff-report. This may inflate the association between dependence and receipt of

treatment, since providers may be more likely to recommend substance-related services for those who

are perceived as having more severe problems. Nonetheless, at least with respect to dependence, staff

screening provides valid and reliable estimates49

. In addition, we could not collect data about referrals

and low rates of use of drug and alcohol services might be explained by poor compliance of people

with SMI. Having to go to two different settings to treat two problems is likely to reduce willingness

to attend treatment. We also restricted the sample to people with SMI with GAF < 60 i.e., the

individuals with more severe and probably more treatment resistant illness. We have thus restricted

also the ability to examine associations between substance use disorders and severity, eliminating

patients who may have had severe illness, but done well under treatment. Furthermore, we did not

cover special populations (e.g., SMI prisoners, homeless, and those in residential long term

programmes) who have perhaps more severe forms of substance disorders21

, as well as tobacco

use/dependence, which is common in severely mentally ill populations. In addition, because of

peculiar characteristics in designing and financing of European health, our results may not generalize

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to other settings, especially with regard to correlates of service use. Finally, limitations regarding

temporal relationship and causality, inherent to cross-sectional design, should be obviously

considered.

5. Conclusions

There are extensive unmet needs for comorbid substance use disorders among individuals receiving

mental health treatment for SMI in CMHTs. A large proportion of them do not receive treatment by

addiction services, especially if schizophrenia is the comorbid SMI. Better integration of programmes

for alcohol and other substances disorders in the mental health care system either more effective

referral procedures across the two separate systems of care are needed.

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Disclosures and acknowledgments

The authors declare that there are no conflicts of interest.

Role of funding source

The “Psychiatric and Addictive Dual Disorder in Italy (PADDI)” Study was funded by the Italian

Government Department for Anti-drug Policies (DPA).

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Table 1. Socio-demographic, clinical and 12 months substance use† characteristics

Total

N=2235

Women

N=552

Men

N=1683

P*

N % N % N %

Age, years (Mean, SD) 39 11 42 11 39 10 <0.001a

Education (compulsory only) 1647 74 363 66 1284 76 <0.001

Unemployed 1258 58 331 62 927 57 ns

Living alone 427 20 99 19 328 20 ns

Family situation (single) 1755 81 387 72 1368 84 <0.001

Children 649 31 247 48 402 26 <0.001

Criminal justice sanctions 373 17 36 7 337 20 <0.001

Geographic area (Italy)

Northern

Central

Southern

1415

331

489

63

15

22

393

105

54

71

19

10

1022

226

435

61

13

26

<0.001b

Liver diseases

Hepatitis B

Hepatitis C

667

108

299

30

5

13

129

19

59

23

3

11

538

89

240

32

5

14

<0.001

ns

ns

HIV-positive 81 4 25 5 56 3 ns

Family history

Psychiatric disorders

Substance use

697

379

31

17

186

112

34

20

511

267

30

16

ns

0.04

Alcohol Dependence 588 26 143 26 445 26 ns

Other than alcohol Dependence

Cannabis

Opioids

Cocaine

Hallucinogens

Prescription drugs

460

103

326

103

11

53

21

5

15

5

0.5

2

83

14

52

21

1

24

15

3

9

4

0.2

4

377

89

274

82

10

29

22

5

16

5

0.6

2

<0.001

ns

<0.01

ns

ns

<0.01

SMI diagnoses

Schizophrenia and other psychotic

Bipolar

Depressive

Cluster A/B personality

681

395

230

929

30

18

10

42

99

115

87

251

18

21

16

45

582

280

143

678

35

17

8

40

<0.001c

12 months substance use specialist

treatment

Specialist counselling

Outpatient maintenance§

Residential treatment

Detoxification hospital admission

1118

671

207

197

79

50

30

9

9

4

262

170

41

38

25

47

31

7

7

5

856

501

166

159

54

51

30

10

9

3

ns

ns

ns

ns

ns †AUS/DUS assessment. *Bonferroni multiple testing correction. aStudent’s t test. All Pearson’s χ2 tests d.f.=1, but b =2 and c=3. §Methadone/buprenorphine. Each participant may have been using more than one substance and having received more than one specialist

programme in the past 12 months.

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Table 2. Dependence† and treatment for substance use by SMI diagnoses 1.Schizophrenia

and other

psychotic

disorders

(N=681)

2.Bipolar

disorders

(N=395)

3.Depressive

disorders

(N=230)

4.Cluster A/B

personality

disorders

(N=929)

P Post hoc#

N % N % N % N %

Alcohol

Dependence

150

22

121

31

65

28

252

27

0.036

1-2*

Other substances

Dependence

122

18

79

20

38

17

221

24

0.033

1-4*

12 months substance use

specialist treatment

Specialist counselling

Outpatient maintenance§

Residential treatment

Inpatient detoxification

265

162

41

40

23

38

24

6

6

3

203

121

43

32

13

51

31

11

8

3

112

75

20

15

4

49

33

9

7

2

547

313

103

110

39

59

34

11

12

4

<0.001

<0.001

0.016

<0.001

ns

1-2***

, 1-3*,

1-4***

, 3-4*

†AUS/DUS assessment. All tests are Pearson’s χ2 test with 3 d.f. #Bonferroni multiple testing correction: *p<0.05 **p<0.01 ***p<0.001. §Methadone/buprenorphine. Each participant may have been using more than one substance and having received more than one specialist

programme

in the past 12 months.

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Table 3. Characteristics significantly associated with 12 month Dependence and with provision of

specialty treatment for substance disorders

Dependence Specialty services treatment

Unadjusted

OR (95%

CI)

P Adjusted

OR*

(95% CI)

P Unadjusted

OR (95%

CI)

P Adjusted

OR§

(95% CI)

P

Gender1 1.39 (1.14

to 1.69) 0.001 1.24

(1.00 to

1.54)

ns 1.15 (0.94

to 1.39)

ns 1.07

(0.85 to

1.34)

ns

Age 1.02 (1.01

to 1.02) <0.001 1.02 (1.01

to 1.03) <0.001 0.98 (0.97

to 0.99) <0.001 0.99 (0.99

to 1.00) ns

Geographic

area2

2.54 (2.12

to 3.05) <0.001 2.17 (1.79

to 2.64) <0.001 1.15 (0.97

to 1.36) ns 0.78 (0.64

to 0.96) 0.020

Criminal

justice

sanctions

1.96 (1.56

to 2.45) <0.001 1.36 (1.04

to 1.76) 0.023 2.43 (1.91

to 3.08) <0.001 1.59 (1.20

to 2.11) 0.001

Education3 0.79 (0.65

to 0.95) 0.012 0.90 (0.73

to 1.12) ns

Employment4 0.86 (0.72

to 1.00) 0.047 1.02 (0.84

to 1.25) ns

Living

condition5

1.36 (1.10

to 1.69) 0.004 1.38 (1.08

to 1.75) 0.010

HIV+ 1.95 (1.24

to 3.07) <0.001 0.98 (0.59

to 1.62) ns 2.96 (1.78

to 4.91) <0.001 1.45 (0.80

to 2.61) ns

Liver disease 2.90 (2.39

to 3.51) <0.001 1.93 (1.56

to 2.37) <0.001 1.79 (1.49

to 2.15) <0.001 1.53 (1.23

to 1.91) <0.001

Substances Opioids 4.18 (3.37

to 5.19) <0.001 4.24 (3.34

to 5.38) <0.001 6.11 (4.77

to 7.82) <0.001 4.71 (3.60

to 6.15) <0.001

Cocaine 2.41 (1.94

to 2.98) <0.001 1.53 (1.19

to 1.98) 0.001

Cannabinoids 0.76 (0.64

to 0.91) 0.003 0.60 (0.47

to 0.75) <0.001

12-month

DSM-IV

diagnoses6

Bipolar

Disorders 1.62 (1.26

to 2.09) <0.001 1.76 (1.36

to 2.26) <0.001 1.96 (1.47

to 2.61) <0.001

Depressive

Disorders 1.20 (0.88

to 1.63) ns 1.58 (1.16

to 2.13) 0.003 2.04 (1.45

to 2.88) <0.001

Cluster A and

B personality

Disorders

1.51 (1.24

to 1.86) <0.001 2.38 (1.93

to 2.93) <0.001 2.46 (1.96

to 3.10) <0.001

Analyzed: *N=2235; §N=2106.

Reference categories: 1females, 2Central and Southern vs. Northern Italy, 3compulsory only, 4unemployed, 5living alone, 6Schizophrenia and other psychotic disorders