History of Alcoholism and the Justice System

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Treatment rates for alcohol use disorders: a systematic review and meta-analysis

Tesfa Mekonen1,2 , Gary C. K. Chan3 , Jason Connor3,4 , Wayne Hall3,5 , Leanne Hides1,3

& Janni Leung1,3,6

School of Psychology, The University of Queensland, Brisbane, QLD, Australia,1 Psychiatry Department, Bahir Dar University, Bahir Dar, Ethiopia,2 National Centre for Youth Substance Use Research, The University of Queensland, Brisbane, QLD, Australia,3 Discipline of Psychiatry, The University of Queensland, Brisbane, QLD, Australia,4 Queensland Alliance for Environmental Health Sciences, The University of Queensland, Brisbane, QLD, Australia5 and National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia6

ABSTRACT

Aims To estimate the treatment rate for alcohol use disorders (AUDs) in the general adult population. Treatment rates were also considered in relation to economic differences. Methods Systematic review and meta-analysis. We searched PubMed, EMBASE, PsycINFO and CINAHL databases to identify studies that reported treatment rates for alcohol use disorders in the general population. Independent reviewers screened the articles based on predefined inclusion criteria. Data were extracted using a standardized data extraction form.We conducted quality assessments of the included studies. The overall treatment rates were estimated from studies that reported any treatment for AUDs from healthcare or informal non-healthcare settings (any treatment). We estimated the separate treatment rates for each diagnostic category as reported in the primary studies: AUD as a single disorder, alcohol abuse and alcohol dependence. Data were pooled using a random-effect model. Results Thirty-two articles were included to estimate the treatment rates (percentage treated among the total number of people with AUDs). The pooled estimate of people with AUDs who received any treatment were 14.3% (95% CI: 9.3–20.3%) for alcohol abuse, 16.5% (95% CI: 12–21.5%) for alcohol dependence and 17.3% (95% CI: 12.8–22.3%) for AUD. A subgroup analysis by World Bank economic classification of countries found that the treatment rate for AUD was 9.3% (95% CI: 4.0–15.7%) in low and lower-middle-income countries. Conclusion Globally, approx- imately one in six people with AUDs receives treatment. Treatment rates for AUDs are generally low, with even lower rates in low and lower-middle-income countries.

Keywords Alcohol use disorders, global mental health, health service utilization, help-seeking, mental health systems, treatment gap.

Correspondence to: Tesfa Mekonen, Level 3 McElwain Building (24A), School of Psychology, The University of Queensland, Brisbane QLD 4072, Australia. E-mail: [email protected]

Submitted 13 August 2020; initial review completed 11 October 2020; final version accepted 25 November 2020

INTRODUCTION

Alcohol use disorders (AUDs) are among the most prevalent mental disorders [1,2]. In the age group of 15–44 years, AUDs were among the top five leading causes of disability-adjusted life years (DALYs) [3]. The most recent global data shows that harmful use of alcohol resulted in 3 million deaths worldwide and this disease burden was higher in low and middle-income countries (LMICs) [4].

Effective pharmacological and psychosocial interven- tions for AUDs [5] are under-used in LMICs [6–8]. This leads to a large ‘treatment gap’, defined as the difference

between the prevalence of the illness and the proportion of individuals who received treatment [9]. Increasing treatment rates is an effective way of reducing this global alcohol-related disease burden.

The 2001 World Health Report [3] made multiple recommendations to address the treatment gap for mental and substance use problems, including AUDs. The World Health Organization’s Mental Health Gap Action Program (mhGAP) to reduce the burden of mental and substance use disorders and promote mental health [10] was endorsed by all member states [11]—health service coverage and treatment for mental and substance use dis- orders were among its actions.

REVIEW doi:10.1111/add.15357

https://orcid.org/0000-0002-3188-0173

https://orcid.org/0000-0002-7569-1948

https://orcid.org/0000-0002-7020-1196

https://orcid.org/0000-0003-1984-0096

https://orcid.org/0000-0002-4550-8460

https://orcid.org/0000-0001-5816-2959

mailto:[email protected]

Despite these recommendations, the treatment rate re- mains low. A review of global psychiatric epidemiology studies in 2004 indicated that the treatment rate for AUDs was 22% (78% treatment gap) [9]. In other words, approx- imately 2 in 10 individuals who could benefit from AUD treatment were accessing it. Multi-national surveys in 17 countries reported that unmet needs for mental health and substance use treatment were persistently high espe- cially in low resource settings [6]. The treatment rate for AUDs is generally low [9], such rate is low even in developed countries [12,13]. The limited evidence in LMICs has reported that the treatment rate for AUDs is be- low 10% [14,15].

Critical to effective international policy is contemporary data that takes into account advances in health systems and treatment approaches and changes in policy and economic conditions. This systematic review and meta-analysis aimed to estimate the treatment rates for AUDs among the general adult population and examine if these rates varied by economic differences between high-income countries (HIC) and LMICs.

Review question

The question addressed was ‘What is the treatment rate for Alcohol Use Disorders?’ A secondary question was ‘Does this treatment rate differ byWorld Bank economic groups?’

METHODS

This review followed the preferred reporting items for systematic reviews andmeta-analyses (PRISMA) guide- line (Supporting information Table S1) and the protocol followed PRISMA for systematic review protocols (PRISMA-P) [16,17]. The protocol was registered at the in- ternational prospective register of systematic reviews (PROSPERO) with registration ID CRD42020161683 as part of a larger systematic review on the treatment rates of depression and AUDs.

Eligibility criteria

The eligibility criteria were developed based on population, exposure, comparison, outcome and studydesign/type (PE- COS) framework [18].

Population

Studies reporting the treatment rate for AUDs in the general adult population (community-based studies) were included.

We excluded studies that focused on a specific popula- tion (e.g. elderly only, ethnic minority group, clinical set- tings, students, prisoners, etc.), and studies that focused on specific comorbid medical conditions (diabetes,

hypertension, etc.). Studies of healthcare utilization were excluded unless they reported service utilization specifically for AUDs.

Exposure

We included studies that assessed AUDs by the Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) based mea- surement tools.

The ICD [19,20] has separate diagnoses for ‘harmful alcohol use’ and ‘dependence’. This distinct diagnostic system was also applied as ‘alcohol abuse’ and ‘alcohol dependence’ from the 3rd edition, DSM-III [21] to the DSM-IV [22]. The DSM-5 [2] integrates the two DSM-IV categories into a single disorder, AUD. Studies that have used ICD-10 or DSM-IV criteria also defined AUD as the presence of abuse or dependence [15,23]. For the purpose of this review, we estimated the separate treatment rates for each diagnostic category as reported in the primary studies (i.e. studies reported (i) ‘AUD’ as a single disorder; (ii) ‘alcohol abuse’; and (iii) ‘alcohol dependence’).

Outcomes

The outcome is ‘treatment rate for AUDs’. The treatment rates for the individual studies were calculated as follows:

Treatment rate ¼ n

N �100%

Where ‘n’ is the number of treated people with AUDs, and ‘N’ is the total number of people with AUDs.

Study design

We included all community-based observational studies (cross-sectional studies, longitudinal studies and cohort studies) published in peer-reviewed journals that reported treatment rates for AUDs (or information that enabled us to retrieve the treatment rates).

Reviews, case reports, case series, conference abstracts, dissertations, book chapters, editorials and commentaries were excluded, but their reference lists were checked for relevant studies.

Search strategy

Four database searches (PubMed, EMBASE, PsycINFO and CINAHL) were conducted on September 2019 to identify articles published in English since 2004. The current systematic review follows on from the previous review published in 2004 that reported on the treatment rate for AUDs [9], therefore, we included studies published from 2004 onward. The search for relevant citations was done using subject headings (MeSH, Thesaurus and EMTREE) and synonym terms. Because this review is part of a larger systematic review on the treatment rates of depression and

2618 Tesfa Mekonen et al.

AUD, the search terms were combined by the concepts of AUDs, depression and treatment rate as: ((AUD OR Depression) AND Treatment rate) (Supporting information Table S2).

Study selection and data extraction

All citations were exported to EndNote X9 reference library [24] and duplicates were removed. Two independent re- viewers screened the title, abstract and full text based on the predefined inclusion and exclusion criteria. Discrepan- cies between the two reviewers were solved by discussion. The agreement between the reviewers during the first stage (title and abstract screening) and second stage (full text) screening were 86% and 95%, respectively.

Articles eligible for full-text reviewwere extracted using a standardized data extraction form recorded in an excel spreadsheet. Data were collected on characteristics of the studies (author’s name, year of data collection, year of pub- lication, countrywhere the studywas conducted, study de- sign, response rate, measurement tool and pertinent findings) and participant characteristics.

Assessment of quality

The methodological quality of the included articles was critically appraised using the modified form of Joanna Briggs Institute (JBI) critical appraisal of prevalence studies tool [25] and the risk of bias tool [26]. The validated tool comprises 10 items to assess the methodological quality of studies of any design reporting prevalence data with modified yes/no scales [27,28] (Supporting information Table S3).

Data analysis and presentation of the results

Results were presented in a narrative summary, tables and charts. Meta-analysis was done using the random effect models, as recommended by JBI’s methodological guidance [29]. The meta-analysis was done using MetaXL version 5.3 [30]. To address the problem of variance instability [29,31], the treatment rate was reported as a proportion by using a double arcsine transformation method that gives the pooled proportion with a 95% CI.

Heterogeneity was assessed using Cochran’s Q value and I2 statistics [32]. Publication bias was assessed by visual examination of funnel plots, Eggers test, and fill- and-trim method [33]. We conducted subgroup analysis by World Bank economic classification of countries to compare the treatment rates between HICs and LMICs. To further examine the heterogeneity, a random-effects meta-regression was performed on selected study charac- teristics, including publication year, gender proportion, urbanicity and measurement tools for AUDs [34]. The meta-regression model was fitted with restricted

maximum likelihood and corrected by the Knapp–Har- tung variance estimator [35] using Stata version 16 (StataCorp, College Station, Texas). Sensitivity analysis (one by one exclusion of individual studies) was conducted to examine the effect of excluding individual studies on the heterogeneity. We examined the changes in I2 values after excluding the outlier studies to identify studies responsible for a significant decrease in I2

[36,37]. The treatment rate was estimated by the treatment

types reported in the studies. In this study, treatment types were summarized as follows (all are separate categories, one is not the composite of others): (i) any form of treat- ment; (ii) treatment from healthcare facilities (general medical andmental health service); (iii) informal help from non-healthcare settings (Alcoholics Anonymous, religious places, etc.). To estimate the overall treatment rate, estimated from studies that reported ‘any form of treat- ment’ were used.

RESULTS

In the larger systematic reviewon depression and AUD, 16 681 unique records were identified through database searching and supplementary searches. After screening titles and abstracts, 185 articles were eligible for full-text assessment. Out of the 185 full text articles, 43 studies were for depression only and 142 were for AUDs. After full-text screeningof AUD studies, 32 articles were included in the qualitative synthesis and meta-analysis (Fig. 1).

Study characteristics

All the included studies were cross-sectional in design and had been conducted in the general population of 25 differ- ent countries. Studies were mostly from HICs (n = 20, 62.5%) [23,38–56] and upper-middle-income countries (n = 8) [57–64]. A small number of studies were from low and lower-middle-income countries (n = 4) [15,65–67]. Two studies were multinational, one from four LMICs and the other from six HICs. The majority of the studies (n = 22) were from nationally representative surveys. According to the World Bank region classification of coun- tries, the highest number of studies (n = 9) were found in Europe and Central Asia region followed by East Asia and Pacific (n = 8) (Table 1).

Almost all (n = 31) studies reported the overall treatment rate (any type of treatment) for AUD, abuse or dependence irrespective of whether it was a formal healthcare service or informal help from non-health care settings. One study reported the prevalence of using reha- bilitation programs, detoxification wards and psychiatric treatment separately, but it did not report the overall treat- ment rate [61]. Regarding the treatment settings, four

Treatment rates for alcohol use disorders 2619

studies reported formal treatment specific to AUDs, treat- ment from any health care provider (n = 6), mental health professionals or mental health setting (n = 16) and general medical setting (n = 16). One study reported estimates for minimally adequate treatment [56] and another study re- ported separate treatment rate estimates for pharmaco- therapy and psychotherapy [38].

Based on the AUDs classification, most studies reported treatment for AUD (n = 17), followed by alcohol depen- dence (n = 16) and alcohol abuse (n = 10). Only one study had a complete report on the treatment rate of all AUDs classifications [42]. Eleven studies reported a lifetime treat- ment rate and 26 studies reported a 12-month treatment rate (Table 2).

Figure 1 PRISMA flow chart

Table 1 Number of included studies by World Bank region and economic classification

WB classificationa Total countries (n) Countries with data (n) Studies found (n)

By region East Asia and Pacific 38 6 8 Europe and Central Asia 58 10 9 Latin America and the Caribbean 42 3 6 Middle East and North Africa 21 N/A No North America 3 2 5 South Asia 8 2 2 Sub-Saharan Africa 48 2 2

By income Low-income 31 3 2 Lower-middle-income 47 2 3 Upper-middle-income 60 5 8 High-income 80 15 20

a World Bank 2020 classification

2620 Tesfa Mekonen et al.

Ta bl e 2

Ch ar ac te ri st ic s of

in cl ud

ed st ud

ie s

St ud

y [R ef .]

Co un

tr y

(s ur ve y ye ar )

R es po ns e

ra te

% M ea n

ag e

% M en

A ss es sm

en t

to ol s

12 m on

th s or

lif et im

e pe ri od

Sa m pl e si ze

N (%

co nd

iti on

) Co

nd iti on

/ ex po su re

Tr ea tm

en t ra te

( % )

Q ua

lit y sc or e

[2 5, 26

]

[2 3]

U SA

(2 01

3– 20

14 )

72 34

64 .7

D SM

-I V ba se d

to ol

12 m on

th s

79 02

2 (9 )

A U D

• A ny

tr ea tm

en t (6 .8 )

• M ed ic al se tt in g (2 .9 )

• Be ha

vi ou

ra lh

ea lth

se tt in g (4 .4 )

• Ja il (0 .6 )

• Se lf- he lp gr ou

p on

ly (1 )

[3 9]

U K (2 00

8– 20

10 )

71 .9

38 43

.6 A U D IT

(I CD

- 10

) 12

m on

th s

16 10

(2 0. 5)

A U D

• A ny

tr ea tm

en t (5 1. 8)

• Fo rm

al on

ly (6 .6 )

• Fo rm

al an

d in fo rm

al (1 6. 6)

• In fo rm

al on

ly (2 8. 6)

[6 5]

La os

(N /A

) 99

.7 38

43 .8

M IN I (I CD

-1 0)

12 m on

th s

66 7 (2 )

66 7 (5 .5 )

A bu

se D ep en de nc e

• Se rv ic e us e (0 .0 )

• U se

(0 .0 )

[6 6]

In di a (2 01

5– 20

16 )

91 .7

41 50

.6 M IN I (I CD

-1 0)

12 m on

th s

28 95

(7 .9 )

A U D

• A ny

tr ea tm

en t (1 8. 6)

8 [4 0]

Si ng

ap or e (2 00

8– 20

10 )

75 .9

42 49

.9 CI D I (D SM

-I V )

Li fe tim

e 66

16 (3 .7 )

66 16

(0 .6 )

A bu

se D ep en de nc e

• A ny

tr ea tm

en t (3 .8 )

• A ny

tr ea tm

en t (1 1. 7)

[4 1]

Fr an

ce (2 00

5) 69

.3 39

73 CI D I (D SM

-I V )

12 m on

th s

22 13

8 (3 .4 )

A U D

• A ny

tr ea tm

en t (4 2. 5)

• G P on

ly (2 3. 8)

• Ps yc hi at ri st on

ly (4 .1 )

• G P an

d ps yc hi at ri st (1 4. 6)

[4 2]

U SA

(2 00

1– 20

02 )

81 35

.5 70

D SM

-I V ba se d

to ol

12 m on

th s

43 09

3 (7 .7 )

A U D

• A ny

tr ea tm

en t (1 5. 4)

• A U D tr ea tm

en t (4 .8 )

• M en ta lh

ea lth

tr ea tm

en t (7 .3 )

43 09

3 (4 .3 )

A bu

se • A ny

tr ea tm

en t (9 .3 )

• A U D tr ea tm

en t (2 .9 )

• M en ta lh

ea lth

tr ea tm

en t (5 .4 )

43 09

3 (3 .4 )

D ep en de nc e

• A ny

tr ea tm

en t (2 2. 9)

• A U D tr ea tm

en t (7 .2 )

• M en ta lh

ea lth

tr ea tm

en t (9 .6 )

[4 2]

U SA

(2 00

1– 20

02 )

74 25

.6 66

.4 D SM

-I V ba se d

to ol

12 m on

th s

55 27

9 (8 .2 )

A U D

• A ny

tr ea tm

en t (2 4. 9)

• A U D tr ea tm

en t on

ly (4 .8 )

• M en ta lh

ea lth

tr ea tm

en t (1 6. 6)

55 27

9 (4 .6 )

A bu

se • A ny

tr ea tm

en t (2 0. 7)

• A U D tr ea tm

en t on

ly (3 .9 )

• M en ta lh

ea lth

tr ea tm

en t (1 5. 1)

(C on

ti nu

es )

Treatment rates for alcohol use disorders 2621

Ta bl e 2.

(C on

tin ue d)

St ud

y [R ef .]

Co un

tr y

(s ur ve y ye ar )

R es po ns e

ra te

% M ea n

ag e

% M en

A ss es sm

en t

to ol s

12 m on

th s or

lif et im

e pe ri od

Sa m pl e si ze

N (%

co nd

iti on

) Co

nd iti on

/ ex po su re

Tr ea tm

en t ra te

( % )

Q ua

lit y sc or e

[2 5, 26

]

55 27

9 (3 .6 )

D ep en de nc e

• A ny

tr ea tm

en t (3 0. 1)

• A U D tr ea tm

en t on

ly (6 .0 )

• M en ta lh

ea lth

tr ea tm

en t (1 8. 5)

[4 3]

Fr an

ce (1 99

9– 03

10 0

47 .7

46 .1

M IN I (I CD

-1 0)

Li fe tim

e 39

61 7( 4. 3)

A U D

• A ny

tr ea tm

en t (4 4. 0)

7 [4 4]

U SA

(2 01

2– 20

13 )

60 .1

46 48

.1 D SM

-5 ba se d

to ol

12 m on

th s

36 30

9 (1 3. 9)

A U D

• A ny

tr ea tm

en t (7 .7 )

• 12

-s te p pr og ra m

(4 .5 )

• Fa m ily /s oc ia ls er vi ce s (1 .4 )

• D et ox ifi ca tio

n w ar d/ cl in ic (1 .3 )

• O th er

in pa tie nt

fa ci lit y (1 .2 )

• O ut pa tie nt

cl in ic (2 .0 )

• R eh ab ili ta tio

n pr og ra m

(1 .8 )

• Em

er ge nc y de pa rt m en t (1 .4 )

• H al fw ay

ho us e/ th er ap eu tic

co m m un

ity (0 .4 )

• Cr is is ce nt re

(0 .2 )

• Em

pl oy ee

as si st an

ce (0 .3 )

• Cl er gy

(0 .9 )

• H ea lth

ca re

pr of es si on

al (3 .6 )

• O th er s (0 .4 )

[4 4]

U SA

(2 01

2– 20

13 )

60 .1

46 48

.1 D SM

-5 ba se d

to ol

Li fe tim

e 36

30 9

(2 9. 1)

A U D

• A ny

tr ea tm

en t (1 9. 8)

• 12

-s te p pr og ra m

(1 5. 4)

• Fa m ily /s oc ia ls er vi ce s (4 .1 )

• D et ox ifi ca tio

n w ar d/ cl in ic (6 .2 )

• O th er

in pa tie nt

fa ci lit y (4 .6 )

• ou

tp at ie nt

cl in ic (6 .5 )

• R eh ab ili ta tio

n pr og ra m

(9 .1 )

• Em

er ge nc y de pa rt m en t (5 .7 )

• H al fw ay

ho us e/ th er ap eu tic

co m m un

ity (1 .9 )

• Cr is is ce nt re

(0 .9 )

• Em

pl oy ee

as si st an

ce (1 .2 )

• Cl er gy

(3 .0 )

• H ea lth

ca re

pr of es si on

al (8 .7 )

(C on

ti nu

es )

2622 Tesfa Mekonen et al.

Ta bl e 2.

(C on

tin ue d)

St ud

y [R ef .]

Co un

tr y

(s ur ve y ye ar )

R es po ns e

ra te

% M ea n

ag e

% M en

A ss es sm

en t

to ol s

12 m on

th s or

lif et im

e pe ri od

Sa m pl e si ze

N (%

co nd

iti on

) Co

nd iti on

/ ex po su re

Tr ea tm

en t ra te

( % )

Q ua

lit y sc or e

[2 5, 26

]

• O th er s (1 .8 )

[4 6]

Cz ec h R ep ub

lic (2 01

7) 75

48 .8

46 M IN I (I CD

-1 0)

12 m on

th s

33 06

(1 0. 6)

A U D

• A ny

tr ea tm

en t (7 .0 )

8 [4 7]

U SA

(2 00

6– 20

07 )

74 26

59 .8

M IN I (I CD

-1 0)

12 m on

th s

11 0 71

4 (3 .6 )

D ep en de nc e

• A ny

tr ea tm

en t (1 1. 0)

[6 0]

Br az il (2 00

5– 20

06 )

66 .4

34 .1

50 .8

CI D I (D SM

-I V )

12 m on

th s

30 07

(9 .6 )

A U D

• A ny

tr ea tm

en t (1 2. 4)

• A lc oh

ol ic an

on ym

ou s (3 .4 )

• Sp ec ia liz ed

su rg er y (3 .0 )

• G en er al ho

sp ita

l( 2. 5)

• Ps yc hi at ri c ho

sp ita

l( 2. 1)

• Pr iv at e cl in ic (0 .7 )

• O th er

al co ho

lp ro gr am

(0 .7 )

[4 9]

K or ea

(2 00

6– 20

07 )

81 .7

36 .1

39 .6

CI D I (D SM

-I V )

Li fe tim

e 65

10 (7 )

D ep en de nc e

• A ny

tr ea tm

en t (1 2. 0)

7 12

m on

th s

65 10

(3 .2 )

D ep en de nc e

• A ny

tr ea tm

en t (3 .4 )

[5 0]

Fi nl an

d 20

00 –2

00 1

75 51

.7 48

.1 CI D I (D SM

-I V )

12 m on

th s

60 05

(3 .9 )

D ep en de nc e

• A ny

tr ea tm

en t (2 5. 3)

• A lc oh

ol tr ea tm

en t (1 5. 6)

• H ea lth

tr ea tm

en t (1 6. 8)

[1 5]

Et hi op ia (2 01

4) 98

.5 39

.4 49

.4 A U D IT

(I CD

- 10

) Li fe tim

e 14

86 (1 3. 9)

A U D

• A ny

tr ea tm

en t (1 3. 1)

• Sp ec ia lis t he al th

pr ov id er

(0 .0 )

• G en er al is t he al th

pr ov id er

(9 .1 )

• Co

m pl em

en ta ry

pr ov id er

(3 .9 )

In di a (2 01

3) 99

.6 40

.2 54

.6 A U D IT

(I CD

- 10

) 12

m on

th s

32 20

(5 .6 )

A U D

• A ny

tr ea tm

en t (2 .8 )

• Sp ec ia lis t he al th

pr ov id er

(0 .0 )

• G en er al is t he al th

pr ov id er

(1 .1 )

• Co

m pl em

en ta ry

pr ov id er

(1 .7 )

N ep al (2 01

3) 98

.9 39

.8 40

.2 A U D IT

(I CD

- 10

) 12

m on

th s

20 40

(5 )

A U D

• A ny

tr ea tm

en t (5 .1 )

• Sp ec ia lis t he al th

pr ov id er

(0 .0 )

• G en er al is t he al th

pr ov id er

(1 .3 )

• Co

m pl em

en ta ry

pr ov id er

(4 .5 )

U ga nd

a (2 01

3) 99

.9 36

34 .4

A U D IT

(I CD

- 10

) 12

m on

th s

12 90

(1 .7 )

A U D

• A ny

tr ea tm

en t (3 .5 )

• Sp ec ia lis t he al th

pr ov id er

(3 .5 )

• G en er al is t he al th

pr ov id er

(0 .0 )

• Co

m pl em

en ta ry

pr ov id er

(0 .0 )

[6 1]

M ex ic o (2 01

6– 20

17 )

73 .6

29 41

.9 CI D I (D SM

-I V )

12 m on

th s

56 87

7 (2 .2 )

D ep en de nc e

• R eh ab ili ta tio

n pr og ra m

(3 2. 4)

(C on

ti nu

es )

Treatment rates for alcohol use disorders 2623

Ta bl e 2.

(C on

tin ue d)

St ud

y [R ef .]

Co un

tr y

(s ur ve y ye ar )

R es po ns e

ra te

% M ea n

ag e

% M en

A ss es sm

en t

to ol s

12 m on

th s or

lif et im

e pe ri od

Sa m pl e si ze

N (%

co nd

iti on

) Co

nd iti on

/ ex po su re

Tr ea tm

en t ra te

( % )

Q ua

lit y sc or e

[2 5, 26

]

• D et ox ifi ca tio

n (2 4. 8)

• Ps yc hi at ri c tr ea tm

en t (1 3. 2)

[5 1]

Ca na

da (2 00

0– 20

01 )

84 .7

38 40

.9 CI D I (D SM

-I V )

12 m on

th s

12 5 49

3 (1 .9 )

D ep en de nc e

• A ny

tr ea tm

en t (1 7. 2)

• N on

-p hy

si ci an

on ly (8 .4 )

• Ph

ys ic ia n on

ly (3 .6 )

• Ps yc hi at ri st on

ly (1 .1 )

• M ul tip

le pr of es si on

al (3 .9 )

[5 2]

Si ng

ap or e (2 00

9– 20

10 )

75 .9

42 48

.5 CI D I (D SM

-I V )

Li fe tim

e 66

16 (3 .6 )

A U D

• A ny

he lp (1 8. 9)

• Ps yc hi at ri st (7 .9 )

• G P (5 .0 )

• Ps yc ho

lo gi st (5 .5 )

• M en ta lh

ea lth

sp ec ia lis t (4 .0 )

• Co

un se llo r (7 .6 )

• O th er

he al th

pr of es si on

al (0 .4 )

• R el ig io us

an d ot he r he al er s (4 .5 )

[5 3]

Si ng

ap or e (2 01

6) 69

.5 45

.2 50

.1 CI D I (D SM

-I V )

12 m on

th s

61 26

(0 .2 )

D ep en de nc e

• A ny

tr ea tm

en t (3 .0 )

7 61

26 (0 .6 )

A bu

se • A ny

tr ea tm

en t (1 9. 4)

[5 4]

A us tr al ia (2 00

7) 60

46 .6

49 .7

CI D I (D SM

-I V )

12 m on

th s

88 41

(4 .3 )

A U D

• A ny

tr ea tm

en t (2 2. 4)

• G P (1 4. 5)

• Ps yc hi at ri st (4 .3 )

• Ps yc ho

lo gi st (9 .8 )

• M en ta lh

ea lth

sp ec ia lis t (1 6. 5)

• O th er

he al th

pr of es si on

al (5 .0 )

• Ps yc hi at ri c in pa tie nt

(4 .2 )

[5 5]

N et he rl an

d (2 00

7– 20

09 )

65 .1

- -

CI D I (D SM

-I V )

Li fe tim

e 66

46 (1 2. 4)

A bu

se • A ny

tr ea tm

en t (6 .5 )

7 66

46 (1 .7 )

D ep en de nc e

• A ny

tr ea tm

en t (3 6. 9)

[6 2]

Tu rk ey

(2 00

7– 08

) 76

.5 37

.4 42

CI D I (D SM

-I V )

12 m on

th s

40 11

(3 .2 )

A bu

se • A ny

tr ea tm

en t (1 1. 6)

8 40

11 (1 .6 )

D ep en de nc e

• Tr ea tm

en t (1 6. 7)

[6 4]

Ch in a (2 00

3) 94

.8 46

46 .2

CI D I (I CD

-1 0)

Li fe tim

e 59

26 (4 .3 )

D ep en de nc e

• A ny

tr ea tm

en t (2 .4 )

7 12

m on

th s

59 26

(1 .7 )

D ep en de nc e

• A ny

tr ea tm

en t (1 .4 )

[6 7]

Et hi op ia (2 01

4) 99

39 .3

45 .7

A U D IT

(I CD

- 10

) Li fe tim

e 14

85 (3 .8 )

A U D

• A ny

tr ea tm

en t (1 3. 0)

• H ea lth

fa ci lit y (7 .0 )

• R el ig io us

se tt in g (3 .5 )

(C on

ti nu

es )

2624 Tesfa Mekonen et al.

Ta bl e 2.

(C on

tin ue d)

St ud

y [R ef .]

Co un

tr y

(s ur ve y ye ar )

R es po ns e

ra te

% M ea n

ag e

% M en

A ss es sm

en t

to ol s

12 m on

th s or

lif et im

e pe ri od

Sa m pl e si ze

N (%

co nd

iti on

) Co

nd iti on

/ ex po su re

Tr ea tm

en t ra te

( % )

Q ua

lit y sc or e

[2 5, 26

]

[4 8]

N ew

Ze al an

d (2 00

3– 20

04 )

73 .3

43 43

.3 CI D I (D SM

-I V )

12 m on

th s

12 99

2 (2 .6 )

A bu

se • A ny

tr ea tm

en t (2 5. 8)

• A ny

he al th

ca re

pr ov id er

(2 4. 8)

• A ny

no n- he al th

se tt in g (6 .5 )

12 99

2 (1 .3 )

D ep en de nc e

• A ny

tr ea tm

en t (3 6. 9)

• A ny

he al th

ca re

pr ov id er

(3 5. 2)

• N on

-h ea lth

se tt in g (9 .4 )

[5 6]

U SA

(2 00

1– 20

03 )

70 .9

41 44

.6 CI D I (D SM

-I V )

12 m on

th s

92 82

(1 .9 )

A bu

se • A ny

tr ea tm

en t (3 7. 2)

• A ny

he al th

ca re

pr ov id er

(3 3. 4)

• A ny

N on

-h ea lth

se tt in g (1 2. 8)

• M in im

al ly ad eq ua

te tr ea tm

en t

(2 7. 4)

[5 6]

U SA

(2 00

1– 20

03 )

70 .9

41 44

.6 CI D I (D SM

-I V )

12 m on

th s

92 82

(0 .8 )

D ep en de nc e

• A ny

tr ea tm

en t (4 8. 4)

• A ny

he al th

ca re

pr ov id er

(4 3. 6)

• A ny

no n- he al th

se tt in g (1 9. 6)

• M in im

al ly ad eq ua

te tr ea tm

en t

(3 1. 9)

[6 3]

Br az il (2 00

5– 20

07 )

81 .3

39 43

.4 CI D I (D SM

-I V )

12 m on

th s

50 37

(2 .7 )

A bu

se • A ny

tr ea tm

en t (1 3. 7)

• A ny

he al th

ca re

pr ov id er

(1 1. 7)

• A ny

no n- he al th

se tt in g (3 .8 )

50 37

(1 .3 )

D ep en de nc e

• A ny

tr ea tm

en t (2 2. 4)

• A ny

he al th

ca re

pr ov id er

(1 8. 5)

• A ny

no n- he al th

se tt in g (6 .9 )

[5 7]

M ex ic o (2 00

1– 20

01 )

76 .6

32 46

.9 CI D I (D SM

-I V )

Li fe tim

e 58

26 (1 4. 5)

A U D

• A ny

tr ea tm

en t (3 0. 9)

6 [5 8]

M ex ic o (2 00

1– 20

02 )

76 .6

32 46

.9 CI D I (D SM

-I V )

12 m on

th s

58 26

(4 )

A U D

• A ny

tr ea tm

en t (2 0. 7)

• A ny

he al th

ca re

se rv ic e (1 8. 8)

• A ny

no n- he al th

se tt in g (2 .4 )

58 26

(2 )

D ep en de nc e

• A ny

tr ea tm

en t (2 3. 4)

• A ny

he al th

ca re

se rv ic e (1 9. 8)

• A ny

no n- he al th

se tt in g (3 .5 )

[4 5]

Fi nl an

d (2 00

0– 20

01 )

75 51

.7 48

.1 CI D I (D SM

-I V )

12 m on

th s

47 06

(5 .4 )

A U D

• A ny

tr ea tm

en t (1 7. 2)

6 [5 9]

A rg en tin

a (2 01

5) 77

- -

CI D I (D SM

-I V )

12 m on

th s

39 27

(1 .5 )

A bu

se • A ny

tr ea tm

en t (1 7. 3)

• A ny

he al th

ca re

pr ov id er

(1 7. 3)

• A ny

no n- he al th

se tt in g (4 .3 )

(C on

ti nu

es )

Treatment rates for alcohol use disorders 2625

The quality of included studies

The quality of included studies ranged from 60–90% with an average quality of 74.7%, summarized as moderate quality. Themost common shortcomingswere failure to re- port appropriate statistical measures (confidence intervals or standard errors), lack of complete reports on the treat- ment rate for each type of care provided and a lack of de- tailed description of participants and settings (Supporting information Table S4).

Treatment rate for AUDs

The pooled treatment rate of AUD from any source of treat- ment was 17.3% (12.8–22.3%) with significant evidence of between studies heterogeneity (Q = 2649, P < 0.001, I2 = 99%). For alcohol abuse, the pooled treatment rate from any source of treatment was 14.3% (9.2–20.3%) with significant between studies heterogeneity (Q = 292, P < 0.001, I2 = 97%). The pooled treatment rate for alco- hol dependence from any source of treatment was 16.5% (12.0–21.5%) with significant heterogeneity between studies (Q = 636, P < 0.001, I2 = 97%) (Supporting information Figs S1, S2 and S3). The treatment rate for AUDs widely varied between countries, ranging from 3.5% in Uganda to 51.8% in the United Kingdom for AUD, 0% in Laos to 25.8% in New Zealand for alcohol abuse, 0% in Laos to 36.9% in New Zealand for alcohol dependence (Fig. 2).

The subgroup analysis by World Bank economic classi- fication of countries indicated that the treatment rate was very low in low and lower-middle-income countries across all treatment types. There were no studies from low and lower-middle-income countries reporting separate treat- ment rate for general medical care, mental health care or informal sources of help for alcohol abuse and dependence (Table 3). The univariate meta regression did not show any significant association between the pooled estimate and the selected study characteristics (measurement tools for AUDs, study setting, percentage of male participants and year of publication) (Supporting information Table S8).

Publication bias and sensitivity analysis

As indicated in Fig. 3, the visual inspection of the funnel plots was slightly asymmetric for the treatment rate of AUDs from any source of treatment. However, an Eggers test indicated no evidence of small study effect (AUD [t = 0.67, P = 0.51], alcohol dependence [t = 0.05, P = 0.96] and alcohol abuse [t = �0.08, P = 0.94]). Sen- sitivity analysis demonstrated no significant difference in I2 statistics. The I2 statistics for the AUDs treatment rates remained very high after one-by-one exclusion of studies (Supporting information Tables S5, S6 and S7) and even

Ta bl e 2.

(C on

tin ue d)

St ud

y [R ef .]

Co un

tr y

(s ur ve y ye ar )

R es po ns e

ra te

% M ea n

ag e

% M en

A ss es sm

en t

to ol s

12 m on

th s or

lif et im

e pe ri od

Sa m pl e si ze

N (%

co nd

iti on

) Co

nd iti on

/ ex po su re

Tr ea tm

en t ra te

( % )

Q ua

lit y sc or e

[2 5, 26

]

[3 8]

M ul tip

le co un

tr ie s in

Eu ro pe

(2 00

1– 20

03 )

61 .2

47 48

CI D I (D SM

-I V )

12 m on

th s

21 42

5 (1 )

A U D

• A ny

tr ea tm

en t (8 .3 )

• D ru g tr ea tm

en t on

ly (1 .6 )

• Ps yc ho

lo gi ca lo nl y (2 .8 )

• D ru g an

d ps yc ho

lo gi ca l( 2. 6)

• N o dr ug

/p sy ch ol og ic al (1 .2 )

n/ a = no

tr ep or te d; A U D = al co ho

lu se

di so rd er ;A

U D IT

= al co ho

lu se

di so rd er

id en tifi

ca tio

n te st ;C

ID I=

co m po si te in te rn at io na

ld ia gn

os tic

in te rv ie w ;G

P = ge ne ra lp ra ct iti on

er ;M

IN I=

m in ii nt er na

tio na

ln eu ro ps yc hi at ri c in te rv ie w .a B

el gi um

, Fr an

ce ,G

er m an

y, It al y, th e N et he rl an

ds ,S pa in .N

ot e: se e su pp le m en ta lfi le fo r qu

al ity

sc or e as se ss m en t ta bl e.

2626 Tesfa Mekonen et al.

after removal of four outlier studies (I2 = 97% for AUD, I2 = 90% for dependence and I2 = 77% for alcohol abuse).

DISCUSSION

This systematic review and meta-analysis found that the treatment rate for AUDs is generally low in the global set- ting. Lowest treatment rates were estimated in low and lower-middle-income countries. The number of included studies in low and lower-middle-income countries was small (n=4, from India, Ethiopia, Nepal, Uganda and Laos) [15,65–67], which introduces considerable variability and therefore restricts generalizability. We also did not have

data on some countries with large populations (e.g. Pakistan and Nigeria) and countries with very high heavy episodic drinking (e.g. Russia Federation) [4]. Although there was heterogeneity at the individual studies level, the pooled estimate and sub-group analysis results were within narrow range (overlapped confidence intervals between the subgroups and the pooled estimate) that indicates a meaningful result from pooled summary statistics [68].

This study estimates the treatment rate for AUDs from different dimensions of treatment sources (any source of treatment, formal healthcare setting and informal non-healthcare settings) based on the AUDs classification

Figure 2 Treatment rates by country for any treatment type. AUD = alcohol use disorder

Treatment rates for alcohol use disorders 2627

reported in the studies. The treatment rates from any source of treatment for AUD, alcohol abuse and alcohol de- pendence were 17.3% (12.8–22.3%), 14.3% (9.2–20.3%) and 16.5% (12.0–21.5%) respectively. This translates to treatment gaps (untreated percentage) of 82.7% (77.7–87.2%) for AUD, 85.7% (79.7–90.8%) for alcohol abuse and 83.5% (78.5–88.0%) for alcohol dependence. The treatment rates estimated in our revieware lower than the previous review reported by Kohn et al., which was an average treatment rate of 23.8% (76.2% treatment gap) for AUDs [9]. This suggests that the treatment rate for AUDs has not increased in the last 15 years despite the WHO recommendations and actions to address the treat- ment gap [3,10,11]. The low treatment rate, including in HICs, may indicate that making mental health services available/accessible alone cannot increase the treatment

seeking behaviour [69,70] unless the public mental health literacy is increased [71]. Moreover, AUDs have not been historically considered as a mental illness, and people with AUDs have been considered to be moral failures, provoking rejection and stigma [72]. These factors are likely to pre- vent treatment seeking. The recent recognition of mental health in the global health agenda [73] is an important milestone to bridge the mental health treatment gap but international funding for mental health remains inade- quate [74].

Natural recovery of AUDs does occur, [75,76] which may in part offset the perceived urgency of the health sys- tem adequately resourcing their treatment [9]. However, untreated remission is associated with a higher risk of re- lapse compared to treated remission [77]. Alcohol con- sumption has a detrimental effect on general health

Table 3 Pooled treatment rate for AUD, abuse and dependence based on the type of treatment

Treatment typea Country income

Treatment rate AUD Abuse Dependence Treated % (CI) N Treated % (CI) N Treated % (CI) N

Treatment from any sourceb Low incomec

9.3 (4.0–15.7) 6 0.00 (0.0–12.9) 1 0.00 (0.00–5.0) 1

Upper-middle 20.3 (9.2–33.0) 3 13.6 (10.1–17.7) 3 11.2 (1.8–23.2) 5 High-income 20.4 (14.2–27.3) 13 15.7 (9.0–23.5) 7 20.8 (15.2–27) 12 Overall 17.3 (12.8–22.3) 22 14.3 (9.2–20.3) 11 16.5 (12–21.5) 18 Statistics Q = 2649,

I2 = 99% Q = 292, I2 = 97%

Q = 636, I2 = 97%

Treatment from any Healthcare settings

Low income 1.9 (0.1–4.4) 10 0.00 (0.00–13.0) 1 0.00 (0.00–5.0) 1 Upper-middle 4.2 (0.3–9.5) 5 12.6 (9.4–16.7) 3 14.6 (7.5–22.8) 8 High-income 6.3 (4.8–8.0) 39 17.8 (8.3–29.1) 4 183 (13.3–23.8) 8 Overall 4.8 (3.7–6.0) 54 14.6 (8.5–21.9) 8 15.5 (11.5–20) 17 Statistics Q = 1276,

I2 = 98% Q = 217, I2 = 97%

Q = 541, I2 = 97%

General medical setting Low income 3.7 (0.5–8.0) 5 No data – No data –

Upper-middle 2.3 (1.2–3.7) 4 9.4 (4.7–15.2) 4 7.3 (0.0–22.5) 3 High-income 4.4 (3.1–6.0) 21 22.0 (15.0–29.7) 4 22.6 (4.4–45.7) 5 Overall 4.0 (2.9–5.3) 30 15.6 (9.9–22.3) 8 16.2 (5.5–30.6) 8 Statistics Q = 2120,

I2 = 99% Q = 69, I2 = 90% Q = 284, I2 = 98%

Mental health setting Low income 0.2 (0.00–25.1) 4 No data – No data –

Upper-middle 7.8 (0.0–25.1) 2 8.8 (6.7–11.3) 6 17.7 (13.3–25.2) 7 High-income 5.1 (3.7–6.6) 25 13.9 (8.8–19.7) 6 15.0 (7.5–24.1) 8 Overall 4.5 (3.3–5.9) 31 11.7 (8.6–15.2) 12 16.1 (9.5–24.1) 15 Statistics Q = 1595,

I2 = 98% Q = 58, I2 = 81% Q = 1123,

I2 = 99% Informal help Low income 3.3 (1.9–4.9) 5 No data – No data –

Upper-middle 2.1 (0.7–4.0) 3 3.1 (1.6–4.9) 6 3.9 (0.8–8.2) 4 High-income 2.3 (1.2–3.5) 24 6.4 (3.9–9.2) 6 9.4 (5.0–14.7) 6 Overall 2.4 (1.4–3.5) 32 4.9 (3.3–6.8) 12 7.1 (4.1–10.8) 10 Statistics Q = 4732,

I2 = 99% Q = 36, I2 = 70% Q = 39.2, I2 = 77%

CI= confidence interval; N = number of observations (a studymay havemore than one observation). P< 0.001 for all statistics. a Treatment types are separate

categories (one is not the composite of others) and each treatment type category has its own pooled estimate. b From studies that reported an overall estimate

for treatment from any source. c Low and lower-middle-income countries.

2628 Tesfa Mekonen et al.

(contributes to 4% of the global mortality) [78], imposes a significant economic burden [79,80] and is responsible for 99.2 million DALYs, [81] which is higher than the disease burden attributable to mood disorders (43.1 million DALYs) [82]. Effective pharmacological treatments for AUDs are available, such as acamprosate and naltrexone that have 9–12 number needed to treat (NNT) [83], an ef- ficacy comparable to tricyclic antidepressants in treating depression (NNT = 8.5) [84]. Low treatment rates are therefore a missed opportunity to effectively treat AUDs.

People with AUDsmight seek services, but this does not imply that they received effective treatment from appropri- ately trained staff. A study conducted in the United States reported that within a sample of treatment seeking individ- uals, only 27.4% received minimally adequate treatment (based on available evidence-based guidelines) for alcohol

abuse and 31.9% for alcohol dependence [56]. This was more pronounced for pharmacotherapies where only 3% of people with alcohol dependence in Australia received a pharmacotherapy and only 15–25% of these were treated for the recommended duration [85]. Low treatment seeking is compounded by low detection rate of AUDs in primary care [86,87]. This underdiagnosis misses opportunities for brief interventions that are effective in reducing problem drinking [83].

HICs (20.4%) and upper-middle-income countries (20.3%) had higher treatment rates for AUD than low and lower-middle-income countries (9.3%). There were not enough studies to reliably compare treatment rates of alcohol abuse and dependence across regions. Our findings were consistent with the previous data that showed lower coverage for mental health services, lower health service

Figure 3 Funnel plots of AUD, alcohol dependence and alcohol abuse for ‘any treatment’. AUD = alcohol use disorder

Treatment rates for alcohol use disorders 2629

utilization and low treatment rate in low-income countries [6,7,88]. Integration of the services for AUDs to primary health care might increase the treatment rate. Informal community-based services are available and can be effec- tive/cost-effective in the treatment of AUDs [89]. These cost-effective informal services could benefit resource lim- ited settings and remote areas in the treatment of AUDs.

The pooled estimates for AUD from studies reporting treatment rates from healthcare settings (4.8% from any healthcare, 4% from general medical and 4.5% from men- tal health settings) were lower than the estimate from any source of treatment (17.3%). Compared to alcohol abuse and dependence, the treatment rate was relatively similar across all treatment sources except for the informal sources. An individuals’ perceived need for care affects their use of healthcare services [90] whereas the severity of the disorder might contribute to seeking help from spe- cialized care. This was supported in our study that found a higher treatment rate for alcohol dependence in mental health services. Lower income countries had the lowest treatment rate from healthcare settings for AUD, and there was only one study that reported the treatment rate for al- cohol abuse and dependence [65]. A research priority is to conduct more high-quality studies on the treatment rate of AUDs in low-income countries.

Previous studies have found that women had higher service use behaviour for general medical purposes and mental health care [91–93]. Our study however did not find statistically significant gender differences in the treat- ment of AUDs. This might be because of the small number of studies and the difference between countries, culture and context that warrants the need for further studies on gender difference in different settings.

Limitations

There are limitations to be considered in the interpretation of these findings. Insufficient data, especially from low-income countries and between studies heterogeneity, makes it difficult to generalize the finding to the global set- ting. Further, this study had insufficient data to estimate the treatment rate by the countries geographical classifica- tion and our estimate was only of countries’ economic clas- sification. Because we estimated the overall treatment rate from any source of help regardless of treatment outcomes and treatment completion, we cannot report if the treat- ment was effective. Given the chronic and relapsing nature of AUDs, individuals often seek treatment many times within the 12 months/lifetime period. Our study did not capture these data.

It is likely there are fewer AUD services in rural areas. Our study was not able to explore this by a robust meta-regression analysis because of the limited number of studies. Within available data, we found a trend that the

treatment rate was low in the rural areas, which was not statistically significant (Supporting information Table S8). For cultural or religious reasons, some population groups are prohibited from drinking alcohol in many countries [94] and therefore would not seek treatment—this study was not able to include these data. It is worth noting that our findings were limited to the articles published in En- glish. Diagnostic differences between studies and across the legacy version of DSM were also a potential limitation.

CONCLUSION

Studies investigating the treatment rate of AUDs are limited and there was substantial inter-study heterogeneity. The meta-analysis showed that the overall treatment rate for AUD from any source of treatment is 17.3%. Lower treat- ment rates were observed in low and lower-middle-income countries. Given the limited data identified in this review, further treatment rate estimation studies are required, par- ticularly in low-income countries. Treatment planners should increase services for people with AUDs.

Data statement

The data associated with this study are available from the corresponding author.

Declaration of interests

None.

Funding

There is no specific funding for this study. T.M. is supported by the University of Queensland research and training pro- gram scholarship.

Acknowledgements

We would like to thank Miranda Newell, Librarian, The University of Queensland (contribution in search strategy), Calvert Tisdale and Sarah Ford, The University of Queens- land (contribution in proofreading) and Danielle Dawson, The University of Queensland (contribution in Title/Ab- stract screening and proofreading). T.M. is supported by the University of Queensland research and training pro- gram scholarship.

Author contributions

Gary C.K. Chan: Conceptualization; data curation; formal analysis; investigation; methodology; resources; supervi- sion; validation. Jason Connor: Data curation; investiga- tion; methodology; resources; supervision; validation. Wayne Hall: Data curation; investigation; methodology; resources; supervision; validation. Leanne Hides:

2630 Tesfa Mekonen et al.

Conceptualization; data curation; investigation; methodol- ogy; resources; supervision; validation. Janni Leung: Conceptualization; data curation; formal analysis; investi- gation; methodology; project administration; resources; software; supervision; validation; visualization. Tesfa Mekonen: Conceptualization-lead; data curation-lead; for- mal analysis-lead; investigation-lead; methodology-lead; project administration-lead; resources-equal; software- equal; validation-equal; visualization-lead; writing-original draft-lead; writing-review; editing-lead

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Supporting Information

Additional supporting information may be found online in the Supporting Information section at the end of the article.

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Figure S1 AUD any treatment by World Bank economy (Forest plot). Figure S2 Alcohol abuse any treatment by WB economic group. Figure S3 Alcohol dependence any treatment by WB eco- nomic group. Table S1 PRISMA checklist. Table S2 PubMed search strategy. Table S3 Quality assessment tool.

Table S4 Quality assessment of included studies. Table S5 Sensitivity analysis for AUD treatment rate (any treatment). Table S6 Sensitivity analysis for alcohol abuse treatment rate (any treatment). Table S7 Sensitivity analysis for alcohol dependence treat- ment rate (any treatment). Table S8 Univariate meta-regression for AUD (n = 22), al- cohol abuse (n = 11) and alcohol dependence (n = 18).

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