Abstract
Aims
To examine the diagnostic overlap in DSM-IV and DSM-5 alcohol use disorder (AUD) and determine the clinical correlates of changing diagnostic status across the two classification systems.
Design
DSM-IV and DSM-5 definitions of AUD were compared using cross-national community survey data.
Setting
Nine low-, middle- and high-income countries.
Participants/Cases
31,367 respondents to surveys in the World Health Organization World Mental Health Survey Initiative.
Measures
Composite International Diagnostic Interview, version 3.0 was used to derive DSM-IV and DSM-5 lifetime diagnoses of AUD. Clinical characteristics, also assessed in the surveys, included lifetime DSM-IV anxiety, mood and drug use disorders, lifetime suicidal ideation, plan and attempt, general functional impairment and psychological distress.
Findings
Compared to DSM-IV AUD (12.3%, SE=0.3%), the DSM-5 definition yielded slightly lower prevalence estimates (10.8%, SE=0.2%). Almost one third (n=802) of all DSM-IV Abuse cases switched to sub-threshold according to DSM-5 and one quarter (n=467) of all DSM-IV diagnostic orphans switched to mild AUD according to DSM-5. New cases of DSM-5 AUD were largely similar to those who maintained their AUD across both classifications. Similarly, new DSM-5 non-cases were similar to those who were sub-threshold across both classifications. The exception to this was with regards to the prevalence of any lifetime drug use disorder.
Conclusions
In this large cross-national community sample, the prevalence of DSM-5 lifetime AUD was only slightly lower than the prevalence of DSM-IV lifetime AUD. Nonetheless there was considerable diagnostic switching, with a large number of people inconsistently identified across the two DSM classifications.
Introduction
Alcohol use and alcohol use disorder (AUD) account for significant disability globally (1). Epidemiological surveys of the general population demonstrate that AUD has a lifetime prevalence close to 20%, a typical onset in young adulthood, is accompanied by substantial lifetime psychiatric comorbidity and can be associated with significant treatment-seeking delay (2–4).
The symptom criteria used to diagnose alcohol use disorder have undergone significant change in the most recent, fifth revision of the American Psychiatric Association’s Diagnostic and Statistical Manual for Mental Disorders (DSM-5) (5). Four major changes occurred (6). Firstly, the distinction between DSM-IV alcohol abuse and DSM-IV alcohol dependence was removed, and DSM-5 AUD is now conceptualized as a unitary disorder. Secondly, the diagnostic criterion reflecting alcohol-related legal problems was removed. Thirdly, a new criterion, reflecting craving or a strong desire to drink alcohol, was added. Arguably the biggest change was to the threshold for a diagnosis of AUD. Instead of separate thresholds for DSM-IV alcohol abuse (one out of four symptom criteria required) and DSM-IV alcohol dependence (three out of seven symptom criteria required) the DSM-5 definition of AUD requires at least two out of a total of eleven symptom criteria. The DSM-5 definition of AUD also specifies severity cut-points with 2–3 symptom criteria indicating mild AUD, 4–5 symptom criteria indicating moderate AUD and 6+ symptom criteria indicating severe AUD.
Even before the official publication of the DSM-5 there was concern that the new criteria would substantially increase the prevalence of AUD in the general population (7). These concerns have been somewhat realised. While some studies have shown modest (8, 9) or no meaningful (10) differences in prevalence between AUD defined according to DSM-IV versus DSM-5, others have demonstrated more substantial differences (11), with one study suggesting that the prevalence of past-year AUD would increase by just over 60% with the new DSM-5 definition (12). These studies have been conducted primarily within single, high-income countries. Little is known about the impact of definitional changes in the diagnosis of AUD to the prevalence of AUD in middle- and low-income countries.
One further issue that has received relatively little attention is the impact of different AUD definitions on movements in and out of AUD “caseness” (i.e. whether a person meets criteria for a diagnosis of AUD or not). There has been considerable interest in the group of people who endorse one or two DSM-IV dependence criteria and no DSM-IV abuse criteria. Known as diagnostic orphans (13) these individuals share similar characteristics to diagnosed cases with alcohol abuse or alcohol dependence (14). A certain proportion of these DSM-IV diagnostic orphans, i.e. those who endorse two dependence criteria, become new cases with the application of the DSM-5 definition of AUD. At the same time, because DSM-IV abuse could be diagnosed with the endorsement of only one criterion yet DSM-5 AUD requires endorsement of at least two criteria, a certain proportion of DSM-IV abuse cases become new non-cases with the application of DSM-5. It is reasonable to assume that these new cases of DSM-5 AUD should be similar in clinical profile to those who maintain their caseness across both DSM-IV and DSM-5 classification systems. Similarly, the new non-cases according to DSM-5 should be similar in clinical profile to DSM-IV diagnostic orphans. However, in practice, this remains to be seen.
With this in mind, the aims of the current study are:
To examine the overlap between DSM-IV and DSM-5 categories of AUD;
To quantify the rates of conversion from sub-threshold DSM-IV AUD to threshold DSM-5 AUD and from threshold DSM-IV to sub-threshold DSM-5 AUD;
To characterize the AUD symptom criteria profiles of subgroups who change their diagnostic status between the two classification systems; and
To investigate the clinical correlates of changing diagnostic status between the two classification systems.
Methods
Sample
Data came from nine countries that participated in the World Health Organization’s (WHO) World Mental Health Survey (WMHS) Initiative, a global initiative designed to collect nationally or regionally representative survey data using a consistent survey instrument. While the WMHS Initiative includes more than nine countries, we only included in the analysis those countries that assessed alcohol dependence regardless of whether or not respondents met criteria for DSM-IV alcohol abuse. Data came from adults in four lower- and middle-income countries and five upper-income countries, as classified by the World Bank (see Table 1). The average response rate across surveys was 64.7% and the total sample size was 44,341. The specific sample characteristics for each of the nine surveys are shown in Table 1. Interviews were carried out by trained lay-interviewers using standardized procedures. In the majority of surveys (except Australia, Iraq and Romania) the interview was carried out in two parts: Part 1 involved the assessment of a set of core mental disorders and Part 2 involved assessment of all associated correlates of these disorders. Part 2 was administered to all respondents who met criteria for at least one core mental disorder as well as a probability sub-sample of all others. Data from Part 2 were weighted to account for the under-representation of non-cases. Part 1 data were used for four countries (Australia, Brazil, Iraq and Romania) and Part 2 data were used for the remaining five countries (Colombia, Northern Ireland, Poland, Portugal and Spain).
Table 1.
Country by income category | Surveyb | Sample characteristicsc | Field dates | Age range | Sample Size | Response rated | |
---|---|---|---|---|---|---|---|
Part 1 | Part 2 | ||||||
I. Low and lower middle income countries | |||||||
Iraq | IMHS | Nationally representative. | 2006–7 | 18–96 | 4,332 | 4,332 | 95.2 |
TOTAL | (4,332) | (4,332) | 95.2 | ||||
II. Upper-middle income countries | |||||||
Brazil - São Paulo | São Paulo Megacity | São Paulo metropolitan area. | 2005–7 | 18–93 | 5,037 | 2,942 | 81.3 |
Colombia – Medellinf | MMHHS | Medellin metropolitan area | 2011–12 | 19–65 | 3,261 | 1,673 | 97.2 |
Romania | RMHS | Nationally representative. | 2005–6 | 18–96 | 2,357 | 2,357 | 70.9 |
TOTAL | (10,655) | (6,972) | 82.8 | ||||
III. High-income countries | |||||||
Australiae | NSMHWB | Nationally representative. | 2007 | 18–85 | 8,463 | 8,463 | 60 |
N. Ireland | NISHS | Nationally representative. | 2004–7 | 18–97 | 4,340 | 1,986 | 68.4 |
Poland | EZOP | Nationally representative | 2010–11 | 18–64 | 10,081 | 4,000 | 50.4 |
Portugal | NMHS | Nationally representative. | 2008–9 | 18–81 | 3,849 | 2,060 | 57.3 |
Spain - Murcia | PEGASUS- Murcia | 2010–12 | 18–64 | 2,621 | 1,459 | 67.4 | |
IV. TOTAL | (29,354) | (17,968) | 56.8 | ||||
TOTAL | (44,341) | (29,272) | 64.7 |
The World Bank (2012) Data. Accessed May 12, 2012 at: http://data.worldbank.org/country. Some of the WMH countries have moved into new income categories since the surveys were conducted. The income groupings above reflect the status of each country at the time of data collection. The current income category of each country is available at the preceding URL.
IMHS (Iraq Mental Health Survey); MMHHS (Medellín Mental Health Household Study); RMHS (Romania Mental Health Survey); NSMHWB (National Survey of Mental Health and Wellbeing); NISHS (Northern Ireland Study of Health and Stress); EZOP (Epidemiology of Mental Disorders and Access to Care Survey); NMHS (Portugal National Mental Health Survey); PEGASUS-Murcia (Psychiatric Enquiry to General Population in Southeast Spain-Murcia).
Most WMH surveys are based on stratified multistage clustered area probability household samples in which samples of areas equivalent to counties or municipalities in the US were selected in the first stage followed by one or more subsequent stages of geographic sampling (e.g., towns within counties, blocks within towns, households within blocks) to arrive at a sample of households, in each of which a listing of household members was created and one or two people were selected from this listing to be interviewed. No substitution was allowed when the originally sampled household resident could not be interviewed. These household samples were selected from Census area data in all countries. 6 of the 9 surveys are based on nationally representative household samples.
The response rate is calculated as the ratio of the number of households in which an interview was completed to the number of households originally sampled, excluding from the denominator households known not to be eligible either because of being vacant at the time of initial contact or because the residents were unable to speak the designated languages of the survey. The weighted average response rate is 64.7%.
For the purposes of cross-national comparisons we limit the sample to those 18+. The NSMHWB surveyed respondents aged 16–85 with a total sample size of 8841. The response rate reported here refers to the full survey sample response rate.
Colombia moved from the “lower and lower-middle income” to the “upper-middle income” category between 2003 (when the Colombian National Study of Mental Health was conducted) and 2010 (when the Medellin Mental Health Household Study was conducted), hence Colombia’s appearance in both income categories. For more information, please see footnote a.
Diagnostic Instrument
Diagnoses of DSM-IV disorders over lifetime were assessed using the World Health Organization’s Composite International Diagnostic Interview Version 3.0 (15), a fully structured interview with questions designed to operationalize the DSM-IV diagnostic criteria for each mental disorder. Substance use disorders assessed were alcohol abuse, alcohol dependence, drug abuse and drug dependence. Anxiety disorders assessed were panic disorder (with or without agoraphobia), agoraphobia without a history of panic disorder, generalized anxiety disorder, posttraumatic stress disorder, separation anxiety disorder, social phobia, specific phobia and obsessive compulsive disorder. Mood disorders included major depressive disorder, dysthymia and bipolar disorder.
A series of 16 questions were used to operationalize the DSM-IV and DSM-5 symptom criteria for AUD. These were asked of people who had consumed alcohol at or above a certain quantity/frequency threshold. In all countries except Australia respondents had to drink at least one to two days per week or, if drinking less often, then they had to consume at least three drinks per drinking day. The threshold was slightly higher in the Australian survey (either drinking three to four days per week or, if drinking less often then consuming at least three drinks per drinking day). To assess the new DSM-5 craving criterion, respondents needed to indicate that there was a time when they felt such a strong desire or urge to drink that they could not keep from drinking, or that they had wanted to drink so badly they could not think of anything else. The DSM-5 clustering criterion, two or more symptoms in the same year, could not be assessed. Therefore, to keep comparisons consistent we also did not apply the clustering criterion to DSM-IV diagnoses.
Statistical Analysis
Cross-tabulations were used to compare and contrast different categories of DSM-IV and DSM-5 AUD. Respondents were grouped into mutually exclusive diagnostic groups which, for DSM-IV, comprised of: 1. No AUD symptom criteria, 2. One or two dependence symptom criteria and no abuse symptom criteria (“Orphans”), 3. Abuse without Dependence, and 4. Dependence with or without Abuse. For DSM-5, these comprised of 1. No AUD symptom criteria, 2. Sub-threshold AUD (1 symptom criterion), 3. Mild AUD (2–3 symptom criteria), 4. Moderate AUD (4–5 symptom criteria) and 5. Severe AUD (6+ symptom criteria).
Specific attention was given to the sub-groups of respondents who moved in and out of caseness across the two classification systems. New DSM-5 cases (i.e. cases that were diagnostic orphans according to DSM-IV but switched to meeting criteria for Mild AUD in DSM-5) were directly compared, on clinical characteristics, to respondents who remained cases across both classification systems. Similarly, new DSM-5 non-cases (i.e. cases that met criteria for DSM-IV Abuse but switched to sub-threshold in DSM-5) were directly compared, on clinical characteristics, to respondents who remained as non-cases across both classification systems.
The clinical characteristics of interest were divided into four categories. Firstly, lifetime comorbid psychopathology was defined separately as DSM-IV any mood, any anxiety or any drug use disorders. Secondly, lifetime suicidality was defined separately as any suicidal ideation, suicide plan or suicide attempt. Thirdly, functional impairment was assessed by the WMHS version of the WHO Disability Assessment Schedule (WHODAS; (16)). This instrument assesses disability over the 30 days prior to interview across the following domains: role impairment, mobility, self-care, social functioning and cognitive functioning. Psychological distress was measured over the 30 days prior to interview by the 6-item version of the Kessler Psychological Distress Scale (K6; (17)).
Comorbid mental disorders and suicidality were treated as binary outcome variables and WHODAS and K6 scores as continuous outcome variables in all regression analyses. Univariate logistic regression was used for all binary variables with coefficients exponentiated and reported as odds ratios with associated 95% confidence intervals. Odds ratios represented the odds of having the clinical characteristic among those who switched their diagnostic caseness compared to those who maintained their diagnostic caseness (the reference group). Univariate linear regression was used to evaluate group differences for all continuous variables with results reported as beta coefficients and associated standard errors. Beta coefficients represented the mean difference in the clinical characteristic among those who switched compared to those who maintained their diagnostic caseness. In order to take into account the complex sampling designs of the individual surveys and accurately estimate error around estimates, data were analyzed using SAS-callable SUDAAN.
Results
In the pooled sample, the lifetime prevalence of DSM-IV AUD was 12.3% (8.0% for abuse and 4.3% for dependence, see Table 2). DSM-IV diagnostic orphans made up a further 5.3% of the total sample. The prevalence of DSM-5 AUD was 10.8% (5.6% mild, 2.3% moderate and 2.8% severe) with a further 6.5% being sub-threshold according to DSM-5.
Table 2.
N | Weighted % | SE | |
---|---|---|---|
No alcohol use | 7,361 | 23.2 | 0.4 |
DSM-IV | |||
Alcohol use, but no DSM-IV alcohol use disorder | 18,361 | 59.2 | 0.5 |
DSM-IV AUD diagnostic orphans1 | 1,778 | 5.3 | 0.2 |
DSM-IV alcohol abuse2 | 2,394 | 8.0 | 0.2 |
DSM-IV alcohol dependence3 | 1,473 | 4.3 | 0.2 |
Any DSM-IV alcohol use disorder | 3,867 | 12.3 | 0.3 |
DSM-5 | |||
Alcohol use, but no DSM-5 alcohol use disorder | 18,415 | 59.5 | 0.5 |
No DSM-5 alcohol use disorder (1 criterion) | 2,150 | 6.5 | 0.2 |
Mild DSM-5 alcohol use disorder (2–3 criteria) | 1,730 | 5.6 | 0.2 |
Moderate DSM-5 alcohol use disorder (4–5 criteria) | 710 | 2.3 | 0.1 |
Severe DSM-5 alcohol use disorder (6+ criteria) | 1,001 | 2.8 | 0.1 |
Any DSM-5 alcohol use disorder | 3,441 | 10.8 | 0.2 |
Nine Countries were included: Iraq, Brazil, Medellin, Romania, Australia, Murcia, Northern Ireland, Poland and Portugal.
Those who meet 1 or 2 DSM-IV dependence criteria and no abuse criteria.
Those who meet DSM-IV abuse criteria but not dependence criteria.
Those who meet DSM-IV dependence criteria regardless of whether they meet criteria for abuse or not.
Almost one third (n=802) of all DSM-IV Abuse cases switched to sub-threshold according to DSM-5, and one quarter (n=467) of all DSM-IV diagnostic orphans switched to mild AUD according to DSM-5 (see Table 3). The net effect was a relative reduction of 12% in the lifetime prevalence of AUD when diagnosed by DSM-5 compared to DSM-IV.
Table 3.
No DSM-IV alcohol use disorder | DSM-IV diagnostic orphans2 | DSM-IV alcohol abuse3 | DSM-IV alcohol dependence4 | Total | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
N | %1 | SE | N | %1 | SE | N | %1 | SE | N | %1 | SE | N | |
No DSM-5 AUD | 25,685 | 99.8 | 0 | 0 | 0 | 0 | 91 | 4.8 | 0.7 | 25,776 | |||
No DSM-5 AUD (1 criterion) | 37 | 0.2 | 0 | 1,311 | 74.3 | 1.3 | 802 | 31 | 1.3 | 2,150 | |||
Mild DSM-5 AUD (2–3 criteria) | 467 | 25.7 | 1.3 | 1,156 | 49.1 | 1.6 | 107 | 8.2 | 1 | 1,730 | |||
Moderate DSM-5 AUD (4–5 criteria) | 325 | 14 | 1.1 | 385 | 28.2 | 1.8 | 710 | ||||||
Severe DSM-5 AUD (6+ criteria) | 20 | 1.1 | 0.3 | 981 | 63.7 | 1.9 | 1,001 | ||||||
Total | 25,722 | 100 | 0 | 1,778 | 100 | 0 | 2,394 | 100 | 0 | 1,473 | 100 | 0 | 31,367 |
Nine Countries were included: Iraq, Brazil, Medellin, Romania, Australia, Murcia, Northern Ireland, Poland and Portugal.
% shown in the table is column percent, so the sum of each column is 100%.
Those who meet 1 or 2 dependence criteria and no abuse criteria.
Those who meet abuse criteria but not dependence criteria.
Those who meet dependence criteria regardless of whether they meet criteria for abuse or not.
The overall prevalence of AUD differed across the nine countries from a low of 0.8% for DSM-IV and 0.9% for DSM-5 AUD in Iraq to a high of 23.2% for DSM-IV and 19.9% for DSM-5 AUD in Australia. In six out of the nine countries (Australia, Spain, Romania, Northern Ireland, Poland and Portugal) the prevalence of AUD was lower in DSM-5 compared to DSM-IV, in two countries (Iraq and Brazil) the prevalence was higher in DSM-5 compared to DSM-IV and in one country (Colombia) the prevalence was identical across the two classification systems (data available on request).
Focusing specifically on the diagnostic switchers, cases of DSM-IV Abuse that switched to sub-threshold under DSM-5 (i.e. new non-cases) were most likely to endorse the use of alcohol in hazardous situations symptom criterion (58.2%; see Table 4). DSM-IV diagnostic orphans who switched to DSM-5 mild AUD (i.e. new cases) were most likely to endorse the larger amount/longer period symptom criterion (92.2%), followed by craving (25.8%), unsuccessful efforts to cut down (25.1%) and tolerance (24.3%).
Table 4.
DSM criterion | DSM-IV diagnosis | DSM-5 diagnosis | Description | Prevalence in the total sample (N=31367) | Prevalence among new DSM-5 AUD non-cases (N=802)1 | Prevalence among new DSM-5 AUD cases (N=467)2 | |||
---|---|---|---|---|---|---|---|---|---|
% | SE | % | SE | % | SE | ||||
Major role | Abuse | AUD | Recurrent use despite the inability to fulfil role obligations | 5.8 | 0.2 | 29.0 | 2.1 | 0.0 | - |
Hazardous | Abuse | AUD | Recurrent use in physically dangerous situations | 7.2 | 0.2 | 58.2 | 2.3 | 0.0 | - |
Social | Abuse | AUD | Recurrent use despite substance-related social problems | 4.4 | 0.2 | 7.9 | 1.1 | 0.0 | - |
Legal | Abuse | N/A | Recurrent use despite substance-related legal problems | 2.6 | 0.1 | 14.1 | 1.5 | 0.0 | - |
Tolerance | Dependence | AUD | Tolerance | 3.8 | 0.1 | 0.1 | 0.1 | 24.3 | 2.5 |
Withdrawal | Dependence | AUD | Withdrawal | 3.2 | 0.1 | 0.3 | 0.2 | 14.4 | 2.1 |
Larger/longer | Dependence | AUD | Drinking larger amounts or for longer than intended | 12.8 | 0.3 | 4.1 | 1.0 | 92.2 | 1.4 |
Cut down | Dependence | AUD | Desire or unsuccessful efforts to cut down | 4.0 | 0.1 | 0.2 | 0.1 | 25.1 | 2.4 |
Time spent | Dependence | AUD | Great deal of time spent drinking or recovering from effects | 3.1 | 0.1 | 0.1 | 0.1 | 16 | 2.2 |
Give up | Dependence | AUD | Reduction in important activities because of drinking | 1.9 | 0.1 | 0.0 | - | 2.2 | 0.7 |
Continue | Dependence | AUD | Continued use despite significant problems | 3.3 | 0.1 | 0.1 | 0.1 | 12.2 | 1.9 |
Craving | N/A | AUD | Craving or strong desire for alcohol | 3.7 | 0.1 | 0.0 | - | 25.8 | 2.5 |
Nine countries were included: Iraq, Brazil, Medellin, Romania, Australia, Murcia, Northern Ireland, Poland and Portugal.
N/A – not applicable.
Individuals who were DSM-IV Abuse cases and switched to DSM-5 sub-threshold AUD
Individuals who were DSM-IV diagnostic orphans and switched to DSM-5 mild AUD
The clinical correlates of switching diagnostic status between the two classification systems are presented in Table 5. New non-cases were similar in many respects to those who remained sub-threshold on both classification systems (“consistent non-cases”). The exception to this was in the likelihood of any DSM-IV drug use disorder where new non-cases were more likely to meet criteria for any drug use disorder compared to consistent non-cases. These two diagnostic groups were no different to each other with regards to lifetime suicidality and past 30-day general functional impairment and psychological distress.
Table 5.
No AUD symptoms1 (N=23,973) | Consistent non-cases2 (N=1,215) | New non-cases3 (N=745) | New cases4 (N=444) | Consistent cases5 (N=1,187) | New non-cases vs consistent non-cases6 | New cases versus consistent cases7 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
% | SE | % | SE | % | SE | % | SE | % | SE | OR | 95%CI | OR | 95%CI | |
Anxiety disorder8 | 15.4 | 0.3 | 20.0 | 1.3 | 16.3 | 1.8 | 31.7 | 2.5 | 25.9 | 1.8 | 0.8 | 0.6–1.1 | 1.4* | 1.0–1.9 |
Mood disorder9 | 11.1 | 0.3 | 13.1 | 1.1 | 11.9 | 1.5 | 22.4 | 2.5 | 18.8 | 1.4 | 1.0 | 0.7–1.4 | 1.3 | 0.9–1.9 |
Drug use disorder10 | 1.1 | 0.1 | 4.7 | 0.7 | 7.6 | 1.1 | 8.4 | 1.7 | 16.4 | 1.6 | 1.7* | 1.1–2.7 | 0.5* | 0.3–0.7 |
Suicidal ideation | 6.6 | 0.2 | 10.6 | 1.0 | 12.0 | 1.6 | 17.5 | 2.0 | 16.9 | 1.6 | 1.2 | 0.9–1.8 | 1.1 | 0.8–1.6 |
Suicide plan | 2.1 | 0.1 | 3.3 | 0.6 | 3.8 | 1.0 | 4.3 | 0.8 | 3.1 | 0.5 | 1.2 | 0.6–2.5 | 1.4 | 0.8–2.4 |
Suicide attempt | 1.3 | 0.1 | 1.9 | 0.5 | 2.0 | 0.4 | 3.3 | 0.8 | 3.4 | 0.8 | 1.2 | 0.6–2.5 | 0.9 | 0.4–1.7 |
Mean | SE | Mean | SE | Mean | SE | Mean | SE | Mean | SE | Beta | 95%CI | Beta | 95%CI | |
Impairment11 | 2.8 | 0.1 | 1.9 | 0.3 | 3.0 | 1.0 | 4.0 | 0.8 | 2.4 | 0.3 | 1.8 | −0.6–4.2 | 1.4 | −0.3–3.1 |
Distress12 | 2.6 | 0.0 | 2.9 | 0.1 | 3.1 | 0.2 | 3.9 | 0.2 | 3.3 | 0.2 | 0.0 | −0.5–0.5 | 0.4 | −0.1–1.0 |
Eight Countries were included: Iraq, Brazil, Medellin, Romania, Australia, Murcia, Northern Ireland, and Poland. Portugal was excluded as substance use data were not collected.
Individuals who have no DSM-IV or DSM-5 AUD symptoms
Individuals who are orphans in DSM-IV and Sub-threshold in DSM-5
Individuals with abuse (w/o dependence) in DSM-IV and Sub-threshold AUD in DSM-5
Individuals who are orphans in DSM-IV and Mild AUD (2–3 criteria) in DSM-5
Individuals with abuse or dependence in DSM-IV who convert to Mild AUD (2–3 criteria) in DSM-5
Odds ratios (OR) comparing consistent non-cases and new non-cases. Consistent non-cases used as the reference group.
Odds ratios (OR) comparing new cases and consistent cases. Consistent cases used as the reference group.
Anxiety disorder includes panic disorder, agoraphobia, specific phobia, social phobia, generalized anxiety disorder, posttraumatic stress disorder, separation anxiety disorder/adult separation anxiety and obsessive compulsive disorder. Note: not all individual anxiety disorders were assessed in all countries.
Mood disorder includes major depressive episode, dysthymia and bipolar I, II and subthreshold.
Drug use disorder includes drug abuse and dependence.
Measured using the Global WHODAS instrument (except for Australia where it was not assessed).
Measured using the K6 instrument.
p<0.05
New cases were also similar in most clinical variables to those who remained as cases on both classification systems (“consistent cases”). Again, the exception to this was in the likelihood of any DSM-IV drug use disorder, where new cases were less likely to meet criteria for any drug use disorder compared to consistent cases. New cases were also at greater odds of meeting criteria for a lifetime anxiety disorder compared to consistent cases. However, these two groups shared similar profiles with regards to suicidality, general functional impairment and psychological distress.
Discussion
The current study provides information on the diagnostic overlap between DSM-IV and DSM-5 AUD using data from a large, cross-national dataset. The novelty of this large cross-national study comes from its careful examination of the cases that fall on either side of the diagnostic threshold, particularly when those thresholds change, as they did between DSM-IV and DSM-5. As Wakefield (18) has recently commented, AUD is not an all-or-none phenomenon but instead exists along a continuum and any diagnostic demarcation along that continuum is likely to be somewhat arbitrary. For this reason, it becomes vital to examine those cases that sit just below or just above the suggested diagnostic threshold. The results indicate that overall, the prevalence declines slightly when cases are defined by DSM-5 compared to DSM-IV. Use of alcohol in hazardous situations is the symptom criterion endorsed most by those cases who changed from DSM-IV Abuse to sub-threshold according to DSM-5. New cases (i.e. those who were sub-threshold according to DSM-IV but became cases according to DSM-5) were largely similar to cases according to both DSM-IV and DSM-5. The same was true for new versus existing non-cases. The exception to this was with regards to the odds of a drug use disorder.
Contrary to previous research (12) in which the prevalence of past-year DSM-5 AUD was around 60% higher than the prevalence of DSM-IV AUD, we found the prevalence of DSM-5 AUD was 12% lower than the prevalence of DSM-IV AUD. While it is difficult to know the exact cause of this discrepancy it is possible that differences between these studies in the ratio of total number of DSM-IV Abuse cases to total number of diagnostic orphans may have driven these opposing findings. In the Mewton et al. study, there were over six times as many diagnostic orphans as there were Abuse cases, affording a greater opportunity for diagnostic switches to result in new DSM-5 cases rather than new DSM-5 non-cases. In the current study the opposite was true, albeit to a lesser extent, with around 1.3 times as many Abuse cases as there were diagnostic orphans. Another explanation for the difference between the current findings and those of Mewton et al. may be the timeframe used to diagnose AUD. The Mewton et al study assessed each and every symptom criterion in the 12 months prior to interview and showed an increase in the prevalence of AUD under DSM-5 compared to DSM-IV, whereas the current study employed a lifetime timeframe and showed a slight decrease. It is notable that this pattern of findings is similar to that shown in a recent nosologic comparison of DSM-IV and DSM-5 alcohol and drug use disorders using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III (19).
The symptom profiles of the different diagnostic groups highlight the symptom criteria that are highly endorsed by those who switch diagnostic status across the diagnostic classification systems. Among new DSM-5 non-cases, the drinking in hazardous situations symptom criterion was highly endorsed. This group of diagnostic switchers, by definition, can only endorse one symptom criterion. Therefore, a significant proportion of cases previously defined as having DSM-IV Abuse solely due to the drinking in hazardous situations are now excluded from a diagnosis of AUD. This finding is consistent with previous research (12, 20). The drinking in hazardous situations symptom criterion remains a contentious criterion. While some studies have suggested that a diagnosis of AUD based solely on the drinking in hazardous situations symptom criterion is unlikely to represent a true AUD (21) other research has demonstrated that diagnoses of DSM-IV Abuse with and without this criterion do not differ substantially with regards to key psychiatric predictors and sequelae such as childhood adversities, parental psychopathology and subsequent onset of other psychiatric disorders (22). In removing the legal problems criterion and adding a craving criterion, DSM-5 construes AUD as being less characterized by continued drinking despite social consequences and more defined by dependence symptoms. This shift may reduce earlier problem recognition, diagnosis, and earlier treatment all of which are typically related to alcohol-related legal, job, and relationship problems (23, 24). In addition, workplace and legal system interventions that influence entry into treatment are more likely to be associated with the behavioral consequences of heavy drinking as opposed to the severity of dependence (25).
Drinking larger amounts, or for longer periods of time, was highly endorsed by those who converted from DSM-IV diagnostic orphan status to DSM-5 AUD. In this context, it is important to note that the larger/longer, tolerance and hazardous use criteria are prone to misinterpretation, particularly by young adults, relatively early in their drinking careers (26). As found in the current study, previous research has shown a very high endorsement of symptom criteria reflecting impaired control over alcohol use (including the larger amount/longer period criterion) (27). Inherent in the definition of both DSM-IV and DSM-5 AUD is the notion that impaired control occurs as a result of a compulsive desire to drink. When probed as to why they drink more or for longer periods than intended a substantial proportion of young adults fail to cite compulsion-based reasons, as defined in the DSM (28). Instead, young adults cite social reasons for drinking more than intended or for longer periods than intended. Given that alcohol use disorders have their peak in young adulthood it is possible that a significant proportion of the new lifetime DSM-5 AUD cases seen in the current study result from such symptom misinterpretations.
The results of Table 4 demonstrate that changing the diagnostic algorithms does not appear to have a significant impact on the clinical characteristics of the cases. In other words new non-cases were relatively similar to consistent non-cases and new cases were similar to consistent cases. The exception to this is with respect to the likelihood of meeting criteria for a drug use disorder where the odds of any drug use disorder was higher in new compared to consistent non-cases, and lower among new compared to consistent cases. Thus, the new diagnostic algorithm is failing to diagnose a sub-group with relatively high odds of any drug use disorder and, at the same time, including a sub-group of people with relatively low odds of meeting criteria for any drug use disorder. Although not fully explored in this study, the net effect of this might be to reduce the overall comorbidity between DSM-5 alcohol use disorders and drug use disorders.
A strengths of the current study include the large cross-national data set. While the prevalence of AUD according to either DSM-IV or DSM-5 differed across the nine countries included in the study, the pattern of results were largely the same. A further strength was the comprehensive, structured diagnostic assessment of both DSM-IV and DSM-5 AUD. These strengths need to be interpreted in the light of a number of limitations. The clustering criterion was not operationalized as we did not have information for all DSM-5 cases on whether the required number of symptoms occurred together in the same year. However, prior research has demonstrated that the clustering criterion may in fact increase the chances of false negative diagnoses (29). It should be noted that the current study, in essence, compared like with like by not operationalizing the clustering criterion for both the DSM-IV and the DSM-5 definition of AUD. By comparing DSM-5 diagnoses to DSM-IV diagnoses the current study makes the assumption that the DSM-IV definition of AUD is the gold standard. As noted previously, both DSM-IV and DSM-5 diagnostic definitions of AUD have been criticized for being over-inclusive (7). Our analytic approach, however, was most appropriate as we were interested not in the diagnostic validity of DSM-5 AUD per se but in the impact of changing definitions on cases defined according to the previous and current diagnostic systems.
In conclusion, the current study has shown that the prevalence of AUD in the general population decreased by a modest amount with the application of the new DSM-5 diagnostic classification system. Despite this decrease in prevalence, the clinical characteristics of those who switched diagnostic status remained largely similar to those who maintained their diagnostic status across the two classification systems.
Supplementary Material
Acknowledgments
This work is carried out in conjunction with the World Health Organization World Mental Health (WMH) Survey Initiative which is supported by the National Institute of Mental Health (NIMH; R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical, GlaxoSmithKline, and Bristol-Myers Squibb. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on data analysis. None of the funders had any role in the design, analysis, interpretation of results, or preparation of this paper. A complete list of all within-country and cross-national WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/. This work was supported by an Australian National Health and Medical Research Council (NHMRC) project grant (#1081984). LD is supported by an NHMRC Principal Research Fellowship (#1041472). The National Drug and Alcohol Research Centre at UNSW Australia is supported by funding from the Australian Government under the Substance Misuse Prevention and Service Improvements Grant Fund. The São Paulo Megacity Mental Health Survey is supported by the State of São Paulo Research Foundation (FAPESP) Thematic Project Grant 03/00204-3. The Mental Health Study Medellín – Colombia was carried out and supported jointly by the Center for Excellence on Research in Mental Health (CES University) and the Secretary of Health of Medellín. Implementation of the Iraq Mental Health Survey (IMHS) and data entry were carried out by the staff of the Iraqi MOH and MOP with direct support from the Iraqi IMHS team with funding from both the Japanese and European Funds through United Nations Development Group Iraq Trust Fund (UNDG ITF). The Northern Ireland Study of Mental Health was funded by the Health & Social Care Research & Development Division of the Public Health Agency. The Polish project Epidemiology of Mental Health and Access to Care –EZOP Poland was carried out by the Institute of Psychiatry and Neurology in Warsaw in consortium with Department of Psychiatry - Medical University in Wroclaw and National Institute of Public Health-National Institute of Hygiene in Warsaw and in partnership with Psykiatrist Institut Vinderen – Universitet, Oslo. The project was funded by the Norwegian Financial Mechanism and the European Economic Area Mechanism as well as Polish Ministry of Health. No support from pharmaceutical industry neither other commercial sources was received. The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health. The Romania WMH study projects “Policies in Mental Health Area” and “National Study regarding Mental Health and Services Use” were carried out by National School of Public Health & Health Services Management (former National Institute for Research & Development in Health, present National School of Public Health Management & Professional Development, Bucharest), with technical support of Metro Media Transilvania, the National Institute of Statistics – National Centre for Training in Statistics, SC. Cheyenne Services SRL, Statistics Netherlands and were funded by Ministry of Public Health (former Ministry of Health) with supplemental support of Eli Lilly Romania SRL. The Psychiatric Enquiry to General Population in Southeast Spain – Murcia (PEGASUS-Murcia) Project has been financed by the Regional Health Authorities of Murcia (Servicio Murciano de Salud and Consejería de Sanidad y Política Social) and Fundación para la Formación e Investigación Sanitarias (FFIS) of Murcia. The US National Comorbidity Survey Replication (NCS-R) is supported by the National Institute of Mental Health (NIMH; U01-MH60220) with supplemental support from the National Institute of Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; Grant 044708), and the John W. Alden Trust.
Footnotes
Declaration of interest:
The views and opinions expressed in this paper are those of the authors only and do not necessarily represent the views, official policy or position of the US. Department of Health and Human Services or any of its affiliated institutions or agencies. Dr. Glantz’s role on this paper is through his involvement as a Science Officer on U01-MH60220. He had no involvement in the other cited grants. In the past three years, Dr. Kessler has been a consultant for Hoffman-La Roche, Inc., Johnson & Johnson Wellness and Prevention, and Sonofi-Aventis Groupe. Dr. Kessler has served on advisory boards for Mensante Corporation, Johnson & Johnson Services Inc. Lake Nona Life Project, and U.S. Preventive Medicine. Dr. Kessler is a co-owner of DataStat, Inc. The Psychiatric Enquiry to General Population in Southeast Spain – Murcia (PEGASUS-Murcia) Project has been financed by the Regional Health Authorities of Murcia (Servicio Murciano de Salud and Consejería de Sanidad y Política Social) and Fundación para la Formación e Investigación Sanitarias (FFIS) of Murcia.
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