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Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study
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Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study Mikael Holma MD, PhD , Irina Holma MD, PhD , Erkki Isometsa¨ MD, PhD PII: DOI: Reference:
S0165-0327(19)32910-6 https://doi.org/10.1016/j.jad.2020.02.024 JAD 11655
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Journal of Affective Disorders
Received date: Revised date: Accepted date:
21 October 2019 31 January 2020 8 February 2020
Please cite this article as: Mikael Holma MD, PhD , Irina Holma MD, PhD , Erkki Isometsa¨ MD, PhD , Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study, Journal of Affective Disorders (2020), doi: https://doi.org/10.1016/j.jad.2020.02.024
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Highlights:
Psychiatric MDD patients with comorbid alcohol use disorder are more often men, inpatients, younger, smoke, have a smaller social network and perceive less social support.
They also have more often comorbid anxiety, and personality disorders, and suicidal ideation.
Prospectively they spend more time depressed, and have more suicide attempts compared to those without alcohol use disorder diagnoses.
Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study
Mikael Holma, MD, PhD (1,2) Irina Holma, MD, PhD (1, 2) Erkki Isometsä, MD, PhD (1,2)
(1) Mental Health Unit National Institute for Health and Welfare Helsinki, Finland (2) Department of Psychiatry University of Helsinki and Helsinki University Hospital, Helsinki, Finland
Correspondence: Erkki T. Isometsä, MD, PhD, Professor of Psychiatry, Department of Psychiatry, P.O. Box 22 (Välskärinkatu 12 A), 00014 University of Helsinki, Finland; Tel: +358-9-4711; Fax: +358-9-471-63735; E-mail: [email protected] Abstract Background: Comorbid alcohol use disorder (AUD) is common among patients with major depressive disorder (MDD), and often complicates presentation and treatment. However, there is a scarcity of clinical studies investigating the characteristics and outcome of psychiatric MDD patients with AUD. Methods: In the Vantaa Depression Study (VDS), a five-year prospective study of psychiatric out- and inpatients (N=269) with MDD, we investigated the clinical features of MDD, comorbid Axis I and II disorders, psychosocial factors, and long-term outcome of patients with or without AUD. Results: Depressed patients with comorbid AUD at baseline (n=66/269, 24.5%) were more often male (OR=3.57, [95% CI 1.72 – 7.41], p=0.001), had more suicidal ideation (OR=1.06 [ 1.02 – 1.11], p=0.008),
comorbid panic disorders (OR=3.44 [1.47 – 8.06], p=0.004), symptoms of any personality disorder (OR=1.04 [1.00 – 1.08], p=0.038), and more often smoked daily (OR=2.79 [1.32 – 5.88], p=0.007) than those without. At five years, 13.9% (25/180) still had AUD. More specifically, alcohol abuse was associated with suicide attempts, and dependence with suicidal ideation, and Cluster B personality disorder. Patients with AUD spent more time depressed and had more suicide attempts during follow-up. Limitations: We did not investigate other substance use disorders. The AUD diagnoses were based on DSM-IV criteria. Conclusions: Psychiatric MDD patients with comorbid alcohol use disorders have characteristics consistent with the epidemiology of AUDs in the general population. They are more often males and smoke, and have more comorbid mental disorders and suicidal behavior. Prospectively they spend more time depressed, thus having worse outcomes than patients without AUDs.
Keywords: Major depressive disorder, alcohol use disorder, comorbidity, suicide, outcome.
Introduction Major depressive disorder (MDD) and alcohol use disorders (AUDs) are both remarkable public health problems. Depression is the third leading cause of global disease burden, predicted to rank first by 2030, while alcohol is a leading risk factor causing early death and disability (Malhi and Mann, 2018; Manthey et al., 2019). Alcohol use disorders are common, and have ranged in major epidemiological studies of the general population from current prevalence of 7.0% to 21.4%, with a lifetime prevalence of 16% to 40% (Alonso et al., 2004; Grant et al., 2015; Grant and Harford, 1995; Harris et al., 2019; Kessler et al., 2005; Kessler et al., 1996; Pena et al., 2018; Pirkola et al., 2005; Regier et al., 1990; Sullivan et al., 2005). AUD among male subjects has been up to five-fold more prevalent compared to females (Pirkola et al., 2005). AUD and MDD very commonly coexist. In a large epidemiological population study, 16% of subjects
with depression had AUD, and 14% of subjects with AUD suffered from depression: the prevalences were twice as high as in the general population. Comorbid AUDs are even more common among psychiatric patients with MDD, where the current prevalence has ranged from 8.6% to 29.4%, with a lifetime prevalence of 30% to 42.8% (Abraham and Fava, 1999; Davis et al., 2006; Davis et al., 2005; Holma et al., 2008; McDermut et al., 2001; Melartin et al., 2002; Sullivan et al., 2005; Zimmerman et al., 2002). The increased co-occurrence of depression and AUD has been found consistently in general population studies. In such studies, AUDs have been associated with male gender, younger age, personality disorders, anxiety disorders, smoking, and suicidal behavior (Darvishi et al., 2015; Grant et al., 2015). It has been also associated with greater severity and worse prognosis of both disorders (McHugh and Weiss, 2019). Despite the strong epidemiological association, there are a few clinical long-term prospective studies with MDD patients from psychiatric settings. Life-chart has been seldom used (Hasin et al., 1996); psychiatric comorbidity has not been comprehensively studied together with features from other domains, and relatively few prospective clinical studies of MDD patients have investigated the longterm outcome of MDD with comorbid AUDs (Hasin et al., 1996; McHugh and Weiss, 2019). The overall effect of AUDs on the outcome of depression may not only be due to the effects of long-term alcohol misuse, but also to other adverse features likely to be prevalent in patients with AUDs. Numerous hypotheses have been proposed to explain the coexistence of MDD and AUD: common causal genetic, neurobiological, and environmental factors; separate, but associated risk factors; same disorder but two different phenotypes; and the self-medication hypothesis (Boden and Ferguson, 2011). There seems to be a dose-response relationship in that the risk of developing depression is related to the severity of alcohol use disorder (Merikangas et al., 1998; Boschloo et al., 2012). DSM-IV alcohol dependence has been associated with persistence of depressive disorders, whereas alcohol abuse has not (Boschloo et al., 2012). We have previously reported that besides comorbid AUD, MDD patients also commonly have comorbid personality and anxiety disorders, and that smoking is more prevalent among MDD patients with AUD (Holma et al., 2013; Holma et al., 2008; Melartin et al., 2002). In addition, we have investigated the longitudinal and individual-level courses of MDD, comorbid anxiety, and alcohol use disorders, and
found that the latter were dependent on the course of depressive symptoms (Melartin et al., 2013). Furthermore, suicidal ideation, suicide attempts, and shorter time to recurrence have been predicted in univariate analyses by AUD (Holma et al., 2018; Holma et al., 2008; Holma et al., 2010; Sokero et al., 2003). However, we have previously not focused our investigation on comorbid AUD. In the present prospective long-term study with MDD patients, our aim was to investigate the clinical, sociodemographic, and psychosocial differences between patients with and without comorbid AUD, and how comorbid AUD affects the outcome of depression. We hypothesized that AUD would be significantly associated with comorbid anxiety and personality disorders, longer time to recovery, recurrence of major depressive episode (MDE), longer time spent ill, suicidal ideation, and a higher risk of suicide attempts.
Methods The Vantaa Depression Study (VDS) is a collaborative depression research project of the Mood, Depression, and Suicidal Behavior Unit of the National Institute for Health and Welfare, Helsinki, Finland, and the Department of Psychiatry, Helsinki University Central Hospital, Finland. The Department of Psychiatry at Peijas Hospital provides secondary care psychiatric services to all residents of the City of Vantaa (223,027 inhabitants). The background and methodology of the VDS have been reported in detail elsewhere (Holma et al., 2008; Melartin et al., 2002). The VDS has been approved by the Helsinki and Uusimaa Hospital District Ethical Committee in Finland.
Screening and baseline evaluation In brief, in the first phase of the study, 806 psychiatric secondary care patients (aged 20-60 years) in the City of Vantaa, who had a possible new episode of DSM-IV MDD, and who were seeking treatment and referred from primary care or already receiving psychiatric care, and showing signs of an
emerging depressive episode were screened for the presence of depressive symptoms in 1997-1998. Of the 703 eligible patients, 542 (77%) agreed to the study and gave written informed consent. Patients with a clinical diagnosis of ICD-10 schizophrenia or bipolar I disorder were excluded. In the second phase, researchers interviewed these patients using the Schedule for Clinical Assessment in Neuropsychiatry (SCAN) version 2.0 (Wing et al., 1990); 269 patients were subsequently diagnosed with DSM–IV MDD (American Psychiatric Association) and included in the study. The patients who were currently abusing alcohol or other substances were interviewed after 2-3 weeks of abstinence to exclude those with substance-induced mood disorder (Melartin et al., 2002). DSM-IV Axis I diagnoses (SCAN) and Axis II diagnoses (SCID-II for DSM-III-R) were made. Data on alcohol use disorder were collected based on selfreported information, and SCAN and SCID-I interviews , at baseline and follow-up. Baseline measurements included the 17-item Hamilton Depression Rating Scale (HAM-D) (Hamilton, 1960), 21item Beck Depression Inventory (BDI) (Beck et al., 1961), Beck Anxiety Inventory (BAI) (Beck et al., 1988), Beck Hopelessness Scale (HS) (Beck et al., 1993), Scale for Suicidal Ideation (SSI) (Beck et al., 1979), Social and Occupational Functioning Assessment Scale of DSM-IV (SOFAS) (Goldman et al., 1992), Perceived Social Support Scale, Revised (PSSS-R) (Blumenthal et al., 1987), Eysenck Personality Inventory (EPI) (Eysenck and Eysenck, 1964), and Interview for Recent Life Events (IRLE) (Paykel, 1983).
Follow-up After baseline assessments, patients were interviewed at 6 and 18 months and at 5 years. Follow-up assessments comprised SCAN 2.0 and SCID-II interviews, all observer- and self-reported symptom scales, and patient record reviews to complement the interview data. SCID-I/P (First et al., 2002) was used in the 5-year follow-up. All data were used to generate graphic life charts based on DSM-IV criteria and definitions; and time after the first baseline interview was divided into periods of full remission (none of the 9 MDE criteria symptoms), partial remission (1-4 of the 9 symptoms), and MDE (5+ of the 9 symptoms) (Melartin et al., 2002).
Attrition rate and characteristics In the VDS, of the 269 MDD patients who enrolled, 229 patients participated in the 6-month, 207 patients in the 18-month, and 182 patients in the 5-year interviews. Altogether 249 patients (92.5%) participated in at least one follow-up interview. During follow-up, 29 patients´ diagnoses switched to bipolar disorder, one to schizophrenia, and two to schizoaffective disorder. These subjects stayed in the study until change of diagnosis. Compared with the participants, those who dropped out of all follow-up interviews (n=20) were younger (mean age 33.0 vs. 40.1 years, t=2.81, P=0.005), had a lower age at onset (mean age 27.1 vs. 31.8 years, t=2.22, P=0.035), more often had dysthymia (35.0% vs. 10.0%, χ2=11.0, df=1, P=0.001), panic disorder with agoraphobia (20.0% vs. 6.4%, χ2=4.96, df=1, P=0.026), less perceived social support (t=2.01, P=0.046), were more often unemployed (70.0% vs. 37.9%, χ2=7.93, df=1, P=0.005), and were less often married or cohabiting (80.0% vs. 47.4%, χ2=7.87, df=1, P=0.005) (Holma et al., 2010). They did not differ significantly in terms of having comorbid alcohol use disorder.
Statistical analysis We investigated the differences between patients with and without comorbid AUD at baseline, and the relationship of AUD with different features of psychiatric MDD patients. These comprised sociodemographic features, outpatient status, clinical features of MDD, symptom and functional ability scales, Axis I and II comorbid disorders, number of Axis III disorders, MDD subtype features, various psychosocial and personality factors, and outcome features related to length of index episode, recurrences, proportion of time spent depressed, and suicide attempts. Patients with or without comorbid AUD were compared using the chi-square statistic with Yates’ continuity correction, or Fisher’s exact test when the expected cell count was less than 5 in the 2x2 table. In comparisons of continuous variables, the two-sample t-test was used for normal distribution, and the Mann-Whitney and Kruskal-Wallis tests for non-normal distribution. Our main analyses were based on the hypotheses, but we also report descriptive comparisons. After detailed univariate analyses, we chose predictors for our final models by first considering their correspondence with the hypotheses; overlap and potential multicollinearity, clinical and
statistical validity, and statistical significance. Non-significant variables were then excluded from the analyses. In the logistic regression analyses, we analyzed the association of AUD with the chosen factors, comprising age, gender, Ham-D, comorbid Axis I disorders, personality disorders, suicidal ideation (SSI), suicide attempt prior to baseline, and proportion of time spent in MDE during follow-up. The final models included multivariate nominal regression models to investigate possible dose-response relationships, classifying alcohol use disorder as the dependent variable into three mutually exclusive categories; patients without comorbid alcohol use disorder (the reference group), patients with DSM-IV alcohol abuse, and patients with alcohol dependence. All analyses were adjusted for age, gender, and, in the case of outcome variables, also for length of follow-up (months). IBM SPSS Statistics 23 was used for these analyses (IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp.).
Results At baseline, a quarter (24.5%, 66/269) of psychiatric patients with MDD suffered from comorbid alcohol use disorder (AUD). Of these, two-fifths (42.4%, 28/66) suffered from alcohol abuse, and threefifths (57.6%, 38/66) from alcohol dependence. During follow-up, the proportion of patients with comorbid AUD diminished: at 6 months 14.2% (30/211), at 18 months 11.6% (24/207), and at 5 years 13.9% (25/180) had AUD. Of those with AUD at baseline, 60.4% (29/48) were without AUD diagnosis at 6 months, and of those without AUD at baseline, 6.7% (11/163) were diagnosed with AUD at 6 months, χ2=30.1, p<0.001. The corresponding rates from 6 to 18 months were 42.9% (12/28) vs. 4.0% (7/174), χ2=62.3, p<0.001, and from 18 months to 5 years, 58.3% (7/12) vs. 10.4% (17/144), χ2=7.1, p=0.008.
Characteristics MDD patients with comorbid AUD at baseline differed significantly from patients without AUD in
several sociodemographic, clinical, psychosocial, and outcome factors (Tables 1 and 2). Comorbid AUD was twice as prevalent among men compared to women, and patients with AUD compared to those without AUD were nearly twice as likely to be inpatients, younger, to have been younger at onset of MDD, to have a smaller social network, and to have less perceived social support. At baseline, they were also numerically but not significantly more severely depressed (Ham-D); significantly more anxious (BAI), more hopeless (HS), and had more suicidal ideation (SSI) and higher neuroticism. In addition, they were more often daily smokers, had more other comorbid Axis I disorders, nearly three times more panic disorders, more Axis II disorders, twice as likely to have Cluster A and B personality disorders, more Cluster C personality disorders , more Cluster A to C personality disorder symptoms, and nearly twice as many Axis III disorders. Furthermore, despite a non-significant rend to recovere in a shorter time to full remission, during followup they spent a mean of 5.5 months longer in major depressive episodes (MDEs). They had attempted suicide more often before baseline and did so over twice as often during follow-up.
Logistic regression models of comorbid alcohol use disorder In multivariate logistic regression analyses, comorbid AUD was significantly associated with male gender, panic disorder, number of personality disorder symptoms, daily smoking, and suicidal ideation (Table 3).
Multinomial logistic regression models of DSM-IV comorbid alcohol abuse and alcohol dependence In multivariate multinomial logistic regression analyses, comorbid alcohol abuse was significantly associated with male gender, panic disorder, and suicide attempts during follow-up, while alcohol dependence was significantly associated with male gender, panic disorder, number of personality disorder symptoms, especially with Cluster B personality disorder symptoms, daily smoking, and suicidal ideation (Table 4).
Discussion In the present prospective long-term study of psychiatric out- and inpatients (N=269) with MDD, we investigated the differences in characteristics, and the outcome of MDD patients with or without comorbid AUD. We observed several significant differences of which the most central factors associated with AUD were male gender, comorbid panic disorder, Cluster A-C personality disorders, suicidal ideation, suicide attempts, longer time spent depressed, and daily smoking. During follow-up, the proportion of comorbid AUD diminished compared to baseline. The present study was motivated by the scarcity of clinical studies investigating the characteristics and outcome of psychiatric MDD patients with AUD. It is a prospective, long-term follow-up assessment of a representative cohort of psychiatric out- and inpatients with MDD in a medium-to-large Finnish city. Two-thirds of all depressed subjects in the City of Vantaa were treated at the facilities where the study was conducted. We used life chart methodology, which enabled us to investigate the effect of variations in risk and time at risk. We investigated a broad range of factors from several domains, including sociodemographic features, clinical features of MDD, Axis I and II comorbid disorders and symptoms, suicidal behavior, and temperamental and psychosocial factors. Structured and semi-structured measures, both objective and subjective, were used. AUD diagnoses were based on structural diagnostic interviews and self-report. The attrition rate was reasonably low, as 249/269 patients (92.6%) participated in at least one follow-up interview. Laboratory results and patient records were also available. Finally, individuals who dropped out did not differ in terms of AUD comorbidity at baseline. Nevertheless, some methodological limitations exist. First, the cohort consisted of depressive psychiatric patients, mostly outpatients, all suffering from MDD at baseline, which determines the
generalizability of our findings. Second, to exclude substance-induced mood disorder, MDD patients currently abusing alcohol or other substances were interviewed after 2-3 weeks of abstinence. This might have led to an underestimation of the prevalence of AUD, and the proportion of men with borderline personality disorder might have otherwise been higher. Third, the study data was collected some years ago, as the five-year interviews ended at year 2003. However, we find it likely, that that the study characteristics and findings overall would be largely similar, if the data were collected now. Nevertheless, the prevalence of other substance use disorders would probably now be higher, and AUDs among women might be more common. Alcohol was at the time of this study the epidemiologically most important substance misused in Finland (Poikolainen, 1997). Only 4% of the patients admitted to occasional misuse of sedatives or use of illicit drugs. However, this would likely affect the prevalence of AUDs more than their risk factors, or associations within the cohort. Fourth, the life chart method was used for the investigation of symptom levels of MDD, outcome, and treatment, but not for the longitudinal variation of alcohol consumption. Fifth, information in the study was naturalistic, and we did not control for treatment. Sixth, the study diagnoses were based on DSM-IV criteria, still separating alcohol abuse from dependence contrary to DSM-5. Patients with comorbid AUD differed clearly by sociodemographic and psychosocial features from those without AUD, as they were twice as often men, inpatients, younger, had a smaller social network and less perceived social support. According to our previous findings, MDD patients with comorbid AUD perceived less social support which was associated with a less favourable outcome in terms of depression severity during follow-up (Leskela et al., 2004). Comorbid AUD was also significantly associated with other comorbid disorders, namely panic disorder, Cluster A-C personality disorders and daily smoking. To the degree investigated before, these findings are in accordance with the previous studies with MDD patients (Davis et al., 2006; Davis et al., 2005). We also explored whether there exists a dose-response relationship, and differences in the associations of comorbid DSM-IV alcohol abuse and dependence. We found that personality disorders were significantly associated with alcohol dependence, especially Cluster B personality disorder symptoms, but not with alcohol abuse. Overall, our findings pertaining to psychiatric
MDD patients also accords well with what is known of the epidemiology of alcohol use disorders from general population studies in Finland (Pirkola et al., 2005) and elsewhere (Grant et al., 2015). Our findings related to the role of AUDs as predictors for outcome of MDD were somewhat complex. Overall, patients with AUDs spent a longer (mean of 5.5 months) time depressed during followup. Longer time spent depressed has, in our previous studies, also been associated with disability pension during follow-up (Holma et al., 2012). Time spent in MDE has also been strongly associated with the risk of suicide attempts (Holma et al., 2014; Holma et al., 2010; Sokero et al., 2005). AUDs has been commonly associated with suicide attempts (Aaltonen et al., 2016; Baldessarini et al., 2019; Holma et al., 2010; Sokero et al., 2003), probably increasing the risk of impulsive acts. DSM-IV alcohol abuse was significantly associated with suicide attempts during follow-up, and dependence with suicidal ideation. AUD combined with Cluster B personality disorders is likely to increase the risk of suicide attempts. In our previous study, suicide attempts were also associated with younger age, a smaller social network, and lack of perceived social support (Holma et al., 2010), which were characteristics associated in the present study with AUD. Thus, there may also be an indirect relationship of AUD with suicide attempts due to common sociodemographic and psychosocial factors. However, contrary to our hypotheses, patients with AUD could at first recover even faster than patients without AUD. The reasons for this remain unclear, but might be due to more reactive forms of depression related to personality disorders or acute stressful life events caused by drinking, or the benefits of discontinuing drinking. According to our previous findings, depression comorbidity in general increased the risk of recurrence, and prolonged recovery from depression (Holma et al., 2008; Melartin et al., 2004). We have also found previously, that the longitudinal and individual-level courses of MDD, comorbid anxiety, and alcohol use disorders have been dependent on the course of depressive symptoms (Melartin et al., 2013). In conclusion, comorbid AUD was associated with a worse outcome in terms of longer time spent depressed and suicidal behavior. On the basis of our findings, recognizing substance use problems among depressive patients is imperative, as they are often accompanied with other comorbid disorders, more psychosocial vulnerability, health problems, and have a
negative impact on the outcome in lengthening time spent ill, and increasing the risk of suicidal behavior. Regarding treatment, an integrative approach is important instead of treating both disorders separately. In conclusion, psychiatric MDD patients with comorbid AUDs have characteristics consistent with the epidemiology of AUDs in the general population. They are more often males and smoke, and have more comorbid mental disorders and suicidal behavior. Prospectively they spend more time depressed, thus having worse outcomes than patients without AUDs.
Acknowledgements: The Vantaa Depression Study has been previously funded by the National Institute for Health and Welfare (THL), Academy of Finland and state subsidiary research grants from the Helsinki and Uusimaa Hospital District (HUS). However, this study has been conducted without external funding. Contributors: Authors Mikael Holma, Irina Holma and Erkki Isometsä designed this study. Author Mikael Holma managed the literature searches, undertook the statistical analyses, and wrote the first draft of the manuscript. Irina Holma critically commented on the manuscript. Erkki Isometsä is principal investigator of the Vantaa Depression Study and supervised this study. All authors contributed to and have approved the final manuscript.
Role of funding source:
This study was conducted without any external funding. No funding source had any role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.
Declaration of interest All authors declare no conflict of interest.
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Table 1. Baseline sociodemographic and clinical characteristics of MDD patients with or without comorbid alcohol use disorder in the Vantaa Depression Study
ALCOHOL USE DISORDER YES
NO
CHARACTERISTIC
n
%
n
%
p
Total
66
24.5
203
75.5
Female
38
19.3
159
80.7
Male
28
38.9
44
61.1
Outpatient
48
21.5
175
78.5
Inpatient
18
39.1
28
60.9
0.012
Any Axis I disorder
48
72.7
119
58.6
0.040
Dysthymic disorder
8
12.1
24
11.8
0.948
Any anxiety disorder
43
65.2
109
53.7
0.103
Phobic disorder
30
45.5
78
38.4
0.311
Panic disorder
19
28.8
26
12.8
0.003
with agoraphobia
8
12.1
12
5.9
0.095
without agoraphobia
11
16.7
14
6.9
0.018
Agoraphobia without panic symptoms
4
6.1
27
13.3
0.110
Specific phobia
18
27.3
50
24.6
0.668
Social phobia
14
21.2
39
19.2
0.723
Obsessive compulsive disorder
6
9.1
12
5.9
0.369
Generalized anxiety disorder
11
16.7
26
12.8
0.429
Any personality disorder
37
56.1
81
39.9
0.022
Cluster A personality disorder
19
28.8
32
15.8
0.019
Cluster B personality disorder
14
21.2
25
12.3
0.075
0.001
Axis I comorbidity
Axis II comorbidity
Cluster C personality disorder
29
43.9
56
27.6
0.013
Melancholic subtype
28
42.4
69
34.0
0.215
Atypical subtype
4
6.1
21
10.3
0.298
Psychotic symptoms
9
13.6
13
6.4
0.063
Daily smoking
35
64.8
59
33.3
<0.001
Suicide attempt prior to entry
31
47.0
61
30.0
0.012
Married or cohabiting
27
40.9
108
53.2
0.083
Lower income level
33
55.9
83
45.4
0.157
Employed
35
53.8
122
61.6
0.268
Vocational education
26
39.4
82
40.4
0.886
Family history of mood disorders
18
66.7
68
53.5
0.212
Family history of anxiety disorders
4
14.8
11
8.7
0.327
Family history of alcoholism
13
48.1
43
33.9
0.161
mean
SD
mean
SD
37.4
9.6
40.3
11.4
0.043
Age at onset
27.4
10.7
32.8
12.7
<0.001
No. of previous episodes
2.2
3.8
1.5
2.2
0.166
Duration of MDE prior to entry (months)
4.8
4.2
5.1
6.3
0.718
No. of suicide attempts prior to entry
1.1
2.7
0.6
1.8
0.073
17-item HAM-D
20.6
6.8
18.9
6.0
0.052
21-item BDI
28.4
8.9
27.5
8.5
0.459
BAI
26.3
11.6
21.1
10.0
<0.001
HS
11.5
4.7
9.9
4.8
0.023
Clinical and outcome features
Psychosocial and family features
Age Clinical features of MDD
Symptoms and functional ability
SSI
10.3
8.6
5.1
7.6
<0.001
SOFAS
50.0
12.8
52.4
10.1
0.157
No. of any personality disorder symptoms
16.1
8.5
10.8
8.2
<0.001
No. of Cluster A symptoms
3.7
2.6
2.2
2.4
<0.001
No. of Cluster B symptoms
4.8
3.6
3.1
3.4
<0.001
No. of Cluster C symptoms
7.6
4.5
5.5
4.3
<0.001
No. of comorbid psychiatric disorders
3.3
1.7
2.7
1.7
0.007
No. of all Axis I-III disorders
3.7
1.9
3.3
2.1
0.161
Number of current somatic disorders
0.4
0.7
0.6
1.1
0.040
Number of daily cigarettes
12.8
11.0
6.4
10.7
<0.001
6.8
3.4
7.8
3.5
0.044
35.0
11.5
40.4
12.9
0.003
9.3
4.1
8.2
4.6
0.107
18.6
3.2
17.0
4.1
0.003
10.5
4.6
9.8
4.6
0.310
Comorbidity
Psychosocial and personality factors Size of social network Perceived social support Negative life events Neuroticism
a
b
c
Extroversion
c
Statistical methods: Categorical variables: Chi-square test with Yates’ continuity correction, or Fisher’s exact test when the expected cell count was less than 5 in the 2x3 table. Continuous variables: Student's t-test for normal distribution; Mann-Whitney test for non-normal distribution. Abbreviations: MDD = Major Depressive Disorder, MDE = Major Depressive Episode, HAM-D = Hamilton Rating Scale for Depression, BDI = Beck Depression Scale, BAI = Beck Anxiety Scale, SSI = Scale for Suicide Ideation, HS = Beck Hopelessness Scale, SOFAS = Social and Occupational Functioning a b Assessment Scale. PSSS-R = Perceived Social Support Scale, Revised; Interview for Recent Life Events: objective c measure of negative impact of adverse life events; Eysenck Personality Inventory.
Table 2. Outcome characteristics of MDD patients with or without comorbid alcohol use disorder in the Vantaa Depression Study during 5-year follow-up ALCOHOL USE DISORDER
Suicide attempt during follow-up
YES (N=66/269)
NO (N=202/269)
n
%
n
%
p
15
25.0
21
11.1
0.008
mean
SD
mean
SD
p
No. of recurrences during follow-up
2.1
2.0
1.7
1.7
0.281
Time to first recurrence (months)
28.8
23.5
35.8
25.5
0.152
Duration of index episode (months)
2.5
3.4
3.5
7.6
0.359
Time to full remission (months)
11.6
16.1
17.6
19.5
0.056
Proportion of time depressed during follow-up
28.0
26.6
19.1
24.4
0.038
Proportion of time spent in partial remission during follow-up (percent) Proportion of time spent in full remission during follow-up (percent) No. of suicide attempts during follow-up (percent)
32.5
26.1
30.4
26.8
0.632
36.7
34.2
45.9
31.8
0.100
0.7
1.5
0.4
1.5
0.173
Statistical methods: Categorical variables: Chi-square test with Yates’ continuity correction, or Fisher’s exact test when the expected cell count was less than 5 in the 2x3 table. Continuous variables: Student's t-test for normal distribution; Mann-Whitney test for non-normal distribution.
Table 3. Logistic regression model of MDD patients with or without comorbid alcohol use disorder in the Vantaa Depression Study
VARIABLE
Odds ratio
95% CI
P
Male gender Panic disorder
3.91 3.52
1.83 – 8.36 1.47 – 8.40
<0.001 0.005
Number of any personality disorder symptoms Daily smoking
1.04
1.00 – 1.09 1.01 – 1.30
3.97
1.93 – 8.20
<0.001
1.06
1-02 – 1.11
0.007
Suicidal ideation
a
0.035
0.038
Multivariate logistic regression models adjusted for age. a Scale for suicidal ideation (SSI)
Table 4. Multinomial logistic regression model of MDD patients with comorbid DSM-IV alcohol abuse or dependence during 5-year follow-up of the Vantaa Depression Study None VARIABLE Male gender (male) Panic disorder Number of any personality disorder
a
Alcohol abuse
Odds ratio 1.0
Odds ratio 4.43
95% CI 1.66 – 11.9
P 0.003
Alcohol dependence Odds ratio 3.33
1.0 1.0
3.60 1.00
1.23 – 10.5 0.95 – 1.06
0.019 0.901
3.34 1.08
95% CI 1.26 – 8.82
P 0.015
1.09 – 10.3 1.03 – 1.13
0.035 0.003
symptoms Daily smoking 1.0 2.35 0.91 – 6.06 Suicidal 1.0 1.04 0.91 – 1.02 b ideation Suicide attempt 1.0 3.01 0.98 – 9.26 during follow-up Multivariate logistic regression models adjusted for age. a Reference category b Scale for suicidal ideation (SSI)
0.076 0.198
7.25 1.07
2.68 – 19.6 1.02 – 1.14
<0.001 0.010
0.050
1.91
0.45 – 8.12
0.383
Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study Mikael Holma MD, PhD , Irina Holma MD, PhD , Erkki Isometsa¨ MD, PhD PII: DOI: Reference:
S0165-0327(19)32910-6 https://doi.org/10.1016/j.jad.2020.02.024 JAD 11655
To appear in:
Journal of Affective Disorders
Received date: Revised date: Accepted date:
21 October 2019 31 January 2020 8 February 2020
Please cite this article as: Mikael Holma MD, PhD , Irina Holma MD, PhD , Erkki Isometsa¨ MD, PhD , Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study, Journal of Affective Disorders (2020), doi: https://doi.org/10.1016/j.jad.2020.02.024
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Highlights:
Psychiatric MDD patients with comorbid alcohol use disorder are more often men, inpatients, younger, smoke, have a smaller social network and perceive less social support.
They also have more often comorbid anxiety, and personality disorders, and suicidal ideation.
Prospectively they spend more time depressed, and have more suicide attempts compared to those without alcohol use disorder diagnoses.
Comorbid alcohol use disorder in psychiatric MDD patients: A five-year prospective study
Mikael Holma, MD, PhD (1,2) Irina Holma, MD, PhD (1, 2) Erkki Isometsä, MD, PhD (1,2)
(1) Mental Health Unit National Institute for Health and Welfare Helsinki, Finland (2) Department of Psychiatry University of Helsinki and Helsinki University Hospital, Helsinki, Finland
Correspondence: Erkki T. Isometsä, MD, PhD, Professor of Psychiatry, Department of Psychiatry, P.O. Box 22 (Välskärinkatu 12 A), 00014 University of Helsinki, Finland; Tel: +358-9-4711; Fax: +358-9-471-63735; E-mail: [email protected] Abstract Background: Comorbid alcohol use disorder (AUD) is common among patients with major depressive disorder (MDD), and often complicates presentation and treatment. However, there is a scarcity of clinical studies investigating the characteristics and outcome of psychiatric MDD patients with AUD. Methods: In the Vantaa Depression Study (VDS), a five-year prospective study of psychiatric out- and inpatients (N=269) with MDD, we investigated the clinical features of MDD, comorbid Axis I and II disorders, psychosocial factors, and long-term outcome of patients with or without AUD. Results: Depressed patients with comorbid AUD at baseline (n=66/269, 24.5%) were more often male (OR=3.57, [95% CI 1.72 – 7.41], p=0.001), had more suicidal ideation (OR=1.06 [ 1.02 – 1.11], p=0.008),
comorbid panic disorders (OR=3.44 [1.47 – 8.06], p=0.004), symptoms of any personality disorder (OR=1.04 [1.00 – 1.08], p=0.038), and more often smoked daily (OR=2.79 [1.32 – 5.88], p=0.007) than those without. At five years, 13.9% (25/180) still had AUD. More specifically, alcohol abuse was associated with suicide attempts, and dependence with suicidal ideation, and Cluster B personality disorder. Patients with AUD spent more time depressed and had more suicide attempts during follow-up. Limitations: We did not investigate other substance use disorders. The AUD diagnoses were based on DSM-IV criteria. Conclusions: Psychiatric MDD patients with comorbid alcohol use disorders have characteristics consistent with the epidemiology of AUDs in the general population. They are more often males and smoke, and have more comorbid mental disorders and suicidal behavior. Prospectively they spend more time depressed, thus having worse outcomes than patients without AUDs.
Keywords: Major depressive disorder, alcohol use disorder, comorbidity, suicide, outcome.
Introduction Major depressive disorder (MDD) and alcohol use disorders (AUDs) are both remarkable public health problems. Depression is the third leading cause of global disease burden, predicted to rank first by 2030, while alcohol is a leading risk factor causing early death and disability (Malhi and Mann, 2018; Manthey et al., 2019). Alcohol use disorders are common, and have ranged in major epidemiological studies of the general population from current prevalence of 7.0% to 21.4%, with a lifetime prevalence of 16% to 40% (Alonso et al., 2004; Grant et al., 2015; Grant and Harford, 1995; Harris et al., 2019; Kessler et al., 2005; Kessler et al., 1996; Pena et al., 2018; Pirkola et al., 2005; Regier et al., 1990; Sullivan et al., 2005). AUD among male subjects has been up to five-fold more prevalent compared to females (Pirkola et al., 2005). AUD and MDD very commonly coexist. In a large epidemiological population study, 16% of subjects
with depression had AUD, and 14% of subjects with AUD suffered from depression: the prevalences were twice as high as in the general population. Comorbid AUDs are even more common among psychiatric patients with MDD, where the current prevalence has ranged from 8.6% to 29.4%, with a lifetime prevalence of 30% to 42.8% (Abraham and Fava, 1999; Davis et al., 2006; Davis et al., 2005; Holma et al., 2008; McDermut et al., 2001; Melartin et al., 2002; Sullivan et al., 2005; Zimmerman et al., 2002). The increased co-occurrence of depression and AUD has been found consistently in general population studies. In such studies, AUDs have been associated with male gender, younger age, personality disorders, anxiety disorders, smoking, and suicidal behavior (Darvishi et al., 2015; Grant et al., 2015). It has been also associated with greater severity and worse prognosis of both disorders (McHugh and Weiss, 2019). Despite the strong epidemiological association, there are a few clinical long-term prospective studies with MDD patients from psychiatric settings. Life-chart has been seldom used (Hasin et al., 1996); psychiatric comorbidity has not been comprehensively studied together with features from other domains, and relatively few prospective clinical studies of MDD patients have investigated the longterm outcome of MDD with comorbid AUDs (Hasin et al., 1996; McHugh and Weiss, 2019). The overall effect of AUDs on the outcome of depression may not only be due to the effects of long-term alcohol misuse, but also to other adverse features likely to be prevalent in patients with AUDs. Numerous hypotheses have been proposed to explain the coexistence of MDD and AUD: common causal genetic, neurobiological, and environmental factors; separate, but associated risk factors; same disorder but two different phenotypes; and the self-medication hypothesis (Boden and Ferguson, 2011). There seems to be a dose-response relationship in that the risk of developing depression is related to the severity of alcohol use disorder (Merikangas et al., 1998; Boschloo et al., 2012). DSM-IV alcohol dependence has been associated with persistence of depressive disorders, whereas alcohol abuse has not (Boschloo et al., 2012). We have previously reported that besides comorbid AUD, MDD patients also commonly have comorbid personality and anxiety disorders, and that smoking is more prevalent among MDD patients with AUD (Holma et al., 2013; Holma et al., 2008; Melartin et al., 2002). In addition, we have investigated the longitudinal and individual-level courses of MDD, comorbid anxiety, and alcohol use disorders, and
found that the latter were dependent on the course of depressive symptoms (Melartin et al., 2013). Furthermore, suicidal ideation, suicide attempts, and shorter time to recurrence have been predicted in univariate analyses by AUD (Holma et al., 2018; Holma et al., 2008; Holma et al., 2010; Sokero et al., 2003). However, we have previously not focused our investigation on comorbid AUD. In the present prospective long-term study with MDD patients, our aim was to investigate the clinical, sociodemographic, and psychosocial differences between patients with and without comorbid AUD, and how comorbid AUD affects the outcome of depression. We hypothesized that AUD would be significantly associated with comorbid anxiety and personality disorders, longer time to recovery, recurrence of major depressive episode (MDE), longer time spent ill, suicidal ideation, and a higher risk of suicide attempts.
Methods The Vantaa Depression Study (VDS) is a collaborative depression research project of the Mood, Depression, and Suicidal Behavior Unit of the National Institute for Health and Welfare, Helsinki, Finland, and the Department of Psychiatry, Helsinki University Central Hospital, Finland. The Department of Psychiatry at Peijas Hospital provides secondary care psychiatric services to all residents of the City of Vantaa (223,027 inhabitants). The background and methodology of the VDS have been reported in detail elsewhere (Holma et al., 2008; Melartin et al., 2002). The VDS has been approved by the Helsinki and Uusimaa Hospital District Ethical Committee in Finland.
Screening and baseline evaluation In brief, in the first phase of the study, 806 psychiatric secondary care patients (aged 20-60 years) in the City of Vantaa, who had a possible new episode of DSM-IV MDD, and who were seeking treatment and referred from primary care or already receiving psychiatric care, and showing signs of an
emerging depressive episode were screened for the presence of depressive symptoms in 1997-1998. Of the 703 eligible patients, 542 (77%) agreed to the study and gave written informed consent. Patients with a clinical diagnosis of ICD-10 schizophrenia or bipolar I disorder were excluded. In the second phase, researchers interviewed these patients using the Schedule for Clinical Assessment in Neuropsychiatry (SCAN) version 2.0 (Wing et al., 1990); 269 patients were subsequently diagnosed with DSM–IV MDD (American Psychiatric Association) and included in the study. The patients who were currently abusing alcohol or other substances were interviewed after 2-3 weeks of abstinence to exclude those with substance-induced mood disorder (Melartin et al., 2002). DSM-IV Axis I diagnoses (SCAN) and Axis II diagnoses (SCID-II for DSM-III-R) were made. Data on alcohol use disorder were collected based on selfreported information, and SCAN and SCID-I interviews , at baseline and follow-up. Baseline measurements included the 17-item Hamilton Depression Rating Scale (HAM-D) (Hamilton, 1960), 21item Beck Depression Inventory (BDI) (Beck et al., 1961), Beck Anxiety Inventory (BAI) (Beck et al., 1988), Beck Hopelessness Scale (HS) (Beck et al., 1993), Scale for Suicidal Ideation (SSI) (Beck et al., 1979), Social and Occupational Functioning Assessment Scale of DSM-IV (SOFAS) (Goldman et al., 1992), Perceived Social Support Scale, Revised (PSSS-R) (Blumenthal et al., 1987), Eysenck Personality Inventory (EPI) (Eysenck and Eysenck, 1964), and Interview for Recent Life Events (IRLE) (Paykel, 1983).
Follow-up After baseline assessments, patients were interviewed at 6 and 18 months and at 5 years. Follow-up assessments comprised SCAN 2.0 and SCID-II interviews, all observer- and self-reported symptom scales, and patient record reviews to complement the interview data. SCID-I/P (First et al., 2002) was used in the 5-year follow-up. All data were used to generate graphic life charts based on DSM-IV criteria and definitions; and time after the first baseline interview was divided into periods of full remission (none of the 9 MDE criteria symptoms), partial remission (1-4 of the 9 symptoms), and MDE (5+ of the 9 symptoms) (Melartin et al., 2002).
Attrition rate and characteristics In the VDS, of the 269 MDD patients who enrolled, 229 patients participated in the 6-month, 207 patients in the 18-month, and 182 patients in the 5-year interviews. Altogether 249 patients (92.5%) participated in at least one follow-up interview. During follow-up, 29 patients´ diagnoses switched to bipolar disorder, one to schizophrenia, and two to schizoaffective disorder. These subjects stayed in the study until change of diagnosis. Compared with the participants, those who dropped out of all follow-up interviews (n=20) were younger (mean age 33.0 vs. 40.1 years, t=2.81, P=0.005), had a lower age at onset (mean age 27.1 vs. 31.8 years, t=2.22, P=0.035), more often had dysthymia (35.0% vs. 10.0%, χ2=11.0, df=1, P=0.001), panic disorder with agoraphobia (20.0% vs. 6.4%, χ2=4.96, df=1, P=0.026), less perceived social support (t=2.01, P=0.046), were more often unemployed (70.0% vs. 37.9%, χ2=7.93, df=1, P=0.005), and were less often married or cohabiting (80.0% vs. 47.4%, χ2=7.87, df=1, P=0.005) (Holma et al., 2010). They did not differ significantly in terms of having comorbid alcohol use disorder.
Statistical analysis We investigated the differences between patients with and without comorbid AUD at baseline, and the relationship of AUD with different features of psychiatric MDD patients. These comprised sociodemographic features, outpatient status, clinical features of MDD, symptom and functional ability scales, Axis I and II comorbid disorders, number of Axis III disorders, MDD subtype features, various psychosocial and personality factors, and outcome features related to length of index episode, recurrences, proportion of time spent depressed, and suicide attempts. Patients with or without comorbid AUD were compared using the chi-square statistic with Yates’ continuity correction, or Fisher’s exact test when the expected cell count was less than 5 in the 2x2 table. In comparisons of continuous variables, the two-sample t-test was used for normal distribution, and the Mann-Whitney and Kruskal-Wallis tests for non-normal distribution. Our main analyses were based on the hypotheses, but we also report descriptive comparisons. After detailed univariate analyses, we chose predictors for our final models by first considering their correspondence with the hypotheses; overlap and potential multicollinearity, clinical and
statistical validity, and statistical significance. Non-significant variables were then excluded from the analyses. In the logistic regression analyses, we analyzed the association of AUD with the chosen factors, comprising age, gender, Ham-D, comorbid Axis I disorders, personality disorders, suicidal ideation (SSI), suicide attempt prior to baseline, and proportion of time spent in MDE during follow-up. The final models included multivariate nominal regression models to investigate possible dose-response relationships, classifying alcohol use disorder as the dependent variable into three mutually exclusive categories; patients without comorbid alcohol use disorder (the reference group), patients with DSM-IV alcohol abuse, and patients with alcohol dependence. All analyses were adjusted for age, gender, and, in the case of outcome variables, also for length of follow-up (months). IBM SPSS Statistics 23 was used for these analyses (IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp.).
Results At baseline, a quarter (24.5%, 66/269) of psychiatric patients with MDD suffered from comorbid alcohol use disorder (AUD). Of these, two-fifths (42.4%, 28/66) suffered from alcohol abuse, and threefifths (57.6%, 38/66) from alcohol dependence. During follow-up, the proportion of patients with comorbid AUD diminished: at 6 months 14.2% (30/211), at 18 months 11.6% (24/207), and at 5 years 13.9% (25/180) had AUD. Of those with AUD at baseline, 60.4% (29/48) were without AUD diagnosis at 6 months, and of those without AUD at baseline, 6.7% (11/163) were diagnosed with AUD at 6 months, χ2=30.1, p<0.001. The corresponding rates from 6 to 18 months were 42.9% (12/28) vs. 4.0% (7/174), χ2=62.3, p<0.001, and from 18 months to 5 years, 58.3% (7/12) vs. 10.4% (17/144), χ2=7.1, p=0.008.
Characteristics MDD patients with comorbid AUD at baseline differed significantly from patients without AUD in
several sociodemographic, clinical, psychosocial, and outcome factors (Tables 1 and 2). Comorbid AUD was twice as prevalent among men compared to women, and patients with AUD compared to those without AUD were nearly twice as likely to be inpatients, younger, to have been younger at onset of MDD, to have a smaller social network, and to have less perceived social support. At baseline, they were also numerically but not significantly more severely depressed (Ham-D); significantly more anxious (BAI), more hopeless (HS), and had more suicidal ideation (SSI) and higher neuroticism. In addition, they were more often daily smokers, had more other comorbid Axis I disorders, nearly three times more panic disorders, more Axis II disorders, twice as likely to have Cluster A and B personality disorders, more Cluster C personality disorders , more Cluster A to C personality disorder symptoms, and nearly twice as many Axis III disorders. Furthermore, despite a non-significant rend to recovere in a shorter time to full remission, during followup they spent a mean of 5.5 months longer in major depressive episodes (MDEs). They had attempted suicide more often before baseline and did so over twice as often during follow-up.
Logistic regression models of comorbid alcohol use disorder In multivariate logistic regression analyses, comorbid AUD was significantly associated with male gender, panic disorder, number of personality disorder symptoms, daily smoking, and suicidal ideation (Table 3).
Multinomial logistic regression models of DSM-IV comorbid alcohol abuse and alcohol dependence In multivariate multinomial logistic regression analyses, comorbid alcohol abuse was significantly associated with male gender, panic disorder, and suicide attempts during follow-up, while alcohol dependence was significantly associated with male gender, panic disorder, number of personality disorder symptoms, especially with Cluster B personality disorder symptoms, daily smoking, and suicidal ideation (Table 4).
Discussion In the present prospective long-term study of psychiatric out- and inpatients (N=269) with MDD, we investigated the differences in characteristics, and the outcome of MDD patients with or without comorbid AUD. We observed several significant differences of which the most central factors associated with AUD were male gender, comorbid panic disorder, Cluster A-C personality disorders, suicidal ideation, suicide attempts, longer time spent depressed, and daily smoking. During follow-up, the proportion of comorbid AUD diminished compared to baseline. The present study was motivated by the scarcity of clinical studies investigating the characteristics and outcome of psychiatric MDD patients with AUD. It is a prospective, long-term follow-up assessment of a representative cohort of psychiatric out- and inpatients with MDD in a medium-to-large Finnish city. Two-thirds of all depressed subjects in the City of Vantaa were treated at the facilities where the study was conducted. We used life chart methodology, which enabled us to investigate the effect of variations in risk and time at risk. We investigated a broad range of factors from several domains, including sociodemographic features, clinical features of MDD, Axis I and II comorbid disorders and symptoms, suicidal behavior, and temperamental and psychosocial factors. Structured and semi-structured measures, both objective and subjective, were used. AUD diagnoses were based on structural diagnostic interviews and self-report. The attrition rate was reasonably low, as 249/269 patients (92.6%) participated in at least one follow-up interview. Laboratory results and patient records were also available. Finally, individuals who dropped out did not differ in terms of AUD comorbidity at baseline. Nevertheless, some methodological limitations exist. First, the cohort consisted of depressive psychiatric patients, mostly outpatients, all suffering from MDD at baseline, which determines the
generalizability of our findings. Second, to exclude substance-induced mood disorder, MDD patients currently abusing alcohol or other substances were interviewed after 2-3 weeks of abstinence. This might have led to an underestimation of the prevalence of AUD, and the proportion of men with borderline personality disorder might have otherwise been higher. Third, the study data was collected some years ago, as the five-year interviews ended at year 2003. However, we find it likely, that that the study characteristics and findings overall would be largely similar, if the data were collected now. Nevertheless, the prevalence of other substance use disorders would probably now be higher, and AUDs among women might be more common. Alcohol was at the time of this study the epidemiologically most important substance misused in Finland (Poikolainen, 1997). Only 4% of the patients admitted to occasional misuse of sedatives or use of illicit drugs. However, this would likely affect the prevalence of AUDs more than their risk factors, or associations within the cohort. Fourth, the life chart method was used for the investigation of symptom levels of MDD, outcome, and treatment, but not for the longitudinal variation of alcohol consumption. Fifth, information in the study was naturalistic, and we did not control for treatment. Sixth, the study diagnoses were based on DSM-IV criteria, still separating alcohol abuse from dependence contrary to DSM-5. Patients with comorbid AUD differed clearly by sociodemographic and psychosocial features from those without AUD, as they were twice as often men, inpatients, younger, had a smaller social network and less perceived social support. According to our previous findings, MDD patients with comorbid AUD perceived less social support which was associated with a less favourable outcome in terms of depression severity during follow-up (Leskela et al., 2004). Comorbid AUD was also significantly associated with other comorbid disorders, namely panic disorder, Cluster A-C personality disorders and daily smoking. To the degree investigated before, these findings are in accordance with the previous studies with MDD patients (Davis et al., 2006; Davis et al., 2005). We also explored whether there exists a dose-response relationship, and differences in the associations of comorbid DSM-IV alcohol abuse and dependence. We found that personality disorders were significantly associated with alcohol dependence, especially Cluster B personality disorder symptoms, but not with alcohol abuse. Overall, our findings pertaining to psychiatric
MDD patients also accords well with what is known of the epidemiology of alcohol use disorders from general population studies in Finland (Pirkola et al., 2005) and elsewhere (Grant et al., 2015). Our findings related to the role of AUDs as predictors for outcome of MDD were somewhat complex. Overall, patients with AUDs spent a longer (mean of 5.5 months) time depressed during followup. Longer time spent depressed has, in our previous studies, also been associated with disability pension during follow-up (Holma et al., 2012). Time spent in MDE has also been strongly associated with the risk of suicide attempts (Holma et al., 2014; Holma et al., 2010; Sokero et al., 2005). AUDs has been commonly associated with suicide attempts (Aaltonen et al., 2016; Baldessarini et al., 2019; Holma et al., 2010; Sokero et al., 2003), probably increasing the risk of impulsive acts. DSM-IV alcohol abuse was significantly associated with suicide attempts during follow-up, and dependence with suicidal ideation. AUD combined with Cluster B personality disorders is likely to increase the risk of suicide attempts. In our previous study, suicide attempts were also associated with younger age, a smaller social network, and lack of perceived social support (Holma et al., 2010), which were characteristics associated in the present study with AUD. Thus, there may also be an indirect relationship of AUD with suicide attempts due to common sociodemographic and psychosocial factors. However, contrary to our hypotheses, patients with AUD could at first recover even faster than patients without AUD. The reasons for this remain unclear, but might be due to more reactive forms of depression related to personality disorders or acute stressful life events caused by drinking, or the benefits of discontinuing drinking. According to our previous findings, depression comorbidity in general increased the risk of recurrence, and prolonged recovery from depression (Holma et al., 2008; Melartin et al., 2004). We have also found previously, that the longitudinal and individual-level courses of MDD, comorbid anxiety, and alcohol use disorders have been dependent on the course of depressive symptoms (Melartin et al., 2013). In conclusion, comorbid AUD was associated with a worse outcome in terms of longer time spent depressed and suicidal behavior. On the basis of our findings, recognizing substance use problems among depressive patients is imperative, as they are often accompanied with other comorbid disorders, more psychosocial vulnerability, health problems, and have a
negative impact on the outcome in lengthening time spent ill, and increasing the risk of suicidal behavior. Regarding treatment, an integrative approach is important instead of treating both disorders separately. In conclusion, psychiatric MDD patients with comorbid AUDs have characteristics consistent with the epidemiology of AUDs in the general population. They are more often males and smoke, and have more comorbid mental disorders and suicidal behavior. Prospectively they spend more time depressed, thus having worse outcomes than patients without AUDs.
Acknowledgements: The Vantaa Depression Study has been previously funded by the National Institute for Health and Welfare (THL), Academy of Finland and state subsidiary research grants from the Helsinki and Uusimaa Hospital District (HUS). However, this study has been conducted without external funding. Contributors: Authors Mikael Holma, Irina Holma and Erkki Isometsä designed this study. Author Mikael Holma managed the literature searches, undertook the statistical analyses, and wrote the first draft of the manuscript. Irina Holma critically commented on the manuscript. Erkki Isometsä is principal investigator of the Vantaa Depression Study and supervised this study. All authors contributed to and have approved the final manuscript.
Role of funding source:
This study was conducted without any external funding. No funding source had any role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.
Declaration of interest All authors declare no conflict of interest.
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Table 1. Baseline sociodemographic and clinical characteristics of MDD patients with or without comorbid alcohol use disorder in the Vantaa Depression Study
ALCOHOL USE DISORDER YES
NO
CHARACTERISTIC
n
%
n
%
p
Total
66
24.5
203
75.5
Female
38
19.3
159
80.7
Male
28
38.9
44
61.1
Outpatient
48
21.5
175
78.5
Inpatient
18
39.1
28
60.9
0.012
Any Axis I disorder
48
72.7
119
58.6
0.040
Dysthymic disorder
8
12.1
24
11.8
0.948
Any anxiety disorder
43
65.2
109
53.7
0.103
Phobic disorder
30
45.5
78
38.4
0.311
Panic disorder
19
28.8
26
12.8
0.003
with agoraphobia
8
12.1
12
5.9
0.095
without agoraphobia
11
16.7
14
6.9
0.018
Agoraphobia without panic symptoms
4
6.1
27
13.3
0.110
Specific phobia
18
27.3
50
24.6
0.668
Social phobia
14
21.2
39
19.2
0.723
Obsessive compulsive disorder
6
9.1
12
5.9
0.369
Generalized anxiety disorder
11
16.7
26
12.8
0.429
Any personality disorder
37
56.1
81
39.9
0.022
Cluster A personality disorder
19
28.8
32
15.8
0.019
Cluster B personality disorder
14
21.2
25
12.3
0.075
0.001
Axis I comorbidity
Axis II comorbidity
Cluster C personality disorder
29
43.9
56
27.6
0.013
Melancholic subtype
28
42.4
69
34.0
0.215
Atypical subtype
4
6.1
21
10.3
0.298
Psychotic symptoms
9
13.6
13
6.4
0.063
Daily smoking
35
64.8
59
33.3
<0.001
Suicide attempt prior to entry
31
47.0
61
30.0
0.012
Married or cohabiting
27
40.9
108
53.2
0.083
Lower income level
33
55.9
83
45.4
0.157
Employed
35
53.8
122
61.6
0.268
Vocational education
26
39.4
82
40.4
0.886
Family history of mood disorders
18
66.7
68
53.5
0.212
Family history of anxiety disorders
4
14.8
11
8.7
0.327
Family history of alcoholism
13
48.1
43
33.9
0.161
mean
SD
mean
SD
37.4
9.6
40.3
11.4
0.043
Age at onset
27.4
10.7
32.8
12.7
<0.001
No. of previous episodes
2.2
3.8
1.5
2.2
0.166
Duration of MDE prior to entry (months)
4.8
4.2
5.1
6.3
0.718
No. of suicide attempts prior to entry
1.1
2.7
0.6
1.8
0.073
17-item HAM-D
20.6
6.8
18.9
6.0
0.052
21-item BDI
28.4
8.9
27.5
8.5
0.459
BAI
26.3
11.6
21.1
10.0
<0.001
HS
11.5
4.7
9.9
4.8
0.023
Clinical and outcome features
Psychosocial and family features
Age Clinical features of MDD
Symptoms and functional ability
SSI
10.3
8.6
5.1
7.6
<0.001
SOFAS
50.0
12.8
52.4
10.1
0.157
No. of any personality disorder symptoms
16.1
8.5
10.8
8.2
<0.001
No. of Cluster A symptoms
3.7
2.6
2.2
2.4
<0.001
No. of Cluster B symptoms
4.8
3.6
3.1
3.4
<0.001
No. of Cluster C symptoms
7.6
4.5
5.5
4.3
<0.001
No. of comorbid psychiatric disorders
3.3
1.7
2.7
1.7
0.007
No. of all Axis I-III disorders
3.7
1.9
3.3
2.1
0.161
Number of current somatic disorders
0.4
0.7
0.6
1.1
0.040
Number of daily cigarettes
12.8
11.0
6.4
10.7
<0.001
6.8
3.4
7.8
3.5
0.044
35.0
11.5
40.4
12.9
0.003
9.3
4.1
8.2
4.6
0.107
18.6
3.2
17.0
4.1
0.003
10.5
4.6
9.8
4.6
0.310
Comorbidity
Psychosocial and personality factors Size of social network Perceived social support Negative life events Neuroticism
a
b
c
Extroversion
c
Statistical methods: Categorical variables: Chi-square test with Yates’ continuity correction, or Fisher’s exact test when the expected cell count was less than 5 in the 2x3 table. Continuous variables: Student's t-test for normal distribution; Mann-Whitney test for non-normal distribution. Abbreviations: MDD = Major Depressive Disorder, MDE = Major Depressive Episode, HAM-D = Hamilton Rating Scale for Depression, BDI = Beck Depression Scale, BAI = Beck Anxiety Scale, SSI = Scale for Suicide Ideation, HS = Beck Hopelessness Scale, SOFAS = Social and Occupational Functioning a b Assessment Scale. PSSS-R = Perceived Social Support Scale, Revised; Interview for Recent Life Events: objective c measure of negative impact of adverse life events; Eysenck Personality Inventory.
Table 2. Outcome characteristics of MDD patients with or without comorbid alcohol use disorder in the Vantaa Depression Study during 5-year follow-up ALCOHOL USE DISORDER
Suicide attempt during follow-up
YES (N=66/269)
NO (N=202/269)
n
%
n
%
p
15
25.0
21
11.1
0.008
mean
SD
mean
SD
p
No. of recurrences during follow-up
2.1
2.0
1.7
1.7
0.281
Time to first recurrence (months)
28.8
23.5
35.8
25.5
0.152
Duration of index episode (months)
2.5
3.4
3.5
7.6
0.359
Time to full remission (months)
11.6
16.1
17.6
19.5
0.056
Proportion of time depressed during follow-up
28.0
26.6
19.1
24.4
0.038
Proportion of time spent in partial remission during follow-up (percent) Proportion of time spent in full remission during follow-up (percent) No. of suicide attempts during follow-up (percent)
32.5
26.1
30.4
26.8
0.632
36.7
34.2
45.9
31.8
0.100
0.7
1.5
0.4
1.5
0.173
Statistical methods: Categorical variables: Chi-square test with Yates’ continuity correction, or Fisher’s exact test when the expected cell count was less than 5 in the 2x3 table. Continuous variables: Student's t-test for normal distribution; Mann-Whitney test for non-normal distribution.
Table 3. Logistic regression model of MDD patients with or without comorbid alcohol use disorder in the Vantaa Depression Study
VARIABLE
Odds ratio
95% CI
P
Male gender Panic disorder
3.91 3.52
1.83 – 8.36 1.47 – 8.40
<0.001 0.005
Number of any personality disorder symptoms Daily smoking
1.04
1.00 – 1.09 1.01 – 1.30
3.97
1.93 – 8.20
<0.001
1.06
1-02 – 1.11
0.007
Suicidal ideation
a
0.035
0.038
Multivariate logistic regression models adjusted for age. a Scale for suicidal ideation (SSI)
Table 4. Multinomial logistic regression model of MDD patients with comorbid DSM-IV alcohol abuse or dependence during 5-year follow-up of the Vantaa Depression Study None VARIABLE Male gender (male) Panic disorder Number of any personality disorder
a
Alcohol abuse
Odds ratio 1.0
Odds ratio 4.43
95% CI 1.66 – 11.9
P 0.003
Alcohol dependence Odds ratio 3.33
1.0 1.0
3.60 1.00
1.23 – 10.5 0.95 – 1.06
0.019 0.901
3.34 1.08
95% CI 1.26 – 8.82
P 0.015
1.09 – 10.3 1.03 – 1.13
0.035 0.003
symptoms Daily smoking 1.0 2.35 0.91 – 6.06 Suicidal 1.0 1.04 0.91 – 1.02 b ideation Suicide attempt 1.0 3.01 0.98 – 9.26 during follow-up Multivariate logistic regression models adjusted for age. a Reference category b Scale for suicidal ideation (SSI)
0.076 0.198
7.25 1.07
2.68 – 19.6 1.02 – 1.14
<0.001 0.010
0.050
1.91
0.45 – 8.12
0.383