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Smoking differently modifies suicide risk of affective disorders, substance use disorders, and social factors
Journal of Affective Disorders 112 (2009) 165 – 173 www.elsevier.com/locate/jad
Research report
Smoking differently modifies suicide risk of affective disorders, substance use disorders, and social factors Barbara Schneider a,⁎, Tilman Wetterling a,b , Klaus Georgi a , Bernadette Bartusch a , Axel Schnabel c , Maria Blettner d a
Centre of Psychiatry, Department of Psychiatry, Psychosomatics, and Psychotherapy, Johann Wolfgang Goethe-University, Frankfurt/Main, Germany b Vivantes Klinikum Hellersdorf, Department of Psychiatry, Psychotherapy and Psychosomatics, Berlin, Germany c Centre of Forensic Medicine, Johann Wolfgang Goethe-University, Frankfurt/Main, Germany d Institute for Medical Biostatistics, Epidemiology, and Informatics, Johannes Gutenberg University, Mainz, Germany Received 5 March 2008; received in revised form 23 April 2008; accepted 23 April 2008 Available online 16 June 2008
Abstract Background: Although an association between smoking and suicide has repeatedly been shown, information about a modifying influence of smoking on other risk factors for suicide is lacking. Methods: Axis I and Axis II disorders, sociodemographic factors, and tobacco use were assessed by a semi-structured interview including the Structured Clinical Interview for DSM-IV Axis I (SCID-I) and Personality Disorders (SCID-II) in 163 suicides (mean age 49.6 +/− 19.3 years; 64.4% men;) by psychological autopsy method and by personal interview in 396 living population-based control persons (mean age 51.6 +/− 17.0 years; 55.8% men). Results: Smoking status (current smokers, lifetime non-smokers, and former smokers) differently modifies the effects of psychiatric disorders and sociodemographic variables on suicide risk. Former and current smoking modified suicide risk associated with affective disorders, but only current smoking increased suicide risk for substance use disorders. Ex-smokers with affective disorders, particularly with major depression, had less increased suicide risk than current smokers and non-smokers with affective disorders. Estimated suicide risks for personality disorders and ‘no professional training’ were strongly increased by smoking. Limitations: Due to the small size of some of the subgroups, confidence intervals are wide. Therefore, precise risk estimation is not possible. Conclusions: Clinicians should interpret smoking as an indicator of increased risk of suicide for individuals with substance use disorders, personality disorders, and adverse social factors. Further studies are needed to investigate the effects of smoking cessation on suicide risk of patients with psychiatric disorders such as major depression and substance use disorders. © 2008 Elsevier B.V. All rights reserved. Keywords: Case–control studies; Mental disorders; Smoking; Suicide
⁎ Corresponding author. Centre of Psychiatry, Department of Psychiatry, Psychosomatics, and Psychotherapy, Johann Wolfgang Goethe-University Frankfurt/Main, Heinrich-Hoffmann-Str. 10, D60528 Frankfurt/Main, Germany. Tel.: +49 69 6301 4784; fax: +49 69 6301 5290. E-mail address: [email protected] (B. Schneider). 0165-0327/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jad.2008.04.018
1. Introduction A link between cigarette smoking and suicide has been reported in epidemiological studies since the 1970s. A meta-analysis (Harris and Barraclough, 1997) has
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shown significantly elevated suicide risks for smokers with higher risks for heavy smokers. More recent prospective studies have also reported a significant relationship between smoking and suicide (Angst and Clayton, 1998; Hemmingsson and Kriebel, 2003; Tanskanen et al., 2000), especially in young men (Riala et al., 2007), and a dose-dependent relationship between smoking and suicide (Davey Smith et al., 1992; Hemenway et al., 1993; Leistikow et al., 2000; Miller et al., 2000a,b; Tverdal et al., 1993) and not elevated suicide risks for former smokers contrary to current smokers (Hemenway et al., 1993; Leistikow et al., 2000; Miller et al., 2000a,b). Despite the known association between suicide risk and consumption of psychotropic substances and the recognition that cigarettes are the most common form of tobacco consumption, the relationship between cigarette smoking and suicide has only been investigated in working female nurses by one psychological autopsy study with case–control design (Hawton et al., 2002). Associations between smoking and suicide were observed in studies that controlled for potential confounders, that is, features shared by smokers and by persons who commit suicide, such as socioeconomic position, ethnicity, previous illness, age, education, race, alcohol consumption, marital status, seat belt use, level of physical exercise, and military rank (Leistikow et al., 2000; Miller et al., 2000a,b; Davey Smith et al., 2001). Hemmingsson and Kriebel (2003) found that after adjustment for other factors such as psychiatric diagnosis, parental divorce, low emotional control, medication for nervous problems, contact with police and childcare, heavy alcohol consumption, drug use, and education, smoking was not longer a risk factor for suicide. However, their analysis was possibly overadjusted (Leistikow, 2003). So, it is still discussed if the smoking–suicide relation should be considered causal, or if other risk factors for suicide, left unmeasured in many studies, might explain the smoking–suicide association. Smokers and non-smokers differ on many characteristics related to the risk of suicide. Nicotine dependence is much more prevalent among psychiatric patients than in the general population (Grant et al., 2004). Associations between tobacco smoking and schizophrenia (De Leon and Diaz, 2005) and smoking and depressive disorders (Breslau, 1995; John et al., 2004) have been shown, but not after adjustment for psychiatric comorbidity (Black et al., 1999). Coexistence between tobacco consumption and use of alcohol and other psychotropic substances (Black et al., 1999; John et al., 2003) and between smoking and certain anxiety disorders, especially panic disorder (Breslau and Klein, 1999), has been repeatedly revealed. Nicotine dependence and
smoking were associated with different personality disorders or personality characteristics like neuroticism (Grant et al., 2004; Terracciano and Costa, 2004). Increased rates of smoking uptake and reduced rates of cessation and higher rates of smokers were found in people with lower socio-economic status and in unemployed (De Vogli and Santinello, 2005; Gilman et al., 2003). Furthermore, traumatic life events were associated with smoking, independent of PTSD (Breslau et al., 2003; Hapke et al., 2005). Axis I disorders, personality disorders, and sociodemographic features are well-known risk factors for suicide (see Schneider, 2003). The first aim of the study was to describe how current, former, and lifetime nonsmoking modify the suicide risk of psychiatric axis I and axis II disorders, of social factors such as partnership, work-related factors, and life events. As sociodemographic factors, e.g. education, and life events are associated with nicotine consumption and also with suicide, we would like to assess if modification of suicide risk by smoking is different after adjustment for these variables. Hypotheses. (1) The association between psychiatric disorders, sociodemographic variables, and suicide is modified by smoking status (never smokers, former smokers, and current smokers). (2) Adjustment for social factors and life events might alter the association between suicide, smoking status and psychiatric disorders. 2. Methods 2.1. Study population All 263 suicides (mean age 50.9 +/− 19.6 years; 66.2% males) who died in the Frankfurt/Main area (864,253 inhabitants on December 31, 1999) in 1999 and 2000 were included in the study. All suicides were classified as certain suicides (ICD-10 X 60–X 84) by the Center of Forensic Medicine, which examines all deaths by unnatural or uncertain causes in this region. Twenty suicides did not have any 1st or 2nd degree relatives or other close persons; the relatives of 22 suicide victims could not be interviewed in German and/or were living outside of Germany. In 58 cases, informants of the deceased declined the participation in the study. The relatives of the resulting 163 suicides (mean age 49.8 +/ − 19.3 years; 64.4% males; men: 48.2 +/− 19.4 years; women: 48.2 +/− 19.4 years) were interviewed employing the psychological autopsy method with a semi-structured interview 8.5 +/− 6.8 [mean +/− S.D.] months after the suicide. There were no significant differences between the included and excluded suicides with respect to gender
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(χ2 = 1.44; df = 1; χ2-test; p = n. s.) and mean age (nonresponders: men: 53.3 +/− 19.5 years; t = 1.82, df = 149.9, p = n. s.; women: 57.2 +/− 15.2 years; t = 1.33, df = 68.9; p = n. s.; t-test). Key informants of the deceased were spouses (35%), adult children (20.9%), parents (17.8%), sisters and brothers (12.9%), and other relatives and friends (13.5%). In addition, out of the 685 population-based controls contacted, 396 persons (mean age 51.6 +/− 17.0 years; 55.8% males), who were comparable to the suicides regarding residential area, age, and gender, were personally interviewed. The controls were chosen by “random digit dialing”, a standard procedure for recruiting control persons. As in Germany about two thirds of all suicides are male and predominantly elderly people commit suicide, we asked in two thirds for an interview with a male control person and also in two thirds for an interview with the oldest persons in the household, selected by a random procedure. All potential informants were told that the participation was voluntary. Control persons were also asked to give their permission for repetition of the interview, for interviews by two interviewers, and for asking a close relative or friend to give an interview about the control person himself or herself. 2.2. Instruments and diagnostic procedure A semi-structured interview, a modified and translated version of the interview applied in the National Suicide Prevention Project in Finland (Henriksson et al., 1993) and the Structured Clinical Interview for DSM-IV Axis I and II (SCID-I, SCID-II, German version) were carried out with control persons and with informants about the suicide cases. The whole interview took about 3 h to complete. As recommended, SCID-II was employed after SCID-I. Dementia and other cognitive disorders were diagnosed using DSM-IValgorithm. All psychiatric diagnoses introduced in the analyses were lifetime diagnoses. We defined “heavy use of cigarettes” as smoking more than 20 cigarettes per day, an amount that would have produced symptoms of toxicity when somebody first started smoking. Former smokers had to have sustained abstinence from smoking for at least three months. The assessment of interrater reliability, test–retest reliability, and agreement between personal and informant's interview for DSM-IVaxis I and axis II diagnoses, number of smoked cigarettes, and sociodemographic features were measured using kappa statistics and were found to be good (described in detail elsewhere (Schneider et al., 2004, 2005)). Interrater and test–retest reliability for current and former nicotine consumption (kappa= 1.0,
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each) and for the number of currently smoked cigarettes (Spearman correlation coefficient = 1.0) were excellent. Agreement between subject-based and proxy-based information of current and former nicotine use (kappa= 0.943 and kappa 1.0, respectively) and number of currently smoked cigarettes (Spearman correlation coefficient = 0.962, p b 0.001) was very high. Specificity (current smoking: 97%; former smoking: 100%) and sensitivity (100%, each), positive (current smoking: 86%, former smoking: 100%) and negative predictive values (100%, each) for current and former smoking were also high. The study protocol was approved by the ethics committee of the Medical Faculty of the University of Frankfurt/Main and performed in accordance with the ethical standards laid down in the Declaration of Helsinki. Written informed consent was obtained by all interviewees after the aim of the study and all procedures had been fully explained. 2.3. Statistical analyses The statistical analyses were performed with SAS version 9.1. Logistic regression analysis (LOGISTIC procedures) was used to estimate the odds ratios (OR) and their 95% confidence intervals (95% CI) for the association between suicide and special diagnoses or sociodemographic features. The logistic regression analysis was adjusted for age group and gender. Odds ratios and confidence intervals were not calculated for variables with less than five subjects in suicides or in controls in one of the smoking subgroups. The interaction between specified variables (smoking status and diagnostic or sociodemographic characteristics) and gender was tested by comparing the likelihood value of the full model including the gender interaction with the likelihood value of the same model excluding only the gender interactions. Adjustment of odds ratios for the potential confounding effects of educational level and life events and for axis I disorders (in personality disorders) may be achieved by incorporating these variables in unconditional logistic regression analysis. Therefore, logistic regression analyses were recalculated adjusted for education and life events during the last three months. As “not regularly working” and being “not married or cohabitated” describe different characteristics of employment status and marital status, educational level was chosen as the sociodemographic variable we adjusted for. 3. Results Age and gender of the suicides and the control persons are shown in Table 1. There were no significant
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Table 1 Age at death (mean +/− SD [years]) and gender in current smokers, former smokers and lifetime non-smokers Age
Current smokers Former smokers Lifetime non-smokeras
Male gender
Suicides
Controls
Suicides
Controls
Suicides
Controls
N = 91 N = 26 N = 45
N = 122 N = 109 N = 165
43.2 +/− 15.3 60.3 +/− 21.6 56.8 +/− 20.5
45.0 +/− 14.5 57.2 +/− 14.5 52.9 +/− 18.6
69.2% 69.2% 48.9%
59.8% 66.1% 46.1%
interactions between gender and the specified variables. All suicides and controls diagnosed with substancerelated disorders fulfilled the criteria of substance use disorders. One suicide diagnosed with substance use disorder had sustained remission for the last twelve months and three control persons had former, but not current depressive episodes at the time of the interview. Table 2 shows the associations between axis I disorders, smoking status (current smokers, former smokers, and lifetime non-smokers) and suicide. In the absence of axis I disorders, suicide risk was about three to four times higher in the presence of current smoking than in the absence of current nicotine consumption (Table 2). In non-smokers, affective disorders, especially major depressive episodes, highly predicted suicide; suicide risk of non-smokers with substance use disorders was also increased, but not after adjustment for education and life events (Table 2). Former smoking without psychiatric axis I disorders was not associated with elevated suicide risk (Table 2). Ex-smokers with
axis I disorders, especially with affective disorders, had increased suicide risk (Table 2). However, the estimated risk for affective disorders — former smoking was less than for that for affective disorders — smoking or affective disorders — non-smoking (Table 2). Suicide risk was also increased for neurotic, stress-related, and somatoform disorders and for the subgroup of adjustment disorders in former smokers; following adjustment for educational level and life events, neurotic, stress-related, and somatoform disorders (and the subgroup of adjustment disorders, too) did not remain a significant risk factor for suicide (Table 2). More than additive odds ratios were found for current smoking substance use disorders (and also for substance dependence), but not for smoking and other axis I disorders (Table 2). The combination of affective disorders and never smoking during lifetime was associated with a higher increased suicide risk than for the combination of affective disorders with current smoking (Table 2).
Table 2 Associations between axis I disorders and suicide in current smokers, former smokers and lifetime non-smokers
Factors
Controls Suicides Former smokers
Former smokers
(n = 396) (n = 163) OR OR (95% CI) without with factor factor
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) without factor with factor without factor with factor
Affective disorders 10% Affective disorders‡ Major depressive disorder 6% (single episode and recurrent) Major depressive disorder (single episode and recurrent)‡ Neurotic, stress-related, and 10% somatoform disorders Neurotic, stress-related, and somatoform disorders‡ Adjustment disorders 5% Adjustment disorders‡ Substance use disorders 17% Substance use disorders‡ Substance dependence 5% Substance dependence‡
37% 28%
20%
14% 41% 29%
Smokers
1 1 1
18.6 (7.6, 46.0) 1.2 (0.6, 2.4) 18.6 (7.0, 49.5) 1.2 (0.6, 2.5) 24.5 (9.1, 65.9) 1.3 (0.7, 2.5)
4.8 (1.6, 14.1) 4.0 (2.2, 7.0) 4.4 (1.4, 13.9) 3.6 (1.9, 6.9) 4.9 (1.4, 16.7) 4.4 (2.5, 7.6)
14.4 (6.7, 30.9) 11.0 (4.8, 25.1) 19.0 (7.3, 50.0)
1
23.1 (8.0, 66.8) 1.3 (0.6, 2.7)
4.0 (1.1, 15.0) 4.0 (2.2, 7.4)
12.5 (4.6, 34.1)
1
2.4 (0.9, 6.3)
0.7 (0.3, 1.3)
3.6 (1.3, 9.7)
2.9 (1.8, 4.8)
5.0 (2.2, 11.3)
1
1.7 (0.6, 4.7)
0.7 (0.3, 1.4)
2.0 (0.6, 6.3)
2.2 (1.3, 3.8)
5.6 (2.3, 13.9)
1 1 1 1 1 1
3.1 (1.0, 9.8) 2.1 (0.6, 7.1) 2.9 (1.2, 7.1) 2.3 (0.8, 6.6) 3.9 (0.9, 17.0) 4.5 (0.8, 25.0)
0.6 0.7 0.9 0.8 – –
7.2 (2.2, 23.2) 3.1 (0.8, 11.5) 1.7 (0.6, 4.7) 1.4 (0.5, 4.3) – –
3.0 (1.9, 4.8) 2.5 (1.5, 4.1) 2.2 (1.3, 3.8) 1.7 (0.9, 3.1) 1.9 (1.1, 3.1) 1.4 (0.8, 2.5)
4.9 (1.5, 15.9) 3.9 (1.1, 13.8) 6.0 (3.3, 10.8) 5.1 (2.7, 9.8) 16.6 (7.5, 36.7) 18.0 (7.5, 43.6)
(0.3, 1.2) (0.3, 1.3) (0.5, 1.6) (0.4, 1.6)
OR: odds ratio, CI: confidence interval; OR: adjusted for age and gender; ‡ adjusted for age, gender, life events, and educational level; –: less than four subjects.
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Table 3 Associations between personality disorders and suicide in current smokers, former smokers and lifetime non-smokers Factors
Controls Suicides Non-smokers
Former smokers
Smokers
(n = 396) (n = 163) OR without OR (95% CI) factor with factor
OR (95% CI) OR (95% CI) without factor with factor
OR (95% CI) OR (95% CI) without factor with factor
1.1 1.1 0.8 0.7 0.7 0.6 1.1 1.0
3.1 2.6 3.9 3.5 2.5 2.3 3.4 3.0
Any personality disorder 26% Any personality disorder‡ Cluster A 8% Cluster A‡ Cluster B 10% Cluster B‡ Cluster C 17% Cluster C‡
70% 28% 46% 46%
1 1 1 1 1 1 1 1
8.6 (3.3, 22.1) 8.1 (3.0, 22.2) 6.1 (1.9, 19.9) 4.8 (1.4, 16.7) 6.2 (1.9, 19.9) 6.2 (1.7, 22.3) 5.8 (2.2, 15.4) 4.9 (1.7, 14.0)
(0.4, 3.4) (0.3, 3.4) (0.3, 1.8) (0.3, 1.7) (0.3, 1.6) (0.2, 1.5) (0.4, 2.6) (0.4, 2.6)
5.0 (1.8, 14.1) 3.8 (1.3, 11.4) 11.0 (2.8, 42.6) 7.3 (1.7, 30.6) 5.5 (1.7, 17.7) 4.5 (1.3, 16.1) 2.8 (1.0, 8.1) 2.2 (0.7, 6.8)
(1.3, 7.6) (1.0, 6.8) (2.1, 7.4) (1.7, 7.0) (1.3, 4.9) (1.1, 4.6) (1.7, 7.0) (1.4, 6.5)
18.1 (7.7, 42.6) 15.4 (6.2, 38.4) 8.0 (3.1, 20.9) 6.2 (2.2, 17.3) 14.8 (6.5, 33.9) 10.9 (4.5, 26.4) 13.4 (5.7, 31.1) 11.0 (4.4, 27.6)
OR: odds ratio, CI: confidence interval; OR: adjusted for age and gender; ‡ adjusted for age, gender, life events, and educational level; Cluster A includes paranoid, schizoid, and schizotypal disorders, Cluster B includes histrionic, narcissistic, borderline, and antisocial disorders, Cluster C includes avoidant, dependent, obsessive–compulsive, depressive, and passive–aggressive disorders.
Former smoking without any personality disorders did not reveal significantly increased odds ratios. Personality disorders in general as well as cluster A and cluster B personality disorders were significantly associated with increased suicide risk independently of smoking status (Table 3). Smoking with Cluster B and with Cluster C personality disorders and smoking with personality disorders in general showed more than additive odds ratios (Table 3). After adjustment for education and life events odds ratios were similar to the odds ratios before adjustment; however, following adjustment for educational level and life events, smoking without any personality disorder did not remain significantly associated with suicide. Following adjustment for educational level, life events, and axis I disorders, more than additive odds ratios were found for smoking with any personality disorders (OR = 8.8, 95% CI 3.2,
24.3), with Cluster B (OR = 6.6, 95% CI 2.5, 17.7), and with Cluster C personality disorders (OR = 5.0, 95% CI 1.8, 13.8). The relationships between sociodemographic features and suicide are presented in Table 4. Being not married, having no professional training, not regularly working, having low education, and at least one significant life event during the last three months revealed significantly elevated odds ratios, independently of smoking status (Table 4). Former smoking without life events had a significantly decreased odds ratio (Table 4). Smoking together with not being married, not having got professional training, not regularly working, being educated less than 12 years, and at least one significant life event during the last three months were significantly associated with increased suicide risk. Smoking and not regularly working or not having got professional
Table 4 Associations between sociodemographic factors and suicide in current smokers, former smokers and lifetime non-smokers Factors
Not married or cohabitating Not married or cohabitating‡ No professional training (or professional training without any examination) No professional training‡ Not regularly working Not regularly working‡ Low education (b12 years) At least one significant life event during the last three months
Controls
Suicides
Non-smokers
Former smokers
Smokers
(n = 396) (n = 163) OR OR (95% CI) without with factor factor
OR (95% CI) without factor
OR (95% CI) with factor
OR (95% CI) without factor
OR (95% CI) with factor
35%
61%
10%
29%
47%
63%
57% 35%
74% 68%
1 1 1
3.9 (1.9, 8.3) 4.0 (1.8, 8.9) 3.7 (1.6, 8.6)
1.1 (0.5, 2.6) 1.1 (0.5, 2.7) 0.8 (0.5, 1.6)
3.5 (1.4, 8.7) 3.3 (1.2, 8.8) 3.6 (1.1, 11.3)
3.7 (1.9, 7.6) 3.0 (1.4, 6.5) 2.6 (1.6, 4.4)
8.1 (4.0, 16.3) 7.1 (3.3, 15.4) 10.1 (4.7, 21.9)
1 1 1 1 1
3.4 (1.3, 9.1) 7.0 (2.9, 17.0) 8.0 (3.0, 21.2) 2.9 (1.4, 6.3) 2.7 (1.3, 5.4)
0.8 (0.4, 1.6) 2.2 (0.8, 5.8) 2.5 (0.9, 7.0) 0.5 (0.1, 1.8) 0.3 (0.1, 0.95)
3.0 (0.8, 10.5) 3.2 (1.2, 8.5) 3.2 (1.1, 9.3) 2.5 (1.1, 5.5) 4.3 (1.9, 9.4)
2.1 (1.2, 3.7) 5.3 (2.4, 11.8) 4.7 (1.9, 11.3) 3.4 (1.5, 7.4) 2.2 (1.1, 4.6)
9.2 (3.9, 21.7) 12.3 (5.4, 27.8) 11.9 (4.8, 29.1) 6.1 (3.0, 12.3) 8.8 (4.5, 17.3)
OR: odds ratio, CI: confidence interval; OR: adjusted for age and gender; ‡ adjusted for age, gender, life events, and educational level.
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training showed about tenfold increased suicide risks compared with professional training and regularly working in non-smokers (Table 4). Odds ratios for ‘no professional training’ were altered by smoking — more than multiplicatively. Following adjustment for educational level and life events, odds ratios for the combinations substance use disorders — non-smoker, smoker — no substance use disorder/dependence, smoker — neurotic disorders/ adjustment disorders (Table 2), and no professional training — ex-smoker (Table 4) did not remain significantly associated with suicide. However, the 95% confidence intervals for not adjusted and adjusted odds ratios were overlapping for all these factors. 4. Discussion 4.1. Methodological considerations In this paper, we analyzed the main and the modifying effects for the association between smoking and suicide. To our knowledge, this is the first controlled psychological autopsy study worldwide which addresses this issue. However, some methodological limitations have to be listed: (1) Our study shares the methodological limitations of all psychological autopsy studies, which include the possibility of incomplete and biased information (Beskow et al., 1990). Yet, our own results (Schneider et al., 2004) and former research (Kelly and Mann, 1996) show validity of the psychiatric diagnoses by proxy approach. (2) A design that included a second control group of deceased who died from other causes than suicide would be helpful. In such a design, it could have been examined whether nicotine use poses an even greater risk for suicide than for death due to other causes. Using a control group of living people might have overestimated the importance of psychiatric disorders as risk factors for suicide, as psychiatric disorders might also be an important risk factor for premature death from other causes than suicide. Furthermore, it is difficult and also ethically questionable to assess living controls by best-estimate method as described by Hawton et al. (1998). (3) Relatively moderate response rates could represent a certain selection of the population studied. Low response rates were also noted in several studies in Western countries (Appleby et al., 1999; Hawton et al., 2002). (4) Unfortunately, due to data protection regulations in Germany, we did not get detailed information about suicides and controls if informants declined an interview. So, we could not perform non-responder analysis in our sample for estimation of selection effects, which might bias the
results. Control persons, especially those with mental disorders, might have refused participation in the study or have concealed psychiatric disorders, which might result in underreporting psychiatric diagnoses in controls. However, we have no hints for selection bias, as prevalences of axis I disorders and also of nicotine use correspond to those of the general population in Germany (Hoch et al., 2004; Jacobi et al., 2004). (5) Due to our small sample, separate analyses for men and women could not have been carried out, although risk constellation and modification may be different for both genders. Furthermore, odds ratios were unstable with wide confidence intervals, and so precise risk estimation is limited and chance could be an alternative explanation of the observed associations. As more differentiated analyses were not possible in these small subgroups, effect modification and confounding by other, not included factors, e. g. comorbidity with other axis I disorders, cannot completely be analyzed. Moreover, odds ratios could not be calculated for disorders with a low prevalence. (6) As the relatives were not aware of symptoms or would overestimate it, exposure might be misclassified. This error may also bias the results. However, this misclassification could only explain a small part of the overall strong effect. (7) A further limitation was that we introduced only lifetime diagnoses, which are more likely to be stable, especially for substance use disorders, in the analyses. In our study, only 1-month prevalences were lower than lifetime prevalences in the control, but not in the case group. This could also lead to an underestimation of relative risks for suicide. (8) The association between smoking and suicide is complex and might reflect the effects of non-observed factors which are associated with the development of smoking or be related to the development of suicidal behaviour. Also the association between smoking and psychiatric disorders and between smoking and sociodemographic factors is complex. 4.2. Findings Our results suggest that affective disorders predicted increased suicide risk in smokers, non-smokers, and former smokers, with the highest increased risk in never smokers. Suicide risk associated with substance use disorders was highly increased by current smoking. No professional training and at least one significant life event during the last three months had a higher increased suicide risk in smokers than in never and former smokers. Smoking status differently modifies suicide risk associated with axis I disorders, axis II disorders, professional training, and significant life events during the
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last three months. Following adjustment for educational level and life events does not substantially alter the suicide risk associated with smoking status and psychiatric disorders. 4.2.1. Associations between diagnostic factors and suicide Our results reveal that smoking status might modify the estimated suicide risk associated with affective disorders, neurotic disorders, and substance-related disorders. Concordant to the literature (see Schneider, 2003), we seldom observed cognitive disorders, schizophrenia, somatoform disorders, eating disorders, and obsessive–compulsive disorders in suicides in our study. Therefore, modification of suicide risk by smoking status unfortunately could not be assessed. Although, it is well-known that smoking, especially nicotine dependent smoking, has increased odds for substance dependence (Breslau, 1995) and that smoking is associated with suicide, it is an interesting finding that current smoking highly elevated the estimated suicide risk of substance dependence. Case control studies comprising all age groups (Cheng, 1995; Foster et al., 1999; Vijayakumar and Rajkumar, 1999) and cohort studies (Harris and Barraclough, 1997; Hiroeh et al., 2001) have already reported increased suicide risks for substance use disorders and substance dependence. However, confounding or modification by smoking status was unfortunately not controlled by stratification or multivariate modeling in these studies. Independently of smoking status, affective disorders, which are well-known risk factors for suicide (Cheng, 1995; Foster et al., 1999), were associated with increased risk for suicide. Having quitted smoking or currently smoking weakened the high increase of suicide risk by affective disorders. The high suicide risk of non-smokers suffering from affective disorders might be influenced by other factors, e. g. personality characteristics. We did not find any significant interaction between gender and affective disorders and smoking status. Ex-smokers and smokers with depression might differ in severity of nicotine dependence (John et al., 2004) and/or depression, and depressed smokers might particularly seek the antidepressant effect of smoking. These antidepressant effects of tobacco may maintain smoking and two medications used to treat depression, bupropion and nortriptyline, help smokers who are trying to quit (Hughes et al., 2007). Suicide risk associated with neurotic disorders, which have not been identified as risk factors for suicide in
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mixed age and gender samples (Cheng, 1995; Foster et al., 1999; Vijayakumar and Rajkumar, 1999), was modified by smoking status with doubled suicide risk for smokers with neurotic disorders than for smokers or patients without neurotic disorders, even after adjustment for life events and educational level. Personality disorders were associated with increased suicide risk, independently of smoking status. Although our results show that suicide risk of personality disorders is highest in current smokers with personality disorders, the odds ratios for “at least one personality disorder” were in the range of the odds ratios calculated by other authors of cohort (Harris and Barraclough, 1997; Cheng et al., 1997) and case–control studies of mixed age and gender samples (Foster et al., 1999; Vijayakumar and Rajkumar, 1999; Cheng et al., 1997) using a semi-structured interview for DSM-III-R and ICD-10. The overall prevalence of personality disorders in our study was high, but in keeping with results of other studies (Cheng et al., 1997). Prevalences of personality disorders are generally higher in studies using structured interviews and operationalized diagnostic systems (Cheng et al., 1997). For Cluster B personality disorders, covering the dramatic, emotional, and erratic personality disorders, and for cluster C personality disorders, representing anxious and fearful temperament, suicide risk was highly and unambiguously increased by current smoking. Perhaps smokers have more “severe” personality disorders than current non-smokers and might try to reduce negative affects by smoking. 4.2.2. Associations between sociodemographic factors and suicide “Being single” predicted suicide. This finding is in line with results of population-based case–control studies encompassing all ages (Vijayakumar and Rajkumar, 1999; Cheng et al., 2000). Smoking modifies suicide risk associated with lack of a partnership with highest risk for unmarried/not cohabitating smokers. In keeping with the literature (Foster et al., 1999; Cheng et al., 2000) unemployment or not being in the labor force was identified as predictor for suicide, even after considering axis I disorders (Foster et al., 1999). Not being in the labor force was a risk factor for suicide independent of smoking; however, this risk was lowest for people who were not regularly working and had stopped smoking. The suicide working association might be influenced by the heterogeneity of the group of not regularly working people. This group comprises disabled persons, housewives for different reasons, and old age pensioners; therefore, it could be
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made up differently in ex-smokers, current smokers, and in never smokers. Also the group of people without completed professional training might be inhomogeneous: it might contain individuals who could not finish their professional training because of different social reasons, but also because of the manifestation of a psychiatric disorder early in life. This could explain the different modification of suicide risk for ‘professional training’ by smoking status; only for ‘no professional training’ odds ratios were clearly, i. e. more than multiplicatively, increased by current smoking. In accordance with controlled psychological autopsy studies (Foster et al., 1999; Vijayakumar and Rajkumar, 1999; Cheng et al., 2000) suicide risk was increased in persons having experienced life events during the last three months. Smoking status shows a modifying effect for suicide risk associated with life events. It is remarkable that suicide risk was about four times greater in the presence of life events in former smokers than in the absence of life events in non-smokers — although former smoking was a protective factor against suicide on the condition that no significant life event had occurred during the last three months. In conclusion, our results demonstrate that smoking status (people, who currently smoke, have never smoked, and used to smoke) modifies suicide risk of psychiatric disorders and sociodemographic variables with only marginal alterations after adjustment for educational level and life events: Suicide risk was differently modified by former and by current smoking for affective disorders and substance use disorders. Personality disorders were risk factors for suicide independent of smoking status, but with highest increased risk for smokers. The present study indicates the importance to determine whether interventions targeting smoking will have an impact on suicide risk, especially in individuals with certain psychiatric disorders. Unfortunately, a causal link or mechanisms of action between smoking and suicide have not yet been established, although a connection between seriousness of suicidal behaviour, smoking, and impaired serotonin function was observed (Malone et al., 2003). There may be major differences between smokers, exsmokers, and non-smokers, e. g. in some personality traits. Even if the association between smoking status and suicide would rather reflect background factors than direct effects of smoking, clinicians should interpret smoking as an indicator of increased risk of suicide, especially of those individuals with substance use disorders, personality disorders, and adverse social factors.
Role of funding source The funding source mentioned in the Acknowledgment had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. If the funding source(s) had no such involvement, authors should so state. Conflict of interest All authors certify that there are not any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the work submitted that could inappropriately influence, or be perceived to influence, their work.
Acknowledgement Dr. Barbara Schneider got research funding as young scientist for the project “Psychopathological, sociodemographic, psychosocial, and work-related risk factors for suicide” from the faculty representative committee of the Faculty of Medicine, Johann Wolfgang Goethe-University of Frankfurt/Main. There are no conflicts of interest. References Angst, J., Clayton, P.J., 1998. Personality, smoking and suicide: a prospective study. Journal of Affective Disorders 51, 55–62. Appleby, L., Cooper, J., Amos, T., Faragher, B., 1999. Psychological autopsy of suicides by people under 35. British Journal of Psychiatry 175, 168–174. Beskow, J., Runeson, B., Asgard, U., 1990. Psychological autopsies: methods and ethics. Suicide and Life-Threatening Behavior 20, 307–323. Black, D.W., Zimmerman, M., Coryell, W.H., 1999. Cigarette smoking and psychiatric disorder in a community sample. Annals of Clinical Psychiatry 11, 129–136. Breslau, N., 1995. Psychiatric comorbidity of smoking and nicotine dependence. Behavior Genetics 25, 95–101. Breslau, N., Klein, D.F., 1999. Smoking and panic attacks: an epidemiologic investigation. Archives of General Psychiatry 56, 1141–1147. Breslau, N., Davis, G.C., Schultz, L.R., 2003. Posttraumatic stress disorder and the incidence of nicotine, alcohol, and other drug disorders in persons who have experienced trauma. Archives of General Psychiatry 60, 289–294. Cheng, A.T.A., 1995. Mental illness and suicide. A case–control study in East Taiwan. Archives of General Psychiatry 52, 594–603. Cheng, A.T.A., Mann, A.H., Chan, K.A., 1997. Personality disorder and suicide. A case–control study. British Journal of Psychiatry 170, 441–446. Cheng, A.T.A., Chen, T.H.H., Chen, C.C., Jenkins, R., 2000. Psychosocial and psychiatric risk factors for suicide. British Journal of Psychiatry 177, 360–365. Davey Smith, G., Phillips, A.N., Neaton, J.D., 1992. Smoking as independent risk factor for suicide: illustration of an artifact from observational epidemiology? The Lancet 340, 709–712. Davey Smith, G., Phillips, A.N., Neaton, J.D., 2001. Re: “Cigarette smoking and suicide: a prospective study of 300,000 male
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John, U., Meyer, C., Rumpf, H.J., Hapke, U., 2003. Probabilities of alcohol high risk drinking, abuse or dependence estimated on grounds of tobacco smoking and nicotine dependence. Addiction 98, 805–814. John, U., Meyer, C., Rumpf, H.J., Hapke, U., 2004. Depressive disorders are related to nicotine dependence in the population but do not necessarily hamper smoking cessation. The Journal of Clinical Psychiatry 65, 169–176. Kelly, T.M., Mann, J.J., 1996. Validity of DSM-III-R diagnosis by psychological autopsy: a comparison with clinician ante-mortem diagnosis. Acta Psychiatrica Scandinavica 94, 337–343. Leistikow, B., 2003. Commentary: questionable premises, overadjustment, and a smoking/suicide association in younger adult men. International Journal of Epidemiology 32, 1005–1006. Leistikow, B.N., Martin, D.C., Samuels, S.J., 2000. Injury death excesses in smokers: a 1990–95 United States national cohort study. Injury Prevention 6, 277–280. Malone, K.M., Waternaux, C., Haas, G.L., Cooper, T.B., Li, S., Mann, J.J., 2003. Cigarette smoking, suicidal behaviour, and serotonin function in major psychiatric disorders. The American Journal of Psychiatry 160, 773–779. Miller, M., Hemenway, D., Bell, N.S., Yore, M.M., Amoroso, P.J., 2000a. Cigarette smoking and suicide: a prospective study of 300,000 male active-duty army soldiers. American Journal of Epidemiology 151, 1060–1063. Miller, M., Hemenway, D., Rimm, E., 2000b. Cigarettes and suicide: a prospective study of 50,000 men. American Journal of Public Health 90, 768–773. Riala, K., Alaräisänen, A., Taanila, A., Hakko, H., Timonen, M., Räsänen, P., 2007. Regular daily smoking among 14-year-old adolescents increases the subsequent risk for suicide: the Northern Finland 1966 Birth Cohort Study. The Journal of Clinical Psychiatry 68, 775–780. Schneider, B., 2003. Psychische Erkrankungen — Achse I-Störungen. In: Schneider, B. (Ed.), Risikofaktoren für Suizid. Roderer Verlag, Regensburg, pp. 29–67 (Psychiatric Disorders — Axis I-disorders. In: Risk factors for suicide.). Schneider, B., Maurer, K., Sargk, D., Heiskel, H., Weber, B., Frölich, L., Georgi, K., Fritze, J., Seidler, A., 2004. Concordance of DSMIV Axis I and II Diagnoses by Personal and Informant's Interview. Psychiatry Research 127, 121–136. Schneider, B., Schnabel, A., Weber, B., Frölich, L., Maurer, K., Wetterling, T., 2005. Nicotine use in suicides: a case–control study. European Psychiatry 20, 129–136. Tanskanen, A., Tuomilehto, J., Viinamaki, H., Vartiainen, E., Lehtonen, J., Puska, P., 2000. Smoking and the risk of suicide. Acta Psychiatrica Scandinavica 101, 243–245. Terracciano, A., Costa Jr., P.T., 2004. Smoking and the Five-Factor Model of personality. Addiction 99, 472–481. Tverdal, A., Thelle, D., Stensvold, J., Leren, P., Beartvett, K., 1993. Mortality in relation to smoking history: 13 years' follow-up of 680000 Norwegian men and women 35–49 years. Journal of Clinical Epidemiology 46, 475–487. Vijayakumar, L., Rajkumar, S., 1999. Are risk factors for suicide universal? A case–control study in India. Acta Psychiatrica Scandinavica 99, 407–411.
Research report
Smoking differently modifies suicide risk of affective disorders, substance use disorders, and social factors Barbara Schneider a,⁎, Tilman Wetterling a,b , Klaus Georgi a , Bernadette Bartusch a , Axel Schnabel c , Maria Blettner d a
Centre of Psychiatry, Department of Psychiatry, Psychosomatics, and Psychotherapy, Johann Wolfgang Goethe-University, Frankfurt/Main, Germany b Vivantes Klinikum Hellersdorf, Department of Psychiatry, Psychotherapy and Psychosomatics, Berlin, Germany c Centre of Forensic Medicine, Johann Wolfgang Goethe-University, Frankfurt/Main, Germany d Institute for Medical Biostatistics, Epidemiology, and Informatics, Johannes Gutenberg University, Mainz, Germany Received 5 March 2008; received in revised form 23 April 2008; accepted 23 April 2008 Available online 16 June 2008
Abstract Background: Although an association between smoking and suicide has repeatedly been shown, information about a modifying influence of smoking on other risk factors for suicide is lacking. Methods: Axis I and Axis II disorders, sociodemographic factors, and tobacco use were assessed by a semi-structured interview including the Structured Clinical Interview for DSM-IV Axis I (SCID-I) and Personality Disorders (SCID-II) in 163 suicides (mean age 49.6 +/− 19.3 years; 64.4% men;) by psychological autopsy method and by personal interview in 396 living population-based control persons (mean age 51.6 +/− 17.0 years; 55.8% men). Results: Smoking status (current smokers, lifetime non-smokers, and former smokers) differently modifies the effects of psychiatric disorders and sociodemographic variables on suicide risk. Former and current smoking modified suicide risk associated with affective disorders, but only current smoking increased suicide risk for substance use disorders. Ex-smokers with affective disorders, particularly with major depression, had less increased suicide risk than current smokers and non-smokers with affective disorders. Estimated suicide risks for personality disorders and ‘no professional training’ were strongly increased by smoking. Limitations: Due to the small size of some of the subgroups, confidence intervals are wide. Therefore, precise risk estimation is not possible. Conclusions: Clinicians should interpret smoking as an indicator of increased risk of suicide for individuals with substance use disorders, personality disorders, and adverse social factors. Further studies are needed to investigate the effects of smoking cessation on suicide risk of patients with psychiatric disorders such as major depression and substance use disorders. © 2008 Elsevier B.V. All rights reserved. Keywords: Case–control studies; Mental disorders; Smoking; Suicide
⁎ Corresponding author. Centre of Psychiatry, Department of Psychiatry, Psychosomatics, and Psychotherapy, Johann Wolfgang Goethe-University Frankfurt/Main, Heinrich-Hoffmann-Str. 10, D60528 Frankfurt/Main, Germany. Tel.: +49 69 6301 4784; fax: +49 69 6301 5290. E-mail address: [email protected] (B. Schneider). 0165-0327/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jad.2008.04.018
1. Introduction A link between cigarette smoking and suicide has been reported in epidemiological studies since the 1970s. A meta-analysis (Harris and Barraclough, 1997) has
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shown significantly elevated suicide risks for smokers with higher risks for heavy smokers. More recent prospective studies have also reported a significant relationship between smoking and suicide (Angst and Clayton, 1998; Hemmingsson and Kriebel, 2003; Tanskanen et al., 2000), especially in young men (Riala et al., 2007), and a dose-dependent relationship between smoking and suicide (Davey Smith et al., 1992; Hemenway et al., 1993; Leistikow et al., 2000; Miller et al., 2000a,b; Tverdal et al., 1993) and not elevated suicide risks for former smokers contrary to current smokers (Hemenway et al., 1993; Leistikow et al., 2000; Miller et al., 2000a,b). Despite the known association between suicide risk and consumption of psychotropic substances and the recognition that cigarettes are the most common form of tobacco consumption, the relationship between cigarette smoking and suicide has only been investigated in working female nurses by one psychological autopsy study with case–control design (Hawton et al., 2002). Associations between smoking and suicide were observed in studies that controlled for potential confounders, that is, features shared by smokers and by persons who commit suicide, such as socioeconomic position, ethnicity, previous illness, age, education, race, alcohol consumption, marital status, seat belt use, level of physical exercise, and military rank (Leistikow et al., 2000; Miller et al., 2000a,b; Davey Smith et al., 2001). Hemmingsson and Kriebel (2003) found that after adjustment for other factors such as psychiatric diagnosis, parental divorce, low emotional control, medication for nervous problems, contact with police and childcare, heavy alcohol consumption, drug use, and education, smoking was not longer a risk factor for suicide. However, their analysis was possibly overadjusted (Leistikow, 2003). So, it is still discussed if the smoking–suicide relation should be considered causal, or if other risk factors for suicide, left unmeasured in many studies, might explain the smoking–suicide association. Smokers and non-smokers differ on many characteristics related to the risk of suicide. Nicotine dependence is much more prevalent among psychiatric patients than in the general population (Grant et al., 2004). Associations between tobacco smoking and schizophrenia (De Leon and Diaz, 2005) and smoking and depressive disorders (Breslau, 1995; John et al., 2004) have been shown, but not after adjustment for psychiatric comorbidity (Black et al., 1999). Coexistence between tobacco consumption and use of alcohol and other psychotropic substances (Black et al., 1999; John et al., 2003) and between smoking and certain anxiety disorders, especially panic disorder (Breslau and Klein, 1999), has been repeatedly revealed. Nicotine dependence and
smoking were associated with different personality disorders or personality characteristics like neuroticism (Grant et al., 2004; Terracciano and Costa, 2004). Increased rates of smoking uptake and reduced rates of cessation and higher rates of smokers were found in people with lower socio-economic status and in unemployed (De Vogli and Santinello, 2005; Gilman et al., 2003). Furthermore, traumatic life events were associated with smoking, independent of PTSD (Breslau et al., 2003; Hapke et al., 2005). Axis I disorders, personality disorders, and sociodemographic features are well-known risk factors for suicide (see Schneider, 2003). The first aim of the study was to describe how current, former, and lifetime nonsmoking modify the suicide risk of psychiatric axis I and axis II disorders, of social factors such as partnership, work-related factors, and life events. As sociodemographic factors, e.g. education, and life events are associated with nicotine consumption and also with suicide, we would like to assess if modification of suicide risk by smoking is different after adjustment for these variables. Hypotheses. (1) The association between psychiatric disorders, sociodemographic variables, and suicide is modified by smoking status (never smokers, former smokers, and current smokers). (2) Adjustment for social factors and life events might alter the association between suicide, smoking status and psychiatric disorders. 2. Methods 2.1. Study population All 263 suicides (mean age 50.9 +/− 19.6 years; 66.2% males) who died in the Frankfurt/Main area (864,253 inhabitants on December 31, 1999) in 1999 and 2000 were included in the study. All suicides were classified as certain suicides (ICD-10 X 60–X 84) by the Center of Forensic Medicine, which examines all deaths by unnatural or uncertain causes in this region. Twenty suicides did not have any 1st or 2nd degree relatives or other close persons; the relatives of 22 suicide victims could not be interviewed in German and/or were living outside of Germany. In 58 cases, informants of the deceased declined the participation in the study. The relatives of the resulting 163 suicides (mean age 49.8 +/ − 19.3 years; 64.4% males; men: 48.2 +/− 19.4 years; women: 48.2 +/− 19.4 years) were interviewed employing the psychological autopsy method with a semi-structured interview 8.5 +/− 6.8 [mean +/− S.D.] months after the suicide. There were no significant differences between the included and excluded suicides with respect to gender
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(χ2 = 1.44; df = 1; χ2-test; p = n. s.) and mean age (nonresponders: men: 53.3 +/− 19.5 years; t = 1.82, df = 149.9, p = n. s.; women: 57.2 +/− 15.2 years; t = 1.33, df = 68.9; p = n. s.; t-test). Key informants of the deceased were spouses (35%), adult children (20.9%), parents (17.8%), sisters and brothers (12.9%), and other relatives and friends (13.5%). In addition, out of the 685 population-based controls contacted, 396 persons (mean age 51.6 +/− 17.0 years; 55.8% males), who were comparable to the suicides regarding residential area, age, and gender, were personally interviewed. The controls were chosen by “random digit dialing”, a standard procedure for recruiting control persons. As in Germany about two thirds of all suicides are male and predominantly elderly people commit suicide, we asked in two thirds for an interview with a male control person and also in two thirds for an interview with the oldest persons in the household, selected by a random procedure. All potential informants were told that the participation was voluntary. Control persons were also asked to give their permission for repetition of the interview, for interviews by two interviewers, and for asking a close relative or friend to give an interview about the control person himself or herself. 2.2. Instruments and diagnostic procedure A semi-structured interview, a modified and translated version of the interview applied in the National Suicide Prevention Project in Finland (Henriksson et al., 1993) and the Structured Clinical Interview for DSM-IV Axis I and II (SCID-I, SCID-II, German version) were carried out with control persons and with informants about the suicide cases. The whole interview took about 3 h to complete. As recommended, SCID-II was employed after SCID-I. Dementia and other cognitive disorders were diagnosed using DSM-IValgorithm. All psychiatric diagnoses introduced in the analyses were lifetime diagnoses. We defined “heavy use of cigarettes” as smoking more than 20 cigarettes per day, an amount that would have produced symptoms of toxicity when somebody first started smoking. Former smokers had to have sustained abstinence from smoking for at least three months. The assessment of interrater reliability, test–retest reliability, and agreement between personal and informant's interview for DSM-IVaxis I and axis II diagnoses, number of smoked cigarettes, and sociodemographic features were measured using kappa statistics and were found to be good (described in detail elsewhere (Schneider et al., 2004, 2005)). Interrater and test–retest reliability for current and former nicotine consumption (kappa= 1.0,
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each) and for the number of currently smoked cigarettes (Spearman correlation coefficient = 1.0) were excellent. Agreement between subject-based and proxy-based information of current and former nicotine use (kappa= 0.943 and kappa 1.0, respectively) and number of currently smoked cigarettes (Spearman correlation coefficient = 0.962, p b 0.001) was very high. Specificity (current smoking: 97%; former smoking: 100%) and sensitivity (100%, each), positive (current smoking: 86%, former smoking: 100%) and negative predictive values (100%, each) for current and former smoking were also high. The study protocol was approved by the ethics committee of the Medical Faculty of the University of Frankfurt/Main and performed in accordance with the ethical standards laid down in the Declaration of Helsinki. Written informed consent was obtained by all interviewees after the aim of the study and all procedures had been fully explained. 2.3. Statistical analyses The statistical analyses were performed with SAS version 9.1. Logistic regression analysis (LOGISTIC procedures) was used to estimate the odds ratios (OR) and their 95% confidence intervals (95% CI) for the association between suicide and special diagnoses or sociodemographic features. The logistic regression analysis was adjusted for age group and gender. Odds ratios and confidence intervals were not calculated for variables with less than five subjects in suicides or in controls in one of the smoking subgroups. The interaction between specified variables (smoking status and diagnostic or sociodemographic characteristics) and gender was tested by comparing the likelihood value of the full model including the gender interaction with the likelihood value of the same model excluding only the gender interactions. Adjustment of odds ratios for the potential confounding effects of educational level and life events and for axis I disorders (in personality disorders) may be achieved by incorporating these variables in unconditional logistic regression analysis. Therefore, logistic regression analyses were recalculated adjusted for education and life events during the last three months. As “not regularly working” and being “not married or cohabitated” describe different characteristics of employment status and marital status, educational level was chosen as the sociodemographic variable we adjusted for. 3. Results Age and gender of the suicides and the control persons are shown in Table 1. There were no significant
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Table 1 Age at death (mean +/− SD [years]) and gender in current smokers, former smokers and lifetime non-smokers Age
Current smokers Former smokers Lifetime non-smokeras
Male gender
Suicides
Controls
Suicides
Controls
Suicides
Controls
N = 91 N = 26 N = 45
N = 122 N = 109 N = 165
43.2 +/− 15.3 60.3 +/− 21.6 56.8 +/− 20.5
45.0 +/− 14.5 57.2 +/− 14.5 52.9 +/− 18.6
69.2% 69.2% 48.9%
59.8% 66.1% 46.1%
interactions between gender and the specified variables. All suicides and controls diagnosed with substancerelated disorders fulfilled the criteria of substance use disorders. One suicide diagnosed with substance use disorder had sustained remission for the last twelve months and three control persons had former, but not current depressive episodes at the time of the interview. Table 2 shows the associations between axis I disorders, smoking status (current smokers, former smokers, and lifetime non-smokers) and suicide. In the absence of axis I disorders, suicide risk was about three to four times higher in the presence of current smoking than in the absence of current nicotine consumption (Table 2). In non-smokers, affective disorders, especially major depressive episodes, highly predicted suicide; suicide risk of non-smokers with substance use disorders was also increased, but not after adjustment for education and life events (Table 2). Former smoking without psychiatric axis I disorders was not associated with elevated suicide risk (Table 2). Ex-smokers with
axis I disorders, especially with affective disorders, had increased suicide risk (Table 2). However, the estimated risk for affective disorders — former smoking was less than for that for affective disorders — smoking or affective disorders — non-smoking (Table 2). Suicide risk was also increased for neurotic, stress-related, and somatoform disorders and for the subgroup of adjustment disorders in former smokers; following adjustment for educational level and life events, neurotic, stress-related, and somatoform disorders (and the subgroup of adjustment disorders, too) did not remain a significant risk factor for suicide (Table 2). More than additive odds ratios were found for current smoking substance use disorders (and also for substance dependence), but not for smoking and other axis I disorders (Table 2). The combination of affective disorders and never smoking during lifetime was associated with a higher increased suicide risk than for the combination of affective disorders with current smoking (Table 2).
Table 2 Associations between axis I disorders and suicide in current smokers, former smokers and lifetime non-smokers
Factors
Controls Suicides Former smokers
Former smokers
(n = 396) (n = 163) OR OR (95% CI) without with factor factor
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) without factor with factor without factor with factor
Affective disorders 10% Affective disorders‡ Major depressive disorder 6% (single episode and recurrent) Major depressive disorder (single episode and recurrent)‡ Neurotic, stress-related, and 10% somatoform disorders Neurotic, stress-related, and somatoform disorders‡ Adjustment disorders 5% Adjustment disorders‡ Substance use disorders 17% Substance use disorders‡ Substance dependence 5% Substance dependence‡
37% 28%
20%
14% 41% 29%
Smokers
1 1 1
18.6 (7.6, 46.0) 1.2 (0.6, 2.4) 18.6 (7.0, 49.5) 1.2 (0.6, 2.5) 24.5 (9.1, 65.9) 1.3 (0.7, 2.5)
4.8 (1.6, 14.1) 4.0 (2.2, 7.0) 4.4 (1.4, 13.9) 3.6 (1.9, 6.9) 4.9 (1.4, 16.7) 4.4 (2.5, 7.6)
14.4 (6.7, 30.9) 11.0 (4.8, 25.1) 19.0 (7.3, 50.0)
1
23.1 (8.0, 66.8) 1.3 (0.6, 2.7)
4.0 (1.1, 15.0) 4.0 (2.2, 7.4)
12.5 (4.6, 34.1)
1
2.4 (0.9, 6.3)
0.7 (0.3, 1.3)
3.6 (1.3, 9.7)
2.9 (1.8, 4.8)
5.0 (2.2, 11.3)
1
1.7 (0.6, 4.7)
0.7 (0.3, 1.4)
2.0 (0.6, 6.3)
2.2 (1.3, 3.8)
5.6 (2.3, 13.9)
1 1 1 1 1 1
3.1 (1.0, 9.8) 2.1 (0.6, 7.1) 2.9 (1.2, 7.1) 2.3 (0.8, 6.6) 3.9 (0.9, 17.0) 4.5 (0.8, 25.0)
0.6 0.7 0.9 0.8 – –
7.2 (2.2, 23.2) 3.1 (0.8, 11.5) 1.7 (0.6, 4.7) 1.4 (0.5, 4.3) – –
3.0 (1.9, 4.8) 2.5 (1.5, 4.1) 2.2 (1.3, 3.8) 1.7 (0.9, 3.1) 1.9 (1.1, 3.1) 1.4 (0.8, 2.5)
4.9 (1.5, 15.9) 3.9 (1.1, 13.8) 6.0 (3.3, 10.8) 5.1 (2.7, 9.8) 16.6 (7.5, 36.7) 18.0 (7.5, 43.6)
(0.3, 1.2) (0.3, 1.3) (0.5, 1.6) (0.4, 1.6)
OR: odds ratio, CI: confidence interval; OR: adjusted for age and gender; ‡ adjusted for age, gender, life events, and educational level; –: less than four subjects.
B. Schneider et al. / Journal of Affective Disorders 112 (2009) 165–173
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Table 3 Associations between personality disorders and suicide in current smokers, former smokers and lifetime non-smokers Factors
Controls Suicides Non-smokers
Former smokers
Smokers
(n = 396) (n = 163) OR without OR (95% CI) factor with factor
OR (95% CI) OR (95% CI) without factor with factor
OR (95% CI) OR (95% CI) without factor with factor
1.1 1.1 0.8 0.7 0.7 0.6 1.1 1.0
3.1 2.6 3.9 3.5 2.5 2.3 3.4 3.0
Any personality disorder 26% Any personality disorder‡ Cluster A 8% Cluster A‡ Cluster B 10% Cluster B‡ Cluster C 17% Cluster C‡
70% 28% 46% 46%
1 1 1 1 1 1 1 1
8.6 (3.3, 22.1) 8.1 (3.0, 22.2) 6.1 (1.9, 19.9) 4.8 (1.4, 16.7) 6.2 (1.9, 19.9) 6.2 (1.7, 22.3) 5.8 (2.2, 15.4) 4.9 (1.7, 14.0)
(0.4, 3.4) (0.3, 3.4) (0.3, 1.8) (0.3, 1.7) (0.3, 1.6) (0.2, 1.5) (0.4, 2.6) (0.4, 2.6)
5.0 (1.8, 14.1) 3.8 (1.3, 11.4) 11.0 (2.8, 42.6) 7.3 (1.7, 30.6) 5.5 (1.7, 17.7) 4.5 (1.3, 16.1) 2.8 (1.0, 8.1) 2.2 (0.7, 6.8)
(1.3, 7.6) (1.0, 6.8) (2.1, 7.4) (1.7, 7.0) (1.3, 4.9) (1.1, 4.6) (1.7, 7.0) (1.4, 6.5)
18.1 (7.7, 42.6) 15.4 (6.2, 38.4) 8.0 (3.1, 20.9) 6.2 (2.2, 17.3) 14.8 (6.5, 33.9) 10.9 (4.5, 26.4) 13.4 (5.7, 31.1) 11.0 (4.4, 27.6)
OR: odds ratio, CI: confidence interval; OR: adjusted for age and gender; ‡ adjusted for age, gender, life events, and educational level; Cluster A includes paranoid, schizoid, and schizotypal disorders, Cluster B includes histrionic, narcissistic, borderline, and antisocial disorders, Cluster C includes avoidant, dependent, obsessive–compulsive, depressive, and passive–aggressive disorders.
Former smoking without any personality disorders did not reveal significantly increased odds ratios. Personality disorders in general as well as cluster A and cluster B personality disorders were significantly associated with increased suicide risk independently of smoking status (Table 3). Smoking with Cluster B and with Cluster C personality disorders and smoking with personality disorders in general showed more than additive odds ratios (Table 3). After adjustment for education and life events odds ratios were similar to the odds ratios before adjustment; however, following adjustment for educational level and life events, smoking without any personality disorder did not remain significantly associated with suicide. Following adjustment for educational level, life events, and axis I disorders, more than additive odds ratios were found for smoking with any personality disorders (OR = 8.8, 95% CI 3.2,
24.3), with Cluster B (OR = 6.6, 95% CI 2.5, 17.7), and with Cluster C personality disorders (OR = 5.0, 95% CI 1.8, 13.8). The relationships between sociodemographic features and suicide are presented in Table 4. Being not married, having no professional training, not regularly working, having low education, and at least one significant life event during the last three months revealed significantly elevated odds ratios, independently of smoking status (Table 4). Former smoking without life events had a significantly decreased odds ratio (Table 4). Smoking together with not being married, not having got professional training, not regularly working, being educated less than 12 years, and at least one significant life event during the last three months were significantly associated with increased suicide risk. Smoking and not regularly working or not having got professional
Table 4 Associations between sociodemographic factors and suicide in current smokers, former smokers and lifetime non-smokers Factors
Not married or cohabitating Not married or cohabitating‡ No professional training (or professional training without any examination) No professional training‡ Not regularly working Not regularly working‡ Low education (b12 years) At least one significant life event during the last three months
Controls
Suicides
Non-smokers
Former smokers
Smokers
(n = 396) (n = 163) OR OR (95% CI) without with factor factor
OR (95% CI) without factor
OR (95% CI) with factor
OR (95% CI) without factor
OR (95% CI) with factor
35%
61%
10%
29%
47%
63%
57% 35%
74% 68%
1 1 1
3.9 (1.9, 8.3) 4.0 (1.8, 8.9) 3.7 (1.6, 8.6)
1.1 (0.5, 2.6) 1.1 (0.5, 2.7) 0.8 (0.5, 1.6)
3.5 (1.4, 8.7) 3.3 (1.2, 8.8) 3.6 (1.1, 11.3)
3.7 (1.9, 7.6) 3.0 (1.4, 6.5) 2.6 (1.6, 4.4)
8.1 (4.0, 16.3) 7.1 (3.3, 15.4) 10.1 (4.7, 21.9)
1 1 1 1 1
3.4 (1.3, 9.1) 7.0 (2.9, 17.0) 8.0 (3.0, 21.2) 2.9 (1.4, 6.3) 2.7 (1.3, 5.4)
0.8 (0.4, 1.6) 2.2 (0.8, 5.8) 2.5 (0.9, 7.0) 0.5 (0.1, 1.8) 0.3 (0.1, 0.95)
3.0 (0.8, 10.5) 3.2 (1.2, 8.5) 3.2 (1.1, 9.3) 2.5 (1.1, 5.5) 4.3 (1.9, 9.4)
2.1 (1.2, 3.7) 5.3 (2.4, 11.8) 4.7 (1.9, 11.3) 3.4 (1.5, 7.4) 2.2 (1.1, 4.6)
9.2 (3.9, 21.7) 12.3 (5.4, 27.8) 11.9 (4.8, 29.1) 6.1 (3.0, 12.3) 8.8 (4.5, 17.3)
OR: odds ratio, CI: confidence interval; OR: adjusted for age and gender; ‡ adjusted for age, gender, life events, and educational level.
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training showed about tenfold increased suicide risks compared with professional training and regularly working in non-smokers (Table 4). Odds ratios for ‘no professional training’ were altered by smoking — more than multiplicatively. Following adjustment for educational level and life events, odds ratios for the combinations substance use disorders — non-smoker, smoker — no substance use disorder/dependence, smoker — neurotic disorders/ adjustment disorders (Table 2), and no professional training — ex-smoker (Table 4) did not remain significantly associated with suicide. However, the 95% confidence intervals for not adjusted and adjusted odds ratios were overlapping for all these factors. 4. Discussion 4.1. Methodological considerations In this paper, we analyzed the main and the modifying effects for the association between smoking and suicide. To our knowledge, this is the first controlled psychological autopsy study worldwide which addresses this issue. However, some methodological limitations have to be listed: (1) Our study shares the methodological limitations of all psychological autopsy studies, which include the possibility of incomplete and biased information (Beskow et al., 1990). Yet, our own results (Schneider et al., 2004) and former research (Kelly and Mann, 1996) show validity of the psychiatric diagnoses by proxy approach. (2) A design that included a second control group of deceased who died from other causes than suicide would be helpful. In such a design, it could have been examined whether nicotine use poses an even greater risk for suicide than for death due to other causes. Using a control group of living people might have overestimated the importance of psychiatric disorders as risk factors for suicide, as psychiatric disorders might also be an important risk factor for premature death from other causes than suicide. Furthermore, it is difficult and also ethically questionable to assess living controls by best-estimate method as described by Hawton et al. (1998). (3) Relatively moderate response rates could represent a certain selection of the population studied. Low response rates were also noted in several studies in Western countries (Appleby et al., 1999; Hawton et al., 2002). (4) Unfortunately, due to data protection regulations in Germany, we did not get detailed information about suicides and controls if informants declined an interview. So, we could not perform non-responder analysis in our sample for estimation of selection effects, which might bias the
results. Control persons, especially those with mental disorders, might have refused participation in the study or have concealed psychiatric disorders, which might result in underreporting psychiatric diagnoses in controls. However, we have no hints for selection bias, as prevalences of axis I disorders and also of nicotine use correspond to those of the general population in Germany (Hoch et al., 2004; Jacobi et al., 2004). (5) Due to our small sample, separate analyses for men and women could not have been carried out, although risk constellation and modification may be different for both genders. Furthermore, odds ratios were unstable with wide confidence intervals, and so precise risk estimation is limited and chance could be an alternative explanation of the observed associations. As more differentiated analyses were not possible in these small subgroups, effect modification and confounding by other, not included factors, e. g. comorbidity with other axis I disorders, cannot completely be analyzed. Moreover, odds ratios could not be calculated for disorders with a low prevalence. (6) As the relatives were not aware of symptoms or would overestimate it, exposure might be misclassified. This error may also bias the results. However, this misclassification could only explain a small part of the overall strong effect. (7) A further limitation was that we introduced only lifetime diagnoses, which are more likely to be stable, especially for substance use disorders, in the analyses. In our study, only 1-month prevalences were lower than lifetime prevalences in the control, but not in the case group. This could also lead to an underestimation of relative risks for suicide. (8) The association between smoking and suicide is complex and might reflect the effects of non-observed factors which are associated with the development of smoking or be related to the development of suicidal behaviour. Also the association between smoking and psychiatric disorders and between smoking and sociodemographic factors is complex. 4.2. Findings Our results suggest that affective disorders predicted increased suicide risk in smokers, non-smokers, and former smokers, with the highest increased risk in never smokers. Suicide risk associated with substance use disorders was highly increased by current smoking. No professional training and at least one significant life event during the last three months had a higher increased suicide risk in smokers than in never and former smokers. Smoking status differently modifies suicide risk associated with axis I disorders, axis II disorders, professional training, and significant life events during the
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last three months. Following adjustment for educational level and life events does not substantially alter the suicide risk associated with smoking status and psychiatric disorders. 4.2.1. Associations between diagnostic factors and suicide Our results reveal that smoking status might modify the estimated suicide risk associated with affective disorders, neurotic disorders, and substance-related disorders. Concordant to the literature (see Schneider, 2003), we seldom observed cognitive disorders, schizophrenia, somatoform disorders, eating disorders, and obsessive–compulsive disorders in suicides in our study. Therefore, modification of suicide risk by smoking status unfortunately could not be assessed. Although, it is well-known that smoking, especially nicotine dependent smoking, has increased odds for substance dependence (Breslau, 1995) and that smoking is associated with suicide, it is an interesting finding that current smoking highly elevated the estimated suicide risk of substance dependence. Case control studies comprising all age groups (Cheng, 1995; Foster et al., 1999; Vijayakumar and Rajkumar, 1999) and cohort studies (Harris and Barraclough, 1997; Hiroeh et al., 2001) have already reported increased suicide risks for substance use disorders and substance dependence. However, confounding or modification by smoking status was unfortunately not controlled by stratification or multivariate modeling in these studies. Independently of smoking status, affective disorders, which are well-known risk factors for suicide (Cheng, 1995; Foster et al., 1999), were associated with increased risk for suicide. Having quitted smoking or currently smoking weakened the high increase of suicide risk by affective disorders. The high suicide risk of non-smokers suffering from affective disorders might be influenced by other factors, e. g. personality characteristics. We did not find any significant interaction between gender and affective disorders and smoking status. Ex-smokers and smokers with depression might differ in severity of nicotine dependence (John et al., 2004) and/or depression, and depressed smokers might particularly seek the antidepressant effect of smoking. These antidepressant effects of tobacco may maintain smoking and two medications used to treat depression, bupropion and nortriptyline, help smokers who are trying to quit (Hughes et al., 2007). Suicide risk associated with neurotic disorders, which have not been identified as risk factors for suicide in
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mixed age and gender samples (Cheng, 1995; Foster et al., 1999; Vijayakumar and Rajkumar, 1999), was modified by smoking status with doubled suicide risk for smokers with neurotic disorders than for smokers or patients without neurotic disorders, even after adjustment for life events and educational level. Personality disorders were associated with increased suicide risk, independently of smoking status. Although our results show that suicide risk of personality disorders is highest in current smokers with personality disorders, the odds ratios for “at least one personality disorder” were in the range of the odds ratios calculated by other authors of cohort (Harris and Barraclough, 1997; Cheng et al., 1997) and case–control studies of mixed age and gender samples (Foster et al., 1999; Vijayakumar and Rajkumar, 1999; Cheng et al., 1997) using a semi-structured interview for DSM-III-R and ICD-10. The overall prevalence of personality disorders in our study was high, but in keeping with results of other studies (Cheng et al., 1997). Prevalences of personality disorders are generally higher in studies using structured interviews and operationalized diagnostic systems (Cheng et al., 1997). For Cluster B personality disorders, covering the dramatic, emotional, and erratic personality disorders, and for cluster C personality disorders, representing anxious and fearful temperament, suicide risk was highly and unambiguously increased by current smoking. Perhaps smokers have more “severe” personality disorders than current non-smokers and might try to reduce negative affects by smoking. 4.2.2. Associations between sociodemographic factors and suicide “Being single” predicted suicide. This finding is in line with results of population-based case–control studies encompassing all ages (Vijayakumar and Rajkumar, 1999; Cheng et al., 2000). Smoking modifies suicide risk associated with lack of a partnership with highest risk for unmarried/not cohabitating smokers. In keeping with the literature (Foster et al., 1999; Cheng et al., 2000) unemployment or not being in the labor force was identified as predictor for suicide, even after considering axis I disorders (Foster et al., 1999). Not being in the labor force was a risk factor for suicide independent of smoking; however, this risk was lowest for people who were not regularly working and had stopped smoking. The suicide working association might be influenced by the heterogeneity of the group of not regularly working people. This group comprises disabled persons, housewives for different reasons, and old age pensioners; therefore, it could be
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made up differently in ex-smokers, current smokers, and in never smokers. Also the group of people without completed professional training might be inhomogeneous: it might contain individuals who could not finish their professional training because of different social reasons, but also because of the manifestation of a psychiatric disorder early in life. This could explain the different modification of suicide risk for ‘professional training’ by smoking status; only for ‘no professional training’ odds ratios were clearly, i. e. more than multiplicatively, increased by current smoking. In accordance with controlled psychological autopsy studies (Foster et al., 1999; Vijayakumar and Rajkumar, 1999; Cheng et al., 2000) suicide risk was increased in persons having experienced life events during the last three months. Smoking status shows a modifying effect for suicide risk associated with life events. It is remarkable that suicide risk was about four times greater in the presence of life events in former smokers than in the absence of life events in non-smokers — although former smoking was a protective factor against suicide on the condition that no significant life event had occurred during the last three months. In conclusion, our results demonstrate that smoking status (people, who currently smoke, have never smoked, and used to smoke) modifies suicide risk of psychiatric disorders and sociodemographic variables with only marginal alterations after adjustment for educational level and life events: Suicide risk was differently modified by former and by current smoking for affective disorders and substance use disorders. Personality disorders were risk factors for suicide independent of smoking status, but with highest increased risk for smokers. The present study indicates the importance to determine whether interventions targeting smoking will have an impact on suicide risk, especially in individuals with certain psychiatric disorders. Unfortunately, a causal link or mechanisms of action between smoking and suicide have not yet been established, although a connection between seriousness of suicidal behaviour, smoking, and impaired serotonin function was observed (Malone et al., 2003). There may be major differences between smokers, exsmokers, and non-smokers, e. g. in some personality traits. Even if the association between smoking status and suicide would rather reflect background factors than direct effects of smoking, clinicians should interpret smoking as an indicator of increased risk of suicide, especially of those individuals with substance use disorders, personality disorders, and adverse social factors.
Role of funding source The funding source mentioned in the Acknowledgment had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. If the funding source(s) had no such involvement, authors should so state. Conflict of interest All authors certify that there are not any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the work submitted that could inappropriately influence, or be perceived to influence, their work.
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