Department of Clinical and Biomedical Science: Barwon Health, The University of Melbourne, Victoria
Department of Clinical and Biomedical Science: Barwon Health, The University of Melbourne, Victoria, and Orygen Research Centre and Mental Health Research Institute, Australia
Correspondence: Julie A. Pasco, Epidemiology and Biostatistics Unit, Department of Clinical and Biomedical Sciences: Barwon Health, The University of Melbourne, PO Box 281, Geelong 3220, Australia. Email: juliep{at}barwonhealth.org.au
J.P., L.W., F.J. and M.B. have received research support from an unrestricted educational grant from Eli Lilly. Funding detailed in Acknowledgements.
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Smoking is disproportionately prevalent among people with psychiatric illness.
Aims
To investigate smoking as a risk factor for major depressive disorder.
Method
A population-based sample of women was studied using case–control and retrospective cohort study designs. Exposure to smoking was self-reported, and major depressive disorder diagnosed using the Structured Clinical Interview for DSM–IV–TR (SCID–I/NP).
Results
Among 165 people with major depressive disorder and 806 controls, smoking was associated with increased odds for major depressive disorder (age-adjusted odds ratio (OR)=1.46, 95% CI 1.03–2.07). Compared with non-smokers, odds for major depressive disorder more than doubled for heavy smokers (>20 cigarettes/day). Among 671 women with no history of major depressive disorder at baseline, 13 of 87 smokers and 38 of 584 non-smokers developed de novo major depressive disorder during a decade of follow-up. Smoking increased major depressive disorder risk by 93% (hazard ratio (HR)=1.93, 95% CI 1.02–3.69); this was not explained by physical activity or alcohol consumption.
Conclusions
Evidence from cross-sectional and longitudinal data suggests that smoking increases the risk of major depressive disorder in women.
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There is already evidence that smoking is a risk factor for depression. Association data from cross-sectional studies5,6 support evidence from prospective studies to suggest that smoking pre-dates the onset of depression.7,8 However, there is only limited longitudinal data in the existing literature, and most longitudinal studies have involved time frames under 2 years, which may not be adequate to demonstrate the insidious effects of nicotine dependence. In this epidemiological study, we investigated the status of tobacco smoking as a risk factor for major depression using not only cross-sectional data but also longitudinal data that extend over a period of 10 years.
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Data
Lifestyle practices including smoking, alcohol consumption, habitual
physical activity levels and exposure to disease were self-reported. Smoking
was recognised if individuals reported regularly smoking more than one or two
cigarettes per day for at least 6 months, and recorded details of smoking
included frequency and period of exposure. Alcohol intake was recognised if
alcohol was consumed several times per week or every day. Habitual physical
activity was classified as active if participants reported `moving, walking
and working energetically and participating in vigorous exercise', otherwise
they were classified as sedentary. Cardiovascular disease included
hypertension, angina and coronary artery disease; diabetes encompassed both
types 1 and 2. Socio-economic status was ascertained using Socio-Economic
Index for Areas index scores based on census data from the Australian Bureau
of Statistics.10
These data were used to derive an Index of Economic Resources (IER), which was
categorised into five groups, according to quintiles of IER for the study
region.
The Structured Clinical Interview for DSM–IV–TR Research Version, Non-patient Edition (SCID–I/NP)11 was used to identify women with a lifetime history of major depressive disorder and to determine age at onset. Psychiatric interviews were conducted by trained personnel.
Study designs
Case–control
Among 1043 women who underwent psychiatric assessment, 237 were diagnosed
with major depressive disorder and 806 had no history of major depressive
disorder. Exposure to smoking was recognised if smoking was practised prior to
the onset of major depression. Sixty-eight individuals were excluded because
their age at major depressive disorder onset was less than 20 years (the
minimum age for controls) and four were excluded because it was unclear
whether smoking pre- or post-dated major depressive disorder onset. Thus, 165
individuals with major depressive disorder and 806 controls were eligible for
analysis in this case–control study.
Retrospective cohort
Among 1043 women who underwent psychiatric assessment, a decade of
longitudinal data was available for 835. Based on retrospective data, 164 were
excluded because they had experienced a major depressive disorder episode
prior to baseline. Among the 671 women aged 20–84 years with no history
of major depressive disorder at baseline and who were thus eligible for
analysis in this retrospective cohort study, 51 developed de novo
major depressive disorder and 620 remained major depressive disorder-free
during follow-up. Participants were classified as smokers if they were current
smokers at baseline, otherwise they were classified as non-smokers.
Statistics
Statistical analyses were performed using Stata (version 9.0) and Minitab
(version 13). Standard descriptive statistics were used to characterise the
participants in each study.
In the case–control study, participants were selected as cases
(people with major depressive disorder) or controls (people with no major
depressive disorder), and exposure to smoking was documented for each group.
Logistic regression modelling was performed to determine the association
between smoking and major depressive disorder. Age was defined as the age at
major depressive disorder onset for cases and age at baseline for controls,
and was categorised into age groups for analysis. Smoking was investigated as
a binary variable and was also categorised into groups according to the
average number of cigarettes smoked per day (0,
10, 11–20, >20
cigarettes/day). Age, socio-economic status, physical illness, physical
activity and alcohol consumption were tested in the models as potential
confounders and effect modifiers.
In the cohort study, participants with no history of major depressive disorder at baseline were selected, categorised as current smokers or not, and followed until a first major depressive disorder episode or until the end of the follow-up period. The effect of smoking on development of de novo major depressive disorder was examined using multivariate Cox proportional hazards regression analysis, using age as the time axis. The proportional hazards assumptions were checked using Schoenfeld residuals before and after adjusting for potential confounding by socio-economic status, physical illness, physical activity and alcohol consumption.
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Table 1 Participant characteristics in the case–control study
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Table 2 Smoking frequency (number of cigarettes per day) and the risk for major
depressiona
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Being physically active was found to be protective against major depressive disorder (age-adjusted OR=0.58, 95% CI 0.37–0.91, P=0.017). None the less, the association between smoking and major depressive disorder was not explained by differences in physical activity. The independent relationships between smoking and physical activity on the risk for major depressive disorder are shown in Fig. 1. Alcohol consumption did not affect this association.
![]() View larger version (19K): [in a new window] [as a PowerPoint slide] |
Fig. 1 Independent contributions of tobacco smoking and physical activity to the
risk for major depression. Non-smokers who are physically active form the
reference group.
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Table 3 Participant characteristics in the retrospective cohort study
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Exposure to smoking was found to increase the risk for developing a first episode of major depressive disorder by 93%, hazard ratio (HR)=1.93 (95% CI 1.02–3.69, P=0.045). A Kaplan–Meier survival plot showing the probability of remaining free of major depressive disorder over a 10-year period for women exposed and unexposed to smoking at baseline is shown in Fig. 2. Adjustment for socio-economic status enhanced the risk (adjusted HR= 2.01, 95% CI 1.03–3.93, P=0.042). Further adjustment for alcohol consumption, physical activity or physical illness did not attenuate this association.
![]() View larger version (10K): [in a new window] [as a PowerPoint slide] |
Fig. 2 Survival plot (Kaplan–Meier) showing the probability of remaining
free of de novo major depressive disorder over a 10-year period for
smokers and non-smokers at baseline.
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Other cross-sectional studies have reported increased odds of depression in smokers,5,6 with results retaining statistical significance after adjusting for other major risk factors.6 Prospective studies, although limited, have further strengthened the suspected role of smoking in depression. In an 11-year population-based longitudinal Norwegian study, the hazard ratio for a first depressive episode increased with smoking in a dose-dependent fashion, such that the heaviest smokers (exceeding 20 cigarettes per day) had over four times the risk of those who had never smoked.7 Increased incidence of major depression in smokers has been reported in other shorter studies,12,13 including data from adolescents.14 Longitudinal studies have also shown a reverse relationship, in which the presence of depression increased the risk of smoking progression.12,13 Positive effects on psychomotor performance and enhanced craving, as demonstrated in a physiological study,15 may be pertinent factors for this observation. Other studies have provided support for a third possibility, that depression and smoking coexist as epiphenomena of a common underlying cause, such as genetic factors.16,17 The efficacy of bupropion in the treatment of both depression and nicotine dependence18 may indicate some commonality between the two conditions on a neurochemical level.
Dopamine is one such factor, which is believed to have a dual role in depression and in the mechanism of addiction. Neurochemical studies of depression, particularly with psychomotor retardation, reported an association with diminished dopamine metabolism, as evidenced by decreased levels of cerebrospinal fluid homovanillic acid.19,20 Reduced striatal dopamine function has also been shown in dopamine D2 receptor neuroimaging binding studies.21,22 Dopamine is regarded as the central neurotransmitter of reward, and as having a key role in the reinforcement of the pathways to addiction.23 Dysregulation of the dopaminergic system in addictive states is also a plausible mechanistic pathway to depressive vulnerability.24
Smoking-induced oxidative stress is another factor. Tobacco smoke generates free radicals, causing lipid peroxidation, oxidation of proteins and other tissue damage in smokers.25,26 Depression has been characterised by elevated markers of oxidative stress27–29 that demonstrates a positive correlation with depressive severity30 and a return to normal levels after treatment.28,29 It seems plausible that depression could be among the oxidative stress sequelae of smoking.
There are several strengths and potential weaknesses in our study. The length of the follow-up period is a key strength, especially when published longitudinal studies have rarely exceeded a few years at most. Given that smoking effects insidious biochemical changes that are naturally accommodated by the body's homeostatic responses, long-term sequelae such as depression, cancers, cardiovascular and pulmonary diseases may only be reliably demonstrated over an extended time frame. Recall limitations may have affected our ability to accurately diagnose the time of onset of depressive episodes and, in the case–control analysis, the potential exists for differential recall bias of smoking practices. However, as this study was nested within a larger prospective study, the latter risk was minimised as exposure to smoking had been documented prior to psychiatric interview. Furthermore, documentation of exposure to smoking and assessment of outcome were performed by different study personnel. The duration of smoking prior to the onset of depression was unknown, precluding estimation of duration of exposure on depression. Inconsistencies in the number of cigarettes smoked per day may have resulted in misclassification of smoking frequency in the case–control analysis but the apparent dose-dependent association strengthens the notion that smoking is a risk factor for major depression. Small numbers limited a comparable investigation in the longitudinal analysis. Also in the longitudinal analysis, changes in exposure status during follow-up have not been identified. Finally, as in all observational studies, there may be unrecognised confounding. We relied on self-reported history of cardiovascular disease and diabetes as indicators of physical illness that may be affected by smoking status. However, we cannot exclude possible confounding by unrecognised comorbidity as individuals were not clinically screened for all potential physical illnesses. Physical activity and alcohol consumption were explored as concomitant lifestyle factors with a potential for confounding because physical activity had been previously reported as protective against depression,31 whereas physical inactivity32–34 and alcohol misuse6 are regarded as risk factors. In this study, alcohol consumption did not appear to confound the association between smoking and depression; however, we acknowledge that our criteria for alcohol consumption may have been too broad to confidently exclude its contribution. Other factors predisposing to depression, such as personality traits, developmental and family history of depression, IQ or stress, were not considered as these data were not available.
Within these limitations, however, our data corroborate literature that reveals a malevolent role of smoking in depression and suggest that greater efforts are required in targeting smoking as a routine intervention.35 Depression's status as a leading cause of global disease burden,36,37 one that is not anticipated to yield in the coming decades,36 can only underscore the potential impact of any effective preventive measures.
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