Department of Psychiatry, Trinity Centre for Health Sciences, St James's Hospital, Dublin
Department of Statistics, Trinity College Dublin
Department of Psychiatry, Trinity Centre for Health Sciences, St James's Hospital, Dublin
Division of Neuroscience, University of Birmingham, Queen Elizabeth Psychiatric Hospital, Birmingham, UK
Department of Psychiatry, Trinity Centre for Health Sciences, St James's Hospital, Dublin, Ireland
Correspondence: Dr Aiden Corvin, Department of Psychiatry, Trinity Centre for Health Sciences, St James's Hospital, Dublin 8, Ireland. Fax: 353 1 6082441; e-mail: acorvin{at}tcd.ie
Declaration of interest A.C. is a Wellcome Trust Mental Health Research Fellow; N.C. is a Wellcome Trust Senior Research Fellow in Clinical Sciences.
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ABSTRACT |
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Aims To determine whether smoking is associated with psychosis in bipolar affective disorder.
Method Smoking data were collected from 92 unrelated patients with bipolar affective disorder. An ordinal logistic regression analysis tested the relationship between smoking severity and psychotic symptomatology, allowing for potential confounders.
Results A significant relationship was detected between smoking/heavy smoking and history of psychosis (68.7%, n=44). Smoking was less prevalent in patients who were less symptomatic (56.5%, n=13) than in patients with a more severe psychosis (75.7, n=31). Prevalence and severity of smoking predicted severity of psychotic symptoms (P=0.001), a relationship independent of other variables (P=0.0272).
Conclusion A link between smoking and psychosis exists in bipolar affective disorder and may be independent of categorical diagnosis.
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INTRODUCTION |
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METHOD |
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Interview schedule
Participants were interviewed on a single occasion by one of four trained
clinicians (A.C., E.O'M., C.C., R.O'C.). The diagnosis was made by structured
interview using the Schedule for Clinical Assessment in Neuropsychiatry (SCAN)
Version 2.1 (World Health Organization,
1992). Additional information was collected from available medical
records and collateral data (from family and/or treating clinician). Subjects
were asked for information about their current and previous smoking behaviour;
where possible this information was verified with family and/or care workers.
Each interviewer completed a detailed case summary and generated a diagnosis
using the computer package OPCRIT
(McGuffin et al,
1991). Each case was reviewed independently by another clinician
blind to the diagnosis (M.G., N.C.). Consensus diagnosis meetings were held,
cases were discussed if consensus was not reached between SCAN, chart review,
case summary and OPCRIT diagnosis. Only cases where a consensus diagnosis of
bipolar affective disorder could be reached were included in the study.
Measures
Individuals were considered as current smokers if they had been smoking
daily for at least 3 months prior to interview. Individuals who had never
smoked or those who had stopped smoking at least a month prior to interview
were considered non-smokers. Cigarette use was further classified as
moderate (defined as 20 cigarettes/day) or
heavy (> 20 cigarettes/day) smoking.
Data were converted into ordinal and nominal variables for statistical analysis. Patients were classified as having psychoses if they had a history of at least one psychotic symptom (delusion or hallucination) as defined by SCAN, and thus met criteria for a psychotic mood episode as defined by ICD10 (World Health Organization, 1993). Patients with a history of psychosis were further divided into those with a history of low-grade symptoms (not significantly contributing to overall illness) and those with severe symptoms (defined as at least 25% of total illness duration). This approach was based on the dimensional classification for bipolar affective disorder as described by Craddock et al (1997). The other variables, namely: gender, age at onset, course of illness, number of manic episodes, number of depressive episodes, duration of illness, comorbid alcohol or non-alcohol substance misuse/dependency, education, socio-economic status and current neuroleptic usage were treated as nominal variables. These variables were selected by a review of smoking and schizophrenia literature as those most likely to confound any association between smoking and psychosis.
Individuals were divided into categories according to age at onset of
illness: <20 years, 20-29 years and 30 years old. Duration of illness
was categorised as <10 years, 10-19 years, 20-29 years and
30 years.
The numbers of episodes of mania or depression were grouped as 0, 1-2, 3-5,
6-9 and 10+ total lifetime episodes. Course of illness (defined as in
ICD10) was simplified to good if single/multiple episodes
with good recovery between episodes occurred, and poor if
recovery between episodes was only partial or the illness was continuous.
Alcohol-related pathology was defined categorically as a lifetime history of
ICD10 alcohol abuse or dependency. Non-alcohol substance misuse was
defined as: never; occasional if less than
monthly; regular if monthly or more frequently, but abstinent
for the last month; and current if used in the month prior to
interview. Education was defined as completion of primary, secondary or
tertiary level education. Socio-economic status was defined using standard
social class measures: (I) professional, (II) managerial and technical, (III)
non-manual, (IV) skilled manual, (V) semi-skilled, (VI) unskilled, (VII) all
others. For analysis these were divided into three groups representing (I) and
(II); (III) and (IV); (V)(VII). Neuroleptic use was defined as a daily
dosage for at least the month prior to interview (including current depot
treatment).
Statistical methods
Basic frequency data were compiled, followed by a 2
analysis of the relationship between smoking, heavy smoking and
presence/absence of a history of psychotic symptoms. Individual
2 testing of all variables was avoided to limit multiple
testing. To further explore the association we chose to use an ordinal
logistic regression model using the computer package JMP
(SAS Institute Inc, 1995). This model analysed the relationship between the dependent variable
psychotic symptoms status/severity and the variable
smoking status/severity controlling for the effects of all other
variables. Within the model we examined the correlation between variables and
multi-co-linearity was excluded.
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RESULTS |
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Other clinical and epidemiological variables
Twenty of the participants (21.7%) fulfilled the ICD10 criteria for
alcohol dependence/abuse. Forty-five patients (48.9%) were taking neuroleptic
medication, 38 (41.3%) were not, and these data were unavailable on the
remaining nine patients (9.8%). Details of social class and education were
available for 88% of the total sample. Nineteen participants (20.7%) reported
a history of non-alcohol substance use, and nine of these (9.8%) admitted to
ever having used substances monthly. All patients denied current substance
misuse, and only one described regular use of a substance other than cannabis
(Ecstasy).
Ordinal logistic regression
We performed an ordinal regression analysis to examine the relationship
between each individual test variable and history and severity of psychotic
symptoms, controlling for all other test variables
(Table 1). Analysis confirmed
that smoking/heavy smoking predicted psychotic symptom status and a history of
severe psychotic symptoms (2=10.73, P=0.027).
Examination of the parameter estimates showed this to be explained by a
significant difference in psychotic symptom severity between non-smokers and
moderate smokers (
2=10.14, P=0.0015). No significant
difference for psychotic symptom severity was detected between the moderate
and heavy smoking groups. Of the other tested variables, only current use of
neuroleptic medication (as we would expect) predicted a history of psychotic
symptoms (
2=6.25, P<0.001); this was independent
of all other variables, including smoking.
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DISCUSSION |
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Relationship to existing literature
Data on smoking behaviour in bipolar affective disorder are conflicting
two studies report increased smoking
(Hughes et al, 1986; Gonzalez-Pinto et al,
1998) but a third found no change
(Diwan et al, 1998).
From our finding we would predict that broadly defined mood disorder samples
(Diwan et al, 1998)
would have a lower smoking prevalence, having more patients with unipolar
depression, in which psychotic symptoms would be less frequent.
Implications for the pathophysiology of psychotic disorders
A regulatory effect for nicotine on the dopaminergic, serotonergic and
glutaminergic systems implicated in schizophrenia has been suggested (for
review see Dalack et al,
1998). Researchers studying abnormal auditory filtering (as
measured by the P50 auditory evoked potential) in patients with schizophrenia
have observed temporary reversal of the deficit with nicotine
(Adler et al, 1993). This group has also studied the role of nicotine in modulating gating
abnormalities in a rat model (Bickford
& Wear, 1995). More recently they have reported genetic
linkage between the human gating defect and a polymorphism of the -7
nicotinic receptor sub-unit in families multiply affected with schizophrenia
(Freedman et al,
1997; Leonard et al,
1998). Similar P50 gating abnormalities reported in bipolar
disorder (Baker et al,
1990) had previously been interpreted as due to excess
catecholamine release in the manic phase of illness. It is unclear whether
excess smoking in psychotic bipolar affective disorder represents a different
mechanism, or a shared mechanism in keeping with continuum
(Crow, 1995) or alternative
categorical models of psychosis (Kendler
et al, 1998).
Methodological issues and future directions
The implications of our findings outside this sample require cautious
interpretation, but we feel that the association warrants further
investigation. In a follow-up study, we will include validated measures of
symptom dimensions for psychosis. We were unable to measure nicotine or carbon
monoxide levels in this study, but collateral information was available in
most cases. There is also good evidence to support the accuracy of self-report
of substance use in psychiatric patient populations
(McLellan et al,
1983). In future studies data derived from longitudinal rather
than cross-sectional data may give the most accurate measure of true smoking
behaviour, and in this regard hair analysis may provide a more objective
measure (Pichini et al,
1997). Our study failed to allow for variations in nicotine
content of different brands of cigarette, although current thinking suggests
that differential extraction of nicotine compensates for different amounts in
cigarette brands. We also failed to find a difference in the severity of
psychosis between moderate and heavy smoking groups. It is likely that we had
insufficient sample size to distinguish such a difference should it exist,
because of the relatively small groups involved.
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Clinical Implications and Limitations |
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LIMITATIONS
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Received for publication May 30, 2000. Revision received January 15, 2001. Accepted for publication January 17, 2001.
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