Division of Mood Disorders, Department of Psychiatry, University of British Columbia, Canada
Department of General Practice, University of Wales College of Medicine
Department of Primary Care, University of Liverpool
Department of Psychiatry, University of Liverpool, UK
Correspondence: E. E. Michalak, Division of Mood Disorders, Department of Psychiatry, 2255 Wesbrook Mall, University of British Columbia, Vancouver V6T 2A1, Canada
Declaration of interest G.W. is Editor of the British Journal of Psychiatry. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To determine the association between demographic/psychosocial factors and increased reported seasonal patterns of mood disorder (seasonality) and SAD in a community sample in the UK.
Method A total of 1250 people, aged between 18 and 64 years, randomly selected from a primary care database were screened for SAD. Those above cut-off underwent diagnostic interview and completed several self-report questionnaires. Multivariate analysis was conducted to determine which variables were significantly associated with increased seasonality.
Results Four factors (having experienced more numerous negative life events, having low levels of social support, being a woman and being non-native) were predictive of higher seasonality. Being a woman was predictive of being diagnosed as a case of SAD.
Conclusions A new association has been identified between increased seasonality, negative life events and social support. Future research should assess the psychosocial causes or consequences of SAD while continuing to examine the biology of the condition.
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INTRODUCTION |
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The present study aimed to assess the association between a range of demographic and psychosocial factors and seasonality (determined by a continuous score on a commonly used screening tool for SAD) and caseness (likelihood of being diagnosed as a case of SAD) in a community sample in the UK.
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METHOD |
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Sample frame
The sample consisted of adults, aged between 18 and 64 years, registered on
the North Wales Health Authority's general practice database and residing
within the former Glyndwr council district in North Wales.
Case finding
A two-phase sampling method (Pickles
et al, 1995) was adopted as a research strategy, using a
self-rating postal survey to identify potential cases, followed by structured
diagnostic interview and more-detailed questionnaires with those participants
scoring above cut-off.
Potential cases of SAD were identified using a sub-scale of the Seasonal Patterns Assessment Questionnaire (SPAQ; Rosenthal et al, 1987), a commonly used screening tool for SAD that provides a global seasonality score (GSS) for a given individual. This score ranges from 0 to 24; it indicates the degree of change that individuals experience between the seasons in their sleep, mood, weight, appetite, energy and social activity, and requires that they describe whether these changes represent a mild, moderate, marked, severe or disabling problem for them. The traditional cut-off score of 11 or more, with seasonal changes amounting to at least a moderate problem, was applied (Kasper et al, 1989; Rosen et al, 1990). The SPAQ shows reasonable psychometric properties but does tend to produce high false-positive rates compared with clinical diagnosis of SAD. Furthermore, the questionnaire has been criticised for relying upon people's subjective evaluation of seasonal problems and upon their retrospective recall of when depressive episodes occurred. Research has indicated that the reliability of recall of depressive episodes and of seasonal patterns is poor (Wicki et al, 1992; McAllister-Williams et al, 1998), and that the degree of seasonality is overestimated when recorded retrospectively as opposed to prospectively (Nayyar & Cochrane, 1996).
Recent negative life events were assessed using the List of Threatening Experiences (LTE), a self-report questionnaire that examines the incidence of 12 categories of negative life events over the previous 6 months (Brugha et al, 1985). The LTE assesses life stressors involving moderate or long-term threat such as illness or injury, death of a close friend or relative, unemployment, financial loss and loss of important relationships. The questionnaire shows acceptable levels of reliability and validity (Brugha & Cragg, 1990) and a high score has been shown to be associated with increased risk of depression (Brugha & Conroy, 1985). Levels of social support were assessed via a three-item questionnaire called the Oslo 3-Item Social Support Scale (Dalgard, 1996; scale available upon request from Professor Odd Dalgard, e-mail: o.s.dalgard{at}samfunnsmed.uio.no), which contained questions concerning: number of people the participant reports being close to; concern shown by others; and ease of getting practical help from neighbours. It provides an overall social support index (SSI) score, where higher scores indicate lower levels of social support. Basic demographic questions also were incorporated into the screening package.
The second diagnostic interview stage of assessment was conducted with all consenting participants who scored above cut-off on the SPAQ. Interviews were performed during the winter of 1997-98 by a psychologist (E.E.M.) according to the revised version of the Structured Interview Guide for the Hamilton Depression Rating Scale Seasonal Affective Disorder Version (SIGHSAD; Williams et al, 1992). Diagnostic criteria utilised were a minimum score of 15 on the Hamilton Rating Scale for Depression (HRSD), with a score of at least 6 on the supplementary atypical item scale, these being equivalent to those applied in another study of SAD conducted in the UK (Wileman et al, 2001). Diagnosed cases of SAD also met DSM-IV criteria for major depressive episodes with a seasonal (winter) pattern (American Psychiatric Association, 1994).
Ethics
Ethical approval for the study was obtained from the South Clwyd Ethics
Committee in North Wales and all participants provided written informed
consent.
Statistics
Univariate analyses were performed using 2 for categorical
data, Student's t-tests for normally distributed continuous data and
MannWhitney tests for non-normally distributed continuous data.
Separate analyses were conducted, examining: factors associated with
continuous GSS score (multiple regression); factors associated with being
below/above cut-off on the SPAQ (stepwise logistic regression); and factors
associated with being diagnosed as a case of SAD (stepwise logistic
regression). Regression analyses examined the relationship between these
categories and the following variables:
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RESULTS |
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Multivariate analyses
The outlined variables were entered into a stepwise multiple regression
model to determine their association with GSS, fitted to 1181 cases with
complete data. Having experienced more negative life events in the past 6
months, having a poorer social support network, being a woman and being born
outside of North Wales were all predictive of higher seasonality scores
(Table 1). These variables, in
the same order of significance, were also predictive of scoring above cut-off
on the SPAQ using a logistic regression model (results not shown). However,
only female gender significantly predicted being diagnosed as a case of SAD
(odds ratio=3.8, 95% CI 1.04-13.9).
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Relationship between negative life events and increased
seasonality
The association observed between negative life events and increased
reported seasonality was surprising and consequently was made the subject of
further analysis. Mean GSS score increased significantly as the number of
negative life events experienced increased; participants experiencing 0, 1 or
2 negative life events had mean GSS scores of 4.0, 4.9 and 6.4,
respectively. Mean number of negative life events experienced by participants
scoring above cut-off on the SPAQ were 1.11 (s.d.=1.39), compared with 0.52
(s.d.=0.91) for those below cut-off (MannWhitney, P<0.001).
In the SPAQ-positive group, a nonsignificant trend towards increased negative
life events in men was apparent (mean 1.42 (s.d.=1.87) v. 0.98
(s.d.=1.15)). Number of negative life events experienced was slightly lower
for diagnosed cases of SAD (mean 1.0 (s.d.=1.15) for men, 0.85 (s.d.=0.88) for
women, NS). In the larger ODIN sample, DSMIV diagnosed cases of
non-seasonal depression reported having experienced a mean number of negative
life events of 1.5 (s.d.=1.6) for men and 1.3 (s.d.=1.4) for women (NS).
It was also of interest to know whether people with increased reported
seasonality experience more negative life events at a particular time of the
year. In order to address this question the responses of two subgroups of
participants were analysed. Screening questionnaires for this project were
sent out between February and November 1997. The first group consisted of
participants who responded in March or April 1997 (who were reporting negative
life events that had occurred in the previous 6 months, i.e. October/November
through to March/April). The second group consisted of participants who
responded in September or October 1997 (who were reporting negative life
events that had occurred between April/May and September/October). Respondents
in each group were then split into two further subgroups: a
non-seasonal group (those with a GSS score of 6) and a
seasonal group (those with a GSS score of
8). A GSS score of
6 has been used previously to define non-seasonal controls
(Andrew et al, 2001),
whereas a GSS score of
8 was selected because it represents the bottom
cut-off score for inclusion as a case of SAD
(Kasper et al,
1989).
Comparison of the number of negative life events between the two time points was conducted using the MannWhitney U-test. No overall significant differences were apparent between the March/April and the September/October subgroups (Table 2). However, the seasonal subgroup experienced significantly more negative life events than the non-seasonal subgroup at both time points. Thus, it appears that people with increased seasonality experience more negative life events throughout the year, and not during one particular season.
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DISCUSSION |
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Negative life events
The present study found that having experienced more recent negative life
events was predictive of higher seasonality scores, as measured by the SPAQ.
Although a large body of research has examined the relationship between
negative life events and non-seasonal depression (Brown & Harris,
1978,
1989;
Henderson & Byrne, 1981),
no previous research has directly examined the relationship between
seasonality and life events. Some research has been conducted in relation to
SAD and negative life events, where it has been reported that the latter can
act as a trigger that shifts seasonal depressives from patterns of seasonal
depression into patterns of non-seasonal depression
(Sakamoto et al,
1995). Other work has indicated that some episodes of seasonal
depression may be triggered by anniversary reactions associated with previous
traumatic experiences, but these appear to be relatively rare (Beratis et
al, 1994,
1996). However, our study was
under-powered to detect an association between negative life events and
diagnosed SAD, and further research is required to determine whether such an
association exists in clinical populations.
An over-arching question here concerns whether these increased negative life events are a cause or a consequence of increased seasonality. Although the evidence has been controversial (Tennant et al, 1981), it is generally accepted that stressful or negative life events have a causal relationship with non-seasonal depression (Kendler et al, 1999). Although seasonal depression should not be diagnosed in the presence of seasonally recurring life events such as regular winter unemployment, an as yet unidentified causal relationship between negative life events and increased seasonality may exist. Alternatively, heightened seasonality may result in people experiencing more negative life events. For example, a person who is socially impaired as a result of seasonality might be more likely to experience a relationship breakdown. Secondary analysis of the data obtained here indicated that people with increased seasonality in fact experience more negative life events throughout the year. If increased seasonality were to cause life events, we might have expected to see these increased events in the subgroup of people who completed their questionnaires in March/April, but not in the September/October subgroup. The finding that people with seasonality experience more negative life events throughout the year does not provide direct support for either the notion that seasonality causes life events or that life events cause increased seasonality.
Of course, there are other possible explanations for this observed relationship. Personality factors, for example, may have a role to play. Longitudinal research has shown that women with high neuroticism scores report having experienced more negative life events (Fergusson & Horwood, 1987), and individuals with seasonality have been shown to have heightened levels of neuroticism (Murray et al, 1995). Again, however, one must question in which direction causality runs in this putative relationship between personality factors and life events. As has been pointed out (Young & Martin, 1981), people with certain personality types may be more likely to be involved in (or indeed create) social environments in which the risks of exposure to life events are increased. Alternatively, exposure to life events may modify personality. Finally, individuals who are high in neuroticism could have a tendency to report more negative life events because of their increased sensitivity and responsiveness (Young & Martin, 1981).
Social support
The observed relationship between impaired social support and increased
reported seasonality is also new. Once again, it must be questioned whether
poor social support results in increased seasonality, or whether heightened
seasonality results in diminished social support. In the former scenario, low
levels of social support could increase the likelihood that an individual will
experience (or report) greater seasonal variation in their mood and behaviour.
In this sense, a good social support network might be said to be having a
buffering effect against seasonal symptoms. Interestingly, other
research has indicated that the buffering effect of social support is
particularly pronounced in people with high external loci of control, a
personality trait that characterises people who are high in seasonality
(Dalgard et al,
1995). Alternatively, people who are high in seasonality are
likely to be relatively unsociable for a proportion of the year, and may
develop poorer social support networks. Further research utilising a larger
subject sample is required to determine whether this association between
social support and seasonality is also present in patients who are diagnosed
with SAD.
Place of birth
Finally, being non-native to North Wales significantly predicted higher
seasonality. The observation that being native to an area is a protective
factor for seasonality is not new. A study of psychiatric nurses in Aberdeen,
for example, found that 17% of incomers were SPAQ cases compared
with 11% of those who had lived in Aberdeen for 5 or more years
(Eagles et al, 1996).
Other research examining seasonality in indigenous White, British Asian and
Asian women found that the last group were more susceptible to winter
depression (Suhail & Cochrane,
1997). Studies in a general population sample in Alaska and an
out-patient sample in Canada have observed similar trends
(Booker & Hellekson, 1992;
Williams & Schmidt, 1993), although a study of Japanese residents in Stockholm did not find an effect for
acclimatisation (Murase et al,
1995). There are several possible explanations for these findings.
People who have lived in one place all their lives may be more acclimatised to
that area's weather conditions. Alternatively, natives may have superior
social support networks, although in the present study both low social support
and being non-native were independent predictors of higher seasonality scores.
It remains unclear what mediating variables unpin the observed relationship
between place of birth and seasonality. However, the fact that this
association has been made in several different countries and populations
indicates that it is probably a genuine one.
Conclusions
The present study has served to generate some new evidence concerning
psychosocial factors and increased seasonality. In particular, the study has
highlighted a new and intriguing relationship between negative life events,
poor social support and heightened seasonality. The cross-sectional nature of
the research, the small number of diagnosed cases of SAD identified and the
fact that the SPAQ is a retrospective, subjectively rated instrument do limit
the inferences that can be made on the basis of the data. Nevertheless, the
study provides further evidence of the importance of evaluating the role of
psychosocial factors in relation to seasonality and SAD in future
research.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication August 2, 2002. Revision received November 5, 2002. Accepted for publication December 12, 2002.
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