From the Netherlands Institute of Mental Health and Addiction (Trimbos Institute), Utrecht, the Netherlands
Correspondence to Dr. Ron de Graaf, Netherlands Institute of Mental Health and Addiction, Da Costakade 45, 3521 VS Utrecht, the Netherlands (e-mail: rgraaf{at}trimbos.nl).
Received for publication January 14, 2005. Accepted for publication May 3, 2005.
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ABSTRACT |
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anxiety disorders; climate; data collection; mental disorders; mood disorders; seasons; substance-related disorders
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INTRODUCTION |
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Studies on seasonal patterns of mental disorders can be divided into 1) surveys of seasonal effects on relapses and remissions in patient populations, 2) population surveys with instruments that focus on seasonal mood and behavioral changes as perceived by respondents, and 3) population surveys measuring disorders in subgroups assessed at different times of the year (3, 4
). The second type of study usually focuses on seasonal affective disorder (SAD).
An overview of epidemiologic studies of SAD in the general population showed that prevalence estimates varied from 0 to 9.7 percent (5). Winter difficulties are reported in Western countries, while summer difficulties are more common in Asia (5
8
). Most studies find that women and younger persons are more at risk of SAD (5
). In general, SAD is more common at higher latitudes (2
, 5
), although the influence of latitude seems to be small and other factors like climate, genetic vulnerability, and social-cultural context might play a more important role (9
). A general population study conducted in Alaska revealed that people acclimatize to living in northern regions with long, dark winters: Subjects who had lived for a shorter duration in these northern latitudes were more frequently affected by SAD (10
). The evidence that SAD has a genetic component (11
, 12
) might explain its low prevalence in some northern countries, such as Iceland (13
).
A few population studies do not focus directly on seasonality in disorders with a specific instrument but measure seasonal change in subgroups assessed at different times of the year. In a workplace population study conducted in Pennsylvania, Schlager et al. (3) found seasonal variations in current symptoms assessed with the Hopkins Symptom Checklist only in females, whose symptoms were most pronounced in late autumn and winter. The amplitude of the seasonal effect was such that the prevalence of female Hopkins Symptom Checklist cases was twice as high in winter as during the rest of the year. Schlager et al. concluded that gender-by-season interactions may contribute to gender differences in the overall prevalence of major depression. In contrast, a general population study conducted in Iceland did not reveal any higher anxiety or depression scores on the Hospital Anxiety and Depression Scale in winter than in summer (4
). Other general population studies carried out in Western countries did find a peak for depression or anxiety in winter or autumn (4
, 8
, 14
); however, these population studies all focused on one or just a few disorders or disorder symptoms.
We know of no large-scale epidemiologic study conducted in the general population, such as any recent studies using the Composite International Diagnostic Interview (CIDI) or any other instrument, that has reported seasonal variations in the prevalence of a range of mental disorders. Knowledge of the seasonality of mental disorders is important for the design of these studies and for accurately calculating the prevalence of mental disorders in the general population. If there are seasonal differences, the fieldwork of large-scale population studies should be spread over a period of at least 1 year, and weighting for the proportion of respondents interviewed per season should be applied in order to render the data representative of a whole year. Until now, some surveys have compensated for possible seasonal influences by extending fieldwork over a 1-year period, because of a lack of knowledge of seasonality in large-scale population studies (15).
We aimed to explore seasonal variations in the prevalence of mental disorders in a representative sample of the Dutch population from the Netherlands Mental Health Survey and Incidence Study (NEMESIS) (15, 16
). In addition, we aimed to study whether women are more sensitive to seasonal variation than men, as most studies have reported (1
3
, 8
, 10
, 13
, 17
, 18
), except for one which found men to be more at risk (19
). We also wished to examine age effects; most studies have found a higher sensitivity for seasonal variation among younger people (2
, 8
, 10
, 13
, 17
), but some have reported this for older people (19
) or have not found any differences (7
). Since seasonal exacerbations and remissions are not limited to mood disorders (5
), we studied a range of mental disorders. We focused on seasonal variations in current (1-month) disorders. In addition, because of the above-mentioned consequences for the design of general population studies, we evaluated seasonal influences on the reporting of 12-month and lifetime disorders; those results are briefly discussed.
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MATERIALS AND METHODS |
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A multistage, stratified, random sampling procedure was used to identify the sample. First, we drew a sample of 90 Dutch municipalities, with the stratification criteria of urbanicity and adequate distribution over the country's 12 provinces. Then, private household addresses were randomly selected from post office registers. Finally, the person aged 1864 years with the most recent birthday in the household was invited to participate. Persons residing in institutions, including psychiatric hospitals, were not included in the sampling frame.
The selected households were sent a letter of introduction signed by the national minister of public health asking them to take part. Shortly thereafter, the households were contacted by telephone by the interviewers. Households with unlisted telephone numbers or no telephone (18 percent) were visited in person. Interviewers made a minimum of 10 calls or visits to an address at different points in time and on different days of the week in an attempt to make contact. To optimize response and compensate for possible seasonal influences, the initial fieldwork was extended to a period of approximately 1 year (from the end of February 1996 to mid-January 1997). During this period, each month a number of randomly selected addresses of respondentssubsamples representative of the whole sample and without specific characteristicswere given to the interviewers. These respondents had to be contacted as soon as possible and within 1 month.
Respondents provided verbal consent after having been informed of the aims of the study. Interviewers entered data into a computer during the face-to-face interview. A total of 7,076 subjects were enlisted at baseline, with a 69.7 percent response rate. The sample followed the same multivariate distribution as the general Dutch population with regard to age, sex, civil status, and urbanicity. Males aged 1824 years were the only group that was slightly underrepresented. Item nonresponse was negligible as a result of the computerized interviewing.
Information on the refusal rate by season was not available, because the dates on which the responders gave permission to participate were not recorded. A comparison between dates of refusal and dates of interview would cause underestimation of the response rate of the season in which the fieldwork began, because an unknown number of interviews were performed not in the season in which permission was given but rather in the next season. However, we gathered some information on the mental health status of nonresponders on the date of refusal. Persons who declined to take part in the full interview were asked to fill in General Health Questionnaire 12 (GHQ-12), a screener for current mental health problems (20); 43.6 percent of the refusers agreed to do so. The percentage of subjects with a GHQ-12 score of 2 or more did significantly differ between refusers and responders; refusers were somewhat more likely to have a better mental health status (
2 = 5.98 (1 df); p = 0.01). However, only one seasonal difference was found: Somewhat more refusers than responders reported a better mental health status in the spring (
2 = 6.76 (1 df); p = 0.01).
A detailed description of the study design and major outcomes has previously been published (15, 16
).
Measures
Season.
We had information on the date of interview for all 7,076 subjects. The dates of interview were categorized into four seasons (spring: March 21June 20; summer: June 21September 20; autumn: September 21December 20; winter: December 21March 20).
The Netherlands is situated on the North Sea and has a mild maritime climate, with an average 24-hour temperature of 9.7°C (spring: 8.7°C; summer: 16.4°C; autumn: 10.3°C; winter: 3.2°C) (21). Summers are not extremely hot, nor are winters extremely cold.
Determination of mental disorders.
Mental disorders were defined according to the Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised (Axis I) (22). The specific instrument used to measure disorders was the CIDI (version 1.1) (23
), which was designed for use by trained interviewers who are not clinicians. The CIDI has acceptable interrater reliability (24
), test-retest reliability (25
), and validity (26
) for practically all diagnoses. The following disorders were included: mood disorders (major depression, dysthymia, bipolar disorder), anxiety disorders (panic disorder, agoraphobia, social phobia, simple phobia, obsessive-compulsive disorder, generalized anxiety disorder), substance-use disorders (alcohol or drug abuse and dependence), eating disorders (anorexia, bulimia), and schizophrenia and other nonaffective psychotic disorders. Prevalences of 1-month, 12-month, and lifetime mental disorders were assessed.
Demographic characteristics.
Demographic variables evaluated included gender, age, educational level, relationship status (living alone vs. living with a steady partner), employment status, and urbanicity.
Statistical analysis
Differences in the prevalence of disorders by date of the interviewthe four seasonswere assessed with the 2 test. Odds ratios and 95 percent confidence intervals were computed as estimates of relative risk in multiple logistic regression analyses, adjusted for gender, age, educational level, relationship status, employment status, and urbanicity. Winter was the reference category for these analyses. Analyses in which the other seasons served as the reference category were also performed. Further analyses were carried out to study the two-way interactions between gender and season of the interview and between age (139 years vs. 4064 years) and season. In these series of multivariate models, the main effects, the interaction term, and other variables used in adjustments were included. All analyses were conducted using weighted data, and for all weighted analyses we obtained robust standard errors based on the first-order Taylor-series linearization method as implemented in Stata 6.0 (27
). We did this in order to obtain correct 95 percent confidence intervals and p values.
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RESULTS |
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Gender differences
Several significant gender-by-season interactions were found. Any mood disorder, major depression, and dysthymia were more frequently observed in winter than in summer among males versus females (p = 0.005, p = 0.008, and p = 0.02, respectively); this was also true for autumn as compared with summer (p = 0.03, p = 0.01, and p = 0.05). Agoraphobia appeared more often in spring than in summer (p = 0.02) or autumn (p = 0.01) among males versus females.
Age differences
For age-by-season interaction analyses, we dichotomized respondents into younger (1839 years) and older (4064 years) age groups. Several significant interactions were found. Any mood disorder and major depression were seen more often in spring than in autumn among younger subjects versus older subjects (p = 0.05 and p = 0.05, respectively). Simple phobia was observed more often in winter than in summer among younger subjects versus older subjects (p = 0.02).
Seasonal influences on reporting of 12-month and lifetime disorders
For the design of general population studies, it is important to have insight into seasonal influences on the reporting of 12-month and lifetime disorders (tables are available from the first author upon request). No seasonal statistical differences were found in the categories "any 12-month disorder" and "any lifetime disorder," although the prevalences were somewhat increased in winter. In addition, no differences were found for the broad category "mood disorders." Twelve-month major depression was reported more often in winter than in summer (p = 0.03). A significant difference was found for 12-month bipolar disorder: The odds for spring as compared with winter were 7.49 (p = 0.05). No differences were found for the broad category "anxiety disorders," but 12-month panic disorder was reported more often in winter than in any other season, 12-month and lifetime generalized anxiety disorder were reported more often in winter than in any other season, and 12-month and lifetime obsessive-compulsive disorder (p = 0.001 and p = 0.008, respectively) were reported more often in autumn than in summer. No differences were found for substance-use disorders, schizophrenia, or eating disorders.
Seasonal differences in 1-month disorders reflect actual seasonal variation in current mental health status, while differences in 12-month and lifetime disorders also reflect seasonal influences at the time of interview on the reporting of former mental health status (recall bias associated with seasonal influence at the time of interview). To distinguish this recall bias from actual seasonal variation in the prevalence of mental disorders, we excluded 1-month cases from the above analyses of 12-month and lifetime disorders. In that situation, not five but none of the 12-month disorders were associated with the season of the interview. The same result was found with respect to lifetime disorders: Not two but none of the lifetime disorders were associated with the season of the interview. Thus, this type of recall bias hardly took place. This also explains why the results for 1-month, 12-month, and lifetime disorders overlapped to a great extent.
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DISCUSSION |
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Despite the many studies of SAD, we hardly found any seasonal variation for the mood disorders. This might be explained by the fact that we did not directly measure SAD. Some population studies that did not focus on seasonal changes in disorders with a specific instrument but rather measured seasonal change among subgroups assessed at different times of the year did not find seasonal differences either (4). It might be that on the individual level, some people have a greater predisposition to mental disorders in winter and others in summer or in another season. If that is true, seasonality may "even out" for the whole sample when investigators use an instrumentlike the CIDIthat does not directly measure seasonal differences in disorders as perceived by the respondents. The fact that the Netherlands has a mild maritime climate, without extremely cold winters or extremely hot summers, could provide an additional explanation for our finding of hardly any seasonal variation.
Gender differences in seasonal variation were not in line with those of most other studies, which found women to be more sensitive to seasonal changes than men (13
, 8
, 10
, 13
, 17
, 18
). We found few gender differences, and when there were differences, men were at higher risk in winter. For example, mood disorder was reported more often in winter than in summer among males versus females: 4.9 percent of males reported mood disorder when interviewed in winter, 3.4 percent in spring, 1.7 percent in summer, and 2.8 percent in autumn, while corresponding figures for females were 3.7 percent, 5.4 percent, 5.7 percent, and 5.2 percent, respectively. Consequently, our findings do not support Schlager et al.'s (3
) conclusion that gender-by-season interactions could contribute to gender differences in the overall prevalence of major depression, based on their finding that the prevalence of female Hopkins Symptom Checklist cases was twice as high in winter as during the rest of the year.
Some studies have found higher sensitivity for seasonal variations among younger people than among older people (8, 10
, 13
, 17
). In our study, we found this for major depression and simple phobia only.
The results regarding seasonal differences in 12-month and lifetime disorders overlapped to a great extent those for 1-month disorders, which can be explained by the fact that 1-month disorders are included in 12-month and lifetime disorders. Seasonal differences in 12-month and lifetime disorders reflect actual seasonal variation in current mental health status but also the seasonal influence at the time of the interview on reporting of former mental health status (recall bias)here, mental health status more than 1 month previously. In our study, this type of recall bias was hardly found. With regard to an accurate estimation of 1-month, 12-month, and lifetime prevalences of the main categories of disorders in large-scale population studies, we conclude that it is not necessary to spread the fieldwork over a period of at least 1 year and that weighting for the proportion of respondents interviewed per season does not necessarily have to be applied in order to render the data representative for the whole year. For reliable estimation of the prevalence of some individual disorders, especially generalized anxiety disorder, obsessive-compulsive disorder, and panic disorders, it is more important to spread the fieldwork over at least 1 year and to weight for the proportion of respondents interviewed per season.
Strengths and limitations
The advantage of studying a general population and measuring seasonal change among subgroups assessed at different times of the year, over direct studies of SAD, is that seasonal peaks found in disorders are not subject to bias in the screening instrument or to the limited reliability of retrospective measures of mood or other disorders, where subjects have to recall whether symptoms of disorders varied according to the time of year (3, 29
).
One limitation of this research is that NEMESIS was not designed to study seasonal variation. Coincidentally, few subjects were interviewed in midwinter (JanuaryFebruary). This could have influenced the results in such a way that winter effects were underestimated. In the third wave of NEMESIS, 3 years after baseline, subjects were interviewed more often in winter (12.4 percent of the sample, compared with 8.4 percent at baseline), and they were also more often interviewed in midwinter. Additional analyses of any diagnoses and the main categories of mood, anxiety, and substance-use disorders did not show any significant seasonal differences either (data not shown). We conclude that the fact that few subjects were interviewed at baseline, in midwinter, did not affect the results much. Because each month a number of randomly chosen addresses of respondents were given to the interviewers and these respondents had to be contacted within 1 month, we believe that no aspects of the process of engaging participants for interview introduced potential biases.
A second limitation of this study was that response rates for the different seasons were not available. If refusers had more negative mental health and if more people refused in winter, somewhat more seasonal differences would exist than are reported here. However, according to the GHQ-12 scores, refusers who were willing to fill in this questionnaire did not have a more negative mental health status than responders.
Conclusions
Data on seasonal variations in the prevalence of mental disorders in general population surveys have rarely been published. We found only limited seasonal variations in a country with a mild maritime climate. Whether this is also true for other countries with other types of climates could be a topic for future research.
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ACKNOWLEDGMENTS |
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Conflict of interest: none declared.
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References |
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