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Evaluation of seasonality in six clinical populations and two normal populations
J. psychiat. Res., Vol. 25, No. 3, pp. 75-87, 1991. Printed in Great Britain.
EVALUATION POPULATIONS
0022-3956/91 $3.00 + .00 (c 1991 Pergamon Press plc
OF SEASONALITY AND
TWO
IN SIX CLINICAL
NORMAL
POPULATIONS
TODD A. HARDIN, I THOMAS A. WEHR, 1 TIMOTHY BREWERTON, 2 SIEGFRIED KASPER, 3 WADE BERRETTINI, 4 JUDITH RABKIN 5 a n d NORMAN E. ROSENTHAL 1 IClinical Psychobiology Branch, NIMH, Bethesda, MD, U.S.A.; 2Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, SC, U.S.A.; 3psychiatric Department, University of Bonn, Bonn, F.R.G.; 4Clinic Neurogenetics Branch, N1MH, Bethesda, MD, U.S.A.; and 5New York State Psychiatric Institute, New York, NY, U.S.A.
(Received 10 July 1989; revised 10 September 1990) Summary--The Seasonal Pattern Assessment Questionnaire (SPAQ) was used to evaluate retrospectively self-reported seasonal changes in mood and behavior (seasonality) of two normal and six clinical populations: patients with winter-seasonal affective disorder (SAD), summer-SAD, eating disorders, bipolar affective disorder, major depressive disorder and subsyndromal winterSAD. The SPAQ successfully discriminated between groups expected to have high seasonality scores, such as winter-SAD, summer-SAD and subsyndromal winter-SAD, and normal controls. Bipolars and major depressives had normal seasonality scores. Patients with eating disorders had unexpectedly high scores. There was a general tendency for all groups to eat and sleep more and to gain weight in the winter. The implications of these findings are discussed.
Introduction ALTHOUGHthe seasonal influence on the timing of manic and depressive episodes has been recognized since classical times (Jones & Wittington, 1923-1931), there has been a recent surge of interest in this area, inspired by the recognition of patients with regularly recurring fall-winter depressions, which can be reversed by bright environmental light (Lewy, Kern, & Rosenthal, 1982; Rosenthal et al., 1984). Since winter-seasonal affective disorder (winterSAD) was first described, it has become apparent that the tendency for people to experience seasonal changes in mood and behavior (seasonality) is not confined to severely affected individuals, but appears to vary in degree across the normal population (Terman, 1988; Kasper, Wehr, Bartko, Gaist, & Rosenthal, 1989; Rosen et al., 1989). It has also become apparent that some patients experience regular summer depressions alternating with remissions in the winter (Wehr, Sack, & Rosenthal, 1987; Boyce & Parker, 1988). We will refer to these patients as suffering from summer-SAD and those with recurrent winter depression as suffering from winter-SAD. Indeed, a great majority of the general population report seasonal changes, and according to the epidemiological studies mentioned above, 20-25% regard these changes as a problem. These studies have used the Seasonal Pattern Assessment Questionnaire (SPAQ) (Rosenthal, Genhart, Jacobsen, Skwerer, & Wehr, 1987), an instrument we developed in order to Please address all correspondence to: Todd Hardin, Clinical Psychobiology Branch, NIMH, Bldg 10, Room 4S-239, 9000 Rocksville Pike, Bethesda, MD 20892, U.S.A. Tel. (301) 496-2141. 75
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TODD A. HARDIN et al.
evaluate retrospectively the pattern and degree of an individual's seasonal changes in mood and behaviour. In the study by Kasper, Wehr, and Bartko (1989), case finding criteria for winter-SAD and subsyndromal winter-SAD, as derived from the SPAQ, yielded conservative prevalence estimates when compared with clinical criteria applied to a representative subsample of the population. In the study by Rosen et al. (1989), the degree of reported seasonality, as measured by the SPAQ, correlated significantly with latitude. The questionnaire can be administered to a variety of populations, and the degree of seasonal variation for different groups can be derived. Thus, Thompson, Stinson, Fernandez, Fine, and Isaacs (1988) administered the instrument to patients with winter-SAD, bipolar disorder, and normal controls, and found that the questionnaire discriminated between these three groups. As anticipated, the winter-SAD group showed a significantly greater degree of seasonal change than normal controls, and the bipolar group tended to fall in between. Patients with winter-SAD and subsyndromal winter-SAD, who have been shown to respond favorably to bright environmental light (For review see Rosenthal, Sack, Skwerer, Jacobsen, & Wehr, 1988; Kasper, Rogers, & Yancey, 1989; Terman, Botticelli, Link, Hardin, & Rosenthal, 1989), reported a higher degree of seasonality than normal individuals without histories of winter difficulties, who do not appear to benefit from exposure to bright light (Rosenthal, Rotter, Jacobsen, & Skwerer, 1987b). The SPAQ distinguishes between these populations and thus has predictive value for response to phototherapy. To judge from the above studies, the SPAQ appears to be a useful and valid instrument for evaluating an individual's history of seasonality. Just as the severity of winter difficulties appears to predict responsiveness to bright light in subsyndromal winter-SAD and normal individuals, so such a history may predict the relative degree of response to light among depressed patients. Thus most studies report a robust antidepressant response in patients with winter-SAD (as reviewed by Rosenthal et al., 1988), whereas the relatively fewer studies performed to date on nonseasonal depressives have thus far shown a smaller degree of improvement (Kripke, Mullaney, Gillin, Risch, & Janowsky, 1985; Kripke, Mullaney, Savides, & Gillin, 1989). It would seem worthwhile to evaluate the degree of seasonality in other clinical populations in order to determine whether their response to treatment with bright light can be predicted. In this study we have administered the SPAQ to several clinical populations and to normal controls, and we report on our results in the present paper. Methods
A. The Instrument The SPAQ is a two-sided, single-page, self-administered questionnaire (Rosenthal, Genhart, & Jacobsen et al., 1987). Besides inquiring about routine demographic information, it asks questions aimed at determining retrospectively: (1) Severity of seasonal change in several items: sleeping, socializing, mood, weight, appetite and energy. By summing the scores obtained on these six items a global seasonality score (GSS) can be determined between 0-24. Further evidence of severity is obtained by asking whether the seasonal changes are experienced as a problem and, if so, to what degree. There are also
EVALUATION OF SEASONALITY IN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
77
questions that ask respondents to quantify changes in weight and sleep length across the seasons; (2) Pattern of seasonal change; patients are asked to note the months during which they feel best and worst, tend to socialize most and least, sleep most and least and gain and lose the most weight. In previous studies in which the SPAQ has been used, researchers have relied exclusively on months during which patients have felt worst in order to classify their seasonal pattern (Kasper, Wehr, & Bartko, 1989; Rosen et al., 1989). Patterns of recurrence that have resulted from such classification include " w i n t e r " (for those who feel worst in winter), " s u m m e r " , "winter-plus-summer", and "nonseasonal"; and (3) Sensitivity to climate and weather changes; several questions address the degree to which the individual is affected by cold, hot, humid, sunny, dry, cloudy, long, short and foggy days, as well as by pollen count.
B. The Populations Populations consisted of patients with winter-SAD, summer-SAD, subsyndromal winterSAD, bipolar affective disorder, major affective disorder, eating disorders (anorexia nervosa and bulimia), and two groups of normal controls. All patient groups had been recruited for a variety of other ongoing studies by means of advertisements or referrals, were diagnosed by means of standardized criteria (see Table 1), were studied in research settings, and provided informed consent for participation in this study. The one normal control group, designated "regular normals", was selected without regard to degree of seasonality, provided their seasonal changes did not constitute a clinical problem; the other normal control group, designated "nonseasonal n o r m a l s " , was specifically selected for a history of minimal seasonal changes. Such histories reflecting the presence or absence of seasonal difficulties were obtained as part of the screening clinical interview. As expected, a preponderance of female normal control subjects was recruited since most winter-SAD, summer-SAD, and subsyndromal winter-SAD patients were women. All groups were drawn from the Metropolitan Washington, D.C. area except for the patients with eating disorders and m a j o r depression, who were recruited nationwide and from the New York area, respectively. The questionnaires were administered to all subjects in a comparable way, in an outpatient clinic setting except in the case of the patients with eating disorders, who were studied on an inpatient unit. SPAQs were administered to patients with winter-SAD and eating disorders and regular normal subjects over the course of the year as part of a battery of screening questionnaires. In the other groups questionnaires were administered over a shorter interval, predominantly during the fall and winter months (see Table 1). Study populations consisted of 149 patients with winter-SAD, 33 patients with summerSAD, 20 patients with subsyndromal winter-SAD, 41 patients with eating disorders (10 with a history of anorexia nervosa, 31 with a history of bulimia), 28 bipolar patients, and 88 patients with RDC (Spitzer, Endicott, & Robins, 1978) or DSM-III (1980) major depression. A subgroup of those in our " m a j o r depression" group actually met RDC criteria for intermittent depression (n = 28) or DSM-III criteria for dysthymia (n = 19). These patients collectively met the Columbia criteria for atypical depression and were thus combined and treated as a single group.
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C. Scoring and Analysis Frequency counts were performed on all variables and descriptive statistics were computed. Comparisons were made across groups by multiple Chi-square or t-test analyses for categorical and continuous variables respectively, and Bonferroni corrections were made for multiple comparisons in interpreting significance levels. Groups were compared with regard to the following variables: age, marital status, years of education, global seasonality score (GSS), seasonal changes in sleep length and weight, and the degree to which seasonal changes were regarded as a problem. Seasonal patterns of behavior, based on four sets of dichotomous variables were tabulated. These included the months when patients felt best or worst; gained or lost the most weight; socialized most or least; and ate most or least. Those individuals whose reports were not internally consistent, for example if they said they felt best and worst in the same months, were removed from the analysis (n = 9). The anorexic and bulimic eating disorder subgroups reported seasonal responses that were sufficiently similar to consolidate these categories, thereby allowing us to use larger sample sizes and more powerful statistical comparisons. The same applied for the major depression subgroups. Since the winter-SAD, and eating disorder patients, and the regular normals were given the questionnaire during different seasons, we examined for possible influence of season on response by comparing global seasonality scores obtained during the spring and summer with those obtained during the fall and winter by means of group t-tests.
D. Test-retest Reliability The questionnaire was completed a second time by a subset of the winter-SAD and subsyndromal winter-SAD patients, and the nonseasonal normal groups. The mean (_+ SD) test-retest interval for the winter-SAD patients was 8.2 months (_+ 7.1 months). Corresponding mean and standard deviation values for subsyndromal winter-SAD patients and nonseasonal normal groups were 3.2 (_+ .8) and 3.1 (_+ .6), respectively. Test-retest reliability was evaluated for the 24 variables, by means of the Spearman-Brown intraclass correlation (Winer, 1971). Comparisons between our test-retest reliability values and those of Thompson et al. are shown in Table 2. Results
Clinical and Demographic Comparisons The clinical and demographic features of the six clinical and two normal populations are shown in Table 1. Multiple Chi-square and t-test comparisons between groups showed significant differences on many of the variables. Women outnumbered men in most groups by at least four to one. The most notable exceptions in this regard were the major depressives, where the sexes were more evenly balanced; the eating disorder group, who were exclusively female; and the regular normal group, where females predominated by about 25 to 1. The only groups that differed significantly in sex distribution were the major depressives who differed from both the eating disorder and the regular normal groups (Chisquare, 29.9 and 29.3, respectively, with DF= 1 and p < .05, respectively). The eating disorder patients and regular normal subjects were significantly younger than the oldest
EVALUATION OF SEASONALITY IN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
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g r o u p , the s u m m e r seasonals ( t = 5 . 1 , D F = 4 4 , p < .05; an d t = 4 . 2 , D F = 8 3 , p < .05, respectively). O t h e r w i s e there were no significant age differences b e t w e e n groups. M a r i t a l status v a r i e d across the g r o u p s , r a n g i n g f r o m 8°7o m a r r i e d in the eating disorder g r o u p to 60°7o m a r r i e d in the s u b s y n d r o m a l w i n t e r - S A D group. Th e difference between these two groups was significant (Chi-square = 28.2, D F = 3, p < .05). Th e eating disorders g r o u p also d i f f e r e d f r o m the n o n s e a s o n a l n o r m a l g r o u p in m a r i t a l status ( C h i - s q u a r e = 25.2, D F = 3, p < .05). Table 1
Demographic and Clinical Features Group
Age (years) Mean +_SD
M:F
N
Months of study
Inclusion criteria
Eating disorder
25.4*+4.7
0:41~
41
All months (over 2.5 years)
Regular normals 33.7*+ 10.0 1:26.5t
55
July-March
No psychiatric history, good health
Local periodical advertisement
Major affective disorders
37.2+ 11.3
l : 1.1
88
Oct-Apr
RDC Spitzer et al. (1978) DSM-III A.P.A. (1980)
Community outreach program
Winter-SAD
38.6 + 8.8
1:3.3
149
All months (over 3 years)
Rosenthal et al. (1984)
Local periodical advertisement, and referral
Nonseasonal normals
39.4 + 11.0
1:4
20
Dec-Feb
Kasper,Rogers and Yancey ( 1 9 8 9 )
Local periodical advertisement
Subsyndromal winter-SAD
39.7 + 7.1
1:4
20
Dec-Feb
Kasper, Rogers and Yancey ( 1 9 8 9 )
Local periodical advertisement
Bipolar
41.7 + 12.4
1:3.7
28
Oct-Nov
RDC Spitzer et al. (1978)
Referral
Summer-SAD
44.4 + 13.5
1: 1.4
33
Sep-Feb
Wehr et al. (1987)
Local periodical advertisement
DSM-III A.P.A. ( 1 9 8 0 )
Recruitment National periodical advertisement
*Significantly different from summer-SAD (p < .05) tSignificantly different from Major Affective Disorder (p < .05)
T e s t - r e t e s t Reliability T e s t - r e t e s t reliability o f the S P A Q is s h o w n in T ab l e 2. T h e w i n t e r - S A D g r o u p exhibited the highest overall t e s t - r e t e s t reliability, with 23 o f 24 items c o r r e l a t i n g at a statistically significant level (p < .05) a n d 19 o f these items h a v i n g c o r r e l a t i o n coefficients o f 0.7 or greater. T e s t - r e t e s t reliability was s o m e w h a t lower for the t w o o t h er g r o u p s in w h o m these d a t a were available. In these latter tw o g r o u p s certain items p r o v e d m o r e reliable, such as seasonal variation in energy level, whereas others showed p o o r reliability, such as seasonal v a r i a t i o n in social activity. T h e m o s t reliable overall i n d i c a t o r o f severity o f seasonal
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TODD A. HARDIN et al.
Table 2
Test-retest Reliability in Four Populations Group
Thompson et al. (winter-SAD, London)
Hardin et al. (winter-SAD, Washington)
(n = 20)
(n = 50)
Kasper et al. (subsyndromal winter-SAD Washington) (n = 20)
Kasper et al. (nonseasonal normals, Washington) (n = 20)
.72 Not reported Not reported Not reported NS Not reported
.80 .72 .71 .80 .68 .67
.80 .49 .58 .80 .57 .76
.32 .35 .50 .33 .48 .90
.67 .80 .715
.49 .80 .67
.32 .90 .415
.80
.44
.61
Reactivity to environmental variables: cold NS hot .74 humid NS sunny .73 dry .72 grey/cloudy NS long NS high pollen NS foggy, smoggy NS short NS
.94 .85 .87 .70 .59 .72 .64 .94 .89 .90
.44 .75 .78 .77 .62 .64 .53 .97 .46 .99
.74 .21 .26 .34 .32 .81 .72 .86 .78 .70
Low High Median
.59 .94 .86
.44 .99 .70
.21 .86 .71
Item Severity of seasonal change: sleep length social activity mood weight appetite energy level Low High Median Global Seasonality Score (sum of above 6 items)
Not reported
Weight change over the year
.74
.78
.79
.46
Sleep length during different seasons: winter spring summer fall
.83 .78 .77 .80
.89 .82 .80 .91
.94 .71 .27 .76
.89 .84 .96 .85
Low High Median
.77 .80 .79
.80 .91 .855
.27 .91 .735
.84 .96 .87
Not reported
.54
.81
.64
.79
.80
.74
1.00
Food preference Degree to which seasonal changes present a problem
Spearman's rank order correlations were used for all data of Thomson et al. (1988). All other correlation coefficients shown were derived by Spearman-Brown intraclass correlations.
EVALUATION OF SEASONALITY IN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
81
variation was the response to the question "do the changing seasons present a problem for you?" The global seasonality score was equally reliable for winter-SAD patients but was less so for subsyndromal winter-SAD and nonseasonal normal individuals. There was no significant difference between global seasonality scores obtained during the spring and summer and those obtained during the fall and winter in the winter-SAD group, eating disorder patients, and regular normals.
Comparison of Seasonal Changes and Weather Sensitivity Among Groups On the six questions about severity of seasonal changes in m o o d and behavior, winterSAD patients consistently scored highest, while the nonseasonal normal group scored lowest (see Figure 1). The summer-SAD and eating disorders groups consistently scored the next highest across variables. The subsyndromal winter-SAD group tended to have scores approximately half way between the winter-SAD and nonseasonal normal groups, and the bipolar and major depressed groups scored just below the subsyndromal subjects. Global seasonality scores (the sum of the 6 individual behavioral variables) yielded results consistent with the component behavioral items as one would have predicted. Global seasonality scores discriminated between the more seasonal groups (winter-SAD, eating disorders, summerSAD, and subsyndromal winter-SAD) and the other, less seasonal groups. Information about how severe a problem the seasonal changes were to the different groups yielded very similar results.
16
~AD
W~AD S~AO ~sAo
W~AO
W~%AD
S.SXD
s=b
EO 2
EO S~AD
W~AD
Sub
I
-3
eP
SSAO EO Be
ep 1
12
• ED
Sub
Sub
MD
MD
I,o
W~SAD / ' l
ae HL
.
iio Me
NL
nP
MO
NL
L"*
NL
NSH
, NSN
~N
NL
• NSN 0
I sleep
I
I
I
social
mood
weight Symptom
I appetite
I energy
Global Seasonality
"7 Degree of Problem
Score (GSS)
Figure 1. The degree of seasonal variation for individual behavioral variables, the global seasonality score (the sum of these variables), and for the extent to which individuals experience the changing seasons as a problem, are shown in this figure. Bracketed groups do not differ significantly from one another. W - S A D = Winter-Seasonal Affective Disorder; S - S A D = Summer-Seasonal Affective Disorder; Sub = Subsyndromal Winter-Seasonal Affective Disorder; B P = Bipolar Disorder; M D = Major Affective Disorder; N S N = Nonseasonal Normals; E D = Eating Disorders; N L - R e g u l a r Normals.
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TODD A. HARDIN et al. SU MME.R-SAD (N--33)
SUBSYNOROMAL W1NTER-SAD(-N=20)
+
-'mm JUL A U G SEP O C T N O V D E C JAN FEB M A R APR ),lAY JUN
~
JUL A U G SEP OC:T N O V [DEC JAN FEB M A R APR M A Y JUN
NONSEASONAL NORMALS (N.=20)
WINTER-SAD (#4=149)
- - m
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
m
m
- - - - m m m
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
REGULAR NORMALS (14=55)
+ +
m
EAriNG D(SORDERS (N=41)
+l +l JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
~
BIPOLARS (N=28)
JLIL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
MAJOR DEPRESSION (N=88)
~
mmmmm
m
~
JUL AUG SEP OCT NOV DEC JAN FEB MAR APFI MAY JUN
Figure 2. The pattern of response to the questions " I n which months do you feel b e s t ? " , and " I n which months do you feel w o r s t ? " are shown in this figure. Bars represent the percentage of the population who report feeling best or worst in each month. Those individuals who reported no particular months when they felt best or worst are excluded from the figure.
EVALUATION OF SEASONALITYIN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
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Questions about sleep durations in different seasons revealed significant differences among groups ( F = 7.92; D F = 21,1317; p < .001). As might have been predicted, patients with winter-SAD showed the greatest average difference in sleep length between the season of longest sleep duration (winter) and that of shortest duration (summer), 2.56 h, followed by patients with subsyndromal winter-SAD (summer-winter sleep difference = 1.65 h), eating disorders (1.12 h) and summer-SAD (1.07 h). All the other groups reported sleep differences of less than one hour across the seasons. There were certain underlying similarities in the patterns of seasonal change across all groups except for the summer-SAD patients (see Figure 2), who uniformly reported summer as the time of year when they felt worst. All the rest, with the exception of the nonseasonal normals, tended to like spring the most, followed by summer and fall, and tended to like winter least. In most groups there was little overlap between when subjects felt best and when they felt worst. The amplitude of the reported seasonal rhythms corresponded to the severity of reported seasonal changes; that is, those groups with the highest global seasonality scores showed the greatest amplitudes (see Figure 2). Comparisons of weather sensitivity between groups showed the summer-SAD patients responding differently from the other groups. They liked cold weather and disliked hot weather more than the other groups. Apart from these responses, there was considerable overlap between groups in their responses to the weather variables. Discussion This is the second study in which the SPAQ has been used to discriminate between different degrees of retrospectively reported seasonal variation in different clinical populations. Thompson et al. (1988) found that winter-SAD patients differed significantly from normal controls on several measures of seasonal change derived from the SPAQ, while bipolar patients occupied an intermediate position between these two groups. These findings are consistent with ours in that in both studies winter-SAD patients and regular normals scored significantly differently on most items reflecting severity of seasonal change, and bipolar subjects were statistically more similar to regular normal subjects than to patients with winter-SAD. These findings suggest that in inquiring about seasonality, the SPAQ is indeed eliciting information about seasonal changes rather than about nonseasonal fluctuations in mood and behavior since the latter would presumably occur to a far greater degree in bipolar patients than in normal controls, but would not necessarily discriminate between bipolar patients and those with winter-SAD. The relative normality of seasonal severity scores in both bipolar and major depressive populations suggests that seasonality may be a dimension that cuts across individuals with varying vulnerabilities to affective disturbance, rather than a simple function of mood dysregulation. One difference between the present study and that of Thompson et al. (1988) is that in the British study the bipolar patients were significantly more seasonal than the normal controls, whereas in the present study the bipolars and major depressives were not significantly more seasonal than the normal controls. In reviewing the literature on affective disorders, we have noted that there is strong evidence of a bimodal seasonal influence on timing of episodes, with both summer and winter peaks (Wehr & Rosenthal, 1989). We
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TODD A . HARDIN et al.
have thus suggested that seasonal influences are important in affectively disturbed populations not selected specifically for their seasonality. This suggestion needs to be reconciled with our present observation that bipolar and m a j o r depressive patients were not abnormally seasonal. Possible explanations for the similar seasonality scores in patient and normal groups are as follows: (1) even though the seasonality scores of the bipolar and m a j o r depressive groups were no greater than that of the general population, all of these groups were seasonal to some degree and this degree of seasonality may be sufficient to exert a significant influence on patterns of hospital admissions for depression or prescriptions of antidepressants; (2) the bipolar and m a j o r depressive populations we studied were treated in research settings and might not have been as seasonal as patients with these diagnoses studied elsewhere. For instance, the bipolar patients of T h o m p s o n et al. had an average global seasonality score of approximately 9.5 as compared with our bipolar patients whose average global seasonality score was approximately 8; and (3) the failure of the SPAQ to distinguish between the affectively disturbed groups and the normal group may reflect a deficiency in the instrument itself. Reliability over time appeared to be greater for those with higher degrees of seasonal change, namely patients with winter-SAD and subsyndromal winter-SAD than for nonseasonal normal controls. Nonseasonal normal individuals showed high levels of reliability on certain items, such as those pertaining to sleep length, reactivity to certain weather variables and global severity of seasonality. On the other hand, reliability scores on other items are unacceptably low and inferences based on these items need to be made with appropriate caution. It is worth noting that test-retest scores were highly reliable in the winter-SAD population despite the far greater variability of the interval between administrations (mean _+S D : 8.2 _+7.1 months), suggesting that test-retest reliability holds up to some degree across seasons. It would be valuable to obtain more data on test-retest reliability in a wider set of populations and at more uniform intervals. Test-retest reliability scores for winter-SAD patients were somewhat lower in the British than in the U.S. study. This difference may be related to methodological differences between studies, namely: (1) the use of different statistical techniques, Spearman rank order correlation in the British study, and Spearman-Brown intraclass correlation in our study; (2) different sample size, 20 in the British study and 50 in our study; and (3) different intervals between tests. In contrast to the findings of Thompson et al., we found reasonable test-retest reliability for several items related to weather variables. Comparisons of seasonal changes between groups indicated that apart from the groups recruited specifically for a history of marked seasonal changes (the winter-SAD, summerSAD, and subsyndromal winter-SAD groups), those with eating disorders reported the highest degree of seasonality. Indeed, there was no significant difference between eating disorder and winter-SAD groups on global seasonality score and most of the subscores that form this index. This high degree of seasonality among eating disorder patients, together with their overall dislike of the winter months, would make them good candidates for phototherapy studies. Insofar as being female is a risk factor for seasonality (Kasper, Wehr, & Bartko, 1989), the higher female to male ratio in the eating disorder group might have influenced the overall seasonality scores. Nonetheless, the female to male ratio was not
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different from that of the regular normal group, whose seasonality scores were significantly lower. Conversely, the seasonality scores of the major depression group might have been lowered by the more balanced sex ratio in that group. All groups with the exception of the summer seasonals expressed a greater aversion for the winter than for the summer, which is in keeping with seasonal preferences in the general population at an equivalent latitude (Terman, 1989; Kasper, Wehr, & Bartko, 1989). Reported seasonal changes in sleep and other behaviors also show a similar pattern in clinical groups and the general population. In other words, most groups--regular normals included--reported increased sleeping, increased eating and weight gain in the winter compared with the summer. In fact, even summer-SAD patients report this pattern of seasonal variation. However, insofar as they become depressed in the summer, sleep loss, anorexia and weight loss are part of their depressive syndrome. The reverse applies for winter-SAD patients (Wehr et al., 1989; Wehr & Rosenthal, 1989). Although winter was the least preferred season for most subjects, there is evidence that summer was also disliked by some individuals in those groups not selected specifically for their seasonality, specifically the nonseasonal depressives, eating disorder patients and regular normals. Adverse influences of summer, as well as winter, have been documented in other studies (Wehr & Rosenthal, 1989). Conclusion In summary, the Seasonal Pattern Assessment Questionnaire (SPAQ) appears to be a useful instrument for evaluating seasonality retrospectively. The SPAQ discriminates successfully between groups who would be expected to differ along a seasonal dimension, for example winter-SAD patients and normal controls. In addition, it has the potential to identify groups whom one might not expect to be highly seasonal, for example, eating disorder patients. Such a finding may be useful insofar as severity of seasonality--associated with an aversion to winter--appears to be a predictor of beneficial mood and behavioral response to phototherapy (Kasper, Rogers, & Yancey, 1989). It would thus seem worthwhile to study the effects of phototherapy in eating disorder patients. An interesting negative finding of this study is that nonseasonally depressed patients do not differ significantly from regular normal subjects in their degree of seasonality. This suggests that seasonality may be a dimension of human behavior transmitted separately from vulnerability to depression. Family and twin studies focusing on heritability of seasonality--as opposed to affective vulnerability--would also seem to be worth undertaking. The relatively low degree of seasonality seen in bipolar and major depressed groups could be taken to suggest that these groups are less likely to benefit from light therapy than winter-SAD patients. Although the overall seasonality score did not differentiate patients with major depression and bipolar disorder patients from regular normals, the prevalence of winter-SAD in the former two groups, as determined by previously derived SPAQ criteria, was 14o7oand 10°70 respectively. These figures are very similar to prevalence estimates of winter-SAD in other major depressive populations.Thus Thase (1986), applying the criteria of Rosenthal et al. (1984), reported a 16.1°70 prevalence of winter-SAD in a clinic for outpatient treatment of recurrent depressives. More recently Kasper (in press),
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applying SPAQ-derived criteria, found a 15% prevalence o f winter-SAD in an outpatient group o f depressives in West Germany. These consistent findings across centers that one in six outpatient depressives have a history of seasonal changes equivalent in severity to those seen in winter-SAD patients, may have therapeutic relevance, given the relationship between seasonality and response to light therapy. Clinicians should thus be on the lookout for seasonality in recurrent depressives who do not label themselves as having winter-SAD, and the S P A Q might be a useful screening instrument to diagnose such patients. Acknowledgement--The authors wish to thank Connie Carpenter for assistance in administering questionnaires, Dr. John Bartko for statistical consultation, and Dennis George for computer programming expertise.
REFERENCES American Psychiatric Association (1980). Diagnostic" and statistical manual o f mental disorders. American Psychiatric Association, Washington, DC. Boyce, P., & Parker, G. (1988). Seasonal affective disorder in the southern hemisphere. American Journal o f Psychiatry, 145, 96-99. Jones, W. H. S., & Wittington, E. T. (Eds & Trans) (1923-1931) Works o f Hippocrates. Regimen in health. Harvard University, Cambridge, MA. Kasper, S., Rogers, S. L. B., Madden, P. A., Joseph-Vanderpool, J. R., & Rosenthal, N. E. (1988). The effects ofphototherapy in the general population. Abstract presented at the 141st annual meeting of the American Psychiatric Association. Kasper, S., Wehr, T. A., Bartko, J. J., Gaist, P. A., & Rosenthal, N. E. (1989). Epidemiological findings of seasonal changes in mood and behavior. Archives o f General Psychiatry, 46, 823-833. Kasper, S., Rogers, S. L. B., Yancey, A., Schulz, P. M., Skwerer, R. G., & Rosenthal, N. E. (1989). Phototherapy in individuals with and without subsyndromal seasonal affective disorder. Archives o f General Psychiatry, 46, 837-844. Kasper, S., & Kamo, T. (in press). Seasonality in major depressed inpatients. Journal o f Affective Disorders. Kripke, D. F., Mullaney, D. J., Gillin, J. C., Risch, S. C., & Janowsky, D. S. 0985). Phototherapy o f nonseasonal depression in biological psychiatry (pp. 993-995). New York: Elsevier Science Publishing. Lewy, A. J., Kern, H. E., & Rosenthal, N. E. (1982). Bright artificial light treatment of a manic-depressive patient with a seasonal mood cycle. American Journal o f Psychiatry, 139, 1496-1498. Rosen, L. N., Targum, S. D., Terman, M., Bryant, M. J., Hoffman, H., Kasper, S., Hamovit, J. R., Docherty, J. P., Welch, B., & Rosenthal, N. E. (1989). Prevalence of seasonal affective disorder at four latitudes. Psychiatry Research, 31, 131-144. Rosenthal, N. E., Sack, D. A., Gillin, J. C., Lewy, A. J., Goodwin, F. K., Davenport, Y., Mueller, P. S., Newsome, D. A., & Wehr, T. A. (1984). Seasonal affective disorder: a description of the syndrome and preliminary findings with light therapy. Archives o f General Psychiatry, 41, 72-80. Rosenthal, N. E., Genhart, M. J., Jacobsen, F. M., Skwerer, R. G., & Wehr, T. A. (1987a). Disturbances of appetite and weight regulation in seasonal affective disorder. Annals o f the New York Academy o f Sciences, 499, 216-230. Rosenthal, N. E., Rotter, A., Jacobsen, F. M., & Skwerer, R. G. (1987b). No mood-altering effects found after treatment of normal subjects with bright light in the morning. Psychiatry Research, 22, 1-9. Rosenthal, N. E., Sack, D. A., Skwerer, R. G., Jacobsen, F. M., & Wehr, T. A. (1988). Phototherapy for seasonal affective disorder. Journal o f Biological Rhythms, 3, 101-120. Spitzer, R. L., Endicott, J., & Robins, E. (1978). Research diagnostic criteria: Rationale and reliability. Archives o f General Psychiatry, 35, 773-782. Terman, M. (1988). On the question of mechanism in phototherapy: consideration of clinical efficacy and epidemiology. Journal o f Biological Rhythms, 3, 155-172. Terman, M., Botticelli, S. R., Link, B., Hardin, T. A., & Rosenthal, N. E. (1989). Patterns of seasonality in New York patients and population. In Thompson, C. and Silverstone (Eds) Seasonalaffective disorder. CRC Neuroscience Press, London. Thase, M. E. (1986). Interview: Defining and treating seasonal affective disorder. Psychiatry Annals, 16, 733-737.
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Thompson, C., Stinson, D., Fernandez, M., Fine, J., & Isaacs, G. (1988). A comparison of normal, bipolar and seasonal affective disorder subjects using the Seasonal Pattern Assessment Questionnaire. Journal of Affective Disorders, 14, 257-264. Wehr, T. A., Sack, D. A., & Rosenthal, N. E. (1987). Seasonal affective disorder with summer depression and winter hypomania. American Journal of Psychiatry, 144, 12. Wehr, T. A., Giesen, H., Schulz, P. M., Joseph-Vanderpool, J. R., Kelly, K., Kasper, S., & Rosenthal, N. E. (1989). Summer depression: description of the syndrome and comparison with winter depression. In N. E. Rosenthal and M. Blehar (Eds) Seasonal affective disorders and phototherapy. New York: Guilford Press. Wehr, T. A., & Rosenthal, N. E. (1989). Seasonality and affective illness. American Journal of Psychiatry, 146, 829-839. Winer, B. J. (1971). Statistical principles in experimental design. New York: McGraw-Hill.
EVALUATION POPULATIONS
0022-3956/91 $3.00 + .00 (c 1991 Pergamon Press plc
OF SEASONALITY AND
TWO
IN SIX CLINICAL
NORMAL
POPULATIONS
TODD A. HARDIN, I THOMAS A. WEHR, 1 TIMOTHY BREWERTON, 2 SIEGFRIED KASPER, 3 WADE BERRETTINI, 4 JUDITH RABKIN 5 a n d NORMAN E. ROSENTHAL 1 IClinical Psychobiology Branch, NIMH, Bethesda, MD, U.S.A.; 2Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, SC, U.S.A.; 3psychiatric Department, University of Bonn, Bonn, F.R.G.; 4Clinic Neurogenetics Branch, N1MH, Bethesda, MD, U.S.A.; and 5New York State Psychiatric Institute, New York, NY, U.S.A.
(Received 10 July 1989; revised 10 September 1990) Summary--The Seasonal Pattern Assessment Questionnaire (SPAQ) was used to evaluate retrospectively self-reported seasonal changes in mood and behavior (seasonality) of two normal and six clinical populations: patients with winter-seasonal affective disorder (SAD), summer-SAD, eating disorders, bipolar affective disorder, major depressive disorder and subsyndromal winterSAD. The SPAQ successfully discriminated between groups expected to have high seasonality scores, such as winter-SAD, summer-SAD and subsyndromal winter-SAD, and normal controls. Bipolars and major depressives had normal seasonality scores. Patients with eating disorders had unexpectedly high scores. There was a general tendency for all groups to eat and sleep more and to gain weight in the winter. The implications of these findings are discussed.
Introduction ALTHOUGHthe seasonal influence on the timing of manic and depressive episodes has been recognized since classical times (Jones & Wittington, 1923-1931), there has been a recent surge of interest in this area, inspired by the recognition of patients with regularly recurring fall-winter depressions, which can be reversed by bright environmental light (Lewy, Kern, & Rosenthal, 1982; Rosenthal et al., 1984). Since winter-seasonal affective disorder (winterSAD) was first described, it has become apparent that the tendency for people to experience seasonal changes in mood and behavior (seasonality) is not confined to severely affected individuals, but appears to vary in degree across the normal population (Terman, 1988; Kasper, Wehr, Bartko, Gaist, & Rosenthal, 1989; Rosen et al., 1989). It has also become apparent that some patients experience regular summer depressions alternating with remissions in the winter (Wehr, Sack, & Rosenthal, 1987; Boyce & Parker, 1988). We will refer to these patients as suffering from summer-SAD and those with recurrent winter depression as suffering from winter-SAD. Indeed, a great majority of the general population report seasonal changes, and according to the epidemiological studies mentioned above, 20-25% regard these changes as a problem. These studies have used the Seasonal Pattern Assessment Questionnaire (SPAQ) (Rosenthal, Genhart, Jacobsen, Skwerer, & Wehr, 1987), an instrument we developed in order to Please address all correspondence to: Todd Hardin, Clinical Psychobiology Branch, NIMH, Bldg 10, Room 4S-239, 9000 Rocksville Pike, Bethesda, MD 20892, U.S.A. Tel. (301) 496-2141. 75
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TODD A. HARDIN et al.
evaluate retrospectively the pattern and degree of an individual's seasonal changes in mood and behaviour. In the study by Kasper, Wehr, and Bartko (1989), case finding criteria for winter-SAD and subsyndromal winter-SAD, as derived from the SPAQ, yielded conservative prevalence estimates when compared with clinical criteria applied to a representative subsample of the population. In the study by Rosen et al. (1989), the degree of reported seasonality, as measured by the SPAQ, correlated significantly with latitude. The questionnaire can be administered to a variety of populations, and the degree of seasonal variation for different groups can be derived. Thus, Thompson, Stinson, Fernandez, Fine, and Isaacs (1988) administered the instrument to patients with winter-SAD, bipolar disorder, and normal controls, and found that the questionnaire discriminated between these three groups. As anticipated, the winter-SAD group showed a significantly greater degree of seasonal change than normal controls, and the bipolar group tended to fall in between. Patients with winter-SAD and subsyndromal winter-SAD, who have been shown to respond favorably to bright environmental light (For review see Rosenthal, Sack, Skwerer, Jacobsen, & Wehr, 1988; Kasper, Rogers, & Yancey, 1989; Terman, Botticelli, Link, Hardin, & Rosenthal, 1989), reported a higher degree of seasonality than normal individuals without histories of winter difficulties, who do not appear to benefit from exposure to bright light (Rosenthal, Rotter, Jacobsen, & Skwerer, 1987b). The SPAQ distinguishes between these populations and thus has predictive value for response to phototherapy. To judge from the above studies, the SPAQ appears to be a useful and valid instrument for evaluating an individual's history of seasonality. Just as the severity of winter difficulties appears to predict responsiveness to bright light in subsyndromal winter-SAD and normal individuals, so such a history may predict the relative degree of response to light among depressed patients. Thus most studies report a robust antidepressant response in patients with winter-SAD (as reviewed by Rosenthal et al., 1988), whereas the relatively fewer studies performed to date on nonseasonal depressives have thus far shown a smaller degree of improvement (Kripke, Mullaney, Gillin, Risch, & Janowsky, 1985; Kripke, Mullaney, Savides, & Gillin, 1989). It would seem worthwhile to evaluate the degree of seasonality in other clinical populations in order to determine whether their response to treatment with bright light can be predicted. In this study we have administered the SPAQ to several clinical populations and to normal controls, and we report on our results in the present paper. Methods
A. The Instrument The SPAQ is a two-sided, single-page, self-administered questionnaire (Rosenthal, Genhart, & Jacobsen et al., 1987). Besides inquiring about routine demographic information, it asks questions aimed at determining retrospectively: (1) Severity of seasonal change in several items: sleeping, socializing, mood, weight, appetite and energy. By summing the scores obtained on these six items a global seasonality score (GSS) can be determined between 0-24. Further evidence of severity is obtained by asking whether the seasonal changes are experienced as a problem and, if so, to what degree. There are also
EVALUATION OF SEASONALITY IN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
77
questions that ask respondents to quantify changes in weight and sleep length across the seasons; (2) Pattern of seasonal change; patients are asked to note the months during which they feel best and worst, tend to socialize most and least, sleep most and least and gain and lose the most weight. In previous studies in which the SPAQ has been used, researchers have relied exclusively on months during which patients have felt worst in order to classify their seasonal pattern (Kasper, Wehr, & Bartko, 1989; Rosen et al., 1989). Patterns of recurrence that have resulted from such classification include " w i n t e r " (for those who feel worst in winter), " s u m m e r " , "winter-plus-summer", and "nonseasonal"; and (3) Sensitivity to climate and weather changes; several questions address the degree to which the individual is affected by cold, hot, humid, sunny, dry, cloudy, long, short and foggy days, as well as by pollen count.
B. The Populations Populations consisted of patients with winter-SAD, summer-SAD, subsyndromal winterSAD, bipolar affective disorder, major affective disorder, eating disorders (anorexia nervosa and bulimia), and two groups of normal controls. All patient groups had been recruited for a variety of other ongoing studies by means of advertisements or referrals, were diagnosed by means of standardized criteria (see Table 1), were studied in research settings, and provided informed consent for participation in this study. The one normal control group, designated "regular normals", was selected without regard to degree of seasonality, provided their seasonal changes did not constitute a clinical problem; the other normal control group, designated "nonseasonal n o r m a l s " , was specifically selected for a history of minimal seasonal changes. Such histories reflecting the presence or absence of seasonal difficulties were obtained as part of the screening clinical interview. As expected, a preponderance of female normal control subjects was recruited since most winter-SAD, summer-SAD, and subsyndromal winter-SAD patients were women. All groups were drawn from the Metropolitan Washington, D.C. area except for the patients with eating disorders and m a j o r depression, who were recruited nationwide and from the New York area, respectively. The questionnaires were administered to all subjects in a comparable way, in an outpatient clinic setting except in the case of the patients with eating disorders, who were studied on an inpatient unit. SPAQs were administered to patients with winter-SAD and eating disorders and regular normal subjects over the course of the year as part of a battery of screening questionnaires. In the other groups questionnaires were administered over a shorter interval, predominantly during the fall and winter months (see Table 1). Study populations consisted of 149 patients with winter-SAD, 33 patients with summerSAD, 20 patients with subsyndromal winter-SAD, 41 patients with eating disorders (10 with a history of anorexia nervosa, 31 with a history of bulimia), 28 bipolar patients, and 88 patients with RDC (Spitzer, Endicott, & Robins, 1978) or DSM-III (1980) major depression. A subgroup of those in our " m a j o r depression" group actually met RDC criteria for intermittent depression (n = 28) or DSM-III criteria for dysthymia (n = 19). These patients collectively met the Columbia criteria for atypical depression and were thus combined and treated as a single group.
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TODDA. HARDINet al.
C. Scoring and Analysis Frequency counts were performed on all variables and descriptive statistics were computed. Comparisons were made across groups by multiple Chi-square or t-test analyses for categorical and continuous variables respectively, and Bonferroni corrections were made for multiple comparisons in interpreting significance levels. Groups were compared with regard to the following variables: age, marital status, years of education, global seasonality score (GSS), seasonal changes in sleep length and weight, and the degree to which seasonal changes were regarded as a problem. Seasonal patterns of behavior, based on four sets of dichotomous variables were tabulated. These included the months when patients felt best or worst; gained or lost the most weight; socialized most or least; and ate most or least. Those individuals whose reports were not internally consistent, for example if they said they felt best and worst in the same months, were removed from the analysis (n = 9). The anorexic and bulimic eating disorder subgroups reported seasonal responses that were sufficiently similar to consolidate these categories, thereby allowing us to use larger sample sizes and more powerful statistical comparisons. The same applied for the major depression subgroups. Since the winter-SAD, and eating disorder patients, and the regular normals were given the questionnaire during different seasons, we examined for possible influence of season on response by comparing global seasonality scores obtained during the spring and summer with those obtained during the fall and winter by means of group t-tests.
D. Test-retest Reliability The questionnaire was completed a second time by a subset of the winter-SAD and subsyndromal winter-SAD patients, and the nonseasonal normal groups. The mean (_+ SD) test-retest interval for the winter-SAD patients was 8.2 months (_+ 7.1 months). Corresponding mean and standard deviation values for subsyndromal winter-SAD patients and nonseasonal normal groups were 3.2 (_+ .8) and 3.1 (_+ .6), respectively. Test-retest reliability was evaluated for the 24 variables, by means of the Spearman-Brown intraclass correlation (Winer, 1971). Comparisons between our test-retest reliability values and those of Thompson et al. are shown in Table 2. Results
Clinical and Demographic Comparisons The clinical and demographic features of the six clinical and two normal populations are shown in Table 1. Multiple Chi-square and t-test comparisons between groups showed significant differences on many of the variables. Women outnumbered men in most groups by at least four to one. The most notable exceptions in this regard were the major depressives, where the sexes were more evenly balanced; the eating disorder group, who were exclusively female; and the regular normal group, where females predominated by about 25 to 1. The only groups that differed significantly in sex distribution were the major depressives who differed from both the eating disorder and the regular normal groups (Chisquare, 29.9 and 29.3, respectively, with DF= 1 and p < .05, respectively). The eating disorder patients and regular normal subjects were significantly younger than the oldest
EVALUATION OF SEASONALITY IN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
79
g r o u p , the s u m m e r seasonals ( t = 5 . 1 , D F = 4 4 , p < .05; an d t = 4 . 2 , D F = 8 3 , p < .05, respectively). O t h e r w i s e there were no significant age differences b e t w e e n groups. M a r i t a l status v a r i e d across the g r o u p s , r a n g i n g f r o m 8°7o m a r r i e d in the eating disorder g r o u p to 60°7o m a r r i e d in the s u b s y n d r o m a l w i n t e r - S A D group. Th e difference between these two groups was significant (Chi-square = 28.2, D F = 3, p < .05). Th e eating disorders g r o u p also d i f f e r e d f r o m the n o n s e a s o n a l n o r m a l g r o u p in m a r i t a l status ( C h i - s q u a r e = 25.2, D F = 3, p < .05). Table 1
Demographic and Clinical Features Group
Age (years) Mean +_SD
M:F
N
Months of study
Inclusion criteria
Eating disorder
25.4*+4.7
0:41~
41
All months (over 2.5 years)
Regular normals 33.7*+ 10.0 1:26.5t
55
July-March
No psychiatric history, good health
Local periodical advertisement
Major affective disorders
37.2+ 11.3
l : 1.1
88
Oct-Apr
RDC Spitzer et al. (1978) DSM-III A.P.A. (1980)
Community outreach program
Winter-SAD
38.6 + 8.8
1:3.3
149
All months (over 3 years)
Rosenthal et al. (1984)
Local periodical advertisement, and referral
Nonseasonal normals
39.4 + 11.0
1:4
20
Dec-Feb
Kasper,Rogers and Yancey ( 1 9 8 9 )
Local periodical advertisement
Subsyndromal winter-SAD
39.7 + 7.1
1:4
20
Dec-Feb
Kasper, Rogers and Yancey ( 1 9 8 9 )
Local periodical advertisement
Bipolar
41.7 + 12.4
1:3.7
28
Oct-Nov
RDC Spitzer et al. (1978)
Referral
Summer-SAD
44.4 + 13.5
1: 1.4
33
Sep-Feb
Wehr et al. (1987)
Local periodical advertisement
DSM-III A.P.A. ( 1 9 8 0 )
Recruitment National periodical advertisement
*Significantly different from summer-SAD (p < .05) tSignificantly different from Major Affective Disorder (p < .05)
T e s t - r e t e s t Reliability T e s t - r e t e s t reliability o f the S P A Q is s h o w n in T ab l e 2. T h e w i n t e r - S A D g r o u p exhibited the highest overall t e s t - r e t e s t reliability, with 23 o f 24 items c o r r e l a t i n g at a statistically significant level (p < .05) a n d 19 o f these items h a v i n g c o r r e l a t i o n coefficients o f 0.7 or greater. T e s t - r e t e s t reliability was s o m e w h a t lower for the t w o o t h er g r o u p s in w h o m these d a t a were available. In these latter tw o g r o u p s certain items p r o v e d m o r e reliable, such as seasonal variation in energy level, whereas others showed p o o r reliability, such as seasonal v a r i a t i o n in social activity. T h e m o s t reliable overall i n d i c a t o r o f severity o f seasonal
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TODD A. HARDIN et al.
Table 2
Test-retest Reliability in Four Populations Group
Thompson et al. (winter-SAD, London)
Hardin et al. (winter-SAD, Washington)
(n = 20)
(n = 50)
Kasper et al. (subsyndromal winter-SAD Washington) (n = 20)
Kasper et al. (nonseasonal normals, Washington) (n = 20)
.72 Not reported Not reported Not reported NS Not reported
.80 .72 .71 .80 .68 .67
.80 .49 .58 .80 .57 .76
.32 .35 .50 .33 .48 .90
.67 .80 .715
.49 .80 .67
.32 .90 .415
.80
.44
.61
Reactivity to environmental variables: cold NS hot .74 humid NS sunny .73 dry .72 grey/cloudy NS long NS high pollen NS foggy, smoggy NS short NS
.94 .85 .87 .70 .59 .72 .64 .94 .89 .90
.44 .75 .78 .77 .62 .64 .53 .97 .46 .99
.74 .21 .26 .34 .32 .81 .72 .86 .78 .70
Low High Median
.59 .94 .86
.44 .99 .70
.21 .86 .71
Item Severity of seasonal change: sleep length social activity mood weight appetite energy level Low High Median Global Seasonality Score (sum of above 6 items)
Not reported
Weight change over the year
.74
.78
.79
.46
Sleep length during different seasons: winter spring summer fall
.83 .78 .77 .80
.89 .82 .80 .91
.94 .71 .27 .76
.89 .84 .96 .85
Low High Median
.77 .80 .79
.80 .91 .855
.27 .91 .735
.84 .96 .87
Not reported
.54
.81
.64
.79
.80
.74
1.00
Food preference Degree to which seasonal changes present a problem
Spearman's rank order correlations were used for all data of Thomson et al. (1988). All other correlation coefficients shown were derived by Spearman-Brown intraclass correlations.
EVALUATION OF SEASONALITY IN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
81
variation was the response to the question "do the changing seasons present a problem for you?" The global seasonality score was equally reliable for winter-SAD patients but was less so for subsyndromal winter-SAD and nonseasonal normal individuals. There was no significant difference between global seasonality scores obtained during the spring and summer and those obtained during the fall and winter in the winter-SAD group, eating disorder patients, and regular normals.
Comparison of Seasonal Changes and Weather Sensitivity Among Groups On the six questions about severity of seasonal changes in m o o d and behavior, winterSAD patients consistently scored highest, while the nonseasonal normal group scored lowest (see Figure 1). The summer-SAD and eating disorders groups consistently scored the next highest across variables. The subsyndromal winter-SAD group tended to have scores approximately half way between the winter-SAD and nonseasonal normal groups, and the bipolar and major depressed groups scored just below the subsyndromal subjects. Global seasonality scores (the sum of the 6 individual behavioral variables) yielded results consistent with the component behavioral items as one would have predicted. Global seasonality scores discriminated between the more seasonal groups (winter-SAD, eating disorders, summerSAD, and subsyndromal winter-SAD) and the other, less seasonal groups. Information about how severe a problem the seasonal changes were to the different groups yielded very similar results.
16
~AD
W~AD S~AO ~sAo
W~AO
W~%AD
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s=b
EO 2
EO S~AD
W~AD
Sub
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-3
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SSAO EO Be
ep 1
12
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Sub
MD
MD
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ae HL
.
iio Me
NL
nP
MO
NL
L"*
NL
NSH
, NSN
~N
NL
• NSN 0
I sleep
I
I
I
social
mood
weight Symptom
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Global Seasonality
"7 Degree of Problem
Score (GSS)
Figure 1. The degree of seasonal variation for individual behavioral variables, the global seasonality score (the sum of these variables), and for the extent to which individuals experience the changing seasons as a problem, are shown in this figure. Bracketed groups do not differ significantly from one another. W - S A D = Winter-Seasonal Affective Disorder; S - S A D = Summer-Seasonal Affective Disorder; Sub = Subsyndromal Winter-Seasonal Affective Disorder; B P = Bipolar Disorder; M D = Major Affective Disorder; N S N = Nonseasonal Normals; E D = Eating Disorders; N L - R e g u l a r Normals.
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TODD A. HARDIN et al. SU MME.R-SAD (N--33)
SUBSYNOROMAL W1NTER-SAD(-N=20)
+
-'mm JUL A U G SEP O C T N O V D E C JAN FEB M A R APR ),lAY JUN
~
JUL A U G SEP OC:T N O V [DEC JAN FEB M A R APR M A Y JUN
NONSEASONAL NORMALS (N.=20)
WINTER-SAD (#4=149)
- - m
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
m
m
- - - - m m m
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
REGULAR NORMALS (14=55)
+ +
m
EAriNG D(SORDERS (N=41)
+l +l JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
~
BIPOLARS (N=28)
JLIL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
MAJOR DEPRESSION (N=88)
~
mmmmm
m
~
JUL AUG SEP OCT NOV DEC JAN FEB MAR APFI MAY JUN
Figure 2. The pattern of response to the questions " I n which months do you feel b e s t ? " , and " I n which months do you feel w o r s t ? " are shown in this figure. Bars represent the percentage of the population who report feeling best or worst in each month. Those individuals who reported no particular months when they felt best or worst are excluded from the figure.
EVALUATION OF SEASONALITYIN SIX CLINICAL POPULATIONS AND T w o NORMAL POPULATIONS
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Questions about sleep durations in different seasons revealed significant differences among groups ( F = 7.92; D F = 21,1317; p < .001). As might have been predicted, patients with winter-SAD showed the greatest average difference in sleep length between the season of longest sleep duration (winter) and that of shortest duration (summer), 2.56 h, followed by patients with subsyndromal winter-SAD (summer-winter sleep difference = 1.65 h), eating disorders (1.12 h) and summer-SAD (1.07 h). All the other groups reported sleep differences of less than one hour across the seasons. There were certain underlying similarities in the patterns of seasonal change across all groups except for the summer-SAD patients (see Figure 2), who uniformly reported summer as the time of year when they felt worst. All the rest, with the exception of the nonseasonal normals, tended to like spring the most, followed by summer and fall, and tended to like winter least. In most groups there was little overlap between when subjects felt best and when they felt worst. The amplitude of the reported seasonal rhythms corresponded to the severity of reported seasonal changes; that is, those groups with the highest global seasonality scores showed the greatest amplitudes (see Figure 2). Comparisons of weather sensitivity between groups showed the summer-SAD patients responding differently from the other groups. They liked cold weather and disliked hot weather more than the other groups. Apart from these responses, there was considerable overlap between groups in their responses to the weather variables. Discussion This is the second study in which the SPAQ has been used to discriminate between different degrees of retrospectively reported seasonal variation in different clinical populations. Thompson et al. (1988) found that winter-SAD patients differed significantly from normal controls on several measures of seasonal change derived from the SPAQ, while bipolar patients occupied an intermediate position between these two groups. These findings are consistent with ours in that in both studies winter-SAD patients and regular normals scored significantly differently on most items reflecting severity of seasonal change, and bipolar subjects were statistically more similar to regular normal subjects than to patients with winter-SAD. These findings suggest that in inquiring about seasonality, the SPAQ is indeed eliciting information about seasonal changes rather than about nonseasonal fluctuations in mood and behavior since the latter would presumably occur to a far greater degree in bipolar patients than in normal controls, but would not necessarily discriminate between bipolar patients and those with winter-SAD. The relative normality of seasonal severity scores in both bipolar and major depressive populations suggests that seasonality may be a dimension that cuts across individuals with varying vulnerabilities to affective disturbance, rather than a simple function of mood dysregulation. One difference between the present study and that of Thompson et al. (1988) is that in the British study the bipolar patients were significantly more seasonal than the normal controls, whereas in the present study the bipolars and major depressives were not significantly more seasonal than the normal controls. In reviewing the literature on affective disorders, we have noted that there is strong evidence of a bimodal seasonal influence on timing of episodes, with both summer and winter peaks (Wehr & Rosenthal, 1989). We
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have thus suggested that seasonal influences are important in affectively disturbed populations not selected specifically for their seasonality. This suggestion needs to be reconciled with our present observation that bipolar and m a j o r depressive patients were not abnormally seasonal. Possible explanations for the similar seasonality scores in patient and normal groups are as follows: (1) even though the seasonality scores of the bipolar and m a j o r depressive groups were no greater than that of the general population, all of these groups were seasonal to some degree and this degree of seasonality may be sufficient to exert a significant influence on patterns of hospital admissions for depression or prescriptions of antidepressants; (2) the bipolar and m a j o r depressive populations we studied were treated in research settings and might not have been as seasonal as patients with these diagnoses studied elsewhere. For instance, the bipolar patients of T h o m p s o n et al. had an average global seasonality score of approximately 9.5 as compared with our bipolar patients whose average global seasonality score was approximately 8; and (3) the failure of the SPAQ to distinguish between the affectively disturbed groups and the normal group may reflect a deficiency in the instrument itself. Reliability over time appeared to be greater for those with higher degrees of seasonal change, namely patients with winter-SAD and subsyndromal winter-SAD than for nonseasonal normal controls. Nonseasonal normal individuals showed high levels of reliability on certain items, such as those pertaining to sleep length, reactivity to certain weather variables and global severity of seasonality. On the other hand, reliability scores on other items are unacceptably low and inferences based on these items need to be made with appropriate caution. It is worth noting that test-retest scores were highly reliable in the winter-SAD population despite the far greater variability of the interval between administrations (mean _+S D : 8.2 _+7.1 months), suggesting that test-retest reliability holds up to some degree across seasons. It would be valuable to obtain more data on test-retest reliability in a wider set of populations and at more uniform intervals. Test-retest reliability scores for winter-SAD patients were somewhat lower in the British than in the U.S. study. This difference may be related to methodological differences between studies, namely: (1) the use of different statistical techniques, Spearman rank order correlation in the British study, and Spearman-Brown intraclass correlation in our study; (2) different sample size, 20 in the British study and 50 in our study; and (3) different intervals between tests. In contrast to the findings of Thompson et al., we found reasonable test-retest reliability for several items related to weather variables. Comparisons of seasonal changes between groups indicated that apart from the groups recruited specifically for a history of marked seasonal changes (the winter-SAD, summerSAD, and subsyndromal winter-SAD groups), those with eating disorders reported the highest degree of seasonality. Indeed, there was no significant difference between eating disorder and winter-SAD groups on global seasonality score and most of the subscores that form this index. This high degree of seasonality among eating disorder patients, together with their overall dislike of the winter months, would make them good candidates for phototherapy studies. Insofar as being female is a risk factor for seasonality (Kasper, Wehr, & Bartko, 1989), the higher female to male ratio in the eating disorder group might have influenced the overall seasonality scores. Nonetheless, the female to male ratio was not
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different from that of the regular normal group, whose seasonality scores were significantly lower. Conversely, the seasonality scores of the major depression group might have been lowered by the more balanced sex ratio in that group. All groups with the exception of the summer seasonals expressed a greater aversion for the winter than for the summer, which is in keeping with seasonal preferences in the general population at an equivalent latitude (Terman, 1989; Kasper, Wehr, & Bartko, 1989). Reported seasonal changes in sleep and other behaviors also show a similar pattern in clinical groups and the general population. In other words, most groups--regular normals included--reported increased sleeping, increased eating and weight gain in the winter compared with the summer. In fact, even summer-SAD patients report this pattern of seasonal variation. However, insofar as they become depressed in the summer, sleep loss, anorexia and weight loss are part of their depressive syndrome. The reverse applies for winter-SAD patients (Wehr et al., 1989; Wehr & Rosenthal, 1989). Although winter was the least preferred season for most subjects, there is evidence that summer was also disliked by some individuals in those groups not selected specifically for their seasonality, specifically the nonseasonal depressives, eating disorder patients and regular normals. Adverse influences of summer, as well as winter, have been documented in other studies (Wehr & Rosenthal, 1989). Conclusion In summary, the Seasonal Pattern Assessment Questionnaire (SPAQ) appears to be a useful instrument for evaluating seasonality retrospectively. The SPAQ discriminates successfully between groups who would be expected to differ along a seasonal dimension, for example winter-SAD patients and normal controls. In addition, it has the potential to identify groups whom one might not expect to be highly seasonal, for example, eating disorder patients. Such a finding may be useful insofar as severity of seasonality--associated with an aversion to winter--appears to be a predictor of beneficial mood and behavioral response to phototherapy (Kasper, Rogers, & Yancey, 1989). It would thus seem worthwhile to study the effects of phototherapy in eating disorder patients. An interesting negative finding of this study is that nonseasonally depressed patients do not differ significantly from regular normal subjects in their degree of seasonality. This suggests that seasonality may be a dimension of human behavior transmitted separately from vulnerability to depression. Family and twin studies focusing on heritability of seasonality--as opposed to affective vulnerability--would also seem to be worth undertaking. The relatively low degree of seasonality seen in bipolar and major depressed groups could be taken to suggest that these groups are less likely to benefit from light therapy than winter-SAD patients. Although the overall seasonality score did not differentiate patients with major depression and bipolar disorder patients from regular normals, the prevalence of winter-SAD in the former two groups, as determined by previously derived SPAQ criteria, was 14o7oand 10°70 respectively. These figures are very similar to prevalence estimates of winter-SAD in other major depressive populations.Thus Thase (1986), applying the criteria of Rosenthal et al. (1984), reported a 16.1°70 prevalence of winter-SAD in a clinic for outpatient treatment of recurrent depressives. More recently Kasper (in press),
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applying SPAQ-derived criteria, found a 15% prevalence o f winter-SAD in an outpatient group o f depressives in West Germany. These consistent findings across centers that one in six outpatient depressives have a history of seasonal changes equivalent in severity to those seen in winter-SAD patients, may have therapeutic relevance, given the relationship between seasonality and response to light therapy. Clinicians should thus be on the lookout for seasonality in recurrent depressives who do not label themselves as having winter-SAD, and the S P A Q might be a useful screening instrument to diagnose such patients. Acknowledgement--The authors wish to thank Connie Carpenter for assistance in administering questionnaires, Dr. John Bartko for statistical consultation, and Dennis George for computer programming expertise.
REFERENCES American Psychiatric Association (1980). Diagnostic" and statistical manual o f mental disorders. American Psychiatric Association, Washington, DC. Boyce, P., & Parker, G. (1988). Seasonal affective disorder in the southern hemisphere. American Journal o f Psychiatry, 145, 96-99. Jones, W. H. S., & Wittington, E. T. (Eds & Trans) (1923-1931) Works o f Hippocrates. Regimen in health. Harvard University, Cambridge, MA. Kasper, S., Rogers, S. L. B., Madden, P. A., Joseph-Vanderpool, J. R., & Rosenthal, N. E. (1988). The effects ofphototherapy in the general population. Abstract presented at the 141st annual meeting of the American Psychiatric Association. Kasper, S., Wehr, T. A., Bartko, J. J., Gaist, P. A., & Rosenthal, N. E. (1989). Epidemiological findings of seasonal changes in mood and behavior. Archives o f General Psychiatry, 46, 823-833. Kasper, S., Rogers, S. L. B., Yancey, A., Schulz, P. M., Skwerer, R. G., & Rosenthal, N. E. (1989). Phototherapy in individuals with and without subsyndromal seasonal affective disorder. Archives o f General Psychiatry, 46, 837-844. Kasper, S., & Kamo, T. (in press). Seasonality in major depressed inpatients. Journal o f Affective Disorders. Kripke, D. F., Mullaney, D. J., Gillin, J. C., Risch, S. C., & Janowsky, D. S. 0985). Phototherapy o f nonseasonal depression in biological psychiatry (pp. 993-995). New York: Elsevier Science Publishing. Lewy, A. J., Kern, H. E., & Rosenthal, N. E. (1982). Bright artificial light treatment of a manic-depressive patient with a seasonal mood cycle. American Journal o f Psychiatry, 139, 1496-1498. Rosen, L. N., Targum, S. D., Terman, M., Bryant, M. J., Hoffman, H., Kasper, S., Hamovit, J. R., Docherty, J. P., Welch, B., & Rosenthal, N. E. (1989). Prevalence of seasonal affective disorder at four latitudes. Psychiatry Research, 31, 131-144. Rosenthal, N. E., Sack, D. A., Gillin, J. C., Lewy, A. J., Goodwin, F. K., Davenport, Y., Mueller, P. S., Newsome, D. A., & Wehr, T. A. (1984). Seasonal affective disorder: a description of the syndrome and preliminary findings with light therapy. Archives o f General Psychiatry, 41, 72-80. Rosenthal, N. E., Genhart, M. J., Jacobsen, F. M., Skwerer, R. G., & Wehr, T. A. (1987a). Disturbances of appetite and weight regulation in seasonal affective disorder. Annals o f the New York Academy o f Sciences, 499, 216-230. Rosenthal, N. E., Rotter, A., Jacobsen, F. M., & Skwerer, R. G. (1987b). No mood-altering effects found after treatment of normal subjects with bright light in the morning. Psychiatry Research, 22, 1-9. Rosenthal, N. E., Sack, D. A., Skwerer, R. G., Jacobsen, F. M., & Wehr, T. A. (1988). Phototherapy for seasonal affective disorder. Journal o f Biological Rhythms, 3, 101-120. Spitzer, R. L., Endicott, J., & Robins, E. (1978). Research diagnostic criteria: Rationale and reliability. Archives o f General Psychiatry, 35, 773-782. Terman, M. (1988). On the question of mechanism in phototherapy: consideration of clinical efficacy and epidemiology. Journal o f Biological Rhythms, 3, 155-172. Terman, M., Botticelli, S. R., Link, B., Hardin, T. A., & Rosenthal, N. E. (1989). Patterns of seasonality in New York patients and population. In Thompson, C. and Silverstone (Eds) Seasonalaffective disorder. CRC Neuroscience Press, London. Thase, M. E. (1986). Interview: Defining and treating seasonal affective disorder. Psychiatry Annals, 16, 733-737.
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Thompson, C., Stinson, D., Fernandez, M., Fine, J., & Isaacs, G. (1988). A comparison of normal, bipolar and seasonal affective disorder subjects using the Seasonal Pattern Assessment Questionnaire. Journal of Affective Disorders, 14, 257-264. Wehr, T. A., Sack, D. A., & Rosenthal, N. E. (1987). Seasonal affective disorder with summer depression and winter hypomania. American Journal of Psychiatry, 144, 12. Wehr, T. A., Giesen, H., Schulz, P. M., Joseph-Vanderpool, J. R., Kelly, K., Kasper, S., & Rosenthal, N. E. (1989). Summer depression: description of the syndrome and comparison with winter depression. In N. E. Rosenthal and M. Blehar (Eds) Seasonal affective disorders and phototherapy. New York: Guilford Press. Wehr, T. A., & Rosenthal, N. E. (1989). Seasonality and affective illness. American Journal of Psychiatry, 146, 829-839. Winer, B. J. (1971). Statistical principles in experimental design. New York: McGraw-Hill.