Methods

2.1. The Questionnaire Study

A total sample of 2183 adults who had lived inTurkmenia (38 deg North, n = 328), Novosibirsk (55 deg North, n = 761), Chukotka and Yakutia (61-66 deg North, n = 1094) was surveyed to examine the relations between self-assessed level of depression and types of seasonal and diurnal rhythms. In overall, these respondents were more likely to be female (54.4%) and older than 34 (54.3%). One of Novosibirsk subsamples (n = 150) was obtained in the process of recruiting female subjects with winter depression and nonseasonal female controls for our LT study in the hospital of the Siberian Branch of the Russian Academy of Medical Sciences near Novosibirsk.

2.1.1. Self-Assessment of Seasonality. The Seasonal Pattern Assessment Questionnaire (SPAQ) (48) was applied to 1) determine the patterns of seasonal variations in the symptoms of seasonal depression and 2) assign the respondents to the diagnostic groups: nonseasonals (N-SAd) and seasonals with subsyndromal SAD (S-SAD) or full-blown SAD (see criteria in (6,19)). The respondents were ask to circle all months during which they: feel the best and feel the worst, more energetic and active than usual and feel drowsy during the daytime, sleep less than usual and sleep more than usual, wake up too early and have difficulty falling asleep, lose the most weight and gain the most weight, eat less than usual and eat more than usual, socialize most and socialize least, etc. Besides, they were asked to assess the degree and severity of seasonal variations in sleep length, social activity, well-being, weight, appetite and energy level.

Figure 1 illustrates the relations between seasonal changes in scotoperiod (nighttime plus twilight, hours) and seasonal variations in some neurovegetative depressive symptoms. The smoothed symptom curves represent the difference between percent of respondents who reported positive symptom and percent of those who reported negative symptom, i.e. early waking minus late waking (post/presleep insomnia), lose weight minus gain weight (under/overweightiness), sleep less minus sleep more (under/oversleeping), and feel more active minus feel more drowsy (hyper/hypoactiv-ity). Moreover, the annual pattern of general well-being (feel best minus feel worst) is shown in Figure 1 to provide a comparison of this pattern with the patterns of neurovegetative symptoms.

Figure 1. Annual rhythms of four typical neurovegetative depressive symptoms in winter seasonals (solid lines). All data are double-plotted. The scotoperiod data are shown with two-week interval. Right scale of Y-axis: duration of scotoperiod in hours. Filled columns show night length, open columns show duration of twilight.The symptom data (n = 324) were reported with one-month interval. Left scale of Y-axis: differences in percent of respondents reported a positive symptom (e.g. sleep less) and percent of respondents reported a negative symptom (e.g. sleep more) in a given month. The thin lines show seasonal variations in general well-being. For better fitting, the amplitude of these variations was adjusted to the amplitudes of seasonal variations in neurovegetative symptoms, and the scotoperiodic data were shifted on two weeks relative to the symptom data.

Figure 1. Annual rhythms of four typical neurovegetative depressive symptoms in winter seasonals (solid lines). All data are double-plotted. The scotoperiod data are shown with two-week interval. Right scale of Y-axis: duration of scotoperiod in hours. Filled columns show night length, open columns show duration of twilight.The symptom data (n = 324) were reported with one-month interval. Left scale of Y-axis: differences in percent of respondents reported a positive symptom (e.g. sleep less) and percent of respondents reported a negative symptom (e.g. sleep more) in a given month. The thin lines show seasonal variations in general well-being. For better fitting, the amplitude of these variations was adjusted to the amplitudes of seasonal variations in neurovegetative symptoms, and the scotoperiodic data were shifted on two weeks relative to the symptom data.

Figure 1. Continued.

MMJSNJMMJSNJM

Figure 1. Continued.

The delays of seasonal variations in 6 depressive symptoms relative to the annual changes in photoperiod were calculated by two methods. First, by searching for maximal crosscorrelation between weekly data on photoperiod and row monthly data on symptom (P). Second, by averaging delays (p) for: 1) month of maximal rate of symptom relative to June (M), 2) month of minimal rate relative to December (m), 3) month of mean level upcrossing relative to March (C) and 4) month of mean level downcrossing relative to September (c). For the purpose of statistical comparison, the delays for every symptom were obtained in 24 subsamples or less (the delays were not calculated when maximal coefficient of crosscorrelation was lower than + 0.82, p > 0.001 for n = 12 months). The mean delays shown Figure 2 were calculated by averaging the delays either over all subsamples (All) or within every of 5 groups of subsamples: #1-6 subsamples of residents of Turkmenia including summer seasonals (n = 51), winter sea-sonals (n = 20), and 4 subsamples of nonseasonals: males younger 35 or older (n = 44 and 47, respectively) and females younger 35 or older (n = 77 and 67, respectively); #2—nonseasonals from Novosibirsk divided on 4 subgroups according to their age and gender (n = 118, 145, 148 and 87, respectively); #3-6 subsamples of winter seasonals from Novosibirsk: females screened for LT study (44 were younger than 35 and 28 were 35 or older), and other winter seasonals divided on 4 groups according to their age and

Figure 2. Delays of annual rhythms of six depressive symptoms relative to the annual light cycle. P—delays for maximal crosscorrelation between weekly data on day length and monthly data on depressive symptoms. p—delays averaged over the following four phases of annual rhythm: M—delays for month of maximal rate of symptom relative to June, m—delays for month of minimal rate relative to December, C—delays for month of mean level upcrossing relative to March, c—delays for month of mean level downcrossing relative to September. ##1-5—delays for separate groups of subsamples, All—delays for all subsamples.

Figure 2. Delays of annual rhythms of six depressive symptoms relative to the annual light cycle. P—delays for maximal crosscorrelation between weekly data on day length and monthly data on depressive symptoms. p—delays averaged over the following four phases of annual rhythm: M—delays for month of maximal rate of symptom relative to June, m—delays for month of minimal rate relative to December, C—delays for month of mean level upcrossing relative to March, c—delays for month of mean level downcrossing relative to September. ##1-5—delays for separate groups of subsamples, All—delays for all subsamples.

Figure 3. Scores on M- and E-scales (Morning- and Evening Lateness). Positive scores suggest a delay of the sleep-wake cycle. Filled columns represent depressed respondents from the questionnaire study or patients with winter depression from the LT-study, open columns represent non-depressed respondents or healthy controls, respectively. O—35 year of age or older, Y—younger than 35. N-SAD, S-SAD and SAD subgroups on the left represent male respondents of the questionnaire study with diagnoses No-SAD, Subsyndromal SAD and SAD; on the right — female respondents of N-SAD, S-SAD and SAD subgroups.

Morning Eveningness Questionnaire

gender (n = 17, 13, 35 and 18, respectively); #4—nonseasonals from Yakutia and Chukotka divided on 4 age-gender groups (n = 148, 279,149 and 258, respectively); and #5—winter seasonals from Yakutia and Chukotka divided on 4 age-gender groups (n = 18, 29, 43 and 58, respectively).

2.1.2. Self-Assessment of the Sleep-Wake Pattern and Level of Depression. Individual traits of the sleep-wake cycle were self-assessed with the 40-item Sleep-Wake Pattern Assessment Questionnaire (SWPAQ) (38). This instrument includes two morn-ingness-eveningness scales which can be defined briefly as levels of morning and evening wakefulness (12-item M-scale and 8-item E-scale). The positive scores indicate the tendencies toward late awakening on M-scale (Morning Lateness) and late bedtimes on E-scales (Evening Lateness). The 20-item Center for Epidemiologic Studies — Depression Scale (CES-D) (44) was used to group respondents into those with lower and higher current level of depressive symptoms (the scores of 16 or more may indicate clinical depression (7,44). Figure 3 gives M- and E-scores in 28 subgroups of respondents: the rightist 4 columns represent the subjects screened for LT-study (younger and older female nonseasonals and younger and older female winter sea-sonals), the other 24 columns represent the rest of the questionnaire sample: more and less depressed male and female respondents of younger and older age grouped in N-SAD, S-SAD and SAD diagnostic categories. To clarify the effects of seasonality and

Table 1. Results of 4-Way ANOVAs for morning and evening lateness

Factor

Morning lateness

score

Factor

Evening lateness

score

F

P

Df

F

P

Df

1 Gender

2.12

0.141

112026

1 Gender

25.30

0.000

112026

2 Age

61.80

0.000

112026

2 Age

40.50

0.000

1/2026

3 Depression

6.62

0.009

112026

3 Depression

0.25

0.621

112026

4 Diagnosis

13.15

0.000

212026

4 Diagnosis

1.17

0.311

212026

Notes. Level of significance (p) for all interactions was higher than 0.05. Gender: Male/Female; Age: younger than 35/older; Depression: CES-D score <16/>15; Diagnosis: N-SAD/S-SAD/SAD.

Notes. Level of significance (p) for all interactions was higher than 0.05. Gender: Male/Female; Age: younger than 35/older; Depression: CES-D score <16/>15; Diagnosis: N-SAD/S-SAD/SAD.

mood state on diurnal type, the M- and E-scores in the latter 24 subsamples were compared using 4-way ANOVA with 4 grouping factors (level of depression, diagnostic category, age and gender; Table 1).

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