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Perceived Work Overload and Chronic Worrying Predict Weekend–Weekday Differences in the Cortisol Awakening Response

From the University of Trier (W.S., J.H., P.S.), Germany; and Stony Brook University (A.A.S.), New York, NY.

Address correspondence and reprint requests to Wolff Schlotz, University of Trier, Department of Psychobiology, Johanniterufer 15, 54290 Trier, Germany. E-mail: schlotz{at}uni-trier.de

	ABSTRACT

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

 
OBJECTIVE: The cortisol increase after awakening has been shown to be associated with work-related stress. Several studies demonstrated a moderate stability of cortisol awakening responses on subsequent days, suggesting situation-dependent variance. This study tests whether cortisol awakening responses are different on weekdays compared with weekend days and whether such differences may be explained by chronic work overload and worrying.

METHODS: Two hundred nineteen participants took saliva samples immediately after awakening and 30, 45, and 60 minutes later on 6 consecutive days starting on Saturday. Perceived chronic work overload and worrying were assessed by a standardized questionnaire.

RESULTS: There is a clear weekend–weekday difference in the cortisol response to awakening. This difference is associated with chronic work overload and worry. Independent of sex and weekend–weekday differences in time of awakening and sleep duration, participants who report higher levels of chronic work overload and worrying show a stronger increase and higher mean levels of cortisol after awakening on weekdays, but not on weekend days.

CONCLUSIONS: The weekend–weekday differences in the cortisol awakening response and their association with chronic stress clearly demonstrate that the day of cortisol assessment is crucial in psychoendocrinological stress studies.

Key Words: cortisol awakening response, • salivary cortisol, • weekend, • perceived stress, • work overload, • worry.

Abbreviations: ANOVA = analysis of variance;; CAR = cortisol awakening response;; GLM = general linear model;; HPA = hypothalamic–pituitary–adrenal axis.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

 
Several studies detect a cortisol increase after awakening (1–6) that may be a marker of hypothalamic–pituitary–adrenal axis (HPA) activity, in particular of the sensitivity of the adrenal cortex (7). This cortisol awakening response (CAR) is influenced by light (8, 9), sex (4), and time of awakening (6,10,11). There is also evidence for an association of the CAR with sleep duration (4), although another study (1) failed to detect it. With regard to psychological stress measures, a relation of morning cortisol levels to self-reported chronic work-related stress is often observed (12–14). Cortisol levels after awakening are moderately stable. Wüst et al. (4) report a range in correlations of 0.37 < r < 0.66 for single measures in the first hour after awakening on 2 consecutive days. Pruessner et al. (1) report a range of 0.39 < r < 0.67 for individual area under the curve measures on 2 consecutive days. These correlations demonstrate a day-to-day variability that suggests situation-dependent variance in the CAR.

This study focuses on the CAR on weekdays compared with weekend days. The standard work schedule divides the week into 2 sections: 5 work days, usually the weekdays Monday through Friday, and 2 off work days, usually the weekend days Saturday and Sunday. Several studies demonstrated increased cardiovascular activity on workdays compared with nonworkdays (15–17). Differences between workdays and nonworkdays in heart rate, systolic blood pressure, and urinary epinephrine levels are more pronounced in persons facing high job demands (18), suggesting an increased work-stress-related sympathetic activation. Because of the abovementioned standard work schedule, these differences are likely to be observed in a weekend–weekday comparison of biological stress reactions.

Weekend–weekday differences may also emerge in the area of cognitive preoccupation with subjectively significant problems. This preoccupation may appear as worrying, which is a common human experience and may constitute constructive problem-solving activity, enabling the individual to cope with life problems (19,20), but may also be dysfunctional, ie, enhancing stress and anxiety instead of reducing it (21,22). Worrying may appear in anticipation of everyday demands after awakening and thus may be more pronounced on weekdays than on weekend days. On the other hand, weekdays and weekend days have been shown to differ in the amount of negative affect (23,24). These differences may also be attributable to the standard work schedule, and thus may be linked to work-related stress and worrying, respectively, as outlined above.

The objectives of this study are to test the hypothesis that the CAR is different on weekdays compared with weekend days and, if so, to determine whether these differences are linked to perceived work-related stress and worry. We hypothesize 1) that the CAR is more pronounced on weekdays compared with weekend days; 2) that this difference is independent of sex, time of awakening, and sleep duration; and 3) that this difference is attributable to perceived work overload and worry.

	METHODS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

 
Participants and Methods
Participants
Participants were recruited by newspaper announcements in the region of Trier, Germany. Because the study originally was designed with an emphasis on the influence of age on psychoneuroendocrinological systems, participants had to be between 24 and 40 years or more than 60 years old to be included in the study; those treated with corticosteroids and those with diabetes were excluded from the study. All participants provided written informed consent and they were paid DM 40 after completion of the study protocol. A subset of 219 participants (117 female [53%], 102 male [47%]) was selected from the whole sample (N = 309) based on the following criteria (see Study Protocol below for details): (a) No missing cortisol, bedtime, and awakening time measure, respectively, on the weekend; and (b) a maximum of 2 missing weekday cortisol, bedtime, and awakening time measures, respectively. These criteria were chosen to assure that the averaged cortisol, bedtime, and awakening time measures are based on at least 2 samples, and hence to reduce the influence of state variability. The mean age of the participants was 48.6 years (SD = 18.2), with a range of 24 to 83 years. One hundred forty participants (64%) were employed (48 full-time occupied, 34 part-time occupied, 36 students, 22 homemakers), 6 were unemployed, and 72 were retired (1 person had a missing employment status).

Study Protocol
All participants completed questionnaires at the University of Trier and received Salivette sampling devices (Sarstedt, Nümbrecht, Germany) to obtain saliva samples (25). They were instructed to take samples immediately after awakening and 30, 45, and 60 minutes later on 7 consecutive days starting on Saturday, resulting in a total of 5256 cortisol measures, 24 per participant (for another reason, participants took 0.5 mg dexamethasone on Thursday night; therefore, the Friday saliva samples were excluded from the analyses). Participants reported bedtime and time of awakening on each night and morning. Seventy (1.3%) samples were missing or deleted because of noncompliance with the protocol (see Compliance with the Protocol below) or were identified as outliers by using an intraindividual comparison of samples (26); these samples were excluded from further analyses. Analyses are therefore based on a total of 5186 cortisol samples, representing 98.7% of the complete sample.

Compliance With the Protocol
Participants were instructed to take the first saliva sample immediately after awakening, and to get up immediately thereafter. They were told to refrain from eating, drinking (except water), and smoking for 60 minutes after awakening. Participants were also instructed not to brush their teeth before completing saliva sampling to avoid contamination of saliva by blood from microinjuries in the oral cavity, and to refrain from sports in the first hour after awakening. No other instructions were given that could interfere with the participants’ normal daily routines. Compliance with this protocol was not monitored, but when participants came to the laboratory to deliver their saliva samples, they were asked about their compliance with the protocol. Cortisol samples were excluded from the analyses if participants reported noncompliance with the protocol. The overall impression of the interviewers is that participants were conscientious about meeting their commitment, although, of course, we cannot be certain about this.

Work Overload and Worry
Perceived chronic stress was measured by the Trier Inventory for the Assessment of Chronic Stress (27). Two scales were included in the analyses. The scale work overload (8 items, Cronbach’s = 0.90) assessed the experience of working overly-long and intensively, handling many demands of everyday life and occupation, ie, quantitative work overload (eg, "I have too little time to perform my daily tasks"; "Times that I must work under time pressure"). The scale worry (6 items; Cronbach’s = 0.86) assessed worrisome thoughts (eg, "Worry that something unpleasant will happen"; "Worry that I will not be able to fulfill my tasks"). For each item, the frequency of the experience in the last year had to be indicated on a 5-point rating scale, ranging from "never" to "very often." Results of extensive studies on correlations between these scales and other stress-related measures in different German samples indicate their validity (eg, 27,28).

Biochemical Analyses
Participants were asked to keep the salivary samples in the freezer until completion of the protocol. After delivery to the laboratory, samples where frozen at -20°C until they were analyzed. Cortisol was analyzed by a time-resolved immunoassay with fluorescence detection (29).

Statistical Analyses
A first test of the difference between cortisol weekend and weekday measures after awakening (Hypothesis 1) was done by a repeated-measures analysis of variance (ANOVA) with 2 within-subject factors: time of day (including the cortisol measures immediately after awakening, and 30, 45, and 60 minutes later) and weekday (including the days Saturday through Thursday), followed by pairwise comparisons of each cortisol measure with the corresponding measures on the other days using 2-sided paired t tests based on the estimated marginal means. Significance levels were Bonferroni-corrected within each level of the factor time of day, ie, on the basis of a total of 15 tests per time of day level. Because a repeated-measures ANOVA requires the same number of measurements per participant, every case missing at least 1 cortisol sample was completely excluded from the analysis automatically by the statistical software. Therefore, this analysis is based on a reduced sample.

To describe the overall association of awakening time and sleep duration with the CAR, three cortisol parameters were computed by averaging over 6 days: The mean cortisol level immediately after awakening (t0mean), the overall mean cortisol level including four measures per day (Cmean), and the mean increase by averaging the measures 30, 45, and 60 minutes after awakening on each day, subtracting the cortisol measure immediately after awakening on that day, and averaging the results (MnInc). Subsequently, correlations of these parameters with time of awakening (AWmean) and sleep duration (DUmean), each averaged over 6 days, were computed.

To test the second and third hypotheses on the basis of the complete sample described above, cortisol raw data were averaged over the 2 weekend days and the 4 weekdays, respectively. The basic statistical model comprised 2 within-subject factors, time of day (including 4 cortisol measures as described above), and week segment (including Saturday and Sunday vs. Monday through Thursday).

To test for the influence on weekend–weekday differences in the CAR, the weekend–weekday difference in time of awakening was computed by subtracting the weekend mean from the weekday mean for each participant. Thus, awakening time differences are positive if a participant reported to have woken up later on weekend than on weekdays. Sleep duration was computed for each night as the difference between time of awakening and bedtime. Subsequently, the weekend–weekday difference in sleep duration was computed by subtracting the weekend mean from the weekday mean for each participant. Thus, similar to awakening time differences, sleep duration differences are positive if a participant reported to have slept longer on weekend than on weekdays. Sex, differences in time of awakening, and differences in sleep time were then included as a predictor in separate General Linear Models (GLMs) to test for their individual influence on cortisol. In the case of a significant effect, the variable was included as a covariate in all subsequent GLMs. Sex differences in cortisol were compared using 2-sided t tests for independent samples.

To test if the cortisol weekend–weekday differences are independent of sex, differences in time of awakening, and differences in sleep duration, these covariates were included as a predictor set in a subsequent GLM to confirm the results from the first analysis while controlling for potentially confounding variables (Hypothesis 2). Significant effects of the cortisol factors were explored using 2-sided paired t tests to compare each averaged weekend cortisol measure with the corresponding averaged weekday measure. These t tests were computed using model-based estimated marginal means with covariates held at their overall mean value.

Analyses of the influence of psychological variables on the CAR on weekend vs. weekdays (Hypothesis 3) were done by a GLM and work overload and worry, respectively, as predictors.

All statistical analyses were done with SPSS 10. Models for hypothesis tests were computed with the command GLM. Degrees of freedom were corrected by the Greenhouse-Geisser method where appropriate. For all analyses, an effect was classified as significant if the Type 1 error probability was p .05. Partial effect sizes were calculated as ² = SS_hypothesis/(SS_hypothesis+SS_error), indicating the proportion of total variance made up by the variance of the respective effect, while excluding variance caused by all other effects (30).

Variables were trichotomized, ie, split into 3 groups of about the same size, to illustrate significant effects of continuous variables. A specific effect is illustrated by averaging over factor levels until the required level of variable crossing is reached. Therefore, the graphs in Figure 2b and c, Figure 3, and Figure 4 describe observed data for groups with low, medium, and high levels on the continuous variable of interest disregarding the influence of covariates, whereas the results of the statistical analyses reported in the text represent the effects of the continuous variables and are covariate adjusted.

View larger version (29K): [in this window] [in a new window]   Figure 2. Cortisol measures averaged over weekend and weekdays, respectively. Bars indicate standard errors. (a) Means for female (N = 117) and male participants (N = 102), averaged over week segment. (b) Mean cortisol levels in the first hour after awakening for 3 awakening time difference groups: Low difference (N = 72), average difference (N = 73), and high difference (N = 74). (c) Cortisol courses after awakening for 3 sleep duration groups: Low difference (N = 72), average difference (N = 73), and high difference (N = 74). (d) Cortisol courses after awakening on weekend vs. weekdays (N = 219); effect is controlled for sex, time of awakening, and sleep duration (see text for details).

View larger version (28K): [in this window] [in a new window]   Figure 3. Influence of work overload on cortisol measures after awakening, for 3 work overload groups: Low (N = 64), average (N = 83), and high (N = 72) work overload scores. (a) Mean cortisol levels in the first hour after awakening on weekend days compared with weekdays. (b) Time course of cortisol levels in the first hour after awakening on weekend vs. weekdays. Both graphs illustrate significant effects controlled for sex, time of awakening, and sleep duration (see text for details).

View larger version (25K): [in this window] [in a new window]   Figure 4. Influence of worry on cortisol measures after awakening, for 3 worry groups: Low (N = 73), average (N = 78), and high (N = 68) worry scores. (a) Mean cortisol levels in the first hour after awakening on weekend days compared with weekdays. (b) Time course of cortisol levels in the first hour after awakening on weekend vs. weekdays. Both graphs illustrate significant effects controlled for sex, time of awakening, and sleep duration (see text for details).

	RESULTS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

View larger version (30K): [in this window] [in a new window]   Figure 1. Observed cortisol levels after awakening on 6 consecutive days of the week (N = 160); bars indicate standard errors.

The factor sex revealed an interaction effect with time of day (F_1.9/404.0 = 6.07; p = .003; ² = 0.027), indicating different courses of cortisol levels after awakening in men vs. women, independent of the week segment (Figure 2a). Comparisons of male’s and female’s cortisol levels, averaged over weekend and weekdays, revealed higher levels for females 60 minutes after awakening (t = 2.07; df = 217; p = .039), whereas the other measures were at the same level.

On average, participants woke up 44.9 minutes (SD = 65.3 minutes) later and slept 11.0 minutes longer (SD = 61.6 minutes) on weekend days compared with weekdays. There was a significant effect of awakening time differences on cortisol levels averaged over time of day (interaction week segment x awakening difference: F_1/217 = 17.40; p < .001; ² = 0.074). Figure 2b shows that mean cortisol levels in the first hour after awakening on weekdays were higher than those on weekend days for all awakening time difference groups. However, the high awakening time difference group showed the most pronounced cortisol differences between weekdays and weekend days, ie, high awakening time differences were associated with high cortisol differences. The sleep duration difference revealed a significant effect on the cortisol increase after awakening (interaction time of day x week segment x sleep duration difference: F_2.3/488.7 = 2.91; p = .049; ² = 0.013). Figure 2c demonstrates similar cortisol increases in the 3 sleep duration difference groups on weekend days, whereas weekday cortisol increases were more pronounced in the high sleep duration difference group. It can also be seen that sleep duration differences had no effect on the cortisol levels immediately after awakening.

These variables were included as a predictor set in a subsequent GLM, predicting CARs averaged over weekend days and weekdays, respectively. The model revealed significant effects of time of day (F_1.9/401.1 = 77.77; p < .001; ² = 0.266), week segment (F_1/215 = 17.46; p < .001; ² = 0.075), and time of day x week segment (F_2.3/485.1 = 13.47; p < .001; ² = 0.059). Figure 2d illustrates the interaction effect. Pairwise comparisons (df = 218) revealed that cortisol levels immediately after awakening were at the same level, whereas mean weekday cortisol levels were higher than mean weekend levels at 30 minutes (t = 4.59; p < .001), 45 minutes (t = 7.05; p < .001), and 60 minutes after awakening (t = 8.36; p < .001).

With respect to the second hypothesis it can be concluded that, although there were effects of sex, time of awakening, and sleep duration, cortisol differences between weekend and weekdays remained stable if these factors were controlled for by including them in the model as covariates. Therefore, the weekend–weekday differences found in the first analysis were confirmed in a broader sample and the CAR differences did not depend on sex, time of awakening, and sleep duration.

Influence of Work Overload and Worry
Hypothesis 3 states that the observed difference between CAR measures on weekdays compared with weekend days is due to chronic work overload and worry, respectively. The GLM estimates revealed significant effects of time of day (F_1.9/399.6 = 6.98; p = .001; ² = 0.032) and time of day x sex (F_1.9/399.6 = 4.91; p = .009; ² = 0.022). However, no effects including awakening difference or sleep duration difference remained significant, and the same is true for the effect of week segment. With respect to work-related stress, there was a significant effect of week segment x work overload (F_1/214 = 7.17; p = .008; ² = 0.032) and time of day x week segment x work overload (F_2.3/487.6 = 3.14; p = .038; ² = 0.014), indicating different associations of work overload to mean cortisol levels, and different associations of work overload to the cortisol increase after awakening at the weekend vs. weekdays. The graphs in Figure 3 were constructed using the method described in the statistics section. Figure 3a illustrates the more pronounced mean cortisol weekend–weekday differences for higher work overload scores; Figure 3b shows the work overload-dependent weekend–weekday difference in the time course of cortisol levels between weekend and weekdays. Although cortisol levels at the weekend were similar for high, median, and low work overload scores, the CAR on weekdays was more pronounced for higher work overload scores.

Comparable to the model including work overload, the worry-model revealed significant effects of time of day (F_1.9/399.9 = 5.73; p = .004; ² = 0.026) and time of day x sex (F_1.9/399.9 = 4.71; p = .011; ² = 0.022). Similarly, no effects including awakening difference or sleep duration difference remained significant, and the same is true for the effect of week segment. There was a significant effect of week segment x worry (F_1/214 = 8.35; p = .004; ² = 0.038) and time of day x week segment x worry (F_2.3/490.7 = 5.79; p = .002; ² = 0.026), indicating different associations of worry to mean cortisol levels, and different associations of worry to the cortisol increase after awakening at the weekend vs. weekdays. The effects were stronger than those for work overload. Moreover, there was a between-subject effect of worry on cortisol measures (F_1/214 = 4.03; p = .046; ² = 0.018), indicating higher cortisol measures in participants who reported worrying a lot, independent of week segment and time of day. Figure 4 illustrates the 2 interactions of worry and the within-subject factors week segment and time of day. Weekend–weekday differences in mean cortisol levels increase with higher worry scores (Figure 4a). Figure 4b shows the difference in the time course of cortisol levels between weekend and weekdays. Although cortisol at the weekend was similar for high, median, and low worry scores, the CAR on weekdays was more pronounced for higher worry scores.

	DISCUSSION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

 
This study demonstrates a clear weekday-related difference in the CAR, with higher cortisol levels on weekdays compared with weekend days, while controlling for sex and weekend–weekday differences in time of awakening and sleep duration. This result clearly confirms our expectations and demonstrates systematic day-to-day variability of the CAR. The possible influence of the variables sex, time of awakening, sleep duration, light, activity, and compliance on this result are discussed in the following.

In this study, women showed higher cortisol levels 60 minutes after awakening than men, and the direction as well as the magnitude of this effect clearly resembles the results of a larger study by Wüst et al. (4). However, because this influence was controlled by including sex as a covariate in the analyses, it had no impact on the weekend–weekday effect found in this study.

Comparable to Edwards et al. (6) and Federenko et al. (11), we found an influence of awakening time on cortisol measures in this study. In contrast to these studies, our analyses were based on differences between weekday and weekend measures of participants’ awakening time, ie, within-subject measures. However, the awakening time influence was controlled for by including this variable in the subsequent models, so that it cannot account for the observed cortisol differences. Interestingly, the correlations between overall cortisol and time of awakening revealed no significant effects and resemble the results of Wüst et al. (4). In our analyses, sleep duration also revealed an association with cortisol after awakening. This is shown by small but significant overall correlations as well as by the GLM interaction effect. The correlations revealed slightly higher cortisol levels immediately after awakening and a slightly smaller mean increase in participants who slept longer. The GLM effect revealed that the higher the sleep duration at the weekend compared with weekdays, the higher was the weekend–weekday difference in cortisol after awakening. The pattern of direction and magnitude of these effects also resembles the results in a previous study (4). On the other hand, in a sleep laboratory study, Späth-Schwalbe et al. (31) observed an effect of the opposite direction, ie, a more pronounced cortisol increase after awakening in individuals with a high sleep time compared with those with a low sleep time. Because the sleep measures in the present study and in the study by Wüst et al. (4) rely on self-report measures and thus did not assess sleep latency and waking periods during the night, they do not reflect actual sleep time, but rather time in bed. This methodological difference may in part account for the inconsistent effects of sleep duration on the cortisol response to awakening. In future studies, a method that may be applied in everyday life and that delivers valid information about sleep duration, such as wrist actigraphy (32), could help to reduce these inconsistencies. In the present study, however, similarly to the awakening time effect, the sleep duration effect cannot account for the observed cortisol differences because it is statistically controlled.

In 2 experimental studies, Leproult et al. (8) and Scheer and Buijs (9) found a positive association between light and cortisol increases in the morning. Because light was not measured here, it cannot be ruled out that a higher amount of light on weekdays triggered the stronger cortisol increase. Nevertheless, taking into account that the analyses reported here control for time of awakening differences between weekdays and weekend days, this explanation seems to be unlikely.

Another explanation of higher weekday cortisol levels could be based on differences in physical activity, assuming that participants are more active in the first hour after awakening on weekdays, probably because of the standardized work schedule outlined in the introduction. There is no evidence of a cortisol reaction under submaximal exercise (25,33), which is the level of exercise likely to occur in everyday morning activity. We know of no study that examined the potential influence of everyday morning activity on the CAR. Therefore, although it seems unlikely, this explanation cannot be ruled out. Although morning activity is a potentially, albeit unlikely, confounding factor for the higher weekday cortisol levels compared with weekend days, it is much less likely to account for the associations of work overload and worry with cortisol increases on weekdays.

There was no monitoring of participant’s compliance in this study, so it cannot be ruled out that differences in participant’s compliance on weekend days compared with weekdays are responsible for the observed pattern. Kudielka et al. (34) recently observed flatter CARs in noncompliant participants compared with compliant participants. The observed cortisol differences in this study therefore have to be interpreted with caution. However, Steptoe et al. (35) also observed weekend–weekday CAR differences in a completely different sample (British civil servants), thus corroborating the validity of our results.

With regard to the standard work schedule outlined in the introduction, these weekend–weekday differences point to an association of CARs with work-related demands. The third hypothesis sought an explanation of the weekday-weekend differences in CARs with reference to the stress variables, work overload and worry. The significant interaction effects of those variables with the within-subject factors time-of-day and week segment corroborate the idea of an influence of work overload and worry, respectively, on cortisol levels and increases after awakening. These relationships may be interpreted as the result of an up-regulation of the HPA-axis’ reactivity as a biological consequence of frequent activation of this axis triggered by stress. This may be part of the neuroendocrine stress system’s adaptation to chronic demands (36,37). This interpretation implicitly assumes that the actual amount of stress on the study days does not differ between participants reporting high or low chronic stress, and that the lack of an association between the stress and cortisol measures on weekend days reflects a relatively low impact of weekend stressors on the HPA axis activity. Alternatively, participants who report a higher amount of worry and work overload in the last year may generally face a higher amount of stress on weekdays than those with less perceived chronic stress. Therefore, they probably also faced more stressors on the days they participated in this study, and their stronger CARs would reflect anticipation effects of upcoming everyday demands. The identification of future problems, the development of coping strategies for these problems, and the anticipation of negative consequences of not being able to manage the upcoming tasks represent strong cognitive or internal stressors and may be linked to increases in the cortisol secretion after awakening (13). Therefore, the CARs on weekdays should be more pronounced than those on weekend days, where less work-related demands occur, and this effect should be stronger in persons who report chronic work overload and frequent worrying, respectively. This interpretation is supported by studies that found anticipation effects on cortisol (eg, 38,39). The evolutionary significance of this anticipation effect could be seen in a suppression of ongoing physiological activity, eg, sleep, relaxation, reproduction, and growth, in order to increase vigilance and to get the organism ready to take action to cope with dangers by avoiding, escaping, or modifying them (40). The CAR differences may also be triggered by negative affect. Negative affective reactions often accompany stress events and have been shown to be related to cortisol reactions in field and laboratory studies (38,41,42), and weekdays and weekend days have been shown to differ in the amount of negative affect (23,24). These findings could also explain the weekday–weekend differences observed in the present study and mediate their association with self-reported stress.

In sum, the present study demonstrates a clear weekend–weekday difference in the CAR, and an association of this difference with perceived chronic stress. However, because of the restricted age range of the participants in our study, the findings may not be generalized to middle-aged people, ie, people who are between 40 and 60 years old. We discussed some interpretations that are consistent with the findings. A test of these interpretations should use a within-subject design, measuring stress events, worrying, worry domain, anticipation, negative affect, and cortisol on a momentary basis during at least 1 complete week. Ecological Momentary Assessment (43) would qualify as a method for this test. This test should rely on a sample with equal age distribution, ie, middle aged people should be represented, and ideally compliance and sleep should be measured using objective monitoring devices. Another unresolved topic is the pattern difference of the CAR in relation to week segment and chronic stress, respectively. Data suggest that the CAR comprises 2 distinguishable components: the increase in the first 30 minutes after awakening, and a decline in the subsequent 30 minutes ("recovery"). Both components seem to be influenced by week segment and chronic stress, but the recovery-part to a greater extent (cf. Figures 2d, 3b, and 4b). Because the causes and consequences of these CAR-components are unknown, future studies could investigate the mechanisms that form the basis of the overall pattern. Independent of the underlying mechanism, our results of week-segment-related CARs and differential cortisol-stress associations on weekend and weekdays clearly demonstrate that the day of cortisol assessment is crucial in psychoendocrinological stress studies. Measuring the CAR on weekend days may result in a false rejection of hypothesis about associations between self-reported stress and cortisol secretion.

	ACKNOWLEDGMENTS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

 
This work was supported by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG, Nr. FOR 255/2–2).

Received for publication January 29, 2003.

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TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION ACKNOWLEDGMENTS REFERENCES

 

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