OBJECTIVE: The study examined the multivariate relationship between mental fatigue and different work-related (work load, work hours) and background/life style factors, as well as disturbed sleep. METHODS: A total of 5720 healthy employed men and women living in the greater Stockholm area participated in a questionnaire study on cardiovascular risk factors. The data were analysed using a multiple logistic regression analysis with self-rated fatigue as the dependent variable. RESULTS: Fatigue was predicted by disturbed sleep (4.31; 3.50-5.45, high immersion in work (4.17; 2.93-5.94), high work demands (2.39; 1.54-3.69), social support, being a female, being a supervisor and high age. Shift work, work hours (including overtime) and influence at work did not become significant predictors. With control for work demands a high number of work hours was associated with lower fatigue. CONCLUSION: Disturbed sleep is an important predictor of fatigue, apparently stronger than previously well-established predictors such as work load, female gender, lack of exercise, etc.
OBJECTIVE: The study examined the multivariate relationship between mental fatigue and different work-related (work load, work hours) and background/life style factors, as well as disturbed sleep. METHODS: A total of 5720 healthy employed men and women living in the greater Stockholm area participated in a questionnaire study on cardiovascular risk factors. The data were analysed using a multiple logistic regression analysis with self-rated fatigue as the dependent variable. RESULTS:Fatigue was predicted by disturbed sleep (4.31; 3.50-5.45, high immersion in work (4.17; 2.93-5.94), high work demands (2.39; 1.54-3.69), social support, being a female, being a supervisor and high age. Shift work, work hours (including overtime) and influence at work did not become significant predictors. With control for work demands a high number of work hours was associated with lower fatigue. CONCLUSION: Disturbed sleep is an important predictor of fatigue, apparently stronger than previously well-established predictors such as work load, female gender, lack of exercise, etc.
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