title: Predicting the two-year course of unexplained fatigue and the onset of long-term sickness absence in fatigued employees: results from the Maastricht Cohort Study.
abstract: Because of the serious adverse consequences of unexplained fatigue, it is important to identify factors that determine the prognosis of unexplained fatigue and the onset of long-term sickness absence in fatigued employees. Analyses were based on the Maastricht Cohort Study, a prospective population-based cohort study among more than 12,000 employees. Severely fatigued employees who were not on sick leave (n = 2108) were selected at baseline and followed up at six time points during the course of 2 years. Point prevalences of severe fatigue (59% to 63%) and long-term sickness absence (1.8% to 3.1%) among participants were fairly stable at all consecutive time points. Lower levels of fatigue severity, work-related exhaustion and anxious mood, absence of conflicts with colleagues, and good self-rated health at baseline were predictors of the onset of recovery from fatigue in survival analyses. Older age, low decision authority, female sex, working in nightshift, a physical attribution of fatigue, and a history of absenteeism were predictors of the onset of long-term absenteeism. The course of unexplained fatigue in employees is characterized by remission and relapse in time while the absolute risk of long-term absenteeism is small. Given the broad range of predictors, it appears that fatigue and long-term sickness absence entangle different underlying processes. Our findings underscore the notion that prevention and treatment of fatigue should be aimed at health perception and emotional well-being.
authors.affiliation: Department of Medical, Clinical and Experimental Psychology, Maastricht University, The Netherlands. m.huibers@dmkep.unimaas.nl
authors.forename: Marcus J H
authors.initials: MJ
authors.lastname: Huibers
authors.forename: Ute
authors.initials: U
authors.lastname: Bültmann
authors.forename: Stanislav V
authors.initials: SV
authors.lastname: Kasl
authors.forename: Ijmert
authors.initials: I
authors.lastname: Kant
authors.forename: Ludovic G P M
authors.initials: LG
authors.lastname: van Amelsvoort
authors.forename: Constant P
authors.initials: CP
authors.lastname: van Schayck
authors.forename: Gerard M H
authors.initials: GM
authors.lastname: Swaen
mesh_terms: D000328:Adult; D017677:Age Distribution; D017668:Age of Onset; D015331:Cohort Studies; D018450:Disease Progression; D005221:Fatigue / Q000175:diagnosis / Q000453:epidemiology*; D015673:Fatigue Syndrome, Chronic / Q000175:diagnosis* / Q000453:epidemiology*; D005260:Female; D006801:Humans; D015994:Incidence; D007221:Industry; D008297:Male; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D009784:Occupational Diseases / Q000175:diagnosis* / Q000453:epidemiology*; D016272:Occupational Health; D011237:Predictive Value of Tests; D011336:Probability; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012307:Risk Factors; D017678:Sex Distribution; D018582:Sick Leave / Q000706:statistics & numerical data; D018434:Sickness Impact Profile