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.
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.
Huibers
Marcus J H
MJ
Department of Medical, Clinical and Experimental Psychology, Maastricht University, The Netherlands. m.huibers@dmkep.unimaas.nl
Bültmann
Ute
U
Kasl
Stanislav V
SV
Kant
Ijmert
I
van Amelsvoort
Ludovic G P M
LG
van Schayck
Constant P
CP
Swaen
Gerard M H
GM
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