Predicting long-term sickness absence from sleep and fatigue

J Sleep Res. 2007 Dec;16(4):341-5. doi: 10.1111/j.1365-2869.2007.00609.x.


Disturbed or shortened sleep is prospectively related to disease. One might also expect that sickness absence would be another consequence but very little data seem to exist. The present study used 8300 individuals in a national sample to obtain information on reports of disturbed sleep and fatigue one [corrected] year and merged this with data on long-term sickness absence two [corrected] years later. A logistic regression analysis was applied to the data with adjustments for demographic and work environment variables. The results showed that individuals without registered sickness absence at the start had a higher probability of entering a period of long-term (>/=90 days, odds ratio [OR] = 1.24 with 95% Confidence Interval [CI] = 1.09[corrected]-2.18[corrected]) sickness absence two [corrected] years later if they reported disturbed sleep at the start. The value [corrected] for fatigue was OR = 1.69[corrected] (CI = 1.23[corrected]-2.33[corrected]). When fatigue or disturbed sleep was separately excluded the OR increased to OR = 1.90[corrected] and OR = 1.86[corrected], respectively. Intermediate sickness absence (14-89 days) showed similar but slightly weaker results. The results indicate that disturbed sleep and fatigue are predictors of long-term absence and it is suggested that impaired sleep may be part of a chain of causation, considering its effects on fatigue.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absenteeism*
  • Adolescent
  • Adult
  • Causality
  • Cross-Sectional Studies
  • Fatigue / epidemiology*
  • Female
  • Health Surveys
  • Humans
  • Job Satisfaction
  • Logistic Models
  • Male
  • Middle Aged
  • Odds Ratio
  • Probability
  • Risk Factors
  • Sick Leave / statistics & numerical data*
  • Sleep Deprivation / epidemiology
  • Sleep Wake Disorders / diagnosis
  • Sleep Wake Disorders / epidemiology*
  • Social Environment
  • Social Support
  • Socioeconomic Factors
  • Sweden
  • Workplace