Common mental disorders and long-term sickness absence in a general working population. The Hordaland Health Study

Acta Psychiatr Scand. 2013 Apr;127(4):287-97. doi: 10.1111/j.1600-0447.2012.01902.x. Epub 2012 Jul 7.


Objective: To examine and compare the prospective effect of the common mental disorders (CMD) anxiety and depression on duration and recurrence of sickness absence (SA), and to investigate whether the effect of CMD on SA is detectable over time.

Method: Information from a large epidemiological health study (N = 13 436) was linked with official records of SA episodes lasting ≥16 days up to 6 years after participation. Common mental disorders were assessed with the Hospital Anxiety and Depression Scale (HADS). Associations were analysed with Cox regression and multinomial logistic regression models controlling for potential covariates.

Results: Comorbid anxiety and depression, and anxiety only were significant risk factors for SA after adjusting for covariates, whilst depression only was not. Anxiety and depression were stronger predictors for longer duration of SA episodes compared with shorter duration and associated with more frequent recurrence of SA. There was a general trend toward the effect of CMD on SA becoming weaker over time; however, the effect of anxiety only on SA remained stable throughout the follow-up.

Conclusion: Common mental disorders are long-lasting predictors of onset, duration and recurrence of SA. Anxiety appears to be a more important contributor to long-term SA than previously described in the literature.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anxiety Disorders / epidemiology*
  • Anxiety Disorders / psychology
  • Cohort Studies
  • Comorbidity
  • Depressive Disorder / epidemiology*
  • Depressive Disorder / psychology
  • Female
  • Follow-Up Studies
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Norway / epidemiology
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Factors
  • Sick Leave / statistics & numerical data*
  • Time Factors