Long-term sickness absence due to adjustment disorder

Occup Med (Lond). 2012 Jul;62(5):375-8. doi: 10.1093/occmed/kqs043. Epub 2012 Apr 27.

Abstract

Background: Although adjustment disorder is frequently reported in clinical settings, scientific evidence is scarce regarding its impact on sickness absence and the variables associated with sickness absence duration.

Aims: To report sickness absence duration and to identify predictors of long-term sickness absence in patients with adjustment disorder.

Methods: This observational, prospective study included subjects with non-work-related sickness absence (>15 days) after a diagnosis of adjustment disorder. A stepwise logistic regression analysis was conducted to identify the best predictors of long-term sickness absence (≥ 6 months).

Results: There were 1182 subjects in the final analysis. The median duration of sickness absence due to adjustment disorder was 91 days. Twenty-two per cent of the subjects reported long-term sickness absence. After multivariate analysis, comorbidity (OR = 2.23, 95% CI 1.43-3.49), age (25-34 years old versus <25 years old: OR = 2.78, 95% CI 1.27-6.07; 35-44 years old versus <25 years old: OR = 3.70, 95% CI 1.71-7.99; 45-54 years old versus <25 years old: OR = 3.58, 95% CI 1.60-8.02; ≥ 55 years old versus <25 years old: OR = 6.35, 95% CI 2.64-15.31) and occupational level (blue collar versus white collar: OR = 1.52, 95% CI 1.10-2.09) remained significantly associated with long-term sickness absence. Comorbidity was the strongest predictor.

Conclusions: It is possible to predict long-term sickness absence due to adjustment disorder on the basis of demographic, work-related and clinical information available during the basic assessment of the patient.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absenteeism*
  • Adjustment Disorders / epidemiology*
  • Adult
  • Comorbidity
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prospective Studies
  • Risk Factors
  • Sick Leave / statistics & numerical data*
  • Spain / epidemiology
  • Time Factors
  • Young Adult