Voorspellers van langdurig ziekteverzuim*

Objective

To examine which factors are associated with the duration of sick leave in employees who had been sick-listed for at least 4 weeks for any cause.

Design

Prospective cohort study.

Method

Data were collected from employees who had been on sick leave for at least 4 weeks. Possible predictors of absenteeism were collected by means of a questionnaire upon study inclusion. The dependent variable, duration until full return to work, was extracted from the Dutch Occupational Health and Safety Services' database at 1 year after the start of sick leave. The Cox proportional hazards regression model was used to calculate the factors predicting the duration of sick leave.

Results

We analysed data from 562 employees. During the first year of sick leave, 71% of the employees had fully returned to work, 9.1% had resigned during this period and 19.9% had not yet returned to work. Predictors for a longer period of absence were: Physically demanding work (HR (hazard ratio): 0.562; 95% CI: 0.348-0.908), contact with medical specialists (HR: 0.691; 95% CI: 0.560-0.854), many physical symptoms (HR: 0.744; 95% CI: 0.583-0.950), moderate to severe symptoms of depression (HR: 0.748; 95% CI: 0.569-0.984) and older age (HR: 0.776; 95% CI: 0.628-0.958).

Conclusion

Sick-listed employees with physically demanding jobs, contact with medical specialists, many physical symptoms, symptoms of moderate to severe depression and older age are at an increased risk for longer absenteeism. Awareness of these predictors of long-term sick leave by occupational physicians helps to identify those employees at high risk.

Conflict of interest: the Dutch Health Insurers Innovation Fund (Innovatiefonds Zorgverzekeraar) financed the RCT from which this cohort study emerged. Prof.dr. C.M. van der Feltz-Cornelis received remuneration from Eli Lilly for a lecture on diabetes and depression as well as royalties from books on psychiatry. Financial support for this article: none declared.