Sick-leave track record and other potential predictors of a disability pension. A population based study of 8,218 men and women followed for 16 years

BMC Public Health. 2009 Apr 15:9:104. doi: 10.1186/1471-2458-9-104.


Background: A number of previous studies have investigated various predictors for being granted a disability pension. The aim of this study was to test the efficacy of sick-leave track record as a predictor of being granted a disability pension in a large dataset based on subjects sampled from the general population and followed for a long time.

Methods: Data from five ongoing population-based Swedish studies was used, supplemented with data on all compensated sick leave periods, disability pensions granted, and vital status, obtained from official registers. The data set included 8,218 men and women followed for 16 years, generated 109,369 person years of observation and 97,160 sickness spells. Various measures of days of sick leave during follow up were used as independent variables and disability pension grant was used as outcome.

Results: There was a strong relationship between individual sickness spell duration and annual cumulative days of sick leave on the one hand and being granted a disability pension on the other, among both men and women, after adjustment for the effects of marital status, education, household size, smoking habits, geographical area and calendar time period, a proxy for position in the business cycle. The interval between sickness spells showed a corresponding inverse relationship. Of all the variables studied, the number of days of sick leave per year was the most powerful predictor of a disability pension. For both men and women 245 annual sick leave days were needed to reach a 50% probability of transition to disability. The independent variables, taken together, explained 96% of the variation in disability pension grantings.

Conclusion: The sick-leave track record was the most important predictor of the probability of being granted a disability pension in this study, even when the influences of other variables affecting the outcome were taken into account.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absenteeism
  • Adult
  • Disabled Persons / statistics & numerical data*
  • Female
  • Health Status Indicators
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Pensions / statistics & numerical data*
  • Sick Leave / statistics & numerical data*
  • Sweden