Long-term sickness absence: changes in risk factors and the population at risk

Int J Occup Med Environ Health. 2009;22(2):157-68. doi: 10.2478/v10001-009-0018-3.


Objectives: To investigate changes over time in factors associated with long-term sickness absence (LTSA) and in the fraction of LTSA attributable to these risk factors in 1986-1989 and 2002, respectively.

Materials and methods: Data from two earlier Swedish studies respectively comprising 1622 and 2009 employees with a history of LTSA (> or = 60 days), and 1019 and 1903 employed members of the general labour force as controls (ages 20-64 years) was used. The studies were conducted before and after extensive changes in the Swedish labour market during the 1990s, and they used sickness absence data from national social insurance records and self-reported information on sociodemographic, lifestyle, and work characteristics. Associations between these factors and LTSA were estimated by logistic regression, and population attributable fractions were calculated.

Results: The results indicate that, after the 1990s, LTSA was associated with female sex (odds ratio = 1.84, 95% CI: 1.57-2.15) and was also more strongly associated with various aspects of the psychosocial work environment and job situations. A larger population at risk, primarily an ageing workforce, account for a large proportion of LTSA.

Conclusions: The results confirm consistent associations between LTSA and several established risk factors, and they also reveal a change in the risk panorama. The current findings demonstrate that, to understand the magnitude of LTSA, both risk factors and the population at risk must be monitored over time. Prevention should aim to create healthy workplaces in general and also focus on female-dominated public sector occupations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absenteeism*
  • Adult
  • Female
  • Humans
  • Life Style
  • Logistic Models
  • Male
  • Middle Aged
  • Risk Factors
  • Sick Leave / statistics & numerical data*
  • Socioeconomic Factors
  • Sweden / epidemiology
  • Time Factors