Pain and disability retirement: a prospective cohort study

Pain. 2012 Mar;153(3):526-531. doi: 10.1016/j.pain.2011.11.005.


This study examined the association of pain with subsequent disability retirement due to all causes as well as musculoskeletal diseases, mental disorders, and a heterogeneous group of other diseases and to study whether pain has an effect of its own after taking into account long-standing illness, physician-diagnosed diseases, working conditions, and occupational class, which are the key factors affecting disability retirement. The data consisted of the Helsinki Health Study baseline survey linked to national pension register data (n=6258). Mean follow-up time was 8.1 years. The data included 594 disability retirement events. Pain (acute or chronic) was stratified by long-standing illness (yes/no). Cox regression analysis was performed. Chronic pain without and with co-occurring long-standing illness was strongly associated with all types of disability retirement outcomes, but the associations were particularly strong for disability retirement due to musculoskeletal diseases. The associations remained even when further adjusted for physician diagnosed chronic conditions and diseases, psychosocial and physical working conditions, and occupational class. Associations for acute pain were also found, but they were clearly weaker than those of chronic pain. Chronic pain contributes to disability retirement. Prevention and effective treatment of chronic pain may help prevent early retirement due to disability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Chronic Pain / epidemiology*
  • Chronic Pain / psychology
  • Cohort Studies
  • Disabled Persons / psychology*
  • Disabled Persons / statistics & numerical data*
  • Female
  • Finland / epidemiology
  • Health Surveys
  • Humans
  • Male
  • Middle Aged
  • Occupational Health
  • Regression Analysis
  • Retirement / psychology*
  • Retirement / statistics & numerical data
  • Risk Factors
  • Socioeconomic Factors
  • Workplace