Determinants of disability pension applications and awarded disability pensions in Finland, 2009 and 2014

Scand J Public Health. 2020 Mar;48(2):172-180. doi: 10.1177/1403494819843778. Epub 2019 May 2.

Abstract

Aims: Examining the non-medical determinants of applying for and being awarded disability pension is important for assessing the functionality of the disability pension system. We examined how demographic and socioeconomic factors as well as factors related to the disability process associate with the probability of applying for disability pension and the probability of applicants being awarded pension in 2009 and 2014. Methods: 70% random samples of Finnish non-retired residents aged 18-64 in 2009 (n = 2,076,881) and in 2014 (n = 2,097,790) were analysed with logistic regression analysis. The application rates were 0.9% in 2009 and 0.7% in 2014, and the rates of awarded pensions were 80.6% in 2009 and 72.2% in 2014. Results: Being an upper-level non-manual employee and having more employment during the preceding four calendar years decreased the odds of applying for disability pension but increased the odds of being awarded one. Older age increased the odds of both applying for and being awarded pension. Compared to applications based on mental disorders, those applying due to neoplasms and diseases of the circulatory system had increased odds of being awarded pension whereas those applying due to musculoskeletal diseases or injuries had decreased odds. Only minor temporal changes were found in the determinants of applying for or being awarded disability pension. Conclusions: With a greater probability of disability pension applications but also a lower probability of being awarded pension, the occupational disability process involves a comprehensive disadvantage for lower socioeconomic status groups.

Keywords: Disability pensions; diagnoses; disability insurance; pension applications; sociodemographics; socioeconomic status.

MeSH terms

  • Adolescent
  • Adult
  • Disabled Persons / statistics & numerical data*
  • Female
  • Finland
  • Humans
  • Male
  • Middle Aged
  • Pensions / statistics & numerical data*
  • Risk Factors
  • Young Adult