Municipal unemployment and municipal typologies as predictors of disability pensioning in Norway: a multilevel analysis

Scand J Public Health. 2013 Mar;41(2):158-65. doi: 10.1177/1403494812472004. Epub 2013 Jan 9.

Abstract

Background and aims: The rise in the number of disability pensioners in Norway has been given much attention by the government and by researchers due to the resulting financial and societal challenges entailed. Eligibility for a disability pension is decided by The Norwegian Labour and Welfare Administration (NAV), and is closely correlated with several socioeconomic predictors. Geographical differences have also been observed in the allocations to recipients of disability pensions, and the purpose of this study was to investigate whether municipal unemployment rates and municipal typologies in Norway may explain some of the geographical variance in individual disability pensioning.

Methods: 436 municipalities in Norway and all 1,507,192 Norwegian males and females between the ages of 30-55 years in 1997 were included in the analysis. Multilevel random intercept analysis was performed to assess the influence on disability pensioning of the individual factors age, education and income together with the contextual factors municipal unemployment, centrality, industry affiliation and residential density.

Results: Individuals in high unemployment municipalities had a 7-17% higher risk of disability pension. Of the total variability in disability pensioning, 2.5% for males and 1.9% for females was between municipalities. The other municipal factors had only small influences.

Conclusion: In addition to individual socioeconomic factors, contextual factors seem to be important determinants of disability pension rates. Municipal unemployment had the greatest influence.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Disabled Persons / statistics & numerical data*
  • Female
  • Geography / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Multilevel Analysis
  • Norway
  • Pensions / statistics & numerical data*
  • Risk Factors
  • Socioeconomic Factors
  • Unemployment / statistics & numerical data*