Industrial differences in disability retirement rates in Denmark, 1996-2000

Int J Occup Med Environ Health. 2004;17(4):465-71.

Abstract

Objectives: The objective of the study was to identify industries associated with a high risk of disability retirement and to roughly estimate the fraction of the retirements that can be attributed to a non-optimum work environment.

Materials and methods: All economically active people in Denmark, aged 20-54 years, in the beginning of 1996 (1196235 men and 1063058 women) were followed-up from 1996 to 2000. Gender stratified and age standardized incidence ratios (SIR) for disability retirement were calculated for each of 58 baseline industries. A Monte-Carlo simulation model was used to estimate attributable fractions.

Results: In total, we observed 17242 disability retirements among the men and 20910 among the women. The attributable fraction was 38% for the women and 40% for the men. Twenty-six of the SIR-values (13 among the men and 13 among the women) were statistically significantly high. Twenty-two of the 26 groups with a high SIR had been identified by previous research as groups at high risk of circulatory disease and/or musculoskeletal disorders. Two of the remaining four groups with a high SIR were associated with hard physical work (men and women engaged in horticulture and forestry) while the other two consisted of men in female-dominated industries (child-care and cleaning).

Conclusions: The present study identified a series of high-risk industries. It also corroborated previous findings, which state that circulatory disease and musculoskeletal disorders are major risk factors and that hard physical work is an independent risk factor of disability retirement. Further research is needed to find out why men in some stereotypically feminine industries are at high risk of disability retirement.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Chronic Disease
  • Denmark / epidemiology
  • Disabled Persons / statistics & numerical data*
  • Female
  • Humans
  • Industry / classification
  • Industry / statistics & numerical data*
  • Male
  • Middle Aged
  • Occupational Health
  • Occupations / classification
  • Occupations / statistics & numerical data*
  • Pensions
  • Retirement / statistics & numerical data*
  • Risk Assessment
  • Sex Distribution
  • Social Security
  • Workplace / classification*
  • Workplace / standards