Current determinants of early retirement among blue collar workers in Poland

Int J Occup Med Environ Health. 2005;18(2):177-84.


Background: The current demographic trend in Poland indicates a progressive ageing process, which will result in a decreased number of persons at the age of work capability. Thus it is essential to find out the reasons for the diminished occupational activity of elderly workers. The aim of the project was to identify the factors that significantly contribute to early retirement during the period of socioeconomic transformation in Poland.

Materials and methods: The analysis concerned 637 workers, aged over 45 years, but before reaching the age of retirement (60 years for women and 65 years for men) who were employed in selected industrial enterprises at technological or production-related departments. The study group was recruited from the population of former workers who quit their employment between 1996 and 2000, before they reached the age of retirement. The reference population, matched for age (+/- 3 years) and gender, comprised workers at similar workposts.

Results: The following groups of variables were found to be significant risk factors for early retirement: variables describing the conditions of work (piecework system, OR = 7.00, 95% CI: 2.01-24.37; heavy lifting at work OR = 2.24, 95% CI: 1.20-4.17) and variables related to the household characteristics (shortage of leisure time, OR = 1.87, 95% CI: 1.16-4.67), health condition (disability, OR = 1.87, 95%CI: 1.09-3.21; increased rate of sickness absence, OR = 2.20, 95% CI: 1.52-3.17), and alcohol abuse (OR = 3.19, 95% CI: 1.33-7.64).

Conclusions: The data analysis revealed a spectrum of factors that either contribute to or decrease the risk for early retirement. These may be used as a reference in taking on activities aimed at preventing this adverse trend and stimulating occupational activity of elderly workers.

MeSH terms

  • Age Factors
  • Disability Evaluation
  • Employment / statistics & numerical data*
  • Family Characteristics
  • Female
  • Humans
  • Industry* / classification
  • Logistic Models
  • Male
  • Middle Aged
  • Occupational Health / statistics & numerical data*
  • Occupations / classification
  • Occupations / statistics & numerical data*
  • Poland
  • Retirement / statistics & numerical data*
  • Risk Factors
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Workforce