Job characteristics as risk factors for early retirement due to ill health: The Korean Longitudinal Study of Aging (2006-2014)

J Occup Health. 2019 Jan;61(1):63-72. doi: 10.1002/1348-9585.12014.

Abstract

Objectives: To investigate work-related factors that contribute to early retirement due to ill health (ERIH) in middle-aged and elderly people in Korea.

Methods: Data were collected from a sample from the first through the fifth phases of the Korean Longitudinal Study of Aging which was conducted biennially from 2006 to 2014. ERIH was defined as the retirement of workers due to health problems before their scheduled or regular retirement age as reported in one of the follow-up surveys. Three broad subdomains of working conditions were examined: work arrangements, physical working conditions, and job satisfactions. Hazard ratios of ERIH were estimated by Cox regression.

Results: Females, older people, unskilled manual workers, and day laborers were more likely to experience ERIH. In adjusted Cox proportional hazard models, the risk for ERIH in male workers was significantly higher among those with the following conditions: high physical demands, awkward posture, dissatisfaction with the working environment, and no industrial compensation insurance or retirement benefits. However, no significant association was found among female participants.

Conclusions: Occupational class, physical working conditions, job satisfaction, and work arrangement were the potential risk factors for ERIH among male workers in Korea. Moreover, our results revealed gender differences in the risk for ERIH.

Keywords: early retirement due to ill health; gender difference; occupational class; work arrangement; working conditions.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Aging
  • Female
  • Health Status*
  • Humans
  • Job Satisfaction
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Occupations* / classification
  • Proportional Hazards Models
  • Republic of Korea
  • Retirement / statistics & numerical data*
  • Risk Factors
  • Sex Distribution
  • Surveys and Questionnaires
  • Workplace / psychology*