A comparison of socio-economic differences in long-term sickness absence in a Japanese cohort and a British cohort of employed men

Eur J Public Health. 2004 Dec;14(4):413-6. doi: 10.1093/eurpub/14.4.413.

Abstract

Objectives: To compare the magnitude of socio-economic differences in sickness absence rates between a Japanese cohort and a British cohort. To assess the effects of self-rated health and behavioural risk factors on sickness absence in the two cohorts, and whether they explain socio-economic differences in sickness absence within and between cohorts.

Methods: An 8 year follow up study of sickness absence in 2504 Japanese male employees in a factory in Japan and 6290 British male employees in civil service departments in London. The rates of first occurrences of long-term (>7 calendar days) sickness absence were determined and compared between these cohorts. Socio-economic status was measured with hierarchical employment grades.

Results: The first time sickness absence rates were about two times higher among British men as compared with Japanese men. The rate ratio of lower to higher employment grade was 1.2, 1.3 and 2.1 among Japanese white-collar, Japanese blue-collar and British white-collar employees respectively. Baseline self-rated health and smoking habit predicted sickness absence in both cohorts. After adjusting for these factors a significant difference between the Japanese and British cohorts, and between employment grades remained.

Conclusions: The rate of long-term sickness absence was higher in the British cohort than the Japanese cohort.

Publication types

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

MeSH terms

  • Absenteeism*
  • Adult
  • Alcohol Drinking / epidemiology
  • Exercise
  • Follow-Up Studies
  • Health Behavior*
  • Health Status*
  • Humans
  • Japan / epidemiology
  • London / epidemiology
  • Male
  • Middle Aged
  • Occupational Health / statistics & numerical data*
  • Occupations / classification
  • Proportional Hazards Models
  • Risk Factors
  • Sick Leave / statistics & numerical data*
  • Smoking / epidemiology
  • Socioeconomic Factors
  • Surveys and Questionnaires