Sickness absence as a global measure of health: evidence from mortality in the Whitehall II prospective cohort study

BMJ. 2003 Aug 16;327(7411):364. doi: 10.1136/bmj.327.7411.364.

Abstract

Objective: To examine the association between sickness absence and mortality compared with associations between established health indicators and mortality.

Design: Prospective cohort study. Medical examination and questionnaire survey conducted in 1985-8; sickness absence records covered the period 1985-98.

Setting: 20 civil service departments in London.

Participants: 6895 male and 3413 female civil servants aged 35-55 years.

Main outcome measure: All cause mortality until the end of 1999.

Results: After adjustment for age and grade, men and women who had more than five medically certified absences (spells > 7 days) per 10 years had a mortality 4.8 (95% confidence interval 3.3 to 6.9) and 2.7 (1.5 to 4.9) times greater than those with no such absence. Poor self rated health, presence of longstanding illness, and a measure of common clinical conditions comprising diabetes, diagnosed heart disease, abnormalities on electrocardiogram, hypertension, and respiratory illness were all associated with mortality--relative rates between 1.3 and 1.9. In a multivariate model including all the above health indicators and additional health risk factors, medically certified sickness absence remained a significant predictor of mortality. No linear association existed between self certified absence (spells 1-7 days) and mortality, but the findings suggest that a small amount of self certified absence is protective.

Conclusion: Evidence linking sickness absence to mortality indicates that routinely collected sickness absence data could be used as a global measure of health differentials between employees. However, such approaches should focus on medically certified (or long term) absences rather than self certified absences.

Publication types

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

MeSH terms

  • Adult
  • Age Distribution
  • Cohort Studies
  • Female
  • Health Status*
  • Humans
  • London / epidemiology
  • Male
  • Middle Aged
  • Mortality*
  • Multivariate Analysis
  • Proportional Hazards Models
  • Prospective Studies
  • Sex Distribution
  • Sick Leave / statistics & numerical data*