Objective The healthy worker survivor effect (HWSE) can affect the validity of occupational studies when data are analysed incorrectly. HWSE depends on three underlying conditions: (1) leaving work predicts future exposure, (2) leaving work is associated with disease outcome and (3) prior exposure increases probability of leaving work. If all these conditions are satisfied, then employment status is a time-varying confounder affected by prior exposure, and standard regression will produce bias. We assessed these conditions for cancer outcomes in a cohort of autoworkers exposed to metalworking fluids (MWF).
Methods The cohort includes 31 485 workers followed for cancer incidence from 1985 to 1994. As occupational exposures to straight, soluble and synthetic MWFs are necessarily zero after leaving work, condition (1) is satisfied. Cox models for cancer incidence and for employment termination were used to assess conditions (2) and (3), respectively. Employment termination by select ages was examined to better gauge the presence of condition (2).
Results The HR for leaving work as a predictor of all cancers combined and prostate cancer was null, but elevated for lung and colorectal cancers among men. Condition (2) was more clearly satisfied for all cancer outcomes when leaving work occurred by age 50. Higher exposures to all three MWF types were associated with increased rates of leaving work (condition (3)), with the exception of straight MWF among women.
Conclusions We found evidence for the structural conditions underlying HWSE in a cohort of autoworkers. G-methods should be applied to reduce HWSE bias in studies of all cancers presently examined.
- healthy worker survivor effect
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.