Occupational epidemiologist's quest to tame measurement error in exposure

Abstract

I aimed to assess current practices and opportunities for addressing the problem of errors in exposure in occupational epidemiology. Occupational epidemiologists appreciate that errors in exposure are a concern, but almost none correct for these errors, although there are currently no theoretical and practical barriers for this inertia. The most serious barrier to change is a faulty belief that a well-conducted epidemiologic study suffers only non-differential exposure misclassification and that its sole impact is to attenuate risk gradients, causing a false negative. On the contrary, differential exposure misclassification is the most defensible model in occupational epidemiology, and errors in exposure increase chance of both false positive and negative results. Resistance to mathematical adjustment for errors in exposure is equivalent to denying the value of more valid exposure estimates and undermines the discipline's relevance to protection of workers by informing workplace exposure limits.

Keywords

• Exposure measurement error
• Observational error
• Exposure misclassification
• Bias (epidemiology)
• Occupational epidemiology
• Bias correction