Underestimation of Risk Due to Exposure Misclassification

ABSTRACT

Aim. Exposure misclassification constitutes a major obstacle when developing dose-response relationships for risk assessment. A non-differentional error results in underestimation of the risk. If the degree of misclassification is known, adjustment may be achieved by sensitivity analysis. The purpose of this study was to examine the full magnitude of measurement error in determining the prenatal exposure to methylmercury. Materials and methods. We used data from a prospective study of a Faroese birth cohort. Two biomarkers of methylmercury exposure were available, i.e., the mercury concentrations in cord blood and in maternal hair (sampled at the time of parturition). The laboratory imprecision on both chemical analyses was thought to be below 5% (coefficient of variation, CV). As a third exposure parameter, we used the dietary questionnaire response on frequency of whale meat dinners. Factor analysis and structural equation analysis were applied to assess the full extent of the imprecision. Results. The calculated total imprecision much exceeded the known laboratory variation: the CV was 28–30% for the cord-blood concentration and 52–55% for the maternal hair concentration. The dietary questionnaire response was even more imprecise. Conclusions. These findings illustrate that measurement error may be greatly underestimated if judged solely from reproducibility or laboratory quality data. Adjustment by sensitivity analysis is meaningful only if realistic measurement errors are applied. When exposure measurement errors are overlooked or underestimated, decisions based on the precautionary principle will not appropriately reflect the degree of precaution that was intended.

Key Words:

• biological markers
• dose-response relationship
• prenatal exposure delayed effects
• risk factors
• statistical models

Acknowledgments

This article is reprinted with permission from the European Journal of Oncology Library, vol. 2, 2003, with which the copyright resides.

Supported by grants from the U.S. National Institute of Environmental Health Sciences (ES06112 and ES09797), the European Commission (Environment Research Programme) and the Danish Medical Research Council. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS, NIH or any other funding agency.