Berkson error adjustment and other exposure surrogates in occupational case-control studies, with application to the Canadian INTEROCC study.

Abstract

Many epidemiological studies assessing the relationship between exposure and disease are carried out without data on individual exposures. When this barrier is encountered in occupational studies, the subject exposures are often evaluated with a job-exposure matrix (JEM), which consists of mean exposure for occupational categories measured on a comparable group of workers. One of the objectives of the seven-country case-control study of occupational exposure and brain cancer risk, INTEROCC, was to investigate the relationship of occupational exposure to electromagnetic fields (EMF) in different frequency ranges and brain cancer risk. In this paper, we use the Canadian data from INTEROCC to estimate the odds of developing brain tumours due to occupational exposure to EMF. The first step was to find the best EMF exposure surrogate among the arithmetic mean, the geometric mean, and the mean of log-normal exposure distribution for each occupation in the JEM, in comparison to Berkson error adjustments via numerical approximation of the likelihood function. Contrary to previous studies of Berkson errors in JEMs, we found that the geometric mean was the best exposure surrogate. This analysis provided no evidence that cumulative lifetime exposure to extremely low frequency magnetic fields increases brain cancer risk, a finding consistent with other recent epidemiological studies.