Research Needed on Cancer and Asbestos Exposure in Blue Collar Work Researchers Lack Stats in Blue Collar Workers, Asbestos and Cancer

Unfortunately, we did not have information on spouse occupation to explore whether a greater proportion of women in the occupations and industries with an increase in peritoneal cancer risk were married to blue collar workers, which might also have explained some of our findings among women. Therefore, difficulties in identifying precisely the sources of exposure to asbestos and the possibility that other causative agents are involved [Peterson et al., 1984], warrant a conservative evaluation for most positive findings on peritoneal cancer and occupation among women.

On the other hand, the hypothesis of an association for female teachers and other workers in elementary and secondary schools cannot be discarded in light of previous reports of pleural mesothelioma cases among these workers.

Spirtas et al. calculated a relative risk (RR) of 3 (95%CI 0.7,16.5) for peritoneal mesothelioma associated with having ever held any of nine activities where asbestos exposure was suspected, based on 20 male cases and 203 controls [Spirtas et al., 1994]. By applying the same criteria to define exposure to asbestos, we obtained an OR of 1.8 (95%CI 1.3,2.4) among men in our study. Therefore, results from our job-exposure matrix are consistent with Spirtas et al.

The lower risk in the present study may have resulted from the exposure misclassification related to the availability of information on the sole occupation and industry reported on the death certificate, compared to lifetime work histories obtained with telephone interview in the cited paper, and to the disease misclassification due to the use of death certificate diagnoses instead of histopathology data. Workplace environments typically involve exposure to a complex mixture of physical and chemical agents, each of which might be responsible for an observed association.

Compared to occupation and industry titles only, using job-exposure matrices in epidemiologic analyses offers the advantages of a clearer definition of the risk factor and of a greater statistical power by assembling subjects with the same exposure in various occupations and industries.

However, level of detail in the occupation and industry coding system and completeness in working histories of study subjects are critical factors for the performance of job-exposure matrices in identifying the exposure of interest [Dosemeci et al., 1994].