Utilisation d’une matrice emplois-exposition pour l’identification des expositions professionnelles à l’amiante

Abstract

According to a recent French legislation (1995), retired people who have been exposed to an occupational carcinogen can benefit from a specific post-occupational medical follow-up program, supported by the "Caisse Primaire d'Assurance-Maladie" (CPAM), the French health insurance system. However, only very few people presently take access to this social measure. The ESPACES project developed and evaluated a procedure to identify retirees who have been exposed to asbestos during their career, and to inform them about the post-occupational medical follow-up program. This pilot study was performed within the health centers ("Centres d'examens de santé" (CES)) of the health insurance system in a random sample of men who have retired from the six main French administrative divisions between 1994 to 1996. A probability of exposure to asbestos was attributed through a job exposure matrix. Subjects were interviewed in the CES to validate their exposure data. Retired subjects with confirmed exposure to asbestos were referred to their CPAM, to apply for the medical follow-up. The whole process was evaluated through a comparison with control CPAMs, and simulations were performed to assess its sensitivity and specificity, as well as the total number of persons in France who could potentially benefit. Among the 737 persons classified as exposed by the matrix who came to the CES, the exposure was confirmed for 53.8%, and 143 benefited from the medical follow-up, 17 times more than in a sample of control CPAMs. Based on an annual number of about 250,000 new retirees, simulations showed that a low detection threshold, taking into account the probability and duration of exposure, would yield approximately 25,000 persons coming to the CES, more 6,000 of them benefiting from the follow-up. The proposed detection threshold would allow for a feasible and ethically acceptable generalization, due to the optimization of the false negative and false positive rate.