A functional regression model for the retrospective assessment of asbestos exposure among Venetian dock workers

Retrospective assessment of individual exposure in occupational settings is often based on the association of individual work histories with quantitative and semi-quantitative exposure information. In the absence of exposure information, researchers have commonly used proxy variables, but with strong assumptions and some limitations. In the present work, we estimate the time-varying exposure-risk function associated with the outcomes of interest, taking into account functional regression models and individual work periods. The work was motivated by the analysis of a cohort of dock workers occupationally exposed to asbestos in Italy. We evaluated the potential of our proposal through a series of simulations. We then compared our approach with traditional methods that use exposure proxy variables.