Abstract

When pooling data across community-based case-control studies exposure assessment has to be redone in order to overcome the issue of the lowest common denominator. Also when exposure assessment is based on expert judgement, no straightforward approaches exist for calibration and pooling of these exposure estimates. Often though, complete and detailed occupational histories of study participants will be available which can be used for a standardised approach across centres/studies. For instance in the SYNERGY project we successfully managed to collect actual exposure measurements across Europa and Canada covering almost 4 decades (1970–2010). Based on this wealth of exposure data a JEM could be elaborated with quantitative estimates of level of exposure by job, year and region. Combining this JEM with occupational histories of cases and controls resulted in quantitative exposure histories which allowed derivation of quantitative exposure response relationships for amongst others silica and asbestos. In industry-based cohort studies exposure assessment can often be performed at a more detailed level by ascertaining detailed occupational histories and collecting production characteristics in multiple companies enrolled in a cohort study. By collecting industry-specific measurements with detailed auxiliary information very detailed exposure models can be derived. Consequently these models will allow for quantitative exposure estimates at the detailed level of exposure scenario (rather than at the level of a job). For instance, in the European Asphalt Workers study we were able to estimate quantitatively workers exposure to bitumen fume, organic vapour, and benzo(a)pyrene. Standardisation of exposure assessment tools, approaches and empirical modelling are needed in this day and age where big data will be the norm and will be needed to discern undetected health risks. However, availability of actual measurements of workers’ exposure will stay a prerequisite in order to calibrate and validate exposure assessment methods employed in large-scale epidemiological studies on occupational health risks.