Respirable crystalline silica and lung cancer in community-based studies: impact of job-exposure matrix specifications on exposure-response relationships

Johan Ohlander, Hans Kromhout, Roel Vermeulen, Lützen Portengen, Benjamin Kendzia, Barbara Savary, Domenico Cavallo, Andrea Cattaneo, Enrica Migliori, Lorenzo Richiardi, Nils Plato, Heinz-Erich Wichmann, Stefan Karrasch, Dario Consonni, Maria Teresa Landi, Neil E Caporaso, Jack Siemiatycki, Per Gustavsson, Karl-Heinz Jöckel, Wolfgang Ahrens, Hermann Pohlabeln, Guillermo Fernández-Tardón, David Zaridze, Jolanta Lissowska Jolanta Lissowska, Beata Swiatkowska Beata Swiatkowska, John K Field John K Field, John R McLaughlin, Paul A Demers, Tamas Pandics, Francesco Forastiere, Eleonora Fabianova, Miriam Schejbalova, Lenka Foretova, Vladimir Janout, Dana Mates, Christine Barul, Thomas Brüning, Thomas Behrens, Kurt Straif, Joachim Schüz, Ann Olsson, Susan Peters. Scand J Work Environ Health. 2024 Apr 1;50(3):178-186.

Objectives: The quantitative job-exposure matrix SYN-JEM consists of various dimensions: job-specific estimates, region-specific estimates, and prior expert ratings of jobs by the semi-quantitative DOM-JEM. We analyzed the effect of different JEM dimensions on the exposure-response relationships between occupational silica exposure and lung cancer risk to investigate how these variations influence estimates of exposure by a quantitative JEM and associated health endpoints.

Methods: Using SYN-JEM, and alternative SYN-JEM specifications with varying dimensions included, cumulative silica exposure estimates were assigned to 16 901 lung cancer cases and 20 965 controls pooled from 14 international community-based case-control studies. Exposure-response relationships based on SYN-JEM and alternative SYN-JEM specifications were analyzed using regression analyses (by quartiles and log-transformed continuous silica exposure) and generalized additive models (GAM), adjusted for age, sex, study, cigarette pack-years, time since quitting smoking, and ever employment in occupations with established lung cancer risk.

Results: SYN-JEM and alternative specifications generated overall elevated and similar lung cancer odds ratios ranging from 1.13 (1st quartile) to 1.50 (4th quartile). In the categorical and log-linear analyses SYN-JEM with all dimensions included yielded the best model fit, and exclusion of job-specific estimates from SYN-JEM yielded the poorest model fit. Additionally, GAM showed the poorest model fit when excluding job-specific estimates.

Conclusion: The established exposure-response relationship between occupational silica exposure and lung cancer was marginally influenced by varying the dimensions of SYN-JEM. Optimized modelling of exposure-response relationships will be obtained when incorporating all relevant dimensions, namely prior rating, job, time, and region. Quantitative job-specific estimates appeared to be the most prominent dimension for this general population JEM.