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Ohlander, J.* ; Kromhout, H.* ; Vermeulen, R.* ; Portengen, L.* ; Kendzia, B.* ; Savary, B.* ; Cavallo, D.* ; Cattaneo, A.* ; Migliori, E.* ; Richiardi, L.* ; Plato, N.* ; Wichmann, H.-E. ; Karrasch, S. ; Consonni, D.* ; Landi, M.T.* ; Caporaso, N.E.* ; Siemiatycki, J.* ; Gustavsson, P.* ; Jöckel, K.H.* ; Ahrens, W.* ; Pohlabeln, H.* ; Fernández-Tardón, G.* ; Zaridze, D.* ; Lissowska, J.* ; Swiatkowska, B.* ; Field, J.K.* ; McLaughlin, J.R.* ; Demers, P.A.* ; Pandics, T.* ; Forastiere, F.E.* ; Fabianova, E.* ; Schejbalova, M.* ; Foretova, L.* ; Janout, V.* ; Mates, D.* ; Barul, C.* ; Brüning, T.* ; Behrens, T.* ; Straif, K.* ; Schüz, J.* ; Olsson, A.* ; Peters, S.*

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

Scand. J. Work Environ. Health 50, 178-186 (2024)

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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 expo-sure–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.

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