TY - JOUR
T1 - Respirable crystalline silica and lung cancer in community-based studies
T2 - impact of job-exposure matrix specifications on exposure–response relationships
AU - Ohlander, Johan
AU - Kromhout, Hans
AU - Vermeulen, Roel
AU - Portengen, Lützen
AU - Kendzia, Benjamin
AU - Savary, Barbara
AU - Cavallo, Domenico
AU - Cattaneo, Andrea
AU - Migliori, Enrica
AU - Richiardi, Lorenzo
AU - Plato, Nils
AU - Wichmann, Heinz Erich
AU - Karrasch, Stefan
AU - Consonni, Dario
AU - Landi, Maria Teresa
AU - Caporaso, Neil E.
AU - Siemiatycki, Jack
AU - Gustavsson, Per
AU - Jöckel, Karl Heinz
AU - Ahrens, Wolfgang
AU - Pohlabeln, Hermann
AU - Fernández-Tardón, Guillermo
AU - Zaridze, David
AU - Lissowska, Jolanta
AU - Swiatkowska, Beata
AU - Field, John K.
AU - McLaughlin, John R.
AU - Demers, Paul A.
AU - Pandics, Tamas
AU - Forastiere, Franc Esco
AU - Fabianova, Eleonora
AU - Schejbalova, Miriam
AU - Foretova, Lenka
AU - Janout, Vladimir
AU - Mates, Dana
AU - Barul, Christine
AU - Brüning, Thomas
AU - Behrens, Thomas
AU - Straif, Kurt
AU - Schüz, Joachim
AU - Olsson, Ann
AU - Peters, Susan
N1 - Publisher Copyright:
© 2024, Nordic Association of Occupational Safety and Health. All rights reserved.
PY - 2024/4/1
Y1 - 2024/4/1
N2 - 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.
AB - 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.
KW - case-control study
KW - general population
KW - JEM
KW - lung neoplasm
KW - quantitative exposure assessment
KW - respirable quartz exposure
UR - http://www.scopus.com/inward/record.url?scp=85189192041&partnerID=8YFLogxK
U2 - 10.5271/sjweh.4140
DO - 10.5271/sjweh.4140
M3 - Article
C2 - 38264956
AN - SCOPUS:85189192041
SN - 0355-3140
VL - 50
SP - 178
EP - 186
JO - Scandinavian Journal of Work, Environment and Health
JF - Scandinavian Journal of Work, Environment and Health
IS - 3
M1 - e4140
ER -