학술논문
Respirable crystalline silica and lung cancer in community-based studies: impact of job-exposure matrix specifications on exposure–response relationships
Document Type
article
Author
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
Source
Scandinavian Journal of Work, Environment & Health, Vol 50, Iss 3, Pp 178-186 (2024)
Subject
Language
English
ISSN
0355-3140
1795-990X
1795-990X
Abstract
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.