Development of job-exposure matrices for trichloroethylene, tetrachloroethylene, and formaldehyde in Chinese workplaces
Abstract
Background: Job-exposure matrices (JEMs) provide a systematic method to assign exposures based on job titles, thereby enabling efficient occupational exposure assessment in observational studies. However, few JEMs have been specifically developed for chemical occupational exposures in China.
Objectives: We aimed to construct semi-quantitative JEMs for trichloroethylene (TCE), tetrachloroethylene (PCE), and formaldehyde in the Chinese context. These JEMs were developed to support occupational exposure assessment needs in the AsiaLymph study, and to highlight key methodological considerations in JEM construction.
Methods: Exposure information was synthesized from the published literature, routine industrial hygiene inspection data retrospectively collected as part of the AsiaLymph study (2012 to 2017), and established international JEMs. The JEMs were structured across 3 dimensions: chemical agents (TCE, PCE, formaldehyde), job titles (ISCO-88, 3- and 4-digit), and calendar period (1980 to 1990, 1991 to 2000, 2001 to 2010, ≥2011). For each chemical-job-period cell, 2 epidemiologists independently assigned exposure probability and level using a harmonized semi-quantitative scale. Consensus estimates across chemicals and inter-rater agreement were evaluated using Spearman's rank correlation coefficients and Cohen's κ statistics, respectively.
Results: Among 478 job titles, non-zero exposure probability was assigned to 116 (24%) for TCE, 109 (23%) for PCE, and 118 (25%) for formaldehyde. When applying a more stringent, high-specificity exposure definition (probability = 1), the number of job titles classified as exposed decreased to 31 (7%), 25 (5%), and 30 (6%), respectively. Consensus exposure probabilities showed the strongest correlation between TCE and PCE (ρ = 0.95). Inter-rater agreement for exposure probability was 0.90 for TCE, 0.78 for PCE, and 0.44 for formaldehyde.
Discussion: Our semi-quantitative JEMs combine empirical data with expert judgment, offering a practical tool to assess occupational exposures in observational studies. While developed to address the specific needs of the Asialymph study, the JEMs are adaptable and can be validated and extended to other chemical agents in similar settings.
Related
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BibTeX
@article{nie2026development,
title = {{Development of job-exposure matrices for trichloroethylene, tetrachloroethylene, and formaldehyde in Chinese workplaces}},
author = {Jia Nie and Calvin B Ge and Melissa C Friesen and Lauren M Hurwitz and Wei Hu and Nathaniel Rothman and Qing Lan and Roel Vermeulen and Susan Peters},
journal = {Annals of Work Exposures and Health},
year = {2026},
month = nov,
doi = {10.1093/annweh/wxag076},
url = {https://doi.org/10.1093/annweh/wxag076},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Development of job-exposure matrices for trichloroethylene, tetrachloroethylene, and formaldehyde in Chinese workplaces
AU - Jia Nie
AU - Calvin B Ge
AU - Melissa C Friesen
AU - Lauren M Hurwitz
AU - Wei Hu
AU - Nathaniel Rothman
AU - Qing Lan
AU - Roel Vermeulen
AU - Susan Peters
PY - 2026
DA - 2026/11/05
JO - Annals of Work Exposures and Health
DO - 10.1093/annweh/wxag076
UR - https://doi.org/10.1093/annweh/wxag076
AB - Background: Job-exposure matrices (JEMs) provide a systematic method to assign exposures based on job titles, thereby enabling efficient occupational exposure assessment in observational studies. However, few JEMs have been specifically developed for chemical occupational exposures in China. Objectives: We aimed to construct semi-quantitative JEMs for trichloroethylene (TCE), tetrachloroethylene (PCE), and formaldehyde in the Chinese context. These JEMs were developed to support occupational exposure assessment needs in the AsiaLymph study, and to highlight key methodological considerations in JEM construction. Methods: Exposure information was synthesized from the published literature, routine industrial hygiene inspection data retrospectively collected as part of the AsiaLymph study (2012 to 2017), and established international JEMs. The JEMs were structured across 3 dimensions: chemical agents (TCE, PCE, formaldehyde), job titles (ISCO-88, 3- and 4-digit), and calendar period (1980 to 1990, 1991 to 2000, 2001 to 2010, ≥2011). For each chemical-job-period cell, 2 epidemiologists independently assigned exposure probability and level using a harmonized semi-quantitative scale. Consensus estimates across chemicals and inter-rater agreement were evaluated using Spearman's rank correlation coefficients and Cohen's κ statistics, respectively. Results: Among 478 job titles, non-zero exposure probability was assigned to 116 (24%) for TCE, 109 (23%) for PCE, and 118 (25%) for formaldehyde. When applying a more stringent, high-specificity exposure definition (probability = 1), the number of job titles classified as exposed decreased to 31 (7%), 25 (5%), and 30 (6%), respectively. Consensus exposure probabilities showed the strongest correlation between TCE and PCE (ρ = 0.95). Inter-rater agreement for exposure probability was 0.90 for TCE, 0.78 for PCE, and 0.44 for formaldehyde. Discussion: Our semi-quantitative JEMs combine empirical data with expert judgment, offering a practical tool to assess occupational exposures in observational studies. While developed to address the specific needs of the Asialymph study, the JEMs are adaptable and can be validated and extended to other chemical agents in similar settings.
SN - 2398-7308
SN - 2398-7316
ER -