Susan Peters

Background: Occupational epidemiological analyses typically focus on a priori hypotheses relating disease to specific exposures or occupations. We used regularized regression models to agnostically identify occupations associated with lung cancer while accounting for known lung carcinogens. Methods: We pooled data from 14 European and Canadian lung cancer case–control studies. The main analysis included 13 587 cases and 16 410 controls for men and 3199 cases and 4408 controls for women. Associations between ever-employment in various occupations and lung cancer risks were evaluated using two selection approaches: a least absolute shrinkage and selection operator regression and a two-stage Bayesian hierarchical horseshoe model accounting for age, study, smoking, and occupational exposure to known lung carcinogens. Unconditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for selected occupations. Results: For men, occupations consistently identified as positively associated with lung cancer included miners (OR = 1.28, 95% CI: 1.06–1.54) and bricklayers (OR = 1.30, 95% CI: 1.12–1.52), while secondary education teachers (OR = 0.37, 95% CI: 0.22–0.60), production managers (OR = 0.66, 95% CI: 0.54–0.81), and government executive officials (OR = 0.72, 95% CI: 0.62–0.83) were negatively associated. For women, secondary language and literature teachers (OR = 0.39, 95% CI: 0.20–0.72) and government executive officials (OR = 0.63, 95% CI: 0.48–0.81) showed negative associations. Conclusion: Two agnostic, data-driven models identified several occupations associated with both increased and decreased lung cancer risks. These associations persisted after accounting for known exposures and covariates, highlighting the need to investigate unidentified occupational factors.

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.

Objective: Shift work is common in healthcare and may contribute to headache disorders through mechanisms such as circadian disruption and sleep disturbance. However, evidence from large prospective cohort studies remains limited. This study investigated the associations between shift work and headache and migraine in a cohort of Dutch nurses. Methods: Participants completed questionnaires in 2011 (n = 59,768) and 2017 (n = 37,713), reporting headache, migraine, work history, sleep problems, and lifestyle factors. Headache and migraine were assessed using the validated Headache Impact Test (HIT-6) and ID-Migraine questionnaires. Associations between shift work and the prevalence of headache or migraine at baseline and follow-up were examined using Poisson regression with robust variance to directly estimate relative risks. Additional analyses examined current shift work status and shift work duration. Results: Ever shift work was associated with a higher prevalence of headache at baseline (relative risk = 1.04, 95% confidence interval: 1.01 to 1.07), although this association attenuated after adjustment for sleep problems (relative risk = 1.01, 95% confidence interval: 0.98 to 1.04). For migraine, ever shift work was associated with a higher prevalence at follow-up (relative risk = 1.13, 95% confidence interval: 1.02 to 1.26), whereas no association was found at baseline. Current shift work was not consistently associated with headache or migraine. Conclusions: Ever shift work was associated with a small increase in the prevalence of migraine. Associations with headache attenuated after adjustment for sleep problems. No consistent associations were observed for current shift work.

Objectives: Occupational exposures may contribute to the development of COPD, a leading cause of morbidity and mortality globally. Using an exposome approach in a follow-up design, we aimed to examine the association between the occupational exposome and new-onset COPD in 2 population-based cohorts: the European Community Respiratory Health Survey (ECRHS) with 2 follow-ups (n = 4,087; observations = 6,224) and the CONSTANCES cohort with 1 follow-up (n = 8,255). Methods: COPD was defined by respiratory symptom(s) and forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) below the lower limit of normal. Occupational exposures were assessed through long-term job histories linked to 6 job exposure matrices representing 49 different chemical, ergonomic, and physical exposures. Cumulative occupational exposures until baseline were assigned to each participant. Three analytical approaches were used: Exposome-Wide Association Study (ExWAS), Least Absolute Shrinkage and Selection Operator (LASSO), and Boruta Random Forest. Results: In ECRHS, across the 3 analytical approaches, the most important exposures associated with increased COPD were heavy lifting, forward-bent posture, gases and fumes, mineral dust, house dust mites, and kneeling/squatting. In CONSTANCES, the most important exposures were diesel exhaust fumes, respirable crystalline silica, other solvents, organic solvents, indoor cleaning, and mineral dust. Differences in follow-up time and cohort characteristics may explain cohort discrepancies. Conclusion: We confirmed the importance of several chemical occupational exposures for COPD and observed new associations between ergonomic and physical occupational exposures and COPD. These associations more likely reflect broader occupational exposure patterns than independent effects and should be interpreted in that context. Despite complexities in interpretation, the results underline the importance of implementing new analytical approaches, as it provide opportunities to identify the interplay of occupational exposures in an occupational exposome context.

Hexavalent chromium (Cr(VI)) is a human carcinogen. It is unclear whether Cr(VI) can cause cancer of the small intestine, oral cavity, pancreas, prostate and urinary bladder. We performed a systematic review and meta-analyses of epidemiological studies on occupational exposure to Cr(VI) and incidence and mortality of these cancer sites. A comprehensive review of human studies on Cr(VI) and cancer was performed in Embase and Scopus. 131 potentially relevant epidemiological studies were identified. Study quality was assessed using the Newcastle-Ottawa Scale. 29 publications including 81 observations for meta-analyses were based on cohort or case–control studies with exposure assessment of sufficient quality. Site-specific random-effects meta-analyses were done separately for incidence and mortality. Sensitivity analyses focused on the studies with the highest quality scores. No indications for an association between Cr(VI) exposure and oral or small intestine cancer were found. Incidence of pancreatic cancer was not associated with Cr(VI) exposure (meta-relative risk (RR) 1.04; 95% CI 0.85 to 1.28) while for specific mortality RR was 1.41 (95% CI 0.96 to 2.08) with moderate heterogeneity (I ² =41%) and an asymmetric funnel plot (Egger’s test; p=0.002). For incidence of prostate cancer meta RR was 1.16 (95% CI 0.99 to 1.37) while the RR for mortality was 1.03 (95% CI 0.84 to 1.25). For bladder cancer, RR was 1.04 (95% CI 0.91 to 1.20) for incidence and 1.76 (95% CI 1.20 to 2.60) for mortality. This comprehensive meta-analysis of epidemiological studies did not provide sufficient evidence that occupational Cr(VI) exposure may cause cancer of the oral cavity, small intestine, pancreas, prostate or the urinary bladder in humans.

Metabolomics was employed to explore perturbations in biological pathways that may be associated with working at night.This study included night-shift and day-shift workers (n = 825) across the Netherlands (n = 76), Spain (n = 385), Sweden (n = 168), and Denmark (n = 196). 179 metabolites from plasma samples, including lipids and lipoproteins, fatty acids, amino acids, and energy key-related, were analysed. A metabolome-wide association study was conducted to explore associations between night-shift work and individual metabolites. Principal Component Analysis (PCA) was used to investigate the correlation pattern of groups of metabolites. In addition, metabolomics-derived risk scores for summary mortality and risk of cardiovascular disease were estimated.Night-shift workers showed higher levels of acetone (β: 0.004, FDR < 0.01), acetoacetate (β: 0.006, FDR < 0.01) and isoleucine (β: 0.005, FDR = 0.05), and lower levels of alanine (β: -0.024, FDR < 0.01) compared to day-shift workers. In the PCA, night-shift was negatively associated with a component characterized by glycine, glutamine and alanine (β = –0.38, 95% CI: –0.55 to –0.20); as well as with lower levels of a component positively loaded by fatty acids unsaturation, DHA, and PUFA/MUFA ratio (β = -0.26, 95% CI: -0.48 to -0.02). Night-shift workers had higher mortality metabolomics-derived risk scores (β = 0.06, 95% CI: –0.01 to 0.13).Modest alterations in ketone bodies, fatty acids and amino acids, and higher metabolomics-derived risk scores were observed in night-shift versus day-shift workers, suggesting an adverse association of night-shift work on health.

Background: Lung cancer compensation systems for occupational exposure to asbestos commonly apply Helsinki criteria, which assume 4% excess lung cancer risk per fibre-year of asbestos exposure. The ′Probability of Causation (PoC)′ is ≥50% at 25 fibre-years (risk doubling threshold). Large case-control studies have suggested steeper exposure-response relations at lower exposures. We aimed to estimate PoC of asbestos-related lung cancer to evaluate exposure thresholds for compensation of lung cancer cases occupationally exposed to asbestos. Methods: Relative risk of asbestos-related lung cancer was estimated using two approaches: » A meta-regression of 22 occupational studies forming the core evidence on cumulative asbestos exposure and lung cancer since the 1980s (130,341 participants). » A meta-analysis of the recently conducted SYNERGY pooled case-control study (14 studies, 37,866 participants), adjusted for age, sex, smoking, and study. The likelihood that lung cancer was caused by asbestos was estimated as the PoC with 95% prediction intervals (95%PI). Results: Occupational cohort studies produced a shallow exposure-response relation with substantial heterogeneity (I² = 92.7%). SYNERGY showed a steeper relation with 6.8% (95%PI: 0% – 17.7%) lung cancer risk increase per fibre-year and lower heterogeneity (I² = 63.4%). PoC ≥50% occurred at 62.9 (point estimate) and 18.2 fibre-years (upper 95%PI) for occupational asbestos studies, compared to 10.5 and 4.3, respectively, in SYNERGY. Conclusions: The SYNERGY pooled case-control study provided exposure-response estimates that are more representative of current exposure to lower mixed asbestos fibres in the Netherlands, supporting lower exposure thresholds than the existing Helsinki criteria when estimating PoC in compensation contexts.

Low-cost particulate matter (PM) sensors are useful for measuring exposure to hazardous particles in the workplace but show different levels of structural under- or overestimation (ie bias) and random variation (ie error) for different types of particles. Traditional calibration methods that are based on comparing with reference measurements can improve sensor performance but require substantial quantities of reference measurements, which may be infeasible to collect when sensors are used in many different situations. This study aimed to quantify sensor performance in different occupational situations and compare methods for improving performance without requiring reference measurements. Sensor measurements with paired reference measurements for particle number (n = 253) and mass (n = 33) concentrations were collected for 6 situations, where particles were assumed to consist of primarily cinnamon, flour, quartz, spruce wood, varnish, or welding fumes. Absolute and relative bias and error were calculated for sensor-reported measurements and 4 methods to calculate mass concentrations from particle number counts. Methods included a literature-derived calibration model and 3 physics-based algorithms that included combinations of particle size, density, and shape. For particle number concentrations, the highest relative bias was observed for the smallest size bin (0.3 to 0.5 µm). PM2.5 mass concentrations were underestimated by 72% compared to reference respirable dust measurements. This underestimation was reduced to 4.5% by recalculating mass from particle number concentrations, assuming uniform particle density and shape and attributing size fractions according to the respirable dust convention. Including particle-specific density and shape showed minor additional changes in overall bias (4.4% overestimation) but halved relative bias for 4 situations. Error was comparable for sensor-reported and recalculated mass concentrations (SD ranging from 93% to 106%) but differed between situations. This study addresses challenges in sensor performance in occupational settings. It shows that recalculating mass from particle counts can reduce bias without extensive reference measurements. This practical approach enhances sensor accuracy, aiding in better monitoring and managing hazardous particle exposure, ultimately improving occupational health.

Objective The association between occupational exposure to chlorinated solvents and lung cancer remains inconclusive. This study investigated this relationship using data from the internationally pooled SYNERGY study. Methods Data from 14 case–control studies conducted in 13 European countries and Canada were pooled, including 28 048 participants (12 329 cases and 15 719 controls). Lifetime occupational exposure to chlorinated solvents was assessed using the ALOHA+job-exposure matrix. ORs and 95% CIs were estimated using unconditional logistic regression, adjusted for study centre, age, sex, smoking (pack-years and cessation), cumulative exposure to five occupational lung carcinogens (asbestos, hexavalent chromium, polycyclic aromatic hydrocarbons, respirable crystalline silica and diesel engine exhaust), cumulative benzene exposure and employment in high-risk occupations (‘List A’ jobs). Associations were estimated across categories of exposure levels, durations and analyses stratified by smoking status and lung cancer subtypes. Results We found no evidence of an association between ever exposure to chlorinated solvents and lung cancer risk (OR 1.03; 95% CI 0.96 to 1.10). Among exposed individuals, a positive trend with cumulative exposure was observed (p=0.031), but not when non-exposed individuals were included (p=0.173). Positive trends were found with exposure duration (p=0.005 for exposed; p=0.048 overall); risks were modestly elevated (OR 1.11) in those exposed for 20 or more years. No increased risk was observed across smoking strata or lung cancer subtypes. Conclusions This pooled analysis provides limited evidence of an association between occupational exposure to chlorinated solvents and lung cancer, though exposure-response trends were noted among exposed individuals.