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Objectives To compare the exposure data generated by using the Canadian job-exposure matrix (CANJEM) with data generated by expert assessment, for jobs held by women. Methods We selected 69 occupational agents that had been assessed by experts for each of 3403 jobs held by 998 women in a population-based case–control study of lung cancer. We then assessed the same agents among the same jobs by linking their occupation codes to CANJEM and thereby derived probability of exposure to each of the agents in each job. To create binary exposure variables, we dichotomized probability of exposure using two cutpoints: 25 and 50% (referred to as CANJEM-25% and CANJEM-50%). Using jobs as units of observation, we estimated the prevalence of exposure to each selected agent using CANJEM-25% and CANJEM-50%, and using expert assessment. Further, using expert assessment as the gold standard, for each agent, we estimated CANJEM's sensitivity, specificity, and kappa. Results CANJEM-based prevalence estimates correlated well with the prevalences assessed by the experts. When comparing CANJEM-based exposure estimates with expert-based exposure estimates, sensitivity, specificity, and kappa varied greatly among agents, and between CANJEM-25% and CANJEM-50% probability of exposure. With CANJEM-25%, the median sensitivity, specificity, and kappa values were 0.49, 0.99, and 0.46, respectively. Analogously, with CANJEM-50%, the corresponding values were 0.26, 1.00, and 0.35, respectively. For the following agents, we observed high concordance between CANJEM- and expert-based assessments (sensitivity ≥0.70 and specificity ≥0.99): fabric dust, cotton dust, synthetic fibres, cooking fumes, soldering fumes, calcium carbonate, and tin compounds. We present concordance estimates for each of 69 agents. Conclusions Concordance between CANJEM and expert assessment varied greatly by agents. Our results indicate which agents provide data that mimic best those obtained with expert assessment. [ABSTRACT FROM AUTHOR]

Background: Worldwide, lung cancer is the second leading cause of cancer death in women. The present study explored associations between occupational exposures that are prevalent among women, and lung cancer., Methods: Data from 10 case-control studies of lung cancer from Europe, Canada, and New Zealand conducted between 1988 and 2008 were combined. Lifetime occupational history and information on nonoccupational factors including smoking were available for 3040 incident lung cancer cases and 4187 controls. We linked each reported job to the Canadian Job-Exposure Matrix (CANJEM), which provided estimates of probability, intensity, and frequency of exposure to each selected agent in each job. For this analysis, we selected 15 agents (cleaning agents, biocides, cotton dust, synthetic fibers, formaldehyde, cooking fumes, organic solvents, cellulose, polycyclic aromatic hydrocarbons from petroleum, ammonia, metallic dust, alkanes C18+, iron compounds, isopropanol, and calcium carbonate) that had lifetime exposure prevalence of at least 5% in the combined study population. For each agent, we estimated lung cancer risk in each study center for ever-exposure, by duration of exposure, and by cumulative exposure, using separate logistic regression models adjusted for smoking and other covariates. We then estimated the meta-odds ratios using random-effects meta-analysis., Results and Conclusions: None of the agents assessed showed consistent and compelling associations with lung cancer among women. The following agents showed elevated odds ratio in some analyses: metallic dust, iron compounds, isopropanol, and organic solvents. Future research into occupational lung cancer risk factors among women should prioritize these agents., (© 2024 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals LLC.)

Background: Few studies have compared different measures of frailty for predicting adverse outcomes. It remains unknown which frailty measurement approach best predicts healthcare utilization such as hospitalization and mortality., Aims: This study aims to compare three approaches to measuring frailty-grip strength, frailty phenotype, and frailty index-in predicting hospitalization and mortality among middle-aged and older Canadians., Methods: We analyzed baseline and the first 3-year follow-up data for 30,097 participants aged 45 to 85 years from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA). Using separate logistic regression models adjusted for multimorbidity, age and biological sex, we predicted participants' risks for overnight hospitalization in the past 12 months and mortality, at the first 3-year follow-up, using each of the three frailty measurements at baseline. Model discrimination was assessed using Harrell's c-statistic and calibration assessed using calibration plots., Results: The predictive performance of all three measures of frailty were roughly similar when predicting overnight hospitalization and mortality risk among CLSA participants. Model discrimination measured using c-statistics ranged from 0.67 to 0.69 for hospitalization and 0.79 to 0.80 for mortality. All measures of frailty yielded strong model calibration., Discussion and Conclusion: All three measures of frailty had similar predictive performance. Discrimination was modest for predicting hospitalization and superior in predicting mortality. This likely reflects the objective nature of mortality as an outcome and the challenges in reducing the complex concept of healthcare utilization to a single variable such as any overnight hospitalization., (© 2024. The Author(s).)