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BACKGROUND: Generic job-exposure matrices (JEMs) are often used in population-based epidemiologic studies to assess occupational risk factors when only the job and industry information of each subject is available. JEM ratings are often based on professional judgment, are usually ordinal or semi-quantitative, and often do not account for changes in exposure over time. We present an empirical Bayesian framework that combines ordinal subjective JEM ratings with benzene measurements. Our aim was to better discriminate between job, industry, and time differences in exposure levels compared to using a JEM alone. METHODS: We combined 63 221 short-term area air measurements of benzene exposure (1954-2000) collected during routine health and safety inspections in Shanghai, China, with independently developed JEM intensity ratings for each job and industry using a mixed-effects model. The fixed-effects terms included the JEM intensity ratings for job and industry (both ordinal, 0-3) and a time trend that we incorporated as a b-spline. The random-effects terms included job (n = 33) and industry nested within job (n = 399). We predicted the benzene concentration in two ways: (i) a calibrated JEM estimate was calculated using the fixed-effects model parameters for calendar year and JEM intensity ratings; (ii) a job-/industry-specific estimate was calculated using the fixed-effects model parameters and the best linear unbiased predictors from the random effects for job and industry using an empirical Bayes estimation procedure. Finally, we applied the predicted benzene exposures to a prospective population-based cohort of women in Shanghai, China (n = 74 942). RESULTS: Exposure levels were 13 times higher in 1965 than in 2000 and declined at a rate that varied from 4 to 15% per year from 1965 to 1985, followed by a small peak in the mid-1990s. The job-/industry-specific estimates had greater differences between exposure levels than the calibrated JEM estimates (97.5th percentile/2.5th percentile exposure level, (B)(G)R(95)(B): 20.4 versus 3.0, respectively). The calibrated JEM and job-/industry-specific estimates were moderately correlated in any given year (Pearson correlation, r(p) = 0.58). We classified only those jobs and industries with a job or industry JEM exposure probability rating of 3 (>50% of workers exposed) as exposed. As a result, 14.8% of the subjects and 8.7% of the employed person-years in the study population were classified as benzene exposed. The cumulative exposure metrics based on the calibrated JEM and job-/industry-specific estimates were highly correlated (r(p) = 0.88). CONCLUSIONS: We provide a useful framework for combining quantitative exposure data with expert-based exposure ratings in population-based studies that maximized the information from both sources. Our framework calibrated the ratings to a concentration scale between ratings and across time and provided a mechanism to estimate exposure when a job/industry group reported by a subject was not represented in the exposure database. It also allowed the job/industry groups' exposure levels to deviate from the pooled average for their respective JEM intensity ratings.

Background: The influence of different types and intensities of physical activity on risk for breast cancer is unclear. Methods: In a prospective cohort of 73 049 Chinese women (40-70 years), who had worked outside the home, we studied breast cancer risk in relation to specific types of self-reported and work history-related physical activity, including adolescent and adult exercise and household activity and walking and cycling for transportation. Occupational sitting time and physical activity energy expenditure were assigned based on lifetime occupational histories. Results: In all, 717 incident breast cancer cases were diagnosed. Breast cancer risk was lower for women in the lowest quartile of average occupational sitting time and in the highest quartile of average occupational energy expenditure (adjusted hazard ratio (HR): 0.81 and 0.73, respectively, P≤0.05). Adult exercise at or above the recommended level (8 metabolic equivalent (MET) h per week per year) was associated with lower risk (adjusted HR: 0.73, P

Shift work involving disruption of circadian rhythms has been classified as a probable cause of human cancer by the International Agency for Research on Cancer, based on limited epidemiologic evidence and abundant experimental evidence. The authors investigated this association in a population-based prospective cohort study of Chinese women. At baseline (1996–2000), information on lifetime occupational history was obtained from 73,049 women. Lifetime night-shift exposure indices were created using a job exposure matrix. During 2002–2004, self-reported data on frequency and duration of night-shift work were collected. Hazard ratios and 95% confidence intervals, adjusted for major breast cancer risk factors, were calculated. During follow-up through 2007, 717 incident cases of breast cancer were diagnosed. Breast cancer risk was not associated with ever working the night shift on the basis of the job exposure matrix (adjusted hazard ratio = 1.0, 95% confidence interval: 0.9, 1.2) or self-reported history of night-shift work (adjusted hazard ratio = 0.9, 95% confidence interval: 0.7, 1.1). Risk was also not associated with frequency, duration, or cumulative amount of night-shift work. There were no indications of effect modification. The lack of an association between night-shift work and breast cancer adds to the inconsistent epidemiologic evidence. It may be premature to consider shift work a cause of cancer.

Background: Pancreatitis is a known risk factor for pancreatic cancer; however, an unknown fraction of the disease is thought to be a consequence of tumor-related duct obstruction. Patients and methods: A pooled analysis of a history of pancreatitis and risk of pancreatic cancer was carried out considering the time interval between diagnoses and potential modification by covariates. Adjusted pooled odds ratios (ORs) and 95% confidence intervals (CIs) were estimated from 10 case-control studies (5048 cases of ductal pancreatic adenocarcinoma and 10 947 controls) taking part in the International Pancreatic Cancer Case-Control Consortium (PanC4). Results: The association between pancreatitis and pancreatic cancer was nearly three-fold at intervals of >2 years between diagnoses (OR: 2.71, 95% CI: 1.96-3.74) and much stronger at intervals of =2 years (OR: 13.56, 95% CI: 8.72-21.90) probably reflecting a combination of reverse causation and antecedent misdiagnosis of pancreas cancer as pancreatitis. The younger (2 years) pancreatitis (OR: 3.91, 95% CI: 2.53-6.04) than the older (=65 years) cases (OR: 1.68, 95% CI: 1.02-2.76; P value for interaction: 0.006). Conclusions: Despite a moderately strong association between pancreatitis (diagnosed before >2 years) and pancreatic cancer, the population attributable fraction was estimated at 1.34% (95% CI: 0.612-2.07%), suggesting that a relatively small proportion of pancreatic cancer might be avoided if pancreatitis could be prevented. © The Author 2012. Published by Oxford University Press on behalf of the European Society for Medical Oncology.