Prevalent occupational exposures and risk of lung cancer among women: Results from the application of the Canadian Job-Exposure Matrix (CANJEM) to a combined set of ten case-control studies.

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.

Adjusting for Berkson error in exposure in ordinary and conditional logistic regression and in Poisson regression.

BACKGROUND: INTEROCC is a seven-country cohort study of occupational exposures and brain cancer risk, including occupational exposure to electromagnetic fields (EMF). In the absence of data on individual exposures, a Job Exposure Matrix (JEM) may be used to construct likely exposure scenarios in occupational settings. This tool was constructed using statistical summaries of exposure to EMF for various occupational categories for a comparable group of workers. METHODS: In this study, we use the Canadian data from INTEROCC to determine the best EMF exposure surrogate/estimate from three appropriately chosen surrogates from the JEM, along with a fourth surrogate based on Berkson error adjustments obtained via numerical approximation of the likelihood function. In this article, we examine the case in which exposures are gamma-distributed for each occupation in the JEM, as an alternative to the log-normal exposure distribution considered in a previous study conducted by our research team. We also study using those surrogates and the Berkson error adjustment in Poisson regression and conditional logistic regression. RESULTS: Simulations show that the introduced methods of Berkson error adjustment for non-stratified analyses provide accurate estimates of the risk of developing tumors in case of gamma exposure model. Alternatively, and under some technical assumptions, the arithmetic mean is the best surrogate when a gamma-distribution is used as an exposure model. Simulations also show that none of the present methods could provide an accurate estimate of the risk in case of stratified analyses. CONCLUSION: While our previous study found the geometric mean to be the best exposure surrogate, the present study suggests that the best surrogate is dependent on the exposure model; the arithmetic means in case of gamma-exposure model and the geometric means in case of log-normal exposure model. However, we could present a better method of Berkson error adjustment for each of the two exposure models. Our results provide useful guidance on the application of JEMs for occupational exposure assessments, with adjustment for Berkson error.

Concordance of Occupational Exposure Assessment between the Canadian Job-Exposure Matrix (CANJEM) and Expert Assessment of Jobs Held by Women.

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.

Impact of Variability in Job Coding on Reliability in Exposure Estimates Obtained via a Job-Exposure Matrix.

OBJECTIVES: The use of a job-exposure matrix (JEM) to assess exposure to potential health hazards in occupational epidemiological studies requires coding each participant's job history to a standard occupation and/or industry classification system recognized by the JEM. The objectives of this study were to assess the impact of inter-coder variability in job coding on reliability in exposure estimates derived from linking the job codes to the Canadian job-exposure matrix (CANJEM) and to identify influent parameters. METHOD: Two trained coders independently coded 1000 jobs sampled from a population-based case-control study to the ISCO-1968 occupation classification at the five-digit resolution level, of which 859 could be linked to CANJEM using both assigned codes. Each of the two sets of codes was separately linked to CANJEM and thereby generated, for each of the 258 occupational agents available in CANJEM, two exposure estimates: exposure status (yes/no) and intensity of exposure (low, medium, and high) for exposed jobs only. Then, inter-rater reliability (IRR) was computed (i) after stratifying agents in 4 classes depending, for each, on the proportion of occupation codes in CANJEM defined as 'exposed' and (ii) for two additional scenarios restricted to jobs coded differently: the first one using experts' codes, the other one using codes randomly selected. IRR was computed using Cohen's kappa, PABAK and Gwet's AC1 index for exposure status, and weighted kappa and Gwet's AC2 for exposure intensity. RESULTS: Across all agents and based on all jobs, median (Q1, Q3; Nagents) values were 0.68 (0.59, 0.75; 220) for kappa, 0.99 (0.95, 1.00; 258) for PABAK, and 0.99 (0.97, 1.00; 258) for AC1. For the additional scenarios, median kappa was 0.28 (0.00, 0.45; 209) and -0.01 (-0.02, 00; 233) restricted to jobs coded differently using experts' and random codes, respectively. A similar decreasing pattern was observed for PABAK and AC1 albeit with higher absolute values. Median kappa remained stable across exposure prevalence classes but was more variable for low prevalent agents. PABAK and AC1 decreased with increasing prevalence. Considering exposure intensity and all exposed jobs, median values were 0.79 (0.68, 0.91; 96) for weighted kappa, and 0.95 (0.89, 0.99; 102) for AC2. For the additional scenarios, median kappa was, respectively, 0.28 (-0.04, 0.42) and -0.05 (-0.18, 0.09) restricted to jobs coded differently using experts' and random codes, with a similar though attenuated pattern for AC2. CONCLUSION: Despite reassuring overall reliability results, our study clearly demonstrated the loss of information associated with jobs coded differently. Especially, in cases of low exposure prevalence, efforts should be made to reliably code potentially exposed jobs.

Spatial and temporal variability of airborne ultrafine particles in the Greater Montreal area: Results of monitoring campaigns in two seasons.

It has been hypothesized that ultrafine particles (UFP) in air pollution may cause lung cancer. In preparation for an epidemiologic case-control study to assess this hypothesis in Montreal, Canada, we conducted a UFP measurement campaign in order to create an exposure surface with which we could assign UFP exposure to subjects corresponding to their residential addresses. The purpose of this paper is to describe the temporal and spatial variability that underlies the creation of an exposure surface in the Montreal area, and to consider the implications for epidemiological exposure assessment. We identified 249 fixed sampling sites, selected to provide a dense spatial representation of the areas of residence of Montreal residents. We conducted a winter campaign and a summer campaign, and each of the sites was visited three times during each seasonal campaign. Each visit entailed a 20-minute measurement period for UFPs with a separate measurement each second. This provided data for temporal comparisons at each site between seasons, between visits and between seconds. The median of UFP measurements was 16,593 particles/cm3 in winter and 8919 particles/cm3 in summer. Across the 249 sampling sites the Spearman correlation coefficient between the UFP measurements of winter and summer was 0.35. Within each visit, correlation was below 0.50 between pairs of UFP measurements taken more than 60 s apart, and there was hardly any correlation among measurements taken more than 300 s apart. When sites were grouped by proximity to certain types of pollution sources, and the seven resulting groups compared, there were modest, albeit statistically significant, differences in UFP levels. There was moderate positive spatial autocorrelation in UFPs over the study area. High temporal variability of UFPs from short-term measurements campaigns will likely compromise the predictive validity of the exposure surface, and will eventually attenuate the epidemiologic risk estimates.

Correction: Development of a source-exposure matrix for occupational exposure assessment of electromagnetic fields in the INTEROCC study.

Corrigendum: This work was also funded by the European Commission grant 603794 (GERoNiMO project).

Occupational exposure to high-frequency electromagnetic fields and brain tumor risk in the INTEROCC study: An individualized assessment approach.

INTRODUCTION: In 2011, the International Agency for Research on Cancer classified radiofrequency (RF) electromagnetic fields (EMF) as possibly carcinogenic to humans (group 2B), although the epidemiological evidence for the association between occupational exposure to RF-EMF and cancer was judged to be inadequate, due in part to limitations in exposure assessment. This study examines the relation between occupational RF and intermediate frequency (IF) EMF exposure and brain tumor (glioma and meningioma) risk in the INTEROCC multinational population-based case-control study (with nearly 4000 cases and over 5000 controls), using a novel exposure assessment approach. METHODS: Individual indices of cumulative exposure to RF and IF-EMF (overall and in specific exposure time windows) were assigned to study participants using a source-exposure matrix and detailed interview data on work with or nearby EMF sources. Conditional logistic regression was used to investigate associations with glioma and meningioma risk. RESULTS: Overall, around 10% of study participants were exposed to RF while only 1% were exposed to IF-EMF. There was no clear evidence for a positive association between RF or IF-EMF and the brain tumors studied, with most results showing either no association or odds ratios (ORs) below 1.0. The largest adjusted ORs were obtained for cumulative exposure to RF magnetic fields (as A/m-years) in the highest exposed category (≥90th percentile) for the most recent exposure time window (1-4 years before the diagnosis or reference date) for both glioma, OR = 1.62 (95% confidence interval (CI): 0.86, 3.01) and meningioma (OR = 1.52, 95% CI: 0.65, 3.55). CONCLUSION: Despite the improved exposure assessment approach used in this study, no clear associations were identified. However, the results obtained for recent exposure to RF electric and magnetic fields are suggestive of a potential role in brain tumor promotion/progression and should be further investigated.

Development of a Coding and Crosswalk Tool for Occupations and Industries.

Introduction: Job coding into a standard occupation or industry classification is commonly performed in occupational epidemiology and occupational health. Sometimes, it is necessary to code jobs into multiple classifications or to convert job codes from one classification to another. We developed a generic tool, called CAPS-Canada (http://www.caps-canada.ca/), that combines a computer-assisted coding tool covering seven International, Canadian and US occupation and industry classifications and an assistant facilitating crosswalks from one classification to another. The objectives of this paper are to present the different functions of the CAPS-Canada tool and to assess their contribution through an inter-rater reliability study. Method: The crosswalk assistant was built based on a database of >30,000 jobs coded during a previous project. We evaluated to what extent it would allow automatic translation between pairs of classifications. The influence of CAPS-Canada on agreement between coders was assessed through an inter-rater reliability study comparing three approaches: manual coding, coding with CAPS-Canada without the crosswalk assistant, and coding with the complete tool. The material for this trial consisted of a random sample of 1000 jobs extracted from a case-control study and divided into three subgroups of equivalent size. Results: Across the classification systems, the crosswalk assistant would provide useful information for 83-99% of jobs (median 95%) in a population similar to ours. Eighteen to eighty-one percent of jobs (median 56%) could be entirely automatically recoded. Based on our sample of 1000 jobs, inter-rater reliability in occupation coding ranged from 35.7 to 66.5% (median 53.7%) depending on the combination of classification/resolution. Compared with manual coding, the use of CAPS-Canada substantially improved inter-rater reliability. Conclusion: CAPS-Canada is an attractive alternative to manual coding and is particularly relevant for coding a job into multiple classifications or for recoding jobs into other classifications.

Development of and Selected Performance Characteristics of CANJEM, a General Population Job-Exposure Matrix Based on Past Expert Assessments of Exposure.

Objectives: We developed a job-exposure matrix called CANJEM using data generated in population-based case-control studies of cancer. This article describes some of the decisions in developing CANJEM, and some of its performance characteristics. Methods: CANJEM is built from exposure information from 31673 jobs held by study subjects included in our past case-control studies. For each job, experts had evaluated the intensity, frequency, and likelihood of exposure to a predefined list of agents based on jobs histories and descriptions of tasks and workplaces. The creation of CANJEM involved a host of decisions regarding the structure of CANJEM, and operational decisions regarding which parameters to present. The goal was to produce an instrument that would provide great flexibility to the user. In addition to describing these decisions, we conducted analyses to assess how well CANJEM covered the range of occupations found in Canada. Results: Even at quite a high level of resolution of the occupation classifications and time periods, over 90% of the recent Canadian working population would be covered by CANJEM. Prevalence of exposure of specific agents in specific occupations ranges from 0% to nearly 100%, thereby providing the user with basic information to discriminate exposed from unexposed workers. Furthermore, among exposed workers there is information that can be used to discriminate those with high exposure from those with low exposure. Conclusions: CANJEM provides good coverage of the Canadian working population and possibly that of several other countries. Available in several occupation classification systems and including 258 agents, CANJEM can be used to support exposure assessment efforts in epidemiology and prevention of occupational diseases.

Associations between occupational exposure to benzene, toluene and xylene and risk of lung cancer in Montréal.

BACKGROUND: Benzene, toluene and xylene (BTX) are aromatic hydrocarbons with inconclusive evidence of lung carcinogenicity. The aim of this research was to assess the associations between occupational exposures to BTX agents and lung cancer. METHODS: In a population-based case-control study of lung cancer, occupational histories were obtained and exposures were assessed by experts. Unconditional multivariate logistic regression was used to estimate ORs and 95% CIs, among men, between various metrics of occupational exposure to BTX and lung cancer, while adjusting for established and possible risk factors. RESULTS: Considerable overlap was found between occupational exposure to BTX, where the majority of exposed participants were exposed to all three chemicals. Lung cancer was associated with exposure to benzene (OR=1.35; 95% CI 0.99 to 1.84), toluene (OR=1.31; 95% CI 0.99 to 1.74) and xylene (OR=1.44; 95% CI 1.03 to 2.01). While these results were adjusted for smoking and other recognised and possible lung cancer risk factors, they were not mutually adjusted among the three BTX agents. CONCLUSIONS: Our study provides suggestive evidence that occupational exposure to one or more of the BTX agents may be associated with lung cancer.

Response rates in case-control studies of cancer by era of fieldwork and by characteristics of study design.

PURPOSE: The purpose of this study was to describe time trends in response rates in case-control studies of cancer and identify study design factors that influence response rate. METHODS: We reviewed 370 case-control studies of cancer published in 12 journals during indicator years in each of the last four decades. We estimated time trends of response rates and reasons for nonresponse in each of the following types of study subjects: cases, medical source controls, and population controls. We also estimated response rates according to characteristics of study context. RESULTS: Median response rates among cases and population controls were between 75% and 80% in the 1970s. Between 1971 and 2010, study response rates declined by 0.31% per year for cases and 0.78% for population controls. Only a minority of studies reported reasons for nonparticipation; subject refusal was the most common reported reason. Studies conducted in North America had lower median response rates than studies conducted in Europe. In-person and telephone interviews elicited higher response rates than mail questionnaires. CONCLUSIONS: Response rates from case-control studies of cancer have declined, and this could threaten the validity of results derived from these studies.

The INTEROCC case-control study: risk of meningioma and occupational exposure to selected combustion products, dusts and other chemical agents.

BACKGROUND: Little is known about occupational risk factors for meningioma. OBJECTIVES: To study whether risk of meningioma is associated with several occupational exposures, including selected combustion products, dusts and other chemical agents. METHODS: The INTEROCC study was an international case-control study of brain cancer conducted in seven countries. Data collection by interview included lifetime occupational histories. A job exposure matrix was used to derive estimates of exposure for the 12 agents. ORs for ever versus never exposed and for exposure-response using duration of exposure and cumulative exposure were derived using conditional logistic regression stratified by sex, age group, country/region, adjusted for education. RESULTS: These analyses included 1906 cases and 5565 controls. For 11 of the 12 agents, no excess risk was found for ever exposed. For ever exposure to oil mists, an elevated OR of 1.57 (95% CI 1.10 to 2.22, 51 exposed cases) was found. Statistically significant exposure-response relationships were observed with cumulative exposure (p=0.01) and duration of exposure (p=0.04). Among women, there were also significant trends for cumulative and duration of exposure to asbestos and excesses in the highest exposure categories for formaldehyde. CONCLUSIONS: Most agents examined did not provoke excess risks of meningioma. The main finding from this study is that it is the first study to identify a statistical association between exposure to oil mists and meningioma. This may be a chance finding or could be due to confounding with iron exposure and further research is required to understand whether the relationship is causal.

Occupational exposures to leaded and unleaded gasoline engine emissions and lung cancer risk.

OBJECTIVES: To determine whether occupational exposure to gasoline engine emissions (GEE) increased the risk of lung cancer and more specifically whether leaded or unleaded GEE increased the risk. METHODS: Two population-based case-control studies were conducted in Montreal, Canada. The first was conducted in the early 1980s and included many types of cancer including lung cancer. The second was conducted in the late 1990s and focused on lung cancer. Population controls were used in both studies. Altogether, there were 1595 cases and 1432 population controls. A comprehensive expert-based exposure assessment procedure was implemented and exposure was assessed for 294 agents, including unleaded GEE, leaded GEE and diesel engine emissions (DEE). Logistic regression analyses were conducted to estimate ORs between various metrics of GEE exposure and lung cancer, adjusting for smoking, DEE and other potential confounders. RESULTS: About half of all controls were occupationally exposed to GEE. Irrespective of the metrics of exposure (any exposure, duration of exposure and cumulative exposure) and the type of lung cancer, and the covariates included in models, none of the point estimates of the ORs between occupational exposure to leaded or unleaded GEE and lung cancer were above 1.0. Pooling two studies, the OR for any exposure to leaded GEE was 0.82 (0.68-1.00). CONCLUSIONS: Our results do not support the hypothesis that occupational exposure to GEE increases the risk of lung cancer.

Berkson error adjustment and other exposure surrogates in occupational case-control studies, with application to the Canadian INTEROCC study.

Many epidemiological studies assessing the relationship between exposure and disease are carried out without data on individual exposures. When this barrier is encountered in occupational studies, the subject exposures are often evaluated with a job-exposure matrix (JEM), which consists of mean exposure for occupational categories measured on a comparable group of workers. One of the objectives of the seven-country case-control study of occupational exposure and brain cancer risk, INTEROCC, was to investigate the relationship of occupational exposure to electromagnetic fields (EMF) in different frequency ranges and brain cancer risk. In this paper, we use the Canadian data from INTEROCC to estimate the odds of developing brain tumours due to occupational exposure to EMF. The first step was to find the best EMF exposure surrogate among the arithmetic mean, the geometric mean, and the mean of log-normal exposure distribution for each occupation in the JEM, in comparison to Berkson error adjustments via numerical approximation of the likelihood function. Contrary to previous studies of Berkson errors in JEMs, we found that the geometric mean was the best exposure surrogate. This analysis provided no evidence that cumulative lifetime exposure to extremely low frequency magnetic fields increases brain cancer risk, a finding consistent with other recent epidemiological studies.

Occupational solvent exposure and risk of glioma in the INTEROCC study.

BACKGROUND: The aetiology of glioma remains largely unknown. Occupational solvent exposure has been suggested as a putative cause of glioma, but past studies have been inconsistent. We examined the association between a range of solvents and glioma risk within the INTEROCC project, a study of brain tumours and occupational exposures based on data from seven national case-control studies conducted in the framework of the INTERPHONE study. We also investigated associations according to tumour grade. METHODS: Data from the seven countries were standardised and then combined into one aggregate data set. Pooled odds ratios (ORs) were estimated for adjusted models that included sex, age, country-region of residence and level of educational attainment. Exposures to any solvent or 11 specific solvents or subgroups were assessed using a modified version of the FINJEM job exposure matrix (JEM) specifically developed for the study, called INTEROCC-JEM. RESULTS: Analysis included 2000 glioma cases and 5565 controls. For glioma and ever/never exposure to any solvent, the OR was 0.91 (95% confidence interval: 0.74-1.11). All ORs were <1.0 for specific solvents/subgroups. There were no increases in risk according to high or low grade of tumour. CONCLUSIONS: The results of this study show no consistent associations for any solvent exposures overall or by grade of tumour.

Lifetime occupational exposure to metals and welding fumes, and risk of glioma: a 7-country population-based case-control study.

BACKGROUND: Brain tumor etiology is poorly understood. Based on their ability to pass through the blood-brain barrier, it has been hypothesized that exposure to metals may increase the risk of brain cancer. Results from the few epidemiological studies on this issue are limited and inconsistent. METHODS: We investigated the relationship between glioma risk and occupational exposure to five metals - lead, cadmium, nickel, chromium and iron- as well as to welding fumes, using data from the seven-country INTEROCC study. A total of 1800 incident glioma cases and 5160 controls aged 30-69 years were included in the analysis. Lifetime occupational exposure to the agents was assessed using the INTEROCC JEM, a modified version of the Finnish job exposure matrix FINJEM. RESULTS: In general, cases had a slightly higher prevalence of exposure to the various metals and welding fumes than did controls, with the prevalence among ever exposed ranging between 1.7 and 2.2% for cadmium to 10.2 and 13.6% for iron among controls and cases, respectively. However, in multivariable logistic regression analyses, there was no association between ever exposure to any of the agents and risk of glioma with odds ratios (95% confidence intervals) ranging from 0.8 (0.7-1.0) for lead to 1.1 (0.7-1.6) for cadmium. Results were consistent across models considering cumulative exposure or duration, as well as in all sensitivity analyses conducted. CONCLUSIONS: Findings from this large-scale international study provide no evidence for an association between occupational exposure to any of the metals under scrutiny or welding fumes, and risk of glioma.

Interactions between occupational exposure to extremely low frequency magnetic fields and chemicals for brain tumour risk in the INTEROCC study.

OBJECTIVES: In absence of clear evidence regarding possible effects of occupational chemical exposures on brain tumour aetiology, it is worthwhile to explore the hypothesis that such exposures might act on brain tumour risk in interaction with occupational exposure to extremely low frequency magnetic fields (ELF). METHODS: INTEROCC is a seven-country (Australia, Canada, France, Germany, Israel, New Zealand and UK), population-based, case-control study, based on the larger INTERPHONE study. Incident cases of primary glioma and meningioma were ascertained from 2000 to 2004. Job titles were coded into standard international occupational classifications and estimates of ELF and chemical exposures were assigned based on job-exposure matrices. Dichotomous indicators of cumulative ELF (≥50th vs <50th percentile, 1-4 year exposure time window) and chemical exposures (ever vs never, 5-year lag) were created. Interaction was assessed on both the additive and multiplicative scales. RESULTS: A total of 1939 glioma cases, 1822 meningioma cases and 5404 controls were included in the analysis, using conditional logistic regression. There was no clear evidence for interactions between ELF and any of the chemical exposures assessed for either glioma or meningioma risk. For glioma, subjects in the low ELF/metal exposed group had a lower risk than would be predicted from marginal effects. Results were similar according to different exposure time windows, to cut-points of exposure or in exposed-only analyses. CONCLUSIONS: There was no clear evidence for interactions between occupational ELF and chemical exposures in relation to glioma or meningioma risk observed. Further research with more refined estimates of occupational exposures is recommended.

Physical activity and lung cancer risk in men and women.

PURPOSE: Although evidence has accumulated that recreational physical activities (PA) may reduce lung cancer risk, there is little evidence concerning the possible role of a potentially more important source of PA, namely occupational PA. We investigated both recreational and lifetime occupational PA in relation to lung cancer risk in a population-based case-control study in Montreal, Canada (NCASES = 727; NCONTROLS = 1,351). METHODS: Unconditional logistic regression was used to estimate odds ratios (OR), separately for men and women, adjusting for smoking, exposure to occupational carcinogens, and sociodemographic and lifestyle factors. RESULTS: In both sexes, increasing recreational PA was associated with a lower lung cancer risk (ORMEN = 0.66, 95% confidence interval (CI) 0.47-0.92; ORWOMEN = 0.55, 95% CI 0.34-0.88, comparing the highest versus lowest tertiles). For occupational PA, no association was observed among women, while increasing occupational PA was associated with increased risk among men (ORMEN = 1.96, 95% CI 1.27-3.01). ORs were not modified by occupational lung carcinogen exposure, body mass index, and smoking level; results were similar across lung cancer histological types. CONCLUSIONS: Our results support the previous findings for recreational PA and lung cancer risk. Unexpectedly, our findings suggest a positive association for occupational PA; this requires replication and more detailed investigation.