Évaluation de l'exposition professionnelle au formaldéhyde à partir de sources de données préexistantes

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

Exposure to welding fumes increases lung cancer risk among light smokers but not among heavy smokers: evidence from two case-control studies in Montreal.

We investigated relationships between occupational exposure to gas and arc welding fumes and the risk of lung cancer among workers exposed to these agents throughout the spectrum of industries. Two population-based case-control studies were conducted in Montreal. Study I (1979-1986) included 857 cases and 1066 controls, and Study II (1996-2001) comprised 736 cases and 894 controls. Detailed job histories were obtained by interview and evaluated by an expert team of chemist-hygienists to estimate degree of exposure to approximately 300 substances for each job. Gas and arc welding fumes were among the agents evaluated. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) of lung cancer using logistic regression, adjusting for smoking history and other covariates. The two studies provided similar results, so a pooled analysis was conducted. Among all subjects, no significant association was found between lung cancer and gas welding fumes (OR = 1.1; 95% CI = 0.9-1.4) or arc welding fumes (OR = 1.0; 95% CI = 0.8-1.2). However, when restricting attention to light smokers, there was an increased risk of lung cancer in relation to gas welding fumes (OR = 2.9; 95% CI = 1.7-4.8) and arc welding fumes (OR = 2.3; 95% CI = 1.3-3.8), with even higher OR estimates among workers with the highest cumulative exposures. In conclusion, there was no detectable excess risk of lung cancer due to welding fumes among moderate to heavy smokers; but among light smokers we found an excess risk related to both types of welding fumes

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

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.

BackgroundWorldwide, 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.MethodsData 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 conclusionsNone 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

A database to aid the identification of chemicals potentially posing a health risk through percutaneous exposure

In the context of recent attempts to redefine the 'skin notation' concept, a position paper summarizing an international workshop on the topic stated that the skin notation should be a hazard indicator related to the degree of toxicity and the potential for transdermal exposure of a chemical. Within the framework of developing a web-based tool integrating this concept, we constructed a database of 7101 agents for which a percutaneous permeation constant can be estimated (using molecular weight and octanol-water partition constant), and for which at least one of the following toxicity indices could be retrieved: Inhalation occupational exposure limit (n=644), Oral lethal dose 50 (LD50, n=6708), cutaneous LD50 (n=1801), Oral no observed adverse effect level (NOAEL, n=1600), and cutaneous NOAEL (n=187). Data sources included the Registry of toxic effects of chemical substances (RTECS, MDL information systems, Inc.), PHYSPROP (Syracuse Research Corp.) and safety cards from the International Programme on Chemical Safety (IPCS). A hazard index, which corresponds to the product of exposure duration and skin surface exposed that would yield an internal dose equal to a toxic reference dose was calculated. This presentation provides a descriptive summary of the database, correlations between toxicity indices, and an example of how the web tool will help industrial hygienist decide on the possibility of a dermal risk using the hazard index

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice

Une nouvelle mesure de distance entre descripteurs de moments de Zernike pour une similarité optimale et un angle de rotation entre les images

National audienceLes moments de Zernike constituent un descripteur robusteà fort pouvoir descriptif. Cependant, la manière classiquede comparer deux descripteurs ne prend pas en comptel’information de phase des moments complexes. Notre approcheintègre cette information dans le processus de comparaisontout en préservant l’invariance en rotation. Lenouveau comparateur renvoie une mesure de similaritéplus précise ainsi qu’un angle optimal de rotation entreles deux images, tout en conservant la même complexitéque l’approche classique. Les expériences démontrent quenotre comparateur surpasse le comparateur classique enterme de mesure de similarité. En particulier, la robustesseenvers le bruit et la déformation est grandement améliorée.Enfin, l’estimation de l’angle de rotation est aussi plusprécise qu’avec les approches existantes