Occupational risk factors have to be considered in the definition of high-risk lung cancer populations

Abstract

Background:The aim of this study was to compute attributable fractions (AF) to occupational factors in an area in North-Eastern France with high lung cancer rates and a past of mining and steel industry.Methods:A population-based case–control study among males aged 40–79 was conducted, including confirmed primary lung cancer cases from all hospitals of the study region. Controls were stratified by broad age-classes, district and socioeconomic classes. Detailed occupational and personal risk factors were obtained in face-to-face interviews. Cumulative occupational exposure indices were obtained from the questionnaires. Attributable fractions were computed from multiple unconditional logistic regression models.Results:A total of 246 cases and 531 controls were included. The odds ratios (ORs) adjusted on cumulative smoking and family history of lung cancer increased significantly with the cumulative exposure indices to asbestos, polycyclic aromatic hydrocarbons and crystalline silica, and with exposure to diesel motor exhaust. The AF for occupational factors exceeded 50%, the most important contributor being crystalline silica and asbestos.Conclusion:These AFs are higher than most published figures. This can be because of the highly industrialised area or methods for exposure assessments. Occupational factors are important risk factors and should not be forgotten when defining high-risk lung cancer populations.

Comparison of exposure assessment methods in a lung cancer case-control study: performance of a lifelong task-based questionnaire for asbestos and PAHs

“…The study protocol and details on the selection of cases and controls have been previously reported 20. The study included male cases and controls aged 40–80 years, living in the study region and giving written statements of informed consent.…”

“…The first contrasted the TBQ estimates (expertise and algorithm) with the JEM-exposure estimates in the subsample of 497 jobs as previously. The second compared the TBQ-algorithm asbestos-estimates with the JEM-asbestos estimates in the model applied to all subjects of the case-control study discussed in the previous publication 20. Briefly, for the purpose of the analysis of the case-control studies, cumulative exposure indices were computed for asbestos, PAHs, and silica by first assigning to each job-period a quantitative exposure level (obtained from the highest semiquantitative assessment with respect to tasks of this job obtained applying the TBQ-algorithmic assessment) which was multiplied by the estimated frequency of this highest exposed task and the duration in years of the period.…”

A critical review of the relationship between occupational exposure to diesel emissions and lung cancer risk

“…This was the oldest study included in our review. We also reviewed two studies conducted in the city of Turin (Richiardi et al 2006) and the Lombardy region of Italy (De Matteis et al 2012), three in France (Menvielle et al 2003;Wild et al 2012;Matrat et al 2015), one in Germany (Br€ uskeHohlfeld et al 1999), one in Stockholm, Sweden (Gustavsson et al 2000), and one study with two reports (one of which was restricted to nonsmokers) in Hong Kong, China (Tse et al 2009(Tse et al , 2011. Furthermore, a pooled analysis of case-control studies in Europe and Canada (Olsson et al 2011) included data from several of the aforementioned studies (Table 11): the German study with two study centers (Br€ uske-Hohlfeld et al 1999), the Italian study in the Lombardy region (EAGLE study) (De Matteis et al 2012), the study from Turin, Italy, which extended to a second study center in the Venetian region (Richiardi et al 2004(Richiardi et al , 2006, and the Swedish study in Stockholm (Gustavsson et al 2000).…”

“…However, of the separate population-based case-control studies reviewed (Table 12), four did not consider any control for socio-economic variables (Lerchen et al 1987;Gustavsson et al 2000;Menvielle et al 2003;Villeneuve et al 2011). Seven studies published main risk estimates adjusted for socioeconomic variables (Br€ uske-Hohlfeld et al 1999;Richiardi et al 2006;Parent et al 2007;Pintos et al 2012;Tse et al 2011;Wild et al 2012), while only two of these studies reported both unadjusted and adjusted results. In the Italian study adjustment for socio-economic status reduced the risk estimate by about 9% to an OR of <1, as reported above (Richiardi et al 2006).…”

“…However, even such a robust strategy cannot guarantee protection against a deficit of mobile workers among controls linked to RDD. Several of the reviewed studies employed RDD for the overall or a subset of the control group (Lerchen et al 1987;Matrat et al 2015;Parent et al 2007;Pintos et al 2012;Tse et al 2011Villeneuve et al 2011;Wild et al 2012) (Table 12). Parent et al (2007) did not mention the use of RDD but in an earlier extensive study report it was noted that 158 of the 533 population-based controls had been recruited using RDD (Siemiatycki 1991;Siemiatycki et al 1994).…”