An innovative method to estimate lifetime prevalence of carcinogenic occupational circumstances: the example of painters and workers of the rubber manufacturing industry in France

Estimated number of cancers attributable to occupational exposures in France in 2017: an update using a new method for improved estimates

BACKGROUND

Over the last 50 years, occupational exposure to carcinogenic agents has been widely regulated in France.

OBJECTIVE

Report population-attributable fraction (PAF) and number of attributable cancer cases linked to occupational exposure in France based on an updated method to estimate lifetime occupational exposure prevalence.

METHODS

Population-level prevalence of lifetime exposure to ten carcinogenic agents (asbestos, benzene, chromium VI, diesel engine exhaust, formaldehyde, nickel compounds, polycyclic aromatic hydrocarbons, silica dust, trichloroethylene, wood dust) and two occupational circumstances (painters and rubber industry workers) were estimated using the French Census linked with MATGÉNÉ job-exposure matrices and French occupational surveys. PAF and number of attributable cancer cases were calculated using the estimated prevalence, relative risks from systematic review and national estimates of cancer incidence in 2017.

RESULTS

The lifetime occupational exposure prevalences were much higher in men than in women ranging from 0.2% (workers in the rubber industry) to 10.2% in men (silica), and from 0.10% (benzene, PAH and workers in the rubber industry) to 5.7% in women (formaldehyde). In total, 4,818 cancer cases (men: 4,223; women: 595) were attributable to the ten studied carcinogens and two occupational circumstances, representing 5.2% of cases among the studied cancer sites (M: 7.0%; W: 1.9%). In both sexes, mesothelioma (M: 689 cases; W: 160) and lung cancer (M: 3,032; W: 308) were the largest cancer sites impacted by the studied occupational agents and circumstances.

SIGNIFICANCE

A moderate proportion of the cancer cases in France is linked to carcinogens in occupational settings. Our method provides more precise estimates of attributable cancer taking into account evolution of exposure to occupational agents by sex, age and time. This methodology can be easily replicated using cross-sectional occupational data to aid priority making and implementation of prevention strategies in the workplace.

Lifetime occupational exposure proportion estimation methods: a sensitivity analysis in the general population

OBJECTIVE

To present a sensitivity analysis of the most widely used means of estimating lifetime occupational exposure proportion (LOEP) and their respective impacts on LOEP and population-attributable fraction (PAF) estimates.

METHODS

A French population-based sample with full job history (N = 10,010) was linked with four Matgéné job-exposure matrices: flour, cement, silica and benzene. LOEP and the 95% confidence interval were estimated using four methods: the maximum exposure probability during the career (Proba_max), two methods subdividing careers into job-periods (job-period_M1, job-period_M2) and one into job-years (job-year). To quantify differences between methods, percentages of variation were calculated for proportion values and PAF, and compared with published results for France using cross-sectional proportion multiplied by a factor.

RESULTS

For each agent, LOEP estimated from the maximum probability during the career (Proba_max) was consistently lower than proportion taking account of job-periods or job-years. LOEP on Proba_max for flour, cement, silica and benzene were, respectively, 4.4% 95% CI (4.0-4.7), 4.3% (3.9-4.6), 6.1% (5.7-6.5) and 3.9% (3.6-4.2). Percentage of variation ranged from 0 to 55.8% according to the agent. The number of cancer cases varied by a twofold factor for exposure to silica and lung cancer and by a fourfold factor for exposure to benzene and acute myeloid lymphoma.

CONCLUSIONS

The present study provides a description of several LOEP estimation methods based on exposure assessment over the entire career and describes their impact on PAF. For health monitoring purposes, we recommend to report a range of LOEP with low and high estimates obtained using job-periods (job-period_M1 and job-period_M2).