Occupational exposure to organic solvents and the risk of developing testicular germ cell tumors (TESTIS study): Effect of combined exposure assessment on risk estimation.

OBJECTIVES: Etiological factors of testicular germ cell tumors (TGCT) remain largely unknown, but a causal role of occupational exposures to solvents has been suggested. Previous studies analyzing these exposures reported discordant results, potentially related to exposure assessment methods. The aim of this study was to investigate the role of occupational exposure to solvents on the risk of developing TGCT among young men. METHODS: This study examined occupational exposures to solvents and TGCT risk based on the lifetime work histories of 454 cases and 670 controls, aged 18-45 years, of the French national TESTIS case-control study. Solvent exposure was estimated using: (i) exposure assignment by job-exposure matrix (JEM) and (ii) JEM combined with self-reported exposure data from specific questionnaires (SQ) and expert assessment (EA). Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. RESULTS: Both approaches (JEM and JEM+SQ+EA) showed a consistent association between TGCT and trichloroethylene exposure (exposed versus not exposed; JEM=OR 1.80 [95% confidence interval (CI) 1.12-2.90] and JEM+SQ+EA= OR 2.59 (95% CI 1.42-4.72). Both approaches also observed positive associations with ketone esters and fuels & petroleum-based solvents. CONCLUSION: The results suggest that some organic solvents might be involved in the pathogenesis of TGCT among occupationally exposed men. The combined use of JEM+SQ+EA seemed to limit misclassification by considering individual exposure variability and is, therefore, an appealing approach to assess occupational exposures in epidemiological studies.

An Integrated Cancer Prevention Strategy: the Viewpoint of the Leon Berard Comprehensive Cancer Center Lyon, France.

This article describes some of the key prevention services in the Leon Berard Comprehensive Cancer Center (CLB) Lyon, France, which are based on clinical prevention services, outreach activities, and collaboration with professional and territorial health communities. In addition, research is embedded at all stages of the prevention continuum, from understanding cancer causes through to the implementation of prevention interventions during and after cancer. Health promotion activities in the community and dedicated outpatient primary cancer prevention services for individuals at increased risk have been implemented. The CLB's experience illustrates how prevention can be integrated into the comprehensive mission of cancer centers, and how in turn, the cancer centers may contribute to bridging the current fragmentation between cancer care and the different components of primary, secondary, and tertiary prevention. With increasing cancer incidence, the shift toward integrated prevention-centered cancer care is not only key for improving population health, but this may also provide a response to the shortage of hospital staff and overcrowding in cancer services, as well as offer opportunities to reduce carbon emissions from cancer care.

Beyond the map: evidencing the spatial dimension of health inequalities.

BACKGROUND: Spatial inequalities in health result from different exposures to health risk factors according to the features of geographical contexts, in terms of physical environment, social deprivation, and health care accessibility. Using a common geographical referential, which combines indices measuring these contextual features, could improve the comparability of studies and the understanding of the spatial dimension of health inequalities. METHODS: We developed the Geographical Classification for Health studies (GeoClasH) to distinguish French municipalities according to their ability to influence health outcomes. Ten contextual scores measuring physical and social environment as well as spatial accessibility of health care have been computed and combined to classify French municipalities through a K-means clustering. Age-standardized mortality rates according to the clusters of this classification have been calculated to assess its effectiveness. RESULTS: Significant lower mortality rates compared to the mainland France population were found in the Wealthy Metropolitan Areas (SMR = 0.868, 95% CI 0.863-0.873) and in the Residential Outskirts (SMR = 0.971, 95% CI 0.964-0.978), while significant excess mortality were found for Precarious Population Districts (SMR = 1.037, 95% CI 1.035-1.039), Agricultural and Industrial Plains (SMR = 1.066, 95% CI 1.063-1.070) and Rural Margins (SMR = 1.042, 95% CI 1.037-1.047). CONCLUSIONS: Our results evidence the comprehensive contribution of the geographical context in the constitution of health inequalities. To our knowledge, GeoClasH is the first nationwide classification that combines social, environmental and health care access scores at the municipality scale. It can therefore be used as a proxy to assess the geographical context of the individuals in public health studies.