title: Occupational exposome: a network-based approach for characterizing Occupational Health Problems.
abstract: Surveillance of work-related diseases and associated exposures is a major issue of public health, in particular for identifying and preventing new threats for health. In the occupational health context, the French national occupational disease surveillance and prevention network (RNV3P) have constructed a growing database that records every year all Occupational Health Problems (OHPs) diagnosed by a network of physician specialists. The network aims to provide and develop an expertise on the disease-exposure relationships, and uses the RNV3P database for developing the surveillance of OHPs and for the detection of emerging associations between diseases and occupational exposures. In this paper, we have developed the theoretical framework of the occupational exposome, defined as a network of OHPs linked by similar occupational exposures, as a novel approach which allows to characterize and to analyze the disease-exposure associations reported in the RNV3P database in the form of a relational network. Next, the occupational exposome is structured in terms of occupational exposure groups which constitute informative sub-sets of hazards considered as the backbone tree spectrum of the occupational exposures potentially related to a disease. To illustrate the wide possibilities of this method, the exposome approach is applied to the RNV3P database's sample of Non-Hodgkin Lymphomas (NHLs). As a result, we found that the NHL occupational exposome could be described in terms of 86 embedded exposure groups, defined as a set of OHPs sharing at least one component of the occupational multi-exposure. For example, "organic solvents and thinners" is the most represented hazards related to NHLs, but is also co-associated to "benzene", "ionizing radiations" or "agricultural products". From the knowledge stored in the database by physician experts, the occupational exposome constitutes a decisive step towards the evolving monitoring of multi-exposure associated to a given disease.
authors.affiliation: Laboratoire Environnement et Prédiction de la Santé des Populations, UMR CNRS 5525 Université Joseph Fourier, Domaine de la Merci, 38706 La Tronche, France. LFaisandier@chu-grenoble.fr
authors.forename: Laurie
authors.initials: L
authors.lastname: Faisandier
authors.forename: Vincent
authors.initials: V
authors.lastname: Bonneterre
authors.forename: Régis
authors.initials: R
authors.lastname: De Gaudemaris
authors.forename: Dominique J
authors.initials: DJ
authors.lastname: Bicout
mesh_terms: D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D005602:France / Q000453:epidemiology; D006801:Humans; D008228:Lymphoma, Non-Hodgkin / Q000453:epidemiology / Q000517:prevention & control; D008490:Medical Informatics / Q000379:methods*; D009784:Occupational Diseases / Q000453:epidemiology / Q000517:prevention & control*; D016273:Occupational Exposure / Q000517:prevention & control*; D016272:Occupational Health; D011159:Population Surveillance; D015203:Reproducibility of Results