Contributor(s)
Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications [Grenoble] (TIMC-IMAG) ; Université Joseph Fourier - Grenoble 1 (UJF) - IMAG - Centre National de la Recherche Scientifique (CNRS)Laboratoire dynamiques sociales et recomposition des espaces (LADYSS) ; Université Panthéon-Sorbonne (UP1) - Université Paris Ouest Nanterre La Défense (UPOND) - Université Paris 8, Vincennes-Saint-Denis (UP8) - Université Paris Diderot - Paris 7 (UP7) - Centre National de la Recherche Scientifique (CNRS)
Katholieke Universiteit Leuven [Leuven] (KUL) ; Katholieke Universiteit Leuven (KU Leuven)
Cape Peninsula University of Technology (CPUT)
Faculty of Medical and Human Sciences ; The University of Manchester [Manchester]
Agence Nationale de Sécurité Sanitaire, de l'Alimentation, de l'environnement et du Travail (ANSES) ; ANSES
Idewe
Centre Hospitalier Universitaire [Grenoble] (CHU)
ISCH COST Action IS1002, ANSES (2012-CRD-06 N°596A), ANSES (2012-CRD-06 N°596A), Erasmus Mundus grant
European Project : 200443, EC:FP7:GA, FP7-2007-COST, COST II(2007)
Keywords
Databasesepidemiology
exposures
geographic information systems
geostatistics
occupational diseases
occupational health
occupational hygiene
[SDV.SPEE] Life Sciences [q-bio]/Public Health and Epidemiology
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https://hal-anses.archives-ouvertes.fr/anses-01230484https://hal-anses.archives-ouvertes.fr/anses-01230484/document
https://hal-anses.archives-ouvertes.fr/anses-01230484/file/Delaunay_Occup%20Med_2015.pdf
Abstract
International audienceBACKGROUND: Occupational health and safety (OHS) information is often complex, diverse and unstructured and suffers from a lack of integration which usually precludes any systemic insight of the situation.AIMS: To analyse to what extent the use of geographical information systems (GISs) can help to integrate, analyse and present OHS data in a comprehensive and communicable way relevant for surveillance purposes.METHODS: We first developed a 'macro-approach' (from national to local level), mapping data related to economic activity (denominator of active workers displayed by activity sectors), as well as work-related ill-health (numerators of workers suffering from work-related ill-health). The latter data are composed of compensated occupational diseases on the one hand and work-related diseases investigated by specialized clinics on the other hand. Then, a 'micro-approach' was worked out, integrating at a plant level, using computer-aided drawing, occupational risks data and OHS surveillance data (e.g. use of medication and sickness absence data).RESULTS: At the macro-level, microelectronics companies and workers were mapped at different scales. For the first time, we were able to compare, up to the enterprise level, complementary data showing different pictures of work-related ill-health, allowing a better understanding of OH issues in this sector. At the micro-level, new information arose from the integration of risk assessment data and medical data.CONCLUSIONS: This work illustrates to what extent GIS is a promising tool in the OHS field, and discusses related challenges (technical, ethical, biases and interpretation) and research perspectives.
Date
2015-11Type
info:eu-repo/semantics/articleIdentifier
oai:HAL:anses-01230484v1anses-01230484
https://hal-anses.archives-ouvertes.fr/anses-01230484
https://hal-anses.archives-ouvertes.fr/anses-01230484/document
https://hal-anses.archives-ouvertes.fr/anses-01230484/file/Delaunay_Occup%20Med_2015.pdf
DOI : 10.1093/occmed/kqv152
DOI
: 10.1093/occmed/kqv152ae974a485f413a2113503eed53cd6c53
: 10.1093/occmed/kqv152