Characterizing environmental geographic inequalities using an integrated exposure assessment

Autor: Laure Malherbe, Mohammed Guedda, Céline Brochot, Roseline Bonnard, Karen Chardon, Julien Caudeville, Maxime Beauchamp, Corentin Regrain, Laurent Létinois, François Lestremau, Frédéric Tognet, Fabrice Marliere, Florence Anna Zeman, Véronique Bach
Přispěvatelé: Institut National de l'Environnement Industriel et des Risques (INERIS), Périnatalité et Risques Toxiques - UMR INERIS_I 1 (PERITOX), Université de Picardie Jules Verne (UPJV)-CHU Amiens-Picardie-Institut National de l'Environnement Industriel et des Risques, Laboratoire Amiénois de Mathématique Fondamentale et Appliquée - UMR CNRS 7352 (LAMFA), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2020
Předmět:
medicine.medical_specialty
Inequities
Insecticides
Geographic information system
Computer science
Health
Toxicology and Mutagenesis
Population
Food Contamination
010501 environmental sciences
01 natural sciences
Representativeness heuristic
Benzoates
Risk Assessment
Exposure
Integrated
11. Sustainability
Nitriles
Pyrethrins
medicine
Spatial
Humans
education
0105 earth and related environmental sciences
Exposure assessment
[SDV.EE.SANT]Life Sciences [q-bio]/Ecology
environment/Health
education.field_of_study
Operationalization
business.industry
Public health
Public Health
Environmental and Occupational Health
Methodology
Modeling
04 agricultural and veterinary sciences
Environmental Exposure
Models
Theoretical
Industrial medicine. Industrial hygiene
RC963-969
Risk analysis (engineering)
13. Climate action
Scale (social sciences)
040103 agronomy & agriculture
Geographic Information Systems
0401 agriculture
forestry
and fisheries
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Public aspects of medicine
RA1-1270
business
Environmental Health
Zdroj: Environmental Health
Environmental Health, BioMed Central, 2021, 20, pp.58. ⟨10.1186/s12940-021-00736-9⟩
Environmental Health, Vol 20, Iss 1, Pp 1-16 (2021)
ISSN: 1476-069X
Popis: Background At a regional or continental scale, the characterization of environmental health inequities (EHI) expresses the idea that populations are not equal in the face of pollution. It implies an analysis be conducted in order to identify and manage the areas at risk of overexposure where an increasing risk to human health is suspected. The development of methods is a prerequisite for implementing public health activities aimed at protecting populations. Methods This paper presents the methodological framework developed by INERIS (French National Institute for Industrial Environment and Risks) to identify a common framework for a structured and operationalized assessment of human exposure. An integrated exposure assessment approach has been developed to integrate the multiplicity of exposure pathways from various sources, through a series of models enabling the final exposure of a population to be defined. Results Measured data from environmental networks reflecting the actual contamination of the environment are used to gauge the population’s exposure. Sophisticated methods of spatial analysis are applied to include additional information and take benefit of spatial and inter-variable correlation to improve data representativeness and characterize the associated uncertainty. Integrated approaches bring together all the information available for assessing the source-to-human-dose continuum using a Geographic Information System, multimedia exposure and toxicokinetic model. Discussion One of the objectives of the integrated approach was to demonstrate the feasibility of building complex realistic exposure scenarios satisfying the needs of stakeholders and the accuracy of the modelling predictions at a fine spatial-temporal resolution. A case study is presented to provide a specific application of the proposed framework and how the results could be used to identify an overexposed population. Conclusion This framework could be used for many purposes, such as mapping EHI, identifying vulnerable populations and providing determinants of exposure to manage and plan remedial actions and to assess the spatial relationships between health and the environment to identify factors that influence the variability of disease patterns.
Databáze: OpenAIRE
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