Éditeur(s) : HAL CCSD Nature Publishing Group
Résumé : International audience
Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise, etc.or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare. We propose to use statistical factor and cluster analyses to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach in a large French metropolitan area. The study was carried out in the Great Lyon area (France, 1.2 M inhabitants) at the census Block Group (BG) scale. We used as environmental indicators ambient air NO2 annual concentrations, noise levels and proximity to green spaces, to industrial plants, to polluted sites and to road traffic. They were synthesized using Multiple Factor Analysis (MFA), a data-driven technique without a priori modeling, followed by a Hierarchical Clustering to create BG classes. The first components of the MFA explained, respectively, 30, 14, 11 and 9% of the total variance. Clustering in five classes group: (1) a particular type of large BGs without population; (2) BGs of green residential areas, with less negative exposures than average; (3) BGs of residential areas near midtown; (4) BGs close to industries; and (5) midtown urban BGs, with higher negative exposures than average and less green spaces. Other numbers of classes were tested in order to assess a variety of clustering. We present an approach using statistical factor and cluster analyses techniques, which seem overlooked to assess cumulative exposure in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.Journal of Exposure Science and Environmental Epidemiology advance online publication, 24 September 2014; doi:10.1038/jes.2014.66.
ISSN: 1559-0631

hal-01069587
https://hal.archives-ouvertes.fr/hal-01069587
https://hal.archives-ouvertes.fr/hal-01069587/document
https://hal.archives-ouvertes.fr/hal-01069587/file/Article_multiexpo_20140708_c.pdf
DOI : 10.1038/jes.2014.66

Éditeur(s) : Wiley-blackwell
Résumé : Aim The aims of this study were: (1) to identify global communities of tuna and billfish species through quantitative statistical analyses of global fisheries data; (2) to describe the spatial distribution, main environmental drivers and species composition of each community detected; and (3) to determine whether the spatial distribution of each community could be linked to the environmental conditions that affect lower trophic levels by comparing the partitions identified in this study with Longhursts biogeochemical provinces. Location The global ocean from 60 degrees S to 65 degrees N. Methods We implemented a new numerical procedure based on a hierarchical clustering method and a nonparametric probabilistic test to divide the oceanic biosphere into biomes and ecoregions. This procedure was applied to a database that comprised standardized data on commercial longline catches for 15 different species of tuna and billfish over a period of more than 50 years (i.e. 1953-2007). For each ecoregion identified (i.e. characteristic tuna and billfish community), we analysed the relationships between species composition and environmental factors. Finally, we compared the biogeochemical provinces of Longhurst with the ecoregions that we identified. Results Tuna and billfish species form nine well-defined communities across the global ocean. Each community occurs in regions with specific environmental conditions and shows a distinctive species composition. High similarity (68.8% homogeneity) between the spatial distribution of the communities of tuna and billfish and the biogeochemical provinces suggests a strong relationship between these species and the physical and chemical characteristics of the global ocean. Main conclusions Despite their high tolerance for a wide range of environmental conditions, these highly migratory species are partitioned into clear geographical communities in the ocean at a global scale. The similarity between biogeochemical and biotic divisions in the ocean suggests that the global ocean is a mosaic of large biogeographical ecosystems, each characterized by specific environmental conditions that have a strong effect on the composition of the trophic web.
Journal Of Biogeography (0305-0270) (Wiley-blackwell), 2012-01 , Vol. 39 , N. 1 , P. 114-129

Droits : 2011 Blackwell Publishing Ltd
http://archimer.ifremer.fr/doc/00060/17141/14716.pdf
DOI:10.1111/j.1365-2699.2011.02582.x
http://archimer.ifremer.fr/doc/00060/17141/

Éditeur(s) : HAL CCSD
Résumé : International audience
Background: Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise...) or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare.Aims: We propose to use data mining techniques to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach on a large French metropolitan area.Methods: The study was carried out in the Great Lyon area (France, 1,260,348 inhabitants in 2007, 527 km²) at the census block group (BG) scale. Indicators on NO2 annual concentrations, noise levels, proximity to green spaces and to industrial plants, and road traffic were synthetized using Multiple Factor Analysis (MFA), which allows to explore the relations between exposures and BGs without a priori knowledge, and to synthetize indicators of different types. Hierarchical clustering was then used to create BG classes. Results: The four first components of the MFA explained respectively 23, 14, 13 and 12% of the total variance. Clustering in 3 classes group: 1) BGs far from industries, greener and with less noise and air pollution than the average; 2) BGs close to industries with less green spaces and air pollution than the average; and 3)BGs far from industries but with higher levels of noise, air pollution and traffic. Greater numbers of classes were tested in order to assess a variety of clustering.Conclusions: We present a data driven approach using data mining techniques, which seem overlooked for cumulative exposure assessment in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.
Environment and Health – Bridging South, North, East and West. Conference of ISEE, ISES and ISIAQ.
Basel, Switzerland

hal-01432884
https://hal.archives-ouvertes.fr/hal-01432884
https://hal.archives-ouvertes.fr/hal-01432884/document
https://hal.archives-ouvertes.fr/hal-01432884/file/Poster_2013_ISEE_20130711.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
To study social health inequalities, contextual data may constitute an appropriate alternative to individual socioeconomic characteristics, often hard to retrieve. Indices can be used to summarize the multiple dimensions of the neighborhood socioeconomic status. The main objectives of this work are to develop a statistical procedure to create a neighborhood socioeconomic index and to investigate the influence of the clustering method of the deprivation index on the measure of health inequalities. Our study setting is composed of three major French metropolitan areas: Lille, Lyon and Marseille. The statistical unit is the French census block. The methodology uses several successive principal components analyses to select variables and create the index. Deprivation categories are drawn with hierarchical clustering on principal components. Twenty socioeconomic variables are selected in the neighborhood deprivation index. An optimal clustering obtained by HC is in three classes and the clusters are ordered along the first axis of the PCA.
SFDS - 44èmes journées de Statistique - 2012
Bruxelles, Belgium

hal-00734769
https://hal.archives-ouvertes.fr/hal-00734769
https://hal.archives-ouvertes.fr/hal-00734769/document
https://hal.archives-ouvertes.fr/hal-00734769/file/submission_44.pdf

Éditeur(s) : HAL CCSD Seismological Society of America
Résumé : International audience
We present an improvement of the maximum intersection (MAXI) method in which absolute earthquake location is defined by the maximum intersection number of hyperbolic equal differential time (EDT) volumes (one EDT volume being described as all grid nodes satisfying the arrival‐time differences between two stations, ± a tolerance value known as TERR). This 3D technique is well adapted to a strongly heterogeneous environment, avoids the depth versus origin‐time trade‐off (even using P arrivals alone), and objectively filters possible erroneous arrival times. Improvements consist of introducing an iterative multiscale approach on the TERR parameter and conducting a hierarchy of grid discretization to refine the preliminary solution (multigrid algorithm). The outlier cleaning process is strengthened by conducting statistical analyses based on the number of EDT volume intersections per station, rather than on travel‐time residues. Processing two series of synthetic arrival times computed in the 3D seismological configuration of the southernmost Ryukyu subduction zone, offshore Taiwan, allows us to (1) confirm MAXI robustness, even when arrival times are highly disturbed or azimuthal coverage largely reduced, and (2) show that MAXI, by limiting trade‐offs between origin time and depth and between epicentral position and depth, is less affected by a wrong velocity model than a technique that minimizes travel‐time residues. To conclude, we apply the MAXI method to locate earthquakes recorded by the combined Central Weather Bureau of Taiwan (CWB) and the Japanese Meteorological Agency (JMA) networks (1991-2008) within a georealistic a priori 3D P‐velocity model. Hypocenter determinations are selected based on MAXI confidence factors, and earthquake clustering along well‐known tectonic features witnesses hypocenter determination accuracy.
ISSN: 0037-1106

hal-00725227
https://hal.archives-ouvertes.fr/hal-00725227
DOI : 10.1785/0120100311

Éditeur(s) : HAL CCSD
Résumé : National audience
We propose a method to solve the problem of clustering individuals described by mixed variables structured in blocks. It is a hierarchical method with two levels similar to Hierarchical Principal Component Analysis presented by Wold, based on the mixed topology maps (MTM). The first step consists in establishing, for each block of mixed variables, a clustering representing a synthesis of local individuals at the block level. The second step is to re-apply MTM on the weighted results of the first level. We obtain a global clustering of individuals, consensus among the partitions from level 1. The proposed method is illustrated on data from the national survey in the French housing stock carried out in 2003-2005 by the Observatory for Indoor Air Quality (OQAI).
Fouille de Données Complexes, complexité liée aux données multiples et massives (FDC)
bordeaux, France

hal-00748841
https://hal.archives-ouvertes.fr/hal-00748841
https://hal.archives-ouvertes.fr/hal-00748841/document

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
INTRODUCTION: In order to study social health inequalities, contextual (or ecologic) data may constitute an appropriate alternative to individual socioeconomic characteristics. Indices can be used to summarize the multiple dimensions of the neighborhood socioeconomic status. This work proposes a statistical procedure to create a neighborhood socioeconomic index. METHODS: The study setting is composed of three French urban areas. Socioeconomic data at the census block scale come from the 1999 census. Successive principal components analyses are used to select variables and create the index. Both metropolitan area-specific and global indices are tested and compared. Socioeconomic categories are drawn with hierarchical clustering as a reference to determine "optimal" thresholds able to create categories along a one-dimensional index. RESULTS: Among the twenty variables finally selected in the index, 15 are common to the three metropolitan areas. The index explains at least 57% of the variance of these variables in each metropolitan area, with a contribution of more than 80% of the 15 common variables. CONCLUSIONS: The proposed procedure is statistically justified and robust. It can be applied to multiple geographical areas or socioeconomic variables and provides meaningful information to public health bodies. We highlight the importance of the classification method. We propose an R package in order to use this procedure.
ISSN: 1475-9276

inserm-00809310
http://www.hal.inserm.fr/inserm-00809310
http://www.hal.inserm.fr/inserm-00809310/document
http://www.hal.inserm.fr/inserm-00809310/file/1475-9276-12-21.pdf
DOI : 10.1186/1475-9276-12-21

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
Background: During the last decade, French Guiana has been affected by major dengue fever outbreaks. Although this arbovirus has been a focus of many awareness campaigns, very little information is available about beliefs, attitudes and behaviors regarding vector-borne diseases among the population of French Guiana. During the first outbreak of the chikungunya virus, a quantitative survey was conducted among high school students to study experiences, practices and perceptions related to mosquito-borne diseases and to identify socio-demographic, cognitive and environmental factors that could be associated with the engagement in protective behaviors. Methodology/Principal Findings: A cross-sectional survey was administered in May 2014, with a total of 1462 students interviewed. Classrooms were randomly selected using a two-stage selection procedure with cluster samples. A multiple correspondence analysis (MCA) associated with a hierarchical cluster analysis and with an ordinal logistic regression was performed. Chikungunya was less understood and perceived as a more dreadful disease than dengue fever. The analysis identified three groups of individual protection levels against mosquito-borne diseases: “low” (30%), “moderate” (42%) and “high” (28%)”. Protective health behaviors were found to be performed more frequently among students who were female, had a parent with a higher educational status, lived in an individual house, and had a better understanding of the disease. Conclusions/Significance: This study allowed us to estimate the level of protective practices against vector-borne diseases among students after the emergence of a new arbovirus. These results revealed that the adoption of protective behaviors is a multi-factorial process that depends on both sociocultural and cognitive factors. These findings may help public health authorities to strengthen communication and outreach strategies, thereby increasing the adoption of protective health behaviors, particularly in high-risk populations. © 2016 Fritzell et al.
ISSN: 1935-2727

hal-01467556
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01467556
DOI : 10.1371/journal.pntd.0005081
PUBMED : 27802275

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
Introduction In order to study social health inequalities, contextual (or ecologic) data may constitute an appropriate alternative to individual socioeconomic characteristics. Indices can be used to summarize the multiple dimensions of the neighborhood socioeconomic status. This work proposes a statistical procedure to create a neighborhood socioeconomic index. Methods The study setting is composed of three French urban areas. Socioeconomic data at the census block scale come from the 1999 census. Successive principal components analyses are used to select variables and create the index. Both metropolitan area-specific and global indices are tested and compared. Socioeconomic categories are drawn with hierarchical clustering as a reference to determine "optimal" thresholds able to create categories along a one-dimensional index. Results Among the twenty variables finally selected in the index, 15 are common to the three metropolitan areas. The index explains at least 57% of the variance of these variables in each metropolitan area, with a contribution of more than 80% of the 15 common variables. Conclusions The proposed procedure is statistically justified and robust. It can be applied to multiple geographical areas or socioeconomic variables and provides meaningful information to public health bodies. We highlight the importance of the classification method. We propose an R package in order to use this procedure.
International Journal for Equity in Health

hal-00854028
https://hal.archives-ouvertes.fr/hal-00854028
https://hal.archives-ouvertes.fr/hal-00854028/document
DOI : 10.1186/1475-9276-12-21

Éditeur(s) : HAL CCSD
Résumé : International audience
The aim was to identify patterns of work organization characteristics using data from epidemiological surveillance program of musculoskeletal disorders (MSD) implemented in the Pays de la Loire region between 2002 and 2005. A total of 3710 workers were included and completed a administered questionnaire including 16 organizational variables. Ascendant hierarchical clustering (AHC) of organizational variables and AHC of workers had identified five patterns of work organization characteristics: technical constraints and weak decision latitude; internal/external demand and mean decision latitude; weak pace constraints and mean decision latitude; internal/external demand and high decision latitude; weak pace constraints and high decision latitude. Relationships with MSD diagnosed by occupational physicians were then studied.
The specific health programs (SHP) are one of the four mechanisms of prevention planned by the Health and Safety at work Law in the province of Quebec. If the Law appoints only a responsible doctor, it is in reality Health at work teams (HWT) that develop these SHP. In this communication, based on the model of the working situation and the diagram of inter professional practices of collaboration, we study the practices of inter professional collaboration (CIP) in the HWT. The observed practices vary between independent practices, in parallel, of consultation, of dialogue and in shared services. Formalization of the teams, coordination of communication, leadership, respect and professional identities influence particularly the practices of CIP.
L’objectif était d’identifier des patterns de caractéristiques d'organisation du travail à partir des données du programme de surveillance épidémiologique des troubles musculo-squelettiques (TMS) mis en œuvre dans les Pays de la Loire entre 2002 et 2005. Au total, 3 710 salariés ont été inclus et ont répondu à un questionnaire comportant notamment 16 variables organisationnelles. Une classification ascendante hiérarchique (CAH) des variables organisationnelles puis une CAH des salariés ont permis d’identifier cinq patterns de caractéristiques d’organisation du travail : contraintes techniques et faible latitude décisionnelle ; demande interne/externe et latitude décisionnelle moyenne ; faibles contraintes de rythme et latitude décisionnelle moyenne ; demande externe/interne et forte latitude décisionnelle ; faibles contraintes de rythme et forte latitude décisionnelle. Les associations avec les TMS diagnostiqués par des médecins du travail ont ensuite été étudiées.
Actes du 50ème congrès de la Société d'Ergonomie de Langue Française
Paris, France

halshs-01307785
https://halshs.archives-ouvertes.fr/halshs-01307785

Éditeur(s) : HAL CCSD
Résumé : One of the major challenges in forest ecology is to understand the ecology, physiology and potential responses of the> 250000 species of vascular plants of the planet through the categorization of this diversity into functional groups. This approach is essentially based on functional traits analysis, but few investigations were made in tropical areas. The aim of this study was to determine functional groups in two contrasted tropical ecosystems, dry (DF) and mountain rain (MRF) forest (respectively rainfall of 1 200 mm/year and 10 000 mm/year). Guadeloupe Island in FWI presents both these ecosystems spread over less 100 km. In a first time, we developed an original species typology based on 7 "soft" traits, easy to measure (stomatal density, leaf trichom density, chlorophyll content, leaf nitrogen content, specific leaf area, wood density, leaf area, plant height). The method was based on principal component analysis (PCA) and agglomerative hierarchical clustering (AHC) applied to these traits measured at the individual level (Blazy et al., 2009). In a second time, we evaluated the relevance of these soft trait-based groups compared to a typology based on 5 "hard" ecophysiological traits, more costly to quantify but with higher functional significance (difference between predawn and minimum leaf water potential, stomatal conductance, maximal carbon assimilation rate, leaf water potential at 90% of loss of stem hydraulic conductivity). When performed on the dominant canopy species in DF and MRF (a total of 13 species and 60 mature individuals), the typological approach based on soft traits seems relevant to discriminate groups with a distinct functional reality. Through both ecosystems, we obtained 4 homogenous groups. Two were exclusively composed by DF's or MRF's species, indicating that a functional strategy can be linked to specific environmental conditions. The two other groups showed a mix of DF and MRF species indicating that different functional strategies can coexist in the same environment. These mixed groups seem distinct by their ecophysiological features, particularly in term of hydraulic characteristics. One group was composed by drought tolerant species, water spender species, with a high xylem embolism resistance, whereas the second one was composed by water saver species, less resistant to embolism. Therefore, a determination of functional groups based on soft traits could be useful to model ecosystem's responses to environmental changes on a global scale.
Book of Abstracts - isem 2013 - Ecological Modelling for Ecosystem Sustainability
Toulouse, France

hal-00964668
https://hal.archives-ouvertes.fr/hal-00964668

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
Background: An environmental health inequality is a major public health concern in Europe. However just few studies take into account a large set of characteristics to analyze this problematic. The aim of this study was to identify and describe how socioeconomic, health accessibility and exposure factors accumulate and interact in small areas in a French urban context, to assess environmental health inequalities related to infant and neonatal mortality.Methods: Environmental indicators on deprivation index, proximity to high-traffic roads, green space, and healthcare accessibility were created using the Geographical Information System. Cases were collected from death certificates in the city hall of each municipality in the Nice metropolitan area. Using the parental addresses, cases were geocoded to their census block of residence. A classification using a Multiple Component Analysis following by a Hierarchical Clustering allow us to characterize the census blocks in terms of level of socioeconomic, environmental and accessibility to healthcare, which are very diverse definition by nature. Relation between infant and neonatal mortality rate and the three environmental patterns which categorize the census blocks after the classification was performed using a standard Poisson regression model for count data after checking the assumption of dispersion.Results: Based on geographic indicators, three environmental patterns were identified. We found environmental inequalities and social health inequalities in Nice metropolitan area. Moreover these inequalities are counterbalance by the close proximity of deprived census blocks to healthcare facilities related to mother and newborn. So therefore we demonstrate no environmental health inequalities related to infant and neonatal mortality.Conclusion: Examination of patterns of social, environmental and in relation with healthcare access is useful to identify census blocks with needs and their effects on health. Similar analyzes could be implemented and considered in other cities or related to other birth outcomes.
ISSN: 1476-069X

halshs-01366285
https://halshs.archives-ouvertes.fr/halshs-01366285
https://halshs.archives-ouvertes.fr/halshs-01366285/document
https://halshs.archives-ouvertes.fr/halshs-01366285/file/art_10.1186_s12940-016-0163-7.pdf
PUBMED : 27449640