Éditeur(s) : HAL CCSD
Résumé : The purpose of this thesis is to improve the knowledge about and apply data mining techniques and some Bayesian model in the field of social and environmental health inequalities. On the neighborhood scale on the Paris, Marseille, Lyon and Lille metropolitan areas, the health event studied is infant mortality. We try to explain its risk with socio-economic data retrieved from the national census and environmental exposures such as air pollution, noise, proximity to traffic, green spaces and industries. The thesis is composed of two parts. The data mining part details the development of a procedure of creation of multidimensional socio-economic indices and of an R package that implements it, followed by the creation of a cumulative exposure index. In this part, data mining techniques are used to synthesize information and provide composite indicators amenable for direct usage by stakeholders or in the framework of epidemiological studies. The second part is about Bayesian models. It explains the "BYM" model. This model allows to take into account the spatial dimension of the data when estimating mortality risks. In both cases, the methods are exposed and several results of their usage in the above-mentioned context are presented. We also show the value of the socio-economic index procedure, as well as the existence of social inequalities of infant mortality in the studied metropolitan areas.
Cette thèse a pour but d'améliorer les connaissances concernant les techniques d'analyse de données et certains modèles bayésiens dans le domaine de l'étude des inégalités sociales et environnementales de santé. À l'échelle géographique de l'IRIS sur les agglomérations de Paris, Marseille, Lyon et Lille, l'événement sanitaire étudié est la mortalité infantile dont on cherchera à expliquer le risque avec des données socio-économiques issues du recensement et des expositions environnementales comme la pollution de l'air, les niveaux de bruit et la proximité aux industries polluantes, au trafic automobile ou aux espaces verts. Deux volets principaux composent cette thèse. Le volet analyse de données détaille la mise au point d'une procédure de création d'indices socio-économiques multidimensionnels et la conception d'un package R l'implémentant, puis la création d'un indice de multi-expositions environnementales. Pour cela, on utilise des techniques d'analyse de données pour synthétiser l'information et fournir des indicateurs composites utilisables directement par les décideurs publics ou dans le cadre d'études épidémiologiques. Le second volet concerne les modèles bayésiens et explique le modèle " BYM ". Celui-ci permet de prendre en compte les aspects spatiaux des données et est mis en œuvre pour estimer le risque de mortalité infantile. Dans les deux cas, les méthodes sont présentées et différents résultats de leur utilisation dans le contexte ci-dessus exposés. On montre notamment l'intérêt de la procédure de création d'indices socio-économiques et de multi-expositions, ainsi que l'existence d'inégalités sociales de mortalité infantile dans les agglomérations étudiées.
https://tel.archives-ouvertes.fr/tel-00943004

tel-00943004
https://tel.archives-ouvertes.fr/tel-00943004
https://tel.archives-ouvertes.fr/tel-00943004/document
https://tel.archives-ouvertes.fr/tel-00943004/file/Manuscrit_LallouA_final.pdf

Éditeur(s) : HAL CCSD Scientific Research Publishing
Résumé : International audience
In order to study social inequalities, indices can be used to summarize the multiple dimensions of the socioeconomic status. As a part of the Equit'Area Project, a public health program focused on social and environmental health inequalities; a statistical procedure to create (neighborhood) socioeconomic indices was developed. This procedure uses successive principal components analyses to select variables and create the index. In order to simplify the application of the procedure for non-specialists, the R package SesIndexCreatoR was created. It allows the creation of the index with all the possible options of the procedure, the classification of the resulting index in categories using several classical methods, the visualization of the results, and the generation of automatic reports.
ISSN: 2161-718X

hal-01161775
https://hal.archives-ouvertes.fr/hal-01161775
https://hal.archives-ouvertes.fr/hal-01161775/document
https://hal.archives-ouvertes.fr/hal-01161775/file/OJS_2015060814030742.pdf
DOI : 10.4236/ojs.2015.54031

Éditeur(s) : HAL CCSD Springer Verlag
Résumé :  
A closed depression is defined as a geomorphologic element where a sediment depository is encircled by hillslopes. Despite the fact that closed depressions are often the only stagnant water points in many European landscapes, few ecological researches on their plant assemblages have been done. The main goal of this study was to give first results of the environmental factors responsible for the vegetation composition, richness and rarity in the closed depressions of the Lorraine biogeographical district (Belgium, France and grand-duche de Luxembourg). We surveyed for plant presence 85 forest and 77 grassland closed depressions. For each site, wetland area, local environmental factors and regional connectivities registered. For each species, the Ellenberg values were compiled. To investigate the main source of variation in species composition and in species richness (including richness in rare species), Non-metric Multidimensional Scaling analyses and Generalized Linear Models were respectively used. Species pools in forest (forest and preforest species) and in grassland (bog plants, pioneers, helophytes) were quite different. In both landscapes, a gradient from plants typical of basic high-productive soils to plants typical of acid low-productive soils reflects a shared successional gradient. The accumulation of organic matter allowed the establishment of Sphagnum spp., which slowly acidified the soil and thus acted as ecosystem engineers for the arrival of bog plants. Moreover, the species composition was additionally driven by the plant light tolerance in forests and by the plant water requirements in grasslands. Mechanisms of species accumulation (increase in species richness) were different in forests and in grasslands: respectively related to the plant light tolerance and to the wetland area. At the regional level, the averaged soil productivity was negatively related to the richness in rare species. Indeed, perennial highly-competitive plants such as Glyceria spp., Iris pseudacorus or Urtica dioica impeded the establishment of smaller and rarer species. At the habitat level, isolated closed depressions (due to either low connectivity or low grazing pressure) have more habitat rare species, giving evidences of dispersal limitation in plant assemblages of closed depressions.
ISSN: 0960-3115

hal-01032125
https://hal.archives-ouvertes.fr/hal-01032125
DOI : 10.1007/s10531-007-9227-x

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 BioMed Central
Résumé : International audience
Background: The evaluation of geographical healthcare accessibility in residential areas provides crucial information to public policy. Traditional methods - such as Physician Population Ratios (PPR) or shortest travel time - offer only a one-dimensional view of accessibility. This paper developed an improved indicator: the Index of Spatial Accessibility (ISA) to measure geographical healthcare accessibility at the smallest available infra-urban level, that is, the Ilot Regroupe pour des Indicateurs Statistiques. Methods: This study was carried out in the department of Nord, France. Healthcare professionals are geolocalized using postal addresses available on the French state health insurance website. ISA is derived from an Enhanced Two-Step Floating Catchment Area (E2FCA). We have constructed a catchment for each healthcare provider, by taking into account residential building centroids, car travel time as calculated by Google Maps and the edge effect. Principal Component Analyses (PCA) were used to build a composite ISA to describe the global accessibility of different kinds of health professionals. Results: We applied our method to studying geographical healthcare accessibility for pregnant women, by selecting three types of healthcare provider: general practitioners, gynecologists and midwives. A total of 3587 healthcare providers are potentially able to provide care for inhabitants of the department of Nord. On average there are 92 general practitioners, 22 midwives and 21 gynecologists per 100,000 residents. The composite ISA for the three types of healthcare provider is 39 per 100,000 residents. A comparative analysis between ISA and physician-population ratios indicates that ISA represents a more even distribution whereas the physician-population ratios show an 'all-or-nothing' approach. Conclusion: ISA is a multidimensional and improved measure, which combines the volume of services relative to population size with the proximity of services relative to the population's location, available at the smallest feasible geographical scale. It could guide policy makers towards highlighting critical areas in need of more healthcare providers, and these areas should be earmarked for further knowledge-based policy making.
ISSN: 1475-9276

hal-01359567
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01359567
DOI : 10.1186/s12939-016-0411-z
PUBMED : 27485740

Éditeur(s) : HAL CCSD
Résumé :  
A closed depression is defined as a geomorphologic element where a sediment depository is encircled by hillslopes. Despite the fact that closed depressions are often the only stagnant water points in many European landscapes, few ecological researches on their plant assemblages have been done. The main goal of this study was to give first results of the environmental factors responsible for the vegetation composition, richness and rarity in the closed depressions of the Lorraine biogeographical district (Belgium, France and grand-duche de Luxembourg). We surveyed for plant presence 85 forest and 77 grassland closed depressions. For each site, wetland area, local environmental factors and regional connectivities registered. For each species, the Ellenberg values were compiled. To investigate the main source of variation in species composition and in species richness (including richness in rare species), Non-metric Multidimensional Scaling analyses and Generalized Linear Models were respectively used. Species pools in forest (forest and preforest species) and in grassland (bog plants, pioneers, helophytes) were quite different. In both landscapes, a gradient from plants typical of basic high-productive soils to plants typical of acid low-productive soils reflects a shared successional gradient. The accumulation of organic matter allowed the establishment of Sphagnum spp., which slowly acidified the soil and thus acted as ecosystem engineers for the arrival of bog plants. Moreover, the species composition was additionally driven by the plant light tolerance in forests and by the plant water requirements in grasslands. Mechanisms of species accumulation (increase in species richness) were different in forests and in grasslands: respectively related to the plant light tolerance and to the wetland area. At the regional level, the averaged soil productivity was negatively related to the richness in rare species. Indeed, perennial highly-competitive plants such as Glyceria spp., Iris pseudacorus or Urtica dioica impeded the establishment of smaller and rarer species. At the habitat level, isolated closed depressions (due to either low connectivity or low grazing pressure) have more habitat rare species, giving evidences of dispersal limitation in plant assemblages of closed depressions.
7th INTECOL International Wetland Conference
Utrecht, Netherlands

hal-01032381
https://hal.archives-ouvertes.fr/hal-01032381

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