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L'analyse des relations entre expositions environnementales et santé suscite un intérêt grandissant mais reste complexe à étudier. Elle fait appel à des disciplines comme l'épidémiologie et la toxicologie, mais celles-ci sont confrontées à des limites méthodologiques. La géographie et l'utilisation des SIG apportent de nouvelles perspectives d'analyse et des méthodes complémentaires, qui permettent de mieux comprendre certains phénomènes spatiaux et temporels de l’impact de l’environnement sur la santé. L'exemple de l’analyse des expositions aux pesticides sur la santé reflète ces difficultés et ces nécessités. Des méthodes SIG ont été développées au niveau international pour évaluer les expositions aux pesticides agricoles afin de comprendre les expositions à échelle fine, rétrospective et la dispersion des pesticides. Les projets menés par le Département Cancer Environnement du Centre Léon Bérard ont permis de développer de telles méthodes en France, à l’échelle individuelle en incluant les variables explicatives de l’exposition résidentielle et de façon rétrospective, qui peuvent ainsi être intégrées et utilisées dans des études épidémiologiques.Parallèlement à ces recherches, des études et des mesures de contrôle de présence de pesticides dans les milieux naturels sont effectuées par différents acteurs, mais ces informations restent souvent limitées à leurs créateurs. Pourtant, elles peuvent se révéler complémentaires dans différents domaines d’action environnementale ou sanitaire. La création d’un outil de partage et d’échange de données sur les pesticides a donc été initiée. La santé environnementale a une place croissante dans les différentes politiques publiques et territoriales, notamment par l'aménagement du territoire. Celles-ci nécessitent cependant des données et des outils pour pouvoir considérer les déterminants environnementaux et de santé. L'exposition aux pesticides peut ainsi être intégrée à ces politiques en renforçant le cadre règlementaire existant et en développant des approches nouvelles afin de réduire l’exposition de la population. / The analysis of the relationship between the environment and health is a growing concern but complex to study. It uses disciplines such as epidemiology and toxicology, but they know some methodological limitations. Geography and the use of GIS provide a new perspective of analysis and complementary methods that allow us to better understand spatial and temporal issues of environmental impact on health. The analysis of the effects of pesticides on health is an example that reflects these difficulties and needs. GIS methods have been developed at international scale to assess exposures to agricultural pesticides at fine scale, retrospective and pesticides dispersion. The Cancer Environment Department in the Centre Léon Bérard developed projects to create such methods in France, at individual level, including the explanatory variables of residential exposure, and retrospectively that can be integrated and used in epidemiological studies.In addition to this research, studies and measures for the control of presence of pesticides in natural environments are carried out by different actors, but the use of this information often stay limited to their creators. However, they may prove to be complementary and necessary in different areas of environmental or health action. The creation of a tool for sharing and exchange of data was initiated.Environmental health has a growing place in different public and territorial policies, including through territorial planning. However, these require data and tools to be able to consider environmental determinants and health. Exposure to pesticides can thus be incorporated into these policies by strengthening the regulatory framework existing and developing new approaches to reduce the exposure to pesticides of the population.

Contexte : Bien que le tabagisme soit de loin le facteur de risque majeur de cancer de poumon, les expositions professionnelles, qui représentent la 2eme étiologie majeure de ces cancers, méritent un intérêt particulier. Peu d'information existe actuellement sur le risque de cancer du poumon associé aux expositions professionnelles aux solvants. Ces substances sont largement utilisées dans différentes industries et certaines professions comme les peintres par exemple, particulièrement exposés aux solvants, sont reconnues à risque de cancer du poumon, sans identification de l'agent cancérogène en cause.Objectifs : L'objectif de mon travail de thèse est l'évaluation du rôle de l'exposition à différents solvants organiques (groupés en solvants chlorés, carburants et solvants pétroliers, solvants oxygénés) sur le risque du cancer du poumon. Dans un premier temps nous avons étudié l'effet de l'exposition professionnelle aux solvants chlorés; ensuite l'analyse a intégré l'exposition aux deux autres familles de solvants, toujours en tenant en compte des principaux facteurs de risque de cancer du poumon, y compris le tabac et l'exposition professionnelle à l'amiante.Population et méthode: Ce travail est basé sur les données d'une large étude de type cas-témoins en population générale, ICARE. Des données détaillées sur l'activité professionnelle vie entière ont été recueillis. Au total, 2,926 cas de cancer de poumon (2,276 hommes et 650 femmes) et 3,555 témoins (2,780 hommes et 775 femmes) ont été inclus. L'exposition aux solvants a été évaluée par des matrices emplois-expositions, élaborés séparément par chaque substance par des hygiénistes industriels. En outre, l'exposition à certains solvants était directement déclarée par les sujets dans le questionnaire. Nous avons d'abord suivi une approche d'analyse statistique classique par régression afin d'étudier le rôle des solvants chlorés. Lors de l'analyse qui intégrait les trois familles des solvants, nous avons suivi une approche méthodologique complexe multidimensionnelle. La méthode bayésienne profil regression nous a permis de contourner les limites de l'analyse classique, dues à la forte multicollinéarité qui existe entre les solvants.Résultats et conclusions: L'analyse focalisée sur les solvants chlorés a suggéré une association entre le cancer du poumon et l'exposition professionnelle au perchloroethylene (PCE), en particulier chez les femmes. En revanche, aucune association avec le risque de cancer du poumon n'a pu être mise en évidence par la seconde analyse intégrant les trois familles de solvants (chlorés, pétroliers et oxygénés). Cependant, parce que nous avons augmenté la spécificité de la définition de l'exposition le PCE n'était pas inclus dans les solvants étudiés, nous empêchant de confirmer ou infirmer l'association mise en évidence précédemment. Bien que les solvants ne soient pas associés au cancer du poumon, nous avons identifié deux groupes de sujets avec un risque de cancer du poumon supérieur à la moyenne. L'un de ces groupes incluait notamment une forte concentration de peintres. Notre analyse ne plaide pas en faveur du rôle des solvants pour expliquer cet excès. Malgré l'absence d'association entre l'exposition aux solvants et le risque de cancer du poumon l'approche Bayésienne utilisée nous a permis d'analyser l'exposition conjointe à un nombre relativement important de substances, ce qui est une situation assez courante en matière d'expositions professionnelles. Notre souhait est maintenant grâce à cette nouvelle méthodologie de nous pencher sur l'étude du rôle des expositions conjointes de substances reconnues cancérigènes pour le poumon comme l'amiante, la poussière de silice et les gaz d'échappement du moteur diesel, toutes trois retrouvés très fréquemment dans l'industrie de la construction par exemple. / Context: The principal risk factor for lung cancer is by far tobacco smoke, however occupational exposures deserve a special interest because they are the 2nd main etiology of this cancer. Little information is currently available on the relationship between lung cancer risk and occupational exposure to solvents that are widely used in several industries. Certain jobs such as painters, who are particularly exposed to solvents, are known to be at increased risk of lung cancer, but the causative agent is still unknown or unproven.Objectives: The aim of the present work was the evaluation of the role of occupational exposure to different organic solvents on lung cancer risk. Initially we studied the effect of occupational exposure to chlorinated solvents; then the analysis integrated exposure to two other solvent families, namely fuels and petroleum solvents and oxygenated solvents, always taking into account the main risk factors for lung cancer, including cigarette smoking and occupational exposure to asbestos.Population and methods: This work was based on a large population-based case-control study, ICARE. Detailed data on the lifelong occupation was collected. A total of 2,926 cases of lung cancer (2,276 men and 650 women) and 3,555 controls (2,780 men and 775 women) were included. Exposure to solvents was assessed by job exposure matrices, developed separately for each substance by industrial hygienists. In addition, exposure to certain solvents was directly reported by subjects in the questionnaire. First we followed a classical statistical regression analysis approach to investigate the role of chlorinated solvents. In the analysis that included three families of solvents, we followed a multidimensional complex methodological approach. Bayesian profile regression method enabled us to overcome traditional analysis limits due to high multicollinearity between solvents.Results and conclusions: The analysis focused on chlorinated solvents suggested an association between lung cancer and occupational exposure to perchloroethylene (PCE), especially in women. While, no association with lung cancer risk could be demonstrated in the second analysis, incorporating the three families of solvents (chlorinated, petroleum and oxygenated). However, as we had increased the specificity of exposure definition, PCE was not included in the studied solvents anymore, preventing us from confirming or denying the association suggested above. Although solvents were not associated with lung cancer, we identified two groups of subjects whose risk of lung cancer was higher than the average. In particular, one of these groups included a high concentration of painters, however our analysis does not advocate the role of solvents to explain this excess. Despite the lack of association between solvent exposure and risk of lung cancer, the Bayesian approach allowed us to analyze the effect of joint exposure to a relatively large number of substances, which is a fairly common situation in occupational exposures. Thanks to this innovative method, our intention is now to look at the role of joint exposure to substances recognized as carcinogenic for the lung such as asbestos, silica dust and diesel engine exhaust, that are frequently found for instance in construction industry.

Studying dopamine-dependent functions such as memory and creativity can help us understand and improve quality of life in populations at risk for dopaminergic network dysfunction. I examined memory and creativity in a series of studies in different at-risk populations. The first study investigated marijuana initiation and learning in 119 inner-city youth, some with prenatal substance exposures, including to cocaine. I hypothesized that earlier-onset marijuana use would predict poorer developmental learning trajectories, and non-use the most positive. Results suggested that initiation’s effects on learning may reflect psychosocial factors rather than prenatal substance exposure status or time of marijuana initiation. The potential importance of the dopamine-related personality factor “openness to experience” motivated additional studies. One hypothesized and found different neurocognitive outcomes in young-adult substance users (n=41) based on maladaptive or adaptive substance use motives. The other studies examined Parkinson’s disease (PD), a disorder characterized by the degeneration of brain dopaminergic networks. Participants were individuals with PD without dementia (33-42 “PDs”/study), age-matched normal control adults (26-28 “NCs”/study), and younger control adults (37-41 “YCs”/study). The first PD study examined neuropsychological and personality correlates of learning and memory. I hypothesized that in each group, openness would explain a significant amount of the variance in learning, and higher openness would be associated with better learning and memory, particularly in PDs. Results supported this hypothesis in PDs only. The second PD study examined creativity—specifically, divergent thinking, which correlates with openness and shares dopaminergic neural substrates. Based on research demonstrating that brief walking improves divergent thinking in young adults, and that exercise changes dopamine transmission, I hypothesized that brief walking would improve divergent thinking in PDs, NCs, and YCs. In PDs, I expected higher disease severity (more compromised dopamine function) to correlate with less improvement after walking. None of the hypotheses were supported, potentially due to the low intensity of the intervention, but openness appeared protective of creativity in YCs and PDs. Taken together, the results of the studies demonstrate the importance of psychosocial factors in dopamine-dependent cognition. In at-risk populations, openness’s benefits may surpass effects of moderate substance use, and they may offer neuroprotection in PD.

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INTRODUCTION: Chemical exposures to US pregnant women have been shown to have adverse health impacts on both mother and fetus. A prior paper revealed that US pregnant women in 2003-2004 had widespread exposure to multiple chemicals. The goal of this research is to examine how environmental chemical exposures to US pregnant women have changed from 2003 to 2010 and to look further at the extent of simultaneous exposure to multiple chemicals in US pregnant women using biomonitoring data available through NHANES (the National Health and Nutritional Examination Survey). METHODS: Using available NHANES data from the following cycles (2003-2004, 2005-2006, 2007-2008, 2009-2010), we analyzed how environmental chemical exposures changed over time. Covariates were used and data was weighted to reflect the population of pregnant US women. Each cycle was then compared to the 2003-2004 cycle in order to assess how exposures have changed over time. We then looked at the data in an entirely different fashion. We examined the total number of chemicals detected in a given pregnant woman by chemical group. Finally, we looked at the total number of detects across various chemical groups and used the Fisher Exact Test to study how the distribution of detections changed in 2009-2010 compared to 2003-2004. RESULTS: While at least one-third of the chemicals analyzed showed one cycle that differed, exposure rates of individual chemicals were generally not increasing from 2003-2010. Median number of detections over chemical groups also did not show much difference over time. However, analysis of the change in frequency distributions revealed that, for some chemical groups, the frequency of detects in US pregnant woman significantly increased in 2010 compared to 2003. CONCLUSIONS: Widespread chemical exposures were seen in US pregnant women from 2003 through 2010. The number of chemical analytes detected in US pregnant women’s bodies is rising. Many chemicals studied had similar mechanisms of action and/or similar adverse health outcomes upon exposure which is known to result in a cumulative health effect. This research suggests that we need to focus not only on exposure rates of individual chemicals but also on the overall number of chemicals detected when assessing the overall picture of environmental chemical exposures to pregnant women in the US.

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 oeuvre 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 / 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

Uma característica dominante do sistema financeiro contemporâneo é a intrincada rede de conexões entre instituições financeiras, destacando-se a rede de empréstimos do mercado interbancário, através da qual é feita a transferência de recursos líquidos de bancos com superavit de liquidez para bancos deficitários. Ao mesmo tempo em que o mercado interbancário é responsável pela alocação eficiente de liquidez, a estrutura das exposições interbancárias pode ser considerada fator de risco sistêmico por ser fonte de contágio em caso de crise financeira. A insolvência de um banco pode se propagar na rede levando à insolvência de um grande subconjunto conectado de bancos. Estudos empíricos tem evidenciado que algumas redes interbancárias apresentam características de redes livres de escala. O presente trabalho explora as características de contágio financeiro em redes cuja distribuição de links se aproxima a uma lei de potência, através de um modelo deliberadamente simplificado que define a estrutura patrimonial dos bancos a partir de informações de conectividade da rede. Variando os parâmetros de formação das redes obtemos distribuições com diferentes concentrações de dívidas e de direitos, criando três perfis principais, que foram analisados quanto a sua resistência ao contágio. Testamos também o efeito da variação da conectividade em conjunto com a variação da concentração dos links. Os resultados encontrados sugerem que redes mais conectadas e com alta concentração de direitos (com nodos caracterizados por serem grandes credores do sistema) apresentam maior resistência ao contágio. Avaliando alguns índices topológicos de risco sistêmico sugeridos na literatura, pudemos verificar sua capacidade de explicar o impacto da quebra de um nodo sobre o sistema. Embora fique evidente a relação positiva entre os índices e o valor do impacto para os casos de maior magnitude de perdas, a relação é mais fraca para os menores valores de impacto, sugerindo um poder menor de previsão em redes mais resistentes. / One of the most striking characteristics of modern financial systems is its complex interdependence, standing out the network of bilateral exposures in interbank market, through which institutions with surplus liquidity can lend to those with liquidity shortage. While the interbank market is responsible for efficient liquidity allocation, it also introduce the possibility for systemic risk via financial contagion. Insolvency of one bank can propagate through interlinkages leading to insolvency of other banks. Empirical studies have shown that some interbank networks have features of scalefree networks. This work explores the characteristics of financial contagion in networks whose links distributions approaches a power law, using a deliberately simplified model that defines banks balance sheets from information of network connectivity. Varying the parameters of the network creation we obtained links distributions with different concentrations of debts and rights, creating three main network types, which were analyzed for their resilience to contagion. We also tested the effect of a variation in connectivity in conjunction with variation in concentration of links. The results suggest that more connected networks with high concentration of rights (featuring nodes that are large creditors of the system) present greater resilience to contagion. Evaluating some topological indices of systemic risk suggested in the literature, we could verify its ability to explain the impact on the system caused by the failure of a node. While it is clear the positive relationship between the indexes and the impact value for cases of greater magnitude of losses, the relationship is weaker for smaller values of impact, suggesting a lower predictive power in more resilient networks.