Caractérisation des inégalités environnementales liées aux Hydrocarbure Aromatique Polycyclique en France : développement de méthodes de traitement des données environnementales pour la spatialisation des indicateurs d'exposition aux substances HAP

Reducing environmental exposure inequalities has become a major focus of public health efforts in France, as evidenced by the French action plans for health and the environment. The aim of this thesis is to develop an integrated approach to characterize environmental inequalities and evaluate the spatialized exposure to PAH in France.The data produced as part of the monitoring quality networks of environmental media reflect the actual contamination of the environment and the overall exposure of the populations. However they do not always provide an adequate spatial resolution to characterize environmental exposures as they are usually not assembled for this specific purpose. Statistical methods are employed to process input databases (environmental concentrations in water, air and soil) in the objective of characterizing the exposure. A multimedia model interfaced with a GIS, allows the integration of environmental variables in order to yield exposure doses related to ingestion of food, water and soil as well as atmospheric contaminants' inhalation.The methodology was applied to three Polycyclic Aromatic Hydrocarbon substances, (benzo[a]pyrene, benzo[ghi]perylene and indeno[1,2,3-cd]pyrene), in France. The results obtained, allowed to map exposure indicators and to identify areas of overexposure and characterize environmental determinants. In the context of exposure characterization, the direct spatialization of available data from environmental measurement datasets poses a certain number of methodological questions which lead to uncertainties related to the sampling and the spatial and temporal representativeness of data. These could be reduced by acquiring additional data or by constructing predictive variables for the spatial and temporal phenomena considered.Data processing algorithms and calculation of exposure carried out in this work, will be integrated in the French coordinated integrated environment and health platform-PLAINE in order to be applied on other pollutants and prioritize preventative actions.La réduction des inégalités d’exposition environnementale constitue un axe majeur en santé publique en France comme en témoignent les priorités des différents Plan Nationaux Santé Environnement (PNSE). L’objectif de cette thèse est de développer une approche intégrée pour la caractérisation des inégalités environnementales et l’évaluation de l’exposition spatialisée de la population aux HAP en France.Les données produites dans le cadre des réseaux de surveillance de la qualités des milieux environnementaux sont le reflet de la contamination réelle des milieux et de l’exposition globale des populations. Toutefois, elles ne présentent généralement pas une représentativité spatiale suffisante pour caractériser finement les expositions environnementales, ces réseaux n’ayant pas été initialement conçus dans cet objectif. Des méthodes statistiques sont développées pour traiter les bases de données d’entrée (concentrations environnementales dans l’eau, l’air et le sol) et les rendre pertinentes vis à vis des objectifs définis de caractérisation de l’exposition. Un modèle multimédia d’exposition, interfacé avec un Système d’Information Géographique pour intégrer les variables environnementales, est développé pour estimer les doses d’exposition liées à l’ingestion d’aliments, d’eau de consommation, de sol et à l’inhalation de contaminants atmosphériques. La méthodologie a été appliquée pour trois Hydrocarbures Aromatiques Polycycliques (benzo[a]pyrène, benzo[ghi]pérylène et indéno[1,2,3-cd]pyrène) sur l’ensemble du territoire français. Les résultats permettent de cartographier des indicateurs d’exposition, d’identifier les zones de surexposition et de caractériser les déterminants environnementaux. Dans une logique de caractérisation de l’exposition, la spatialisation des données issues des mesures environnementales pose un certain nombre de questions méthodologiques qui confèrent aux cartes réalisées de nombreuses incertitudes et limites relatives à l’échantillonnage et aux représentativités spatiales et temporelles des données. Celles-ci peuvent être réduites par l’acquisition de données supplémentaires et par la construction de variables prédictives des phénomènes spatiaux et temporels considérés.Les outils de traitement statistique de données développés dans le cadre de ces travaux seront intégrés dans la plateforme PLAINE pour être déclinés sur d’autres polluants en vue de prioriser les mesures de gestion à mettre en œuvre

Évaluation des risques cumulatifs en Lorraine : un cadre de travail pour caractériser les inégalités environnementales

International audienceThe study explores spatial data processing methods and the associated impact on the characterization and quantification of a combined health risk indicator at a regional scale with fine resolution. To illustrate the methodology of combining multiple publicly available data sources, we present a case study of the Lorraine region (France), where regional stakeholders were involved in the global procedures for data collection and data processing. Different indicators are developed by combining technical approaches for assessing and characterizing human health exposure to chemical substances (in soil, air and water) and noise risk factors. The results allow identification of pollutant sources, determinants of exposure, and potential hotspot areas. A test of the model’s assumptions to changes in sub-indicator spatial distribution showed the impact of data transformation on identifying more impacted areas. Cumulative risk assessment enable the combination of quantitative and qualitative evaluation of health risks by including stakeholders in the decision process, helping to define a subjective conceptual analysis framework or assumptions when uncertainties or knowledge gaps exist.Le Plan national santé environnement (PNSE) vise à prendre en compte, de façon pérenne, la santé environnementale dans les politiques publiques. Ainsi, les actions des PNSE sont développées selon deux axes structurants : • réduire les expositions responsables de pathologies à fort impact sur la santé ; • réduire les inégalités environnementales

Cumulative risk assessment in the Lorraine region : a framework to characterize environmental health inequalities

International audienceThe study explores spatial data processing methods and the associated impact on the characterization and quantification of a combined health risk indicator at a regional scale and at fine resolution. To illustrate the methodology of combining multiple publicly available data sources, we present a case study of the Lorraine region (France), where regional stakeholders were involved in the global procedures for data collection and organization. Different indicators are developed by combining technical approaches for assessing and characterizing human health exposure to chemical substances (in soil, air and water) and noise risk factors. The results permit identification of pollutant sources, determinants of exposure, and potential hotspot areas. A test of the model’s assumptions to changes in sub-indicator spatial distribution showed the impact of data transformation on identifying more impacted areas. Cumulative risk assessment permits the combination of quantitative and qualitative evaluation of health risks by including stakeholders in the decision process, helping to define a subjective conceptual analysis framework or assumptions when uncertainties or knowledge gaps operate

Smoking and Obstructive Sleep Apnea: Is There An Association between These Cardiometabolic Risk Factors?—Gender Analysis

Background and Objectives: Studies have tried to establish a relationship between Obstructive Sleep Apnea syndrome (OSA) and smoking but data still remain controversial. We aimed: 1. To evaluate the relationship between smoking and OSA; 2. To explore potential differences according to gender, and 3. To analyze the prevalence of cardiovascular disease (CVD) co-morbidities according to gender and smoking status. Materials and Methods: This retrospective study included 3791 (70.6% males) adult patients who visited a Sleep Clinic. All participants underwent nocturnal polysomnography. Daytime somnolence and insomnia were assessed by using the Epworth Sleepiness Scale (ESS) and the Athens Insomnia Scale (AIS). Ever-smokers completed the Fagerstrom Test for Nicotine Dependence (FTND). Results: OSA was confirmed in 72.1% of participants with 62.2% suffering from moderate-to-severe disease. The number of cigarettes/day, Pack/Years, and FTND were significantly higher in patients with more severe OSA. The prevalence of current smokers was higher in those without OSA or with mild disease, whereas the prevalence of former smokers was higher in moderate and severe OSA. In univariate analysis, current smokers were found to be 1.2 times more likely to have OSA compared with never and former smokers combined and former smokers 1.49 times more likely compared with never smokers. In the multiple regression analysis, after adjusting for BMI, gender, age and number of alcoholic drinks per week, smoking was not found to be significantly associated with OSA. In gender stratified multivariate analyses, no significant associations were observed. CVD co-morbidities were more frequent in more severe OSA. Hypertension, coronary disease and diabetes were more prevalent in former smokers with AHI ≥ 15, compared with current smokers, especially in men. Conclusions: Even if an independent effect of smoking on OSA was not found, the number of cigarettes/day, Pack/Years, and FTND were higher in patients with more severe OSA with more prevalent CVD co-morbidities

Smoking and Obstructive Sleep Apnea: Is There An Association between These Cardiometabolic Risk Factors?—Gender Analysis

Background and Objectives: Studies have tried to establish a relationship between Obstructive Sleep Apnea syndrome (OSA) and smoking but data still remain controversial. We aimed: 1. To evaluate the relationship between smoking and OSA; 2. To explore potential differences according to gender, and 3. To analyze the prevalence of cardiovascular disease (CVD) co-morbidities according to gender and smoking status. Materials and Methods: This retrospective study included 3791 (70.6% males) adult patients who visited a Sleep Clinic. All participants underwent nocturnal polysomnography. Daytime somnolence and insomnia were assessed by using the Epworth Sleepiness Scale (ESS) and the Athens Insomnia Scale (AIS). Ever-smokers completed the Fagerstrom Test for Nicotine Dependence (FTND). Results: OSA was confirmed in 72.1% of participants with 62.2% suffering from moderate-to-severe disease. The number of cigarettes/day, Pack/Years, and FTND were significantly higher in patients with more severe OSA. The prevalence of current smokers was higher in those without OSA or with mild disease, whereas the prevalence of former smokers was higher in moderate and severe OSA. In univariate analysis, current smokers were found to be 1.2 times more likely to have OSA compared with never and former smokers combined and former smokers 1.49 times more likely compared with never smokers. In the multiple regression analysis, after adjusting for BMI, gender, age and number of alcoholic drinks per week, smoking was not found to be significantly associated with OSA. In gender stratified multivariate analyses, no significant associations were observed. CVD co-morbidities were more frequent in more severe OSA. Hypertension, coronary disease and diabetes were more prevalent in former smokers with AHI ≥ 15, compared with current smokers, especially in men. Conclusions: Even if an independent effect of smoking on OSA was not found, the number of cigarettes/day, Pack/Years, and FTND were higher in patients with more severe OSA with more prevalent CVD co-morbidities

Developing environmental data processing methods to spatialize exposure indicators for three polycyclic aromatic hydrocarbon substances

International audienc

Characterizing environmental health inequalities with spatial environmental database, exposure model and biomonitoring measures

Environmental health inequalities have become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. The third plan (2015-2019) has highlighted that the development of a methodology to derive indicators for identifying and characterizing environmental health inequalities is a priority. At a regional scale, environmental monitoring networks are not sufficient to capture the multidimensionality of the exposure at finer resolution. In order to increase representativeness, exposure composite indicators could be built using additional available databases and statistical modeling. To tackle these objectives, the proposed methodology is to combine contaminant source and environmental concentration databases, exposure model and population biological impregnation measurements with a spatial approach. To elicit the proposed methodology we will consider a pesticide case study developed in the context of the MecoExpo study conducted in Picardy (France). Notably in this framework, topsoil concentrations are estimated using a spatial interpolation, method able to integrate topsoil concentration and pesticide deposit data. For water, concentrations are temporally interpolated with methodology that allows us to overcome the problem of under the detection limit concentrations. Then, an exposure multimedia model developed by INERIS is employed to estimate exposure dose in comparison with biological impregnations of cohort participants (neonatal meconium assays - 700 participants). Analysis’ outputs enable to build cumulative exposure indicator, identify pollutant sources and determinants of exposure and vulnerable populations. As a perspective, spatial relationships of exposure indicators, biological impregnation and health data will be estimated to identify potential factors influencing variability in disease spatial pattern in the French coordinated integrated environment and health inequality platform project

Vigabatrin-Induced Encephalopathy in a 5.5-Month-Old Girl with Infantile Spasms due to Tuberous Sclerosis

A 5.5-month-old female infant with tuberous sclerosis complex presented with infantile spasms and was treated with vigabatrin. As her condition did not improve, she was given adrenocorticotropic hormone (ACTH) intramuscularly which stopped the spasms and improved the electroencephalogram (EEG) abnormalities. However, she developed encephalopathy with apathy, drowsiness, and generalized slowing in the EEG. Discontinuation of vigabatrin quickly improved her symptoms and reversed the EEG slowing. A high index of suspicion is required in order to diagnose vigabatrin-induced encephalopathy, especially as the underlying disorders of these patients can be erroneously considered the cause of the observed encephalopathy

Characterization of Environmental Health Inequalities Due to Polyaromatic Hydrocarbon Exposure in France

Characterization of Environmental Health Inequalities Due to Polyaromatic Hydrocarbon Exposure in Franc

A Study of Blood Fatty Acids Profile in Hyperlipidemic and Normolipidemic Subjects in Association with Common PNPLA3 and ABCB1 Polymorphisms

Adiponutrin (patatin-like phospholipase domain-containing 3; PNPLA3), encoded in humans by the PNPLA3 gene, is a protein associated with lipid droplet and endoplasmic reticulum membranes, where it is apparently involved in fatty acid redistribution between triglycerides and phospholipids. A common polymorphism of PNPLA3 (I148M, rs738409), linked to increased PNPLA3 presence on lipid droplets, is a strong genetic determinant of non-alcoholic fatty liver disease (NAFLD) and of its progression. P-glycoprotein (Pgp, MDR1—multidrug resistance protein 1, ABCB1—ATP-binding cassette sub-family B member 1), encoded by the ABCB1 gene, is another membrane protein implicated in lipid homeostasis and steatosis. In the past, common ABCB1 polymorphisms have been associated with the distribution of serum lipids but not with fatty acids (FA) profiles. Similarly, data on the effect of PNPLA3 I148M polymorphism on blood FAs are scarce. In this study, a gas chromatography-flame ionization detection (GC-FID) method was optimized, allowing us to analyze twenty FAs (C14: 0, C15: 0, C15: 1, C16: 0, C16: 1, C17: 0, C17: 1, C18: 0, C18: 1cis, C18: 2cis, C20: 0, C20: 1n9, C20: 2, C20: 3n6, C20: 4n6, C20: 5, C23: 0, C24: 0, C24: 1 and C22: 6) in whole blood, based on the indirect determination of the fatty acids methyl esters (FAMES), in 62 hyperlipidemic patients and 42 normolipidemic controls. FA concentrations were then compared between the different genotypes of the rs738409 and rs2032582 (ABCB1 G2677T) polymorphisms, within and between the hyperlipidemic and normolipidemic groups. The rs738409 polymorphism appears to exert a significant effect on the distribution of blood fatty acids, in a lipidemic and fatty acid saturation state-depending manner. The effect of rs2032582 was less pronounced, but the polymorphism did appear to affect the relative distribution of blood fatty acids between hyperlipidemic patients and normolipidemic controls