Reliability of methods used for the risk assessment of mixture of micropollutants in aquatic enviromments : from theoretical concepts to field observations

Ces dernières années, de nombreuses recherches ont mis en évidence les effets toxiques des micropolluants organiques pour les espèces de nos lacs et rivières. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, alors que les organismes sont exposés tous les jours à des milliers de substances en mélange. Or les effets de ces cocktails ne sont pas négligeables. Cette thèse de doctorat s'est ainsi intéressée aux modèles permettant de prédire le risque environnemental de ces cocktails pour le milieu aquatique. Le principal objectif a été d'évaluer le risque écologique des mélanges de substances chimiques mesurées dans le Léman, mais aussi d'apporter un regard critique sur les méthodologies utilisées afin de proposer certaines adaptations pour une meilleure estimation du risque. Dans la première partie de ce travail, le risque des mélanges de pesticides et médicaments pour le Rhône et pour le Léman a été établi en utilisant des approches envisagées notamment dans la législation européenne. Il s'agit d'approches de « screening », c'est-à-dire permettant une évaluation générale du risque des mélanges. Une telle approche permet de mettre en évidence les substances les plus problématiques, c'est-à-dire contribuant le plus à la toxicité du mélange. Dans notre cas, il s'agit essentiellement de 4 pesticides. L'étude met également en évidence que toutes les substances, même en trace infime, contribuent à l'effet du mélange. Cette constatation a des implications en terme de gestion de l'environnement. En effet, ceci implique qu'il faut réduire toutes les sources de polluants, et pas seulement les plus problématiques. Mais l'approche proposée présente également un biais important au niveau conceptuel, ce qui rend son utilisation discutable, en dehors d'un screening, et nécessiterait une adaptation au niveau des facteurs de sécurité employés. Dans une deuxième partie, l'étude s'est portée sur l'utilisation des modèles de mélanges dans le calcul de risque environnemental. En effet, les modèles de mélanges ont été développés et validés espèce par espèce, et non pour une évaluation sur l'écosystème en entier. Leur utilisation devrait donc passer par un calcul par espèce, ce qui est rarement fait dû au manque de données écotoxicologiques à disposition. Le but a été donc de comparer, avec des valeurs générées aléatoirement, le calcul de risque effectué selon une méthode rigoureuse, espèce par espèce, avec celui effectué classiquement où les modèles sont appliqués sur l'ensemble de la communauté sans tenir compte des variations inter-espèces. Les résultats sont dans la majorité des cas similaires, ce qui valide l'approche utilisée traditionnellement. En revanche, ce travail a permis de déterminer certains cas où l'application classique peut conduire à une sous- ou sur-estimation du risque. Enfin, une dernière partie de cette thèse s'est intéressée à l'influence que les cocktails de micropolluants ont pu avoir sur les communautés in situ. Pour ce faire, une approche en deux temps a été adoptée. Tout d'abord la toxicité de quatorze herbicides détectés dans le Léman a été déterminée. Sur la période étudiée, de 2004 à 2009, cette toxicité due aux herbicides a diminué, passant de 4% d'espèces affectées à moins de 1%. Ensuite, la question était de savoir si cette diminution de toxicité avait un impact sur le développement de certaines espèces au sein de la communauté des algues. Pour ce faire, l'utilisation statistique a permis d'isoler d'autres facteurs pouvant avoir une influence sur la flore, comme la température de l'eau ou la présence de phosphates, et ainsi de constater quelles espèces se sont révélées avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps. Fait intéressant, une partie d'entre-elles avait déjà montré des comportements similaires dans des études en mésocosmes. En conclusion, ce travail montre qu'il existe des modèles robustes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques, et qu'ils peuvent être utilisés pour expliquer le rôle des substances dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application. - Depuis plusieurs années, les risques que posent les micropolluants organiques pour le milieu aquatique préoccupent grandement les scientifiques ainsi que notre société. En effet, de nombreuses recherches ont mis en évidence les effets toxiques que peuvent avoir ces substances chimiques sur les espèces de nos lacs et rivières, quand elles se retrouvent exposées à des concentrations aiguës ou chroniques. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, c'est à dire considérées séparément. Actuellement, il en est de même dans les procédures de régulation européennes, concernant la partie évaluation du risque pour l'environnement d'une substance. Or, les organismes sont exposés tous les jours à des milliers de substances en mélange, et les effets de ces "cocktails" ne sont pas négligeables. L'évaluation du risque écologique que pose ces mélanges de substances doit donc être abordé par de la manière la plus appropriée et la plus fiable possible. Dans la première partie de cette thèse, nous nous sommes intéressés aux méthodes actuellement envisagées à être intégrées dans les législations européennes pour l'évaluation du risque des mélanges pour le milieu aquatique. Ces méthodes sont basées sur le modèle d'addition des concentrations, avec l'utilisation des valeurs de concentrations des substances estimées sans effet dans le milieu (PNEC), ou à partir des valeurs des concentrations d'effet (CE50) sur certaines espèces d'un niveau trophique avec la prise en compte de facteurs de sécurité. Nous avons appliqué ces méthodes à deux cas spécifiques, le lac Léman et le Rhône situés en Suisse, et discuté les résultats de ces applications. Ces premières étapes d'évaluation ont montré que le risque des mélanges pour ces cas d'étude atteint rapidement une valeur au dessus d'un seuil critique. Cette valeur atteinte est généralement due à deux ou trois substances principales. Les procédures proposées permettent donc d'identifier les substances les plus problématiques pour lesquelles des mesures de gestion, telles que la réduction de leur entrée dans le milieu aquatique, devraient être envisagées. Cependant, nous avons également constaté que le niveau de risque associé à ces mélanges de substances n'est pas négligeable, même sans tenir compte de ces substances principales. En effet, l'accumulation des substances, même en traces infimes, atteint un seuil critique, ce qui devient plus difficile en terme de gestion du risque. En outre, nous avons souligné un manque de fiabilité dans ces procédures, qui peuvent conduire à des résultats contradictoires en terme de risque. Ceci est lié à l'incompatibilité des facteurs de sécurité utilisés dans les différentes méthodes. Dans la deuxième partie de la thèse, nous avons étudié la fiabilité de méthodes plus avancées dans la prédiction de l'effet des mélanges pour les communautés évoluant dans le système aquatique. Ces méthodes reposent sur le modèle d'addition des concentrations (CA) ou d'addition des réponses (RA) appliqués sur les courbes de distribution de la sensibilité des espèces (SSD) aux substances. En effet, les modèles de mélanges ont été développés et validés pour être appliqués espèce par espèce, et non pas sur plusieurs espèces agrégées simultanément dans les courbes SSD. Nous avons ainsi proposé une procédure plus rigoureuse, pour l'évaluation du risque d'un mélange, qui serait d'appliquer d'abord les modèles CA ou RA à chaque espèce séparément, et, dans une deuxième étape, combiner les résultats afin d'établir une courbe SSD du mélange. Malheureusement, cette méthode n'est pas applicable dans la plupart des cas, car elle nécessite trop de données généralement indisponibles. Par conséquent, nous avons comparé, avec des valeurs générées aléatoirement, le calcul de risque effectué selon cette méthode plus rigoureuse, avec celle effectuée traditionnellement, afin de caractériser la robustesse de cette approche qui consiste à appliquer les modèles de mélange sur les courbes SSD. Nos résultats ont montré que l'utilisation de CA directement sur les SSDs peut conduire à une sous-estimation de la concentration du mélange affectant 5 % ou 50% des espèces, en particulier lorsque les substances présentent un grand écart- type dans leur distribution de la sensibilité des espèces. L'application du modèle RA peut quant à lui conduire à une sur- ou sous-estimations, principalement en fonction de la pente des courbes dose- réponse de chaque espèce composant les SSDs. La sous-estimation avec RA devient potentiellement importante lorsque le rapport entre la EC50 et la EC10 de la courbe dose-réponse des espèces est plus petit que 100. Toutefois, la plupart des substances, selon des cas réels, présentent des données d' écotoxicité qui font que le risque du mélange calculé par la méthode des modèles appliqués directement sur les SSDs reste cohérent et surestimerait plutôt légèrement le risque. Ces résultats valident ainsi l'approche utilisée traditionnellement. Néanmoins, il faut garder à l'esprit cette source d'erreur lorsqu'on procède à une évaluation du risque d'un mélange avec cette méthode traditionnelle, en particulier quand les SSD présentent une distribution des données en dehors des limites déterminées dans cette étude. Enfin, dans la dernière partie de cette thèse, nous avons confronté des prédictions de l'effet de mélange avec des changements biologiques observés dans l'environnement. Dans cette étude, nous avons utilisé des données venant d'un suivi à long terme d'un grand lac européen, le lac Léman, ce qui offrait la possibilité d'évaluer dans quelle mesure la prédiction de la toxicité des mélanges d'herbicide expliquait les changements dans la composition de la communauté phytoplanctonique. Ceci à côté d'autres paramètres classiques de limnologie tels que les nutriments. Pour atteindre cet objectif, nous avons déterminé la toxicité des mélanges sur plusieurs années de 14 herbicides régulièrement détectés dans le lac, en utilisant les modèles CA et RA avec les courbes de distribution de la sensibilité des espèces. Un gradient temporel de toxicité décroissant a pu être constaté de 2004 à 2009. Une analyse de redondance et de redondance partielle, a montré que ce gradient explique une partie significative de la variation de la composition de la communauté phytoplanctonique, même après avoir enlevé l'effet de toutes les autres co-variables. De plus, certaines espèces révélées pour avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps, ont montré des comportements similaires dans des études en mésocosmes. On peut en conclure que la toxicité du mélange herbicide est l'un des paramètres clés pour expliquer les changements de phytoplancton dans le lac Léman. En conclusion, il existe diverses méthodes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques et celui-ci peut jouer un rôle dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application, avant d'utiliser leurs résultats pour la gestion des risques environnementaux. - For several years now, the scientists as well as the society is concerned by the aquatic risk organic micropollutants may pose. Indeed, several researches have shown the toxic effects these substances may induce on organisms living in our lakes or rivers, especially when they are exposed to acute or chronic concentrations. However, most of the studies focused on the toxicity of single compounds, i.e. considered individually. The same also goes in the current European regulations concerning the risk assessment procedures for the environment of these substances. But aquatic organisms are typically exposed every day simultaneously to thousands of organic compounds. The toxic effects resulting of these "cocktails" cannot be neglected. The ecological risk assessment of mixtures of such compounds has therefore to be addressed by scientists in the most reliable and appropriate way. In the first part of this thesis, the procedures currently envisioned for the aquatic mixture risk assessment in European legislations are described. These methodologies are based on the mixture model of concentration addition and the use of the predicted no effect concentrations (PNEC) or effect concentrations (EC50) with assessment factors. These principal approaches were applied to two specific case studies, Lake Geneva and the River Rhône in Switzerland, including a discussion of the outcomes of such applications. These first level assessments showed that the mixture risks for these studied cases exceeded rapidly the critical value. This exceeding is generally due to two or three main substances. The proposed procedures allow therefore the identification of the most problematic substances for which management measures, such as a reduction of the entrance to the aquatic environment, should be envisioned. However, it was also showed that the risk levels associated with mixtures of compounds are not negligible, even without considering these main substances. Indeed, it is the sum of the substances that is problematic, which is more challenging in term of risk management. Moreover, a lack of reliability in the procedures was highlighted, which can lead to contradictory results in terms of risk. This result is linked to the inconsistency in the assessment factors applied in the different methods. In the second part of the thesis, the reliability of the more advanced procedures to predict the mixture effect to communities in the aquatic system were investigated. These established methodologies combine the model of concentration addition (CA) or response addition (RA) with species sensitivity distribution curves (SSD). Indeed, the mixture effect predictions were shown to be consistent only when the mixture models are applied on a single species, and not on several species simultaneously aggregated to SSDs. Hence, A more stringent procedure for mixture risk assessment is proposed, that would be to apply first the CA or RA models to each species separately and, in a second step, to combine the results to build an SSD for a mixture. Unfortunately, this methodology is not applicable in most cases, because it requires large data sets usually not available. Therefore, the differences between the two methodologies were studied with datasets created artificially to characterize the robustness of the traditional approach applying models on species sensitivity distribution. The results showed that the use of CA on SSD directly might lead to underestimations of the mixture concentration affecting 5% or 50% of species, especially when substances present a large standard deviation of the distribution from the sensitivity of the species. The application of RA can lead to over- or underestimates, depending mainly on the slope of the dose-response curves of the individual species. The potential underestimation with RA becomes important when the ratio between the EC50 and the EC10 for the dose-response curve of the species composing the SSD are smaller than 100. However, considering common real cases of ecotoxicity data for substances, the mixture risk calculated by the methodology applying mixture models directly on SSDs remains consistent and would rather slightly overestimate the risk. These results can be used as a theoretical validation of the currently applied methodology. Nevertheless, when assessing the risk of mixtures, one has to keep in mind this source of error with this classical methodology, especially when SSDs present a distribution of the data outside the range determined in this study Finally, in the last part of this thesis, we confronted the mixture effect predictions with biological changes observed in the environment. In this study, long-term monitoring of a European great lake, Lake Geneva, provides the opportunity to assess to what extent the predicted toxicity of herbicide mixtures explains the changes in the composition of the phytoplankton community next to other classical limnology parameters such as nutrients. To reach this goal, the gradient of the mixture toxicity of 14 herbicides regularly detected in the lake was calculated, using concentration addition and response addition models. A decreasing temporal gradient of toxicity was observed from 2004 to 2009. Redundancy analysis and partial redundancy analysis showed that this gradient explains a significant portion of the variation in phytoplankton community composition, even when having removed the effect of all other co-variables. Moreover, some species that were revealed to be influenced positively or negatively, by the decrease of toxicity in the lake over time, showed similar behaviors in mesocosms studies. It could be concluded that the herbicide mixture toxicity is one of the key parameters to explain phytoplankton changes in Lake Geneva. To conclude, different methods exist to predict the risk of mixture in the ecosystems. But their reliability varies depending on the underlying hypotheses. One should therefore carefully consider these hypotheses, as well as the limits of the approaches, before using the results for environmental risk management

Objective Sleep Structure and Cardiovascular Risk Factors in the General Population: The HypnoLaus Study.

STUDY OBJECTIVES: To evaluate the association between objective sleep measures and metabolic syndrome (MS), hypertension, diabetes, and obesity. DESIGN: Cross-sectional study. SETTING: General population sample. PARTICIPANTS: There were 2,162 patients (51.2% women, mean age 58.4 ± 11.1). INTERVENTIONS: Patients were evaluated for hypertension, diabetes, overweight/obesity, and MS, and underwent a full polysomnography (PSG). MEASUREMENTS AND RESULTS: PSG measured variables included: total sleep time (TST), percentage and time spent in slow wave sleep (SWS) and in rapid eye movement (REM) sleep, sleep efficiency and arousal index (ArI). In univariate analyses, MS was associated with decreased TST, SWS, REM sleep, and sleep efficiency, and increased ArI. After adjustment for age, sex, smoking, alcohol, physical activity, drugs that affect sleep and depression, the ArI remained significantly higher, but the difference disappeared in patients without significant sleep disordered breathing (SDB). Differences in sleep structure were also found according to the presence or absence of hypertension, diabetes, and overweight/obesity in univariate analysis. However, these differences were attenuated after multivariate adjustment and after excluding subjects with significant SDB. CONCLUSIONS: In this population-based sample we found significant associations between sleep structure and MS, hypertension, diabetes, and obesity. However, these associations were cancelled after multivariate adjustment. We conclude that normal variations in sleep contribute little if any to MS and associated disorders.

Piercing among adolescents: body art as risk marker.

PURPOSE: To ascertain the prevalence of piercing among a nationally representative sample of adolescents; to assess whether having a piercing is a marker for risk behaviors; and to determine whether having more than one piercing is a cumulative marker for risk behaviors. METHODS: Data were drawn from a cross-sectional survey of a nationally representative sample of adolescents aged 16 to 20 years (N=7548). Controlling for background variables, pierced and non-pierced youth were compared on risk behaviors related to drug use, sexual behavior, and suicide. In a second step, adolescents having one piercing were compared with those having more than one. In both cases, statistically significant variables in the bivariate analysis were included in a logistic regression. Analyses were conducted separately by gender. RESULTS: Overall, 20.2% of our sample had a piercing (excluding earlobes), and it was significantly more prevalent among females than among males (33.8% vs. 7.4%; P<.001). In the bivariate analysis, all risk behaviors were significantly associated with having a piercing, and most of them remained significant in the multivariate analysis. One third of pierced subjects had more than one piercing, with no gender difference in prevalence. In the multivariate analysis, females with more than one piercing were more likely to have had multiple partners and to use cannabis, while no differences were noted for males. CONCLUSIONS: Body piercing is becoming popular among Swiss adolescents, especially females. Having a body piercing seems to be a risk marker for risk behaviors. Moreover, having multiple piercings is a cumulative risk marker for females.

A multicenter, cross-sectional study on the prevalence and risk factors for nasal colonization with Staphylococcus aureus in patients admitted to children's hospitals in Switzerland.

The rate of nasal carriage of Staphylococcus aureus and associated risk factors were determined in a cross-sectional study involving Swiss children's hospitals. S. aureus was isolated in 562 of 1363 cases. In a stepwise multivariate analysis, the variables age, duration of antibiotic use, and hospitalization of a household member were independently associated with carriage of S. aureus.

Risk adjustment in Switzerland

In Switzerland the new law on Health Insurance, effective since 1996, introduced pro competitive changes in the market of sickness funds. The legislator expected high mobility between sickness funds of both healthy and sick insured as open enrolment was introduced with the new law. That is why the risk adjustment scheme, that was already introduced 1993, was limited until 2005. However, consumer mobility remained low and risk selection strategies are still profitable, since risk-adjustment is based only on demographic variables. This paper describes risk adjustment, consumer mobility, risk selection activities of sickness funds and the impact of imperfect risk adjustment on the development of HMO and PPO models. The paper concludes with a description of the current political and scientific discussion in Switzerland.

Using register data to assess the impact of response enhancement methods on the risk of nonresponse bias and survey costs

The pursuit of high response rates to minimise the threat of nonresponse bias continues to dominate decisions about resource allocation in survey research. Yet a growing body of research has begun to question this practice. In this study, we use previously unavailable data from a new sampling frame based on population registers to assess the value of different methods designed to increase response rates on the European Social Survey in Switzerland. Using sampling data provides information about both respondents and nonrespondents, making it possible to examine how changes in response rates resulting from the use of different fieldwork methods relate to changes in the composition and representativeness of the responding sample. We compute an R-indicator to assess representativity with respect to the sampling register variables, and find little improvement in the sample composition as response rates increase. We then examine the impact of response rate increases on the risk of nonresponse bias based on Maximal Absolute Bias (MAB), and coefficients of variation between subgroup response rates, alongside the associated costs of different types of fieldwork effort. The results show that increases in response rate help to reduce MAB, while only small but important improvements to sample representativity are gained by varying the type of effort. These findings lend further support to research that has called into question the value of extensive investment in procedures aimed at reaching response rate targets and the need for more tailored fieldwork strategies aimed both at reducing survey costs and minimising the risk of bias.

Serum resistin concentrations and risk of new onset heart failure in older persons: the health, aging, and body composition (Health ABC) study.

OBJECTIVE: Resistin is associated with inflammation and insulin resistance and exerts direct effects on myocardial cells including hypertrophy and altered contraction. We investigated the association of serum resistin concentrations with risk for incident heart failure (HF) in humans. METHODS AND RESULTS: We studied 2902 older persons without prevalent HF (age, 73.6+/-2.9 years; 48.1% men; 58.8% white) enrolled in the Health, Aging, and Body Composition (Health ABC) Study. Correlation between baseline serum resistin concentrations (20.3+/-10.0 ng/mL) and clinical variables, biochemistry panel, markers of inflammation and insulin resistance, adipocytokines, and measures of adiposity was weak (all rho <0.25). During a median follow-up of 9.4 years, 341 participants (11.8%) developed HF. Resistin was strongly associated with risk for incident HF in Cox proportional hazards models controlling for clinical variables, biomarkers, and measures of adiposity (HR, 1.15 per 10.0 ng/mL in adjusted model; 95% CI, 1.05 to 1.27; P=0.003). Results were comparable across sex, race, diabetes mellitus, and prevalent and incident coronary heart disease subgroups. In participants with available left ventricular ejection fraction at HF diagnosis (265 of 341; 77.7%), association of resistin with HF risk was comparable for cases with reduced versus preserved ejection fraction. CONCLUSIONS: Serum resistin concentrations are independently associated with risk for incident HF in older persons.

Assessing the associations between mental disorders, cardiovascular risk factors, and cardiovascular disease : the CoLaus/PsyCoLaus study

Background: Cardio-vascular diseases (CVD), their well established risk factors (CVRF) and mental disorders are common and co-occur more frequently than would be expected by chance. However, the pathogenic mechanisms and course determinants of both CVD and mental disorders have only been partially identified.Methods/Design: Comprehensive follow-up of CVRF and CVD with a psychiatric exam in all subjects who participated in the baseline cross-sectional CoLaus study (2003-2006) (n=6'738) which also included a comprehensive genetic assessment. The somatic investigation will include a shortened questionnaire on CVRF, CV events and new CVD since baseline and measurements of the same clinical and biological variables as at baseline. In addition, pro-inflammatory markers, persistent pain and sleep patterns and disorders will be assessed. In the case of a new CV event, detailed information will be abstracted from medical records. Similarly, data on the cause of death will be collected from the Swiss National Death Registry. The comprehensive psychiatric investigation of the CoLaus/PsyCoLaus study will use contemporary epidemiological methods including semi-structured diagnostic interviews, experienced clinical interviewers, standardized diagnostic criteria including threshold according to DSM-IV and sub-threshold syndromes and supplementary information on risk and protective factors for disorders. In addition, screening for objective cognitive impairment will be performed in participants older than 65 years.Discussion: The combined CoLaus/PsyCoLaus sample provides a unique opportunity to obtain prospective data on the interplay between CVRF/CVD and mental disorders, overcoming limitations of previous research by bringing together a comprehensive investigation of both CVRF and mental disorders as well as a large number of biological variables and a genome-wide genetic assessment in participants recruited from the general population.

School burnout in adolescents : Differences in background variables and exploration of school-related stress at the end of compulsory schooling

The aim of this study is to contribute to a better understanding of the risk factors associated with school burnout, which has recently been described as a syndrome of emotional exhaustion due to school demands, cynical and detached attitude towards school and feelings of inadequacy as a student (Salmela-Aro, Kiuru, Pietikainen & Jokela, 2008a). The research focuses on students in the last years of compulsory schooling, period in which burnout has not received much attention yet. A total of 342 adolescents (Mean age = 14.84) were asked to complete questionnaires about school burnout, school-related stress and background variables. The results showed differences in school burnout by gender, grade level and school track, with girls, last grade of compulsory school and high-track classes, showing the highest scores. No difference was observed with respect to grade retention. Several types of school stress were identified, with stress type Success related to pressures to succeed and concerns about the academic future being the highest. Finally, stress and burnout were strongly and positively correlated, and the type of stress Success was the best predictor of overall Burnout, Exhaustion and Inadequacy dimension scores. The results are discussed in relation to their theoretical relevance and implications for the prevention of school burnout in adolescents.

Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: a test with plants in an arid environment

Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

At-risk drinking and drug use among patients seeking care in an emergency department.

OBJECTIVE: This study reports the frequency of alcohol use and associated tobacco and drug use among emergency department (ED) patients, in order to increase physician awareness and treatment of women and men seeking care in ED settings. METHOD: All adults seen in the ED at the University Hospital in Lausanne, Switzerland, between 11 AM and 11 PM were screened by direct interview for at-risk drinking, tobacco use, drug use, and depression during an 18-month period. RESULTS: A total of 8,599 patients (4,006 women and 4,593 men) participated in the screening procedure and provided full data on the variables in our analysis. The mean age was 51.9 years for women and 45.0 years for men; 57.5% (n = 2,304) of women and 58.5% (n = 2,688) of men were being treated for trauma. Based on guidelines of the National Institute on Alcohol Abuse and Alcoholism, 13.1% (n = 523) of the women were at-risk drinkers, 57.3% (n = 2,301) were low-risk drinkers, and 29.6% (n = 1,182) were abstinent. Among men, 32.8% (n = 1,507) met criteria for at-risk drinking, 51.8% (n = 2,380) met criteria for low-risk drinking, and 15.4% (n = 706) were abstinent. Younger individuals (ages 18-30) had significantly higher rates of episodic heavy drinking episodes, whereas at-risk older patients were more likely to drink on a daily basis. A binary model found that women and men who drank at at-risk levels are more likely to use tobacco (odds ratio [OR] = 2.48, 95% confidence interval [CI]: 2.0-3.08) and illicit drugs (OR = 5.91, CI: 3.32- 10.54) compared with abstinent and low-risk drinkers. CONCLUSIONS: This study supports systematic alcohol screening of women and men seen in EDs and suggests that patterns of alcohol and drug use vary by age and gender.

Use of niche models in invasive species risk assessments.

Risk maps summarizing landscape suitability of novel areas for invading species can be valuable tools for preventing species' invasions or controlling their spread, but methods employed for development of such maps remain variable and unstandardized. We discuss several considerations in development of such models, including types of distributional information that should be used, the nature of explanatory variables that should be incorporated, and caveats regarding model testing and evaluation. We highlight that, in the case of invasive species, such distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using (1) all distributional information available, including information from both the native range and other invaded regions; (2) predictors linked as directly as is feasible to the physiological requirements of the species; and (3) modelling procedures that carefully avoid overfitting to the training data. Finally, model testing and evaluation should focus on well-predicted presences, and less on efficient prediction of absences; a k-fold regional cross-validation test is discussed.

Lung Function and Risk for Heart Failure Among Older Adults: The Health ABC Study.

BACKGROUND: The impact of abnormal spirometric findings on risk for incident heart failure among older adults without clinically apparent lung disease is not well elucidated.METHODS: We evaluated the association of baseline lung function with incident heart failure, defined as first hospitalization for heart failure, in 2125 participants of the community-based Health, Aging, and Body Composition (Health ABC) Study (age, 73.6 +/- 2.9 years; 50.5% men; 62.3% white; 37.7% black) without prevalent lung disease or heart failure. Abnormal lung function was defined either as forced vital capacity (FVC) or forced expiratory volume in 1(st) second (FEV1) to FVC ratio below lower limit of normal. Percent predicted FVC and FEV1 also were assessed as continuous variables.RESULTS: During follow-up (median, 9.4 years), heart failure developed in 68 of 350 (19.4%) participants with abnormal baseline lung function, as compared with 172 of 1775 (9.7%) participants with normal lung function (hazard ratio [HR] 2.31; 95% confidence interval [CI], 1.74-3.07; P <.001). This increased risk persisted after adjusting for previously identified heart failure risk factors in the Health ABC Study, body mass index, incident coronary heart disease, and inflammatory markers (HR 1.83; 95% CI, 1.33-2.50; P <.001). Percent predicted (%) FVC and FEV 1 had a linear association with heart failure risk (HR 1.21; 95% CI, 1.11-1.32 and 1.18; 95% CI, 1.10-1.26, per 10% lower % FVC and % FEV1, respectively; both P <.001 in fully adjusted models). Findings were consistent in sex and race subgroups and for heart failure with preserved or reduced ejection fraction.CONCLUSIONS: Abnormal spirometric findings in older adults without clinical lung disease are associated with increased heart failure risk. (C) 2011 Elsevier Inc. All rights reserved. The American Journal of Medicine (2011) 124, 334-341

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Premenopausal serum androgens and breast cancer risk: a nested case-control study.

ABSTRACT: INTRODUCTION: Prospective epidemiologic studies have consistently shown that levels of circulating androgens in postmenopausal women are positively associated with breast cancer risk. However, data in premenopausal women are limited. METHODS: A case-control study nested within the New York University Women's Health Study was conducted. A total of 356 cases (276 invasive and 80 in situ) and 683 individually-matched controls were included. Matching variables included age and date, phase, and day of menstrual cycle at blood donation. Testosterone, androstenedione, dehydroandrosterone sulfate (DHEAS) and sex hormone-binding globulin (SHBG) were measured using direct immunoassays. Free testosterone was calculated. RESULTS: Premenopausal serum testosterone and free testosterone concentrations were positively associated with breast cancer risk. In models adjusted for known risk factors of breast cancer, the odds ratios for increasing quintiles of testosterone were 1.0 (reference), 1.5 (95% confidence interval (CI), 0.9 to 2.3), 1.2 (95% CI, 0.7 to 1.9), 1.4 (95% CI, 0.9 to 2.3) and 1.8 (95% CI, 1.1 to 2.9; Ptrend = 0.04), and for free testosterone were 1.0 (reference), 1.2 (95% CI, 0.7 to 1.8), 1.5 (95% CI, 0.9 to 2.3), 1.5 (95% CI, 0.9 to 2.3), and 1.8 (95% CI, 1.1 to 2.8, Ptrend = 0.01). A marginally significant positive association was observed with androstenedione (P = 0.07), but no association with DHEAS or SHBG. Results were consistent in analyses stratified by tumor type (invasive, in situ), estrogen receptor status, age at blood donation, and menopausal status at diagnosis. Intra-class correlation coefficients for samples collected from 0.8 to 5.3 years apart (median 2 years) in 138 cases and 268 controls were greater than 0.7 for all biomarkers except for androstenedione (0.57 in controls). CONCLUSIONS: Premenopausal concentrations of testosterone and free testosterone are associated with breast cancer risk. Testosterone and free testosterone measurements are also highly reliable (that is, a single measurement is reflective of a woman's average level over time). Results from other prospective studies are consistent with our results. The impact of including testosterone or free testosterone in breast cancer risk prediction models for women between the ages of 40 and 50 years should be assessed. Improving risk prediction models for this age group could help decision making regarding both screening and chemoprevention of breast cancer.