Biomaterial Database

Empirical Bayes and adjusted estimates approach to estimating the relation of mortality to exposure of PM(10). 2005

Alain Le Tertre, and Joel Schwartz, and Giota Touloumi

InVS, Environmental Health Unit, Saint-Maurice Cedex, France. a.letertre@invs.sante.fr

In the framework of the APHEIS program (Air Pollution and Health: A European Information System), a health impact assessment of air pollution in 26 European cities was performed for particles of an aerodynamic diameter less than or equal to 10 microns (PM(10)). For short-term effects, it was based on overall estimates from the APHEA-2 project (Air Pollution and Health: A European Approach). These city-specific risk assessments require city-specific concentration-response functions, raising the question of which concentration-response is most appropriate. Estimates from city-specific models are more specific, but have greater uncertainty than those provided from multicity analyses. We compared several estimates derived from the city-specific analyses in cities that were part of the APHEA-2 project, as well as in a city that was not included in APHEA-2 but was part of the APHEIS project. These estimates were: the estimates from a local regression model, the adjusted estimates based on two significant effect modifiers identified through meta-regression models, and the city-specific empirical Bayes (shrunken) estimates and their underlying distribution. The shrunken and adjusted estimates were used to improve the estimation of city-specific concentration-response function. From these different estimates, attributable numbers of deaths per year were calculated. The advantages and limits of the different approaches are discussed through real data and in a simulation study.

UI	MeSH Term	Description	Entries
D010316	Particle Size	Relating to the size of solids.	Particle Sizes,Size, Particle,Sizes, Particle
D004781	Environmental Exposure	The exposure to potentially harmful chemical, physical, or biological agents in the environment or to environmental factors that may include ionizing radiation, pathogenic organisms, or toxic chemicals.	Exposure, Environmental,Environmental Exposures,Exposures, Environmental
D004782	Environmental Health	The science of controlling or modifying those conditions, influences, or forces surrounding man which relate to promoting, establishing, and maintaining health.	Environmental Health Science,Health, Environmental,Environmental Health Sciences,Environmental Healths,Health Science, Environmental,Health Sciences, Environmental,Healths, Environmental,Science, Environmental Health,Sciences, Environmental Health
D005060	Europe	The continent north of AFRICA, west of ASIA and east of the ATLANTIC OCEAN.	Northern Europe,Southern Europe,Western Europe
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000393	Air Pollutants	Any substance in the air which could, if present in high enough concentration, harm humans, animals, vegetation or materials. Substances include GASES; PARTICULATE MATTER; and volatile ORGANIC CHEMICALS.	Air Pollutant,Air Pollutants, Environmental,Environmental Air Pollutants,Environmental Pollutants, Air,Air Environmental Pollutants,Pollutant, Air,Pollutants, Air,Pollutants, Air Environmental,Pollutants, Environmental Air
D001499	Bayes Theorem	A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.	Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D018570	Risk Assessment	The qualitative or quantitative estimation of the likelihood of adverse effects that may result from exposure to specified health hazards or from the absence of beneficial influences. (Last, Dictionary of Epidemiology, 1988)	Assessment, Risk,Benefit-Risk Assessment,Risk Analysis,Risk-Benefit Assessment,Health Risk Assessment,Risks and Benefits,Analysis, Risk,Assessment, Benefit-Risk,Assessment, Health Risk,Assessment, Risk-Benefit,Benefit Risk Assessment,Benefit-Risk Assessments,Benefits and Risks,Health Risk Assessments,Risk Analyses,Risk Assessment, Health,Risk Assessments,Risk Benefit Assessment,Risk-Benefit Assessments