A Bayesian analysis of the effects of particulate matter using a human exposure simulator

Particulate air pollution has been associated with mortality in several epidemiological studies. The US EPA currently regulates PM10 and PM2.5 (mass concentration of particles less than 10 μm and 2.5 μm, respectively), but it is not clear which size of particles are most responsible for adverse heath outcomes. A current hypothesis is that ultrafine particles with diameter less than 0.1μm are particularly harmful because their small size allows them to deeply penetrate the lungs. This paper investigates the effect of exposure to particles of varying diameter on daily mortality. We propose a new dynamic factor analysis model to relate the ambient concentrations of PM10, PM2.5, and several sizes of particles with diameters ranging from 0.01 to 0.40 μm with mortality. We introduce a Bayesian model that converts ambient concentrations into simulated personal personal exposure using the EPA’s Stochastic Human Exposure and Dose Simulator, and relates simulated exposure with mortality. While no function of ambient PM levels are found to be associated with mortality, our analysis indicates that exposure to particles with diameter 0.20μm is associated with mortality.

[1]  D Hémon,et al.  Comparison of relative risks obtained in ecological and individual studies: some methodological considerations. , 1987, International journal of epidemiology.

[2]  J. Besag,et al.  Bayesian image restoration, with two applications in spatial statistics , 1991 .

[3]  D. Rubin,et al.  Inference from Iterative Simulation Using Multiple Sequences , 1992 .

[4]  D. Dockery,et al.  An association between air pollution and mortality in six U.S. cities. , 1993, The New England journal of medicine.

[5]  D. Thomas,et al.  Exposure measurement error: influence on exposure-disease. Relationships and methods of correction. , 1993, Annual review of public health.

[6]  J. Schwartz,et al.  Air pollution and daily mortality: a review and meta analysis. , 1994, Environmental research.

[7]  J. Neher,et al.  Health effects of outdoor air pollution. , 1994, American family physician.

[8]  David E. Burmaster,et al.  Residential Air Exchange Rates in the United States: Empirical and Estimated Parametric Distributions by Season and Climatic Region , 1995 .

[9]  J. Xue,et al.  Personal exposure to airborne particles and metals: results from the Particle TEAM study in Riverside, California. , 1996, Journal of exposure analysis and environmental epidemiology.

[10]  Health effects of outdoor air pollution. Part 2. Committee of the Environmental and Occupational Health Assembly of the American Thoracic Society. , 1996, American journal of respiratory and critical care medicine.

[11]  Michael A. West,et al.  Bayesian Forecasting and Dynamic Models (2nd edn) , 1997, J. Oper. Res. Soc..

[12]  F P Wheeler,et al.  Bayesian Forecasting and Dynamic Models (2nd edn) , 1998, J. Oper. Res. Soc..

[13]  O. Aguilar,et al.  Bayesian Inference on Latent Structure in Time Series , 1998 .

[14]  W G Kreyling,et al.  Daily mortality and fine and ultrafine particles in Erfurt, Germany part I: role of particle number and particle mass. , 2000, Research report.

[15]  M. West,et al.  Bayesian Dynamic Factor Models and Portfolio Allocation , 2000 .

[16]  P. Lawless,et al.  Characterization of Indoor-Outdoor Aerosol Concentration Relationships during the Fresno PM Exposure Studies , 2001 .

[17]  J. Burke,et al.  A population exposure model for particulate matter: case study results for PM2.5 in Philadelphia, PA , 2001, Journal of Exposure Analysis and Environmental Epidemiology.

[18]  Bert Brunekreef,et al.  Particulate Air Pollution and Risk of ST-Segment Depression During Repeated Submaximal Exercise Tests Among Subjects With Coronary Heart Disease: The Exposure and Risk Assessment for Fine and Ultrafine Particles in Ambient Air (ULTRA) Study , 2002, Circulation.

[19]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[20]  J Pekkanen,et al.  Effects of fine and ultrafine particles on cardiorespiratory symptoms in elderly subjects with coronary heart disease: the ULTRA study. , 2003, American journal of epidemiology.

[21]  Melanie M Wall,et al.  Generalized common spatial factor model. , 2003, Biostatistics.

[22]  A. Peters,et al.  Daily variation in fine and ultrafine particulate air pollution and urinary concentrations of lung Clara cell protein CC16 , 2004, Occupational and Environmental Medicine.

[23]  D. Catelan,et al.  Bayesian Ecological Regression with Latent Factors: Atmospheric Pollutants Emissions and Mortality for Lung Cancer , 2005, Environmental and Ecological Statistics.

[24]  James S Hodges,et al.  Generalized spatial structural equation models. , 2005, Biostatistics.

[25]  Jon Wakefield,et al.  Health-exposure modeling and the ecological fallacy. , 2005, Biostatistics.