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Effect of housing factors and surficial uranium on the spatial prediction of residential radon in Iowa.
Environmetrics 2007 Aug; 18(5):481-497
Growing epidemiologic evidence suggests that residential radon is an important risk factor for lung cancer. Consequently, public health professionals have expressed interest in characterizing the spatial distribution of radon concentrations in order to identify geographic regions of high exposure. Ambient radon concentrations are a function of geologic features including soil radium content. Indoor radon concentrations can vary based on building characteristics that affect the entry of radon into the building and movement between rooms therein. We present a geostatistical hierarchical Bayesian model for radon that allows for spatial prediction based on geologic data and housing characteristics. Our model is applied to radon data from an epidemiologic study in Iowa that consist of 136 outdoor measurements and 2590 indoor measurements from 614 residential homes. Housing characteristics collected in the Iowa Study are included as predictors in the model. Geologic data in the form of county-average surficial uranium concentrations from the USGS National Uranium Resource Evaluation project are also considered. A 'change of support' approach is implemented to combine the radon measurements, collected at points in space, and the uranium concentrations, averaged over counties, so that point-source concentrations for the latter are available for the analysis. Estimates of the effect of select housing factors on radon are provided along with spatial maps of predicted radon concentrations in Iowa.
Environmental-exposure; Exposure-levels; Exposure-limits; Risk-factors; Lung-disease; Lung-cancer; Lung; Cancer; Pulmonary-cancer; Pulmonary-disorders; Pulmonary-function; Pulmonary-system; Pulmonary-system-disorders; Spatial-perception; Models; Author Keywords: environmental exposure; hierarchical Bayesian model; Markov chain Monte Carlo simulation; radon gas; spatial statistics; uranium
Brian J. Smith, Department of Biostatistics, 200 Hawkins Drive, C22 GH, The University of Iowa, IowaCity, Iowa 52242-1009
10043-92-2; 7440-14-4; 7440-61-1
Issue of Publication
University of Iowa