Estimation of Groundwater Radon in North Carolina Using Land Use Regression and Bayesian Maximum Entropy

Abstract

Radon ((222)Rn) is a naturally occurring chemically inert, colorless, and odorless radioactive gas produced from the decay of uranium ((238)U), which is ubiquitous in rocks and soils worldwide. Exposure to (222)Rn is likely the second leading cause of lung cancer after cigarette smoking via inhalation; however, exposure through untreated groundwater is also a contributing factor to both inhalation and ingestion routes. A land use regression (LUR) model for groundwater (222)Rn with anisotropic geological and (238)U based explanatory variables is developed, which helps elucidate the factors contributing to elevated (222)Rn across North Carolina. The LUR is also integrated into the Bayesian Maximum Entropy (BME) geostatistical framework to increase accuracy and produce a point-level LUR-BME model of groundwater (222)Rn across North Carolina including prediction uncertainty. The LUR-BME model of groundwater (222)Rn results in a leave-one out cross-validation r(2) of 0.46 (Pearson correlation coefficient = 0.68), effectively predicting within the spatial covariance range. Modeled results of (222)Rn concentrations show variability among intrusive felsic geological formations likely due to average bedrock (238)U defined on the basis of overlying stream-sediment (238)U concentrations that is a widely distributed consistently analyzed point-source data.

Lung and stomach cancer associations with groundwater radon in North Carolina, USA

“…Groundwater radon concentration (Bq=LÞ exposure is estimated from Messier et al, 3 which are address-level estimates of groundwater radon concentration based on a land use regression and Bayesian Maximum Entropy (LUR-BME) geostatistical model with geologically based explanatory variables. The LUR-BME model provides address-level estimates of groundwater radon concentration for individual exposure assessment, and spatial averaging of estimates provides a precise assessment of observed census tract levels (Pearson correlation ¼ 0.9; see supplementary material for more details on the LUR-BME exposure models and their validation, available as Supplementary data at IJE online).…”

“…Last, we control for all confounders including indoor air radon, smoking, public water supply, residential tenure, race, gender and age with a single full model. To utilize the address-level exposure information from the groundwater radon estimates, 3 we conduct a logistic regression analysis on lung and stomach cancer cases that are assigned a 0/1 status based on their membership in a cluster 20,22 (referred hereinafter as the cluster membership model).…”

“…where logitðMÞ is the logit link function that transforms the binary membership dependent variable M to the appropriate scale for estimation, b n are linear coefficients for the individual predictor variables X n and e is the error term. Groundwater radon at the address of the cancer case is obtained via a spatial join from the estimated address-level groundwater radon estimates of Messier et al 3 The same confounding variables are included in the logistic cluster membership model as in the incidence rate model; however, differences due to the address-level information are present, which are explained in detail in the supplementary material (available as Supplementary data at IJE online). The odds ratio (OR), or the ratio of the odds that a case is a member of a cluster when a given predictor variable is increased by one unit, is calculated for each variable by exponentiating the logistic regression model coefficient.…”

“…Radon is a naturally occurring radioactive gas and human carcinogen found in the groundwater drinking supply and indoor air across the world. Countries with documented groundwater radon occurrence include the USA, [1][2][3] Finland, 4 Belgium, 5 Italy 6 and many other European countries. 7 The carcinogenic risk associated with radon exposure is due to its radioactive decay and emission of high energy alpha decay particles (a-decay); 8,9 thus when referring to radon, it is generally understood to be radon and its associated a-decay.…”

“…North Carolina contains geological features commonly associated with elevated radon and has many areas across the state with high concentration of radon in the groundwater. 3 Additionally, Messier et al 3 recently provided a geologically based land use regression and Bayesian Maximum Entropy (LUR-BME) model to spatially estimate groundwater radon, affording the possibility to quantify exposure across the state at a fine resolution not previously possible with other models of groundwater radon exposure. Lastly, state-wide lung cancer incidence rates are higher than the national average for 2007-11 (72.7 versus 64.9 per 100 000 person-years) and near the national average for stomach cancer (6.7 versus 6.3 per 100 000 person-years).…”