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Abstract

Data from a case-control study of lung cancer and residential radon exposure con- ducted in Worcester County, Massachusetts, are presented. Lung cancer risk was estimated using conditional logistic regression models that controlled for demographic, smoking, and occupational exposure covariates. Preliminary exploratory analyses using lowess smoothing revealed a non-linear association between exposure and the log odds of lung cancer. Radon exposure was considered by using linear spline terms in order to model this nonlinearity. The best fit of this linear spline model to these data predicted a shift from a positive to a negative slope in the log-odds of lung cancer at a radon concentration of 70 Bq m-3. A statistically significant decrease in cancer risk with increased exposure was found for values ≤ 157 Bq m-3 normalized to the reference exposure of 4.4 Bq m-3, the lowest radon concentration measured(adjusted odds ratio (AOR) [95% CI] = 0.42 [0.180, 1.00], p = 0.049). This result is consistent with those reported elsewhere that considered radon exposure with cubic spline terms (Thompson, RE et al. 2008). Furthermore, this model predicts an AOR that is numerically less than 1.0 for radon exposures up to 545 Bq m-3 versus the above baseline, reference exposure.

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