@misc{oai:repo.qst.go.jp:00063671,
 author = {Doi, Kazutaka and Tokonami, Shinji and Yonehara, Hidenori and Yoshinaga, Shinji and 土居 主尚 and 床次 眞司 and 米原 英典 and 吉永 信治},
 month = {Oct},
 note = {In most countries, radon is the dominant contributor among natural radiation sources to the radiation exposure dose of the general population. Many studies of underground miners have consistently demonstrated that exposure to high levels of radon gas and its decay products increase the risk of lung cancer, and the radon progeny are now a well-recognized cause of lung cancer. Since radon is found in homes and is also present outdoors although the concentration is lower outside, numerical case-control studies of residential radon and lung cancer have been conducted using passive radon (Rn-222) detectors. These studies showed that radon may increase lung cancer risk, but most of them did not show a significant risk.
Recently it was shown that the readings of passive radon detectors that do not employ thoron (Rn-220) discrimination techniques are affected by thoron. Therefore, we conducted a simulation study to evaluate the possible effect of thoron interference on the estimation of radon-related lung cancer risk. Various assumptions were made based on the number of cases, matching ratio, baseline risk, true radon-related risk, distribution of radon and thoron concentrations, correlation between radon and thoron, and radon detectors. The results suggested that in certain circumstances thoron interference in radon measurements resulted in an approximately 90% downward bias. In addition, the magnitude of the bias increased as the geometric mean and geometric standard error of radon concentration decreased and those of thoron increased. In order to resolve this problem, it is necessary to use passive radon detectors with thoron discrimination techniques in epidemiological studies., The First Meeting for the International Joint Research on Construction of Natural Radiation Exposure Study Network},
 title = {Thoron influence on radon risk estimate in epidemiological studies},
 year = {2009}
}