Analysis of Indoor Radon Data Using Bayesian, Random Binning, and Maximum Entropy Methods

Abstract

Three statistical methods: Bayesian, randomized data binning and Maximum Entropy Method (MEM) are described and applied in the analysis of US radon data taken from the US registry. Two confounding factors—elevation of inhabited dwellings, and UVB (ultra-violet B) radiation exposure—were considered to be most correlated with the frequency of lung cancer occurrence. MEM was found to be particularly useful in extracting meaningful results from epidemiology data containing such confounding factors. In model testing, MEM proved to be more effective than the least-squares method (even via Bayesian analysis) or multi-parameter analysis, routinely applied in epidemiology. Our analysis of the available residential radon epidemiology data consistently demonstrates that the relative number of lung cancers decreases with increasing radon concentrations up to about 200 Bq/m3, also decreasing with increasing altitude at which inhabitants live. Correlation between UVB intensity and lung cancer has also been demonstrated.

Relationships among Indoor Radon, Earthquake Magnitude Data and Lung Cancer Risks in a Residential Building of an Apulian Town (Southern Italy)

“…Recently some studies have discussed the so called "radon effect" as the long-term radon residential exposure estimates may be subject to errors due to different methodology for radon risk assessment and for retrospective assessment of smoking habits [37][38][39]. Likewise, other studies applying various statistical methods and considering additional carcinogenic risk factors and risk modifiers or confounding factors (gender, age, smoke habits, ultraviolet B (UVB), elevation of inhabited dwellings) found that the relative risk of lung cancer is independent of low radon concentration below about 800 Bq/m 3 [40][41][42].…”

Can Low-Level Ionizing Radiation Do Us Any Harm?

“…41 The results of these radon studies were later confirmed by a group of investigators from the Polish National Centre of Nuclear Studies led by Professor Ludwik Dobrzyński who in their sequential analyses of the available data demonstrated that breathing air containing even several hundred Bq/m 3 is unlikely to cause lung cancer. 42,43 Despite these clear indications, which pertain to indoor and outdoor radon concentrations in the air, Rn-222 and its progeny continue to be considered as one of the leading causes of lung cancer. 36 Recently, a large-scale statistical study to evaluate the impact of natural background radiation on human longevity and cancer mortality has been published.…”

“…Also, the choice of data 'binning' in order to reduce the number of data points in such an analysis may significantly affect the slope of the resulting dependence. 43 Proponents of LNT often resort to studies biased ab initio (i.e. such, where the validity of the LNT model is never contested), or where circular reasoning, 'doctoring' of data in statistical analyses or other methodological shortcomings are apparent.…”

Indoor Radon Research in the Asia-Pacific Region

“…In addition, the results of a meta-analysis involving thirty-two case-control studies and two ecological radon studies on lung cancer, focusing on radon concentrations below 1000 Bq m −3 , do not support the finding that radon may be a cause of a statistically significant increase in the incidence of lung cancer [15]. The discussion about the effects of low radon exposure as well as low-level ionizing radiation is ongoing [16,17].…”