The Linear-No Threshold Hypothesis (LNT) states that risk from ionizing radiation is linearly related to dose with no dose threshold below which there was no risk. The LNT is an important fundament in practical radioprotection and for assessment of population risk, e.g., of estimating lung cancer risk or incidence attributable to exposure to indoor radon. The popularity of the LNT stems largely from its mathematical simplicity and therefore, its practicability. It seems that this has obscured the question of whether it is physically true, or “only” a useful practical rule. Distribution of exposure and dose to radon through the population is strongly right-skew, with the bulk of dose low. Therefore, attribution of risk, i.e., mainly lung cancer incidence, depends strongly on the risk model for low dose. As long as no micro-dosimetric model exists which causally relates incident radiation flux or exposure to radon progeny to a sequence of effects, starting on sub-cellular level, which results in clinical evidence, it is impossible to make statements on the effect of very low doses, since it is in principle impossible to extend empirical epidemiological inference to arbitrarily small doses. Therefore, epidemiological findings are extrapolated towards low doses. The most quoted large-scale epidemiological radon meta-study is Darby et al. (2006), which concludes that the LNT model is statistically compatible with the findings. This has been essentially corroborated by newer studies. However, with availability or more data, there seems to be increasing evidence that the model may not be applicable to estimate risk for low doses, which represent the bulk of exposure, if the objective is assessment of population risk. We review literature about the strongly debated question about validity of the LNT. Data are not publicly available, therefore statistical re-analysis is impossible. However, published information in the form of graphs and statistics allows some hypotheses alternative to the LNT. The debate is so serious because of the political consequences regarding radon abatement policy. We refrain from stating any “alternative truth” but investigate the possible consequences for risk assessment and what they entail for radon regulation and policy, resulting from different risk models.

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