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1.
Health Phys ; 47(3): 345-59, 1984 Sep.
Article in English | MEDLINE | ID: mdl-6500938

ABSTRACT

Risk estimators for ionizing radiation at low doses are dependent upon the assumptions and mathematical relationships which are used for extrapolating the risk estimates obtained at high doses and high dose rates to low doses and dose rates. Much of the current controversy regarding the potential effects of low-level ionizing radiation centers upon the choice of the dose-effect relationship used for this extrapolation. The linear dose-rate independent nonthreshold relationship has, until recently, been used almost exclusively for this purpose. It is generally assumed that, if the risks from low-level radiation are much higher than currently estimated from the linear extrapolation, then radiation protection standards should be lowered. Conversely, if the risks are about the same or lower than current estimates, the standards might be raised or be maintained at the current levels. This reasoning is based upon considering only the risk to the individual. If the potential impact on the exposed population is also considered, different conclusions are warranted. Consideration of the collective dose impact shows that if models such as the dose-squared model, D2, were valid, then the potential risks at low doses would be substantially less than predicted by the linear model. However, under these circumstances, it would be advisable to reduce individual doses, even at the expense of increasing the collective dose. This could be done, for example, by drastically lowering the existing dose limits. On the other hand, if a fractional power model, D1/m, was valid, spreading the dose over a large number of people could greatly increase the potential health impact. For this case, exposing fewer workers to higher individual doses might be the strategy to minimize collective risk. Linear quadratic and linear models differed only by a factor of 3 at low doses. For both of these models both the individual and collective dose (and risk) are important.


Subject(s)
Dose-Response Relationship, Radiation , Radiation Protection/standards , Humans , Mathematics , Models, Biological , Neoplasms, Radiation-Induced , Population Surveillance , Risk
2.
Science ; 205(4406): 544-5, 1979 Aug 10.
Article in English | MEDLINE | ID: mdl-17729655
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