On statistical methods for analysing the geographical distribution of cancer cases near nuclear installations.
There is great public concern, often based on anecdotal reports, about risks from ionising radiation. Recent interest has been directed at an excess of leukaemia cases in the locality of civil nuclear installations at Sellafield and Sizewell, and epidemiologists have a duty to pursue such information vigorously. This paper sets out to show that the epidemiological methods most commonly used can be improved upon. When analysing geographical data it is necessary to consider location. The most obvious quantification of location is ranked distance, though other measures which may be more meaningful in relation to aetiology may be substituted. A test based on distance ranks, the "Poisson maximum test", depends on the maximum of observed relative risk in regions of increasing size, but with significance level adjusted for selection. Applying this test to data from Sellafield and Sizewell shows that the excess of leukaemia incidence observed at Seascale, near Sellafield, is not an artefact due to data selection by region, and that the excess probably results from a genuine, if as yet unidentified cause (there being little evidence of any other locational association once the Seascale cases have been removed). So far as Sizewell is concerned, geographical proximity to the nuclear power station does not seem particularly important.
Bithell
J F
JF
Department of Statistics, University of Oxford.
Stone
R A
RA
D016000:Cluster Analysis; D004739:England / Q000453:epidemiology; D005843:Geography; D006801:Humans; D007953:Leukemia, Radiation-Induced / Q000453:epidemiology; D009381:Neoplasms, Radiation-Induced / Q000453:epidemiology*; D009688:Nuclear Reactors; D016012:Poisson Distribution; D013223:Statistics as Topic