Methods for eliciting aetiological clues from geographically clustered cases of disease, with application to leukaemia-lymphoma data

The nearest neighbour analysis method has been developed to determine wheth er a disease case may be regarded as being unusually close to other neighbo uring cases of the same disease. Using this method, each disease case is cl assified as spatially 'clustered' or 'non-clustered'. The method is also us ed to provide a test for global clustering. 'Clusters' are constructed by a malgamating geographically neighbouring clustered cases into one contiguous 'cluster area'. This paper describes a method for studying differences bet ween clustered and non-clustered cases, in terms of case 'attributes'. Thes e attributes may be person related, such as age and sex, or area based, suc h as geographical isolation. The area-based variables are subject to geogra phical correlation. The comparison of clustered and non-clustered cases may reveal similarities or differences, which may, in turn, give clues to dise ase aetiology. A method for studying 'linkage' or similarities in attribute s between cases that occur in the same clusters is also described. The meth ods are illustrated by application to incidence data for leukaemias and lym phomas.