Spatial statistical methods in environmental epidemiology: a critique

Abstract

Despite recent advances in the available statistical methods for geographical analysis, there are many constraints to their application in environmental epidemiology. These include problems of data availability and quality, especially the lack in most situations of environmental exposure measurements. Methods for disease 'cluster' investigation, point source exposures, small-area disease mapping and ecological correlation studies are critically reviewed, with the emphasis on practical applications and epidemiological interpretation. It is shown that, unless dealing with rare diseases, high specificity exposures and high relative risks, cluster investigation is unlikely to be fruitful, and is often complicated by the post hoc nature of such studies. However, it is recognized that in these circumstances proper assessment of the available data is often required as part of the public health response. Newly available methods, particularly in Bayesian statistics, offer an appropriate framework for geographical analysis and disease mapping. Again, it is uncertain whether they will give important clues as to aetiology, although they do give valuable description. Perhaps the most satisfactory approach is to test a priori hypotheses using a geographical database, although problems of interpretation remain.