CONSTRUCTING REGIONS FOR SMALL-AREA ANALYSIS - MATERIAL DEPRIVATION AND COLORECTAL-CANCER

Background This paper is about constructing small areas for the analys is of health data with the aims of health service delivery in mind. Th e areal framework should enable the analyst to link health data and ce nsus data and the areas should have large enough populations to ensure that rates are reliable and be homogeneous with respect to important socio-economic attributes. Methods An information-based statistic is u sed for the construction of regions in Sheffield based on the Townsend deprivation index. Enumeration districts are used as the geographical building blocks for the regions. The new regional framework is used f or computing Bayes adjusted standardized incidence rates for colorecta l cancer (CRC) across Sheffield. The paper then examines the statistic al relationship between CRC incidence and deprivation across the set o f regions using bivariate regression. Results The method yields region s that are considerably more homogeneous in terms of deprivation than wards, and using this framework it is shown that there is a (weak) sta tistical association at the regional scale between deprivation and CRC . Conclusion We conclude that statistical tools can be employed to pro vide regions that meet the criteria for small area analysis of health data and the analyst does not have to be tied to large administrative units such as wards. There are some benefits to executing this work wi thin a Geographic Informative System. The method should be of interest to those concerned with health service delivery and the identificatio n of 'problem regions'.