ISEE Symposium August 2002 Abstract Exploring zone design methods for a small-area environmental epidemiological study Cockings, S1, Poulstrup, A2, Martin, D1, Hansen, HL2 1 Department of Geography, University of Southampton, UK; 2 Medical Office of Health, Province of Vejle, Denmark Objective: To explore whether methods that have recently been developed for the design of geographical areas for the 2001 UK Census of Population can also be employed to develop purposespecific sets of geographical units for use in environmental epidemiological studies. Introduction: Many epidemiological investigations use data aggregated to a set of geographical units. This is generally because individual level data are not available (often due to confidentiality constraints) or because area-level effects are important to the relationships under investigation or simply because we wish to calculate rates within an area. The design of such geographical areas (in terms of their size, shape and the characteristics of the population that they contain) can have a significant influence on the relationships observed between environmental factors, socio-economic factors and health and on any practical or policy decisions emanating from such research. Whilst recent studies have demonstrated the usefulness of zone design methods for the collection and dissemination of Census data, few have explored the potential usefulness of such techniques for designing zones specifically for health studies. The research presented here uses these zone design methods to develop geographical areas for use in a study investigating the possible health effects of exposure to air pollution in a city (Kolding) in Denmark. Methods: The existence of a Central Population Register (CPR) in Denmark (where all individuals are identified by a unique number and which is updated daily), together with geo-referencing of all addresses, means that the place of residence of all individuals is known to a very high spatial and temporal resolution. Residents living within the city during the time period of interest are identified using these datasets. A set of building blocks is then developed from these points (the georeferenced addresses) by drawing (Thiessen) polygons around the points using geographical information systems (GIS) techniques. A recently developed automated zone matching (AZM) tool is then used to aggregate these building blocks into sets of geographical units according to usercontrolled zone design criteria. Design parameters used include: meeting minimum population thresholds, seeking to minimise variation in population size between units, maintaining features of the natural and built environment as boundaries of units, and maximising socio-economic homogeneity within units. Results: Sets of units are produced according to the varying zone design parameters. The characteristics of the units (in terms of shape, size and characteristics of the population within them) are compared. Selected sets of units are then employed to calculate rates of cancers within the city and the sensitivity of these rates to the zone design parameters is explored. Conclusion: Zone design methods and tools developed for other applications provide the opportunity for users within the health field to design purpose-specific sets of geographical areas for use in environmental epidemiological investigations.