A Temporal-Spatial Analysis of Breast Cancer in Upper C*

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DESCRIPTION (provided by applicant): The reason for elevated breast cancer rates on Cape Cod, Massachusetts remains unknown despite epidemiological studies to investigate possible environmental risk factors. Two existing population-based breast cancer case-control studies of upper Cape Cod (1983-1993) provide a geocoded residential history and information on confounders for all subjects. Combining the two studies creates an invaluable dataset for temporal-spatial analysis of subjects' residences from 1943 to 1993. Geographic Information Systems (GIS) have allowed the use of spatial analytic techniques in public health studies previously not feasible. Generalized Additive Models (GAMs) are an effective approach to mapping spatial distributions of data, combining a number of desirable features: smoothing of geographical location and calendar years, inclusion of risk factors, selection of optimum degree of smoothing (bandwidth), hypothesis testing, ability to handle various types of outcome data, and use of standard software. The combination of mapping and statistical modeling provides a powerful tool for visualizing disease risk. Temporal-spatial analysis of the breast cancer epidemiological data will help researchers understand the role of environmental risk factors in the etiology of breast cancer. The application of GAMs and GIS to the casecontrol data will create breast cancer risk maps that are smoothed over time and space. The proposed research will track the magnitude, geographic size and location of elevated risk for the fifty years of residential history. The study will also investigate the spatial effects of temporal variables: residency duration, promoter periods, and non-upper Cape Cod residency. GIS will be used to overlay breast cancer maps and environmental data to generate new hypotheses for future research. The elevated risk of breast cancer on upper Cape Cod cannot be entirely explained by known risk factors. By learning where breast cancer "hot spots" are and if they grow, intensify, or move over time, researchers will have a better understanding of how environmental risk factors may be involved.