Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data

We investigated the association between residence and bladder, kidney, and pancreatic cancer on upper Cape Cod. We estimated adjusted odds ratios using GAMs, smoothing on location. A 40-year residential history allowed for latency restrictions. We mapped spatially continuous odds ratios using GIS and identified statistically significant clusters using permutation tests.Maps of bladder cancer are essentially flat ignoring latency, but show a statistically significant hot spot near known Massachusetts Military Reservation (MMR) groundwater plumes when 15 years latency is assumed. The kidney cancer map shows significantly increased ORs in the south of the study area and decreased ORs in the north.Spatial epidemiology using individual level data from population-based studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of bladder cancer near MMR plumes that suggest further investigation using detailed exposure modeling.In 1988, elevated cancer incidence in the upper Cape Cod region of Massachusetts (Figure 1) prompted a large epidemiological study of all cancers to investigate possible environmental risk factors, including air and water pollution associated with the Massachusetts Military Reservation (MMR), pesticide applications to cranberry bogs, particulate air pollution from a large electric power plant, and tetrachloroethylene-contaminated drinking water from vinyl-lined asbestos cement distribution pipes [1-11]. Positive associations were observed, but environmental exposures explained only a portion of the excess cancer incidence. This population-based case-control study provides information on individual-level covariates and residential history useful for a secondary spatial analysis.Methods for mapping point-based epidemiologic data have received less attention than mapping areal data [12]. Generalized additive models (GAMs), a type of statistical model tha