Use of density equalizing map projections (DEMP) in the analysis of childhood cancer in four California counties.
In studying geographic disease distributions, one normally compares rates among arbitrarily defined geographic subareas (for example, census tracts), thereby sacrificing the geographic detail of the original data. The sparser the data, the larger the subareas must be in order to calculate stable rates. This dilemma is avoided with the technique of density equalizing map projections (DEMP). Boundaries of geographic subregions are adjusted to equalize population density over the entire study area. Case location plotted on the transformed map should have a uniform distribution if the underlying disease rates are constant. The present report describes the application of the DEMP technique to 401 childhood cancer cases occurring between 1980 and 1988 in four California counties, with the use of map files and population data for the 262 tracts of the 1980 Census. A kth nearest neighbour analysis provides strong evidence for geographic non-uniformity in tract rates (p < 10(-4)). No such effect is observed for artificial cases generated under the assumption of constant rates. Work is in progress to repeat the analysis with improved population estimates derived from both 1980 and 1990 Census data. Final epidemiologic conclusions will be reported when that analysis is complete.
Merrill
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Information and Computing Sciences Division, Ernest Orlando Lawrence Berkeley National Laboratory, University of California 94720, USA.
Selvin
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Close
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Holmes
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D002140:California / Q000453:epidemiology; D019352:Censuses; D002648:Child; D006801:Humans; D008377:Maps as Topic; D015233:Models, Statistical; D009369:Neoplasms / Q000453:epidemiology*; D016011:Normal Distribution; D011156:Population Density; D011159:Population Surveillance / Q000379:methods*; D018401:Sample Size; D017062:Small-Area Analysis