Abstract
Prenatal environmental exposures are among the risk factors being explored for associations with autism. We applied a new procedure combining multiple scan cluster detection tests to identify geographically defined areas of increased autism incidence. This procedure can serve as a first hypothesis-generating step aimed at localized environmental exposures, but would not be useful for assessing widely distributed exposures, such as household products, nor for exposures from nonpoint sources, such as traffic. Geocoded mothers' residences on 2,453,717 California birth records, 1996-2000, were analyzed including 9,900 autism cases recorded in the California Department of Developmental Services (DDS) database through February 2006 which were matched to their corresponding birth records. We analyzed each of the 21 DDS Regional Center (RC) catchment areas separately because of the wide variation in diagnostic practices. Ten clusters of increased autism risk were identified in eight RC regions, and one Potential Cluster in each of two other RC regions.After determination of clusters, multiple mixed Poisson regression models were fit to assess differences in known demographic autism risk factors between the births within and outside areas of elevated autism incidence, independent of case status.Adjusted for other covariates, the majority of areas of autism clustering were characterized by high parental education, e.g. relative risks >4 for college-graduate vs. nonhigh-school graduate parents. This geographic association possibly occurs because RCs do not actively conduct case finding and parents with lower education are, for various reasons, less likely to successfully seek services.
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