Geographic distribution of autism in California: A retrospective birth cohort analysis*
Abbreviations
CDERClient Development Evaluation Report
CDTcluster detection test
DDSCalifornia Department of Developmental Services
ESREarly Start Report
ICD‐9‐CMInternational Classification of Diseases, 9th revision, Clinical Modification, U.S. Department of Health and Human Services
MEETMaximized Excess Event Test, a global clustering test
RCRegional Center of the DDS
RRrelative risk, incidence within a cluster population/ incidence in the population in the rest of the study region as determined by CDTs
.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.
Number of times cited: 5
- Aisha S. Dickerson, Mohammad H. Rahbar, Amanda V. Bakian, Deborah A. Bilder, Rebecca A. Harrington, Sydney Pettygrove, Russell S. Kirby, Maureen S. Durkin, Inkyu Han, Lemuel A. Moyé, Deborah A. Pearson, Martha Slay Wingate and Walter M. Zahorodny, Autism spectrum disorder prevalence and associations with air concentrations of lead, mercury, and arsenic, Environmental Monitoring and Assessment, 188, 7, (2016).
- Sumi Hoshiko, Judith K. Grether, Gayle C. Windham, Daniel Smith and Karen Fessel, Are thyroid hormone concentrations at birth associated with subsequent autism diagnosis?, Autism Research, 4, 6, (456-463), (2011).
- Judith Pinborough‐Zimmerman, Deborah Bilder, Amanda Bakian, Robert Satterfield, Paul S. Carbone, Barry E. Nangle, Harper Randall and William M. McMahon, Sociodemographic risk factors associated with autism spectrum disorders and intellectual disability, Autism Research, 4, 6, (438-448), (2011).
- John J Cannell, On the aetiology of autism, Acta Paediatrica, 99, 8, (1128-1130), (2010).
- Bernard J. Crespi, Autism As a Disorder of High Intelligence, Frontiers in Neuroscience, 10.3389/fnins.2016.00300, 10, (2016).




