title: Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability.
abstract: Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6×10(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], p = 0.02475 and 99% CI: [68%, 99.99%], p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).
authors.affiliation: Department of Medicine, the University of Chicago, Chicago, Illinois, United States of America; Institute for Genomics and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America; Computation Institute, Department of Human Genetics, the University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Andrey
authors.initials: A
authors.lastname: Rzhetsky
authors.affiliation: Department of Genetics, Stanford University, Stanford, California, United States of America.
authors.forename: Steven C
authors.initials: SC
authors.lastname: Bagley
authors.affiliation: Institute for Genomics and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America; Committee on Genetics, Genomics, and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Kanix
authors.initials: K
authors.lastname: Wang
authors.affiliation: The Center for Health and the Social Sciences, the University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Lyttle
authors.affiliation: Department of Psychiatry, Institute for Juvenile Research, University of Illinois at Chicago, Chicago, Illinois, United States of America.
authors.forename: Edwin H
authors.initials: EH
authors.lastname: Cook
authors.affiliation: Departments of Bioengineering, Genetics, Medicine, and Computer Science, Stanford University, Stanford, California, United States of America.
authors.forename: Russ B
authors.initials: RB
authors.lastname: Altman
authors.affiliation: Departments of Medicine and Health Studies, the University of Chicago, Center for Health Statistics, Chicago, Illinois, United States of America.
authors.forename: Robert D
authors.initials: RD
authors.lastname: Gibbons
mesh_terms: D000465:Algorithms; D001321:Autistic Disorder / Q000175:diagnosis* / Q000453:epidemiology*; D016000:Cluster Analysis; D000013:Congenital Abnormalities / Q000175:diagnosis / Q000453:epidemiology; D004777:Environment; D005260:Female; D006801:Humans; D015994:Incidence; D007345:Insurance Claim Review; D008607:Intellectual Disability / Q000175:diagnosis* / Q000453:epidemiology*; D008297:Male; D008390:Markov Chains; D009010:Monte Carlo Method; D010641:Phenotype; D016012:Poisson Distribution; D012307:Risk Factors; D014481:United States