Objectives: We estimated the effect of community and school district resources on the identification of children with autistic disorder.
Methods: Latent growth curve regression models were applied to school district-level data from one large state.
Results: The rate of identification of autistic disorder increased on average by 1.0 child per 10000 per year (P<.001), with statistically significant district variation. After adjustment for district and community characteristics, each increase in decile of school revenue was associated with an increase of 0.16 per 10000 children identified with autistic disorder. The proportion of economically disadvantaged children per district was inversely associated with autistic disorder cases.
Conclusions: District revenue was associated with higher proportions of children identified with autistic disorder at baseline and increasing rates of identification when measured longitudinally. Economically disadvantaged communities may need assistance to identify children with autistic spectrum disorders and other developmental delays that require attention.