Developmental functioning and symptom severity influence age of diagnosis in Canadian preschool children with autism
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abstract
BACKGROUND: Early diagnosis of autism spectrum disorder (ASD) is essential in most Canadian jurisdictions to access interventions that improve long-term child outcomes. Our main objective was to identify factors associated with timing of ASD diagnosis in five provinces across Canada. METHODS: Factors influencing age of diagnosis were assessed in the analyses of an inception cohort of children diagnosed with ASD between ages 2 and 5 years. We examined bivariate associations and using a series of multiple variable regression models, evaluated the unique contributions of developmental functioning, ASD symptoms and demographic variables. Children with known genetic abnormalities, or severe sensory or motor impairments interfering with assessment were excluded. RESULTS: Participants were 421 children (84.6% boys). The mean age of diagnosis was 38.2 months (SD=8.7), an average of 19 months after parents identified initial concerns. Factors associated with later diagnosis included more advanced language and cognitive skills, and higher levels of restricted repetitive behaviour symptoms. Child sex and family demographics were not associated with age of diagnosis. In regression analyses, language and cognitive skills accounted for 6.8% of variance in age of diagnosis and ASD symptoms contributed an additional 5.5%. Provincial site accounted for 4.0% of variance in age of diagnosis, independent of developmental skills and ASD symptoms. INTERPRETATION: Diagnosis of ASD occurred, on average, 19 months after parents' initial concerns. Language and cognitive skills, symptom severity and provincial site accounted for variation in age of ASD diagnosis in this Canadian cohort. Variable presentation across the developmental continuum must be considered in planning assessment services to ensure timely ASD diagnosis so that outcomes can be improved. Policy and practice leadership is also needed to reduce interprovincial variability.
