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Child and Family Characteristics Associated With Age of Diagnosis of an Autism Spectrum Disorder in a Tertiary Care Setting

Bickel, Julie MD; Bridgemohan, Carolyn MD; Sideridis, Georgios PhD; Huntington, Noelle PhD

Journal of Developmental & Behavioral Pediatrics: January 2015 - Volume 36 - Issue 1 - p 1–7
doi: 10.1097/DBP.0000000000000117
Original Article

Objective: To identify child and family characteristics associated with age of diagnosis of autism spectrum disorder (ASD) in a tertiary care setting using objective, standardized assessments ensuring diagnostic validity and timing.

Methods: The authors conducted a chart review of children who received their initial ASD diagnosis from 2007 to 2011. Child variables included gender, birth order, cognitive functioning, and for children ≤36 months, language and adaptive assessments. Family variables included insurance, maternal age, maternal education, sibling or family member with ASD, and number of children in the house. Primary outcome was age of ASD diagnosis. The authors ran multiple regression models evaluating the impact of child and family variables on the total sample and on the subsample of children ≤36 months.

Results: Median age of diagnosis was 2.9 years (range, 15 mo–13.8 yr; n = 591). In the total sample, significant predictors of earlier age of diagnosis were later birth order, higher maternal education, fewer children in the house, and a sibling with ASD. In a separate analysis of children ≤36 months of age (n = 315) with additional data for language and adaptive assessments, significant predictors of younger age of diagnosis were higher cognitive and adaptive functioning, lower receptive and expressive language, and having a sibling with ASD.

Conclusions: This study suggests that both family and child characteristics play an important role in the early identification of ASD and that predictive variables may vary based on a child's age. Future research should help to elucidate this finding so that screening measures and policies aimed at early identification can target the most predictive factors.

Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.

Address for reprints: Julie Bickel, MD, Boston Children's Hospital, 1 Autumn St, 6th floor, Boston, MA 02115; e-mail:

Disclosure: The authors declare no conflict of interest.

Received June , 2014

Accepted October , 2014

© 2015 by Lippincott Williams & Wilkins