title: The co-morbidity burden of children and young adults with autism spectrum disorders.
abstract: OBJECTIVE
  Use electronic health records Autism Spectrum Disorder (ASD) to assess the comorbidity burden of ASD in children and young adults.
  
  
  METHODS
  A retrospective prevalence study was performed using a distributed query system across three general hospitals and one pediatric hospital. Over 14,000 individuals under age 35 with ASD were characterized by their co-morbidities and conversely, the prevalence of ASD within these comorbidities was measured. The comorbidity prevalence of the younger (Age<18 years) and older (Age 18-34 years) individuals with ASD was compared.
  
  
  RESULTS
  19.44% of ASD patients had epilepsy as compared to 2.19% in the overall hospital population (95% confidence interval for difference in percentages 13.58-14.69%), 2.43% of ASD with schizophrenia vs. 0.24% in the hospital population (95% CI 1.89-2.39%), inflammatory bowel disease (IBD) 0.83% vs. 0.54% (95% CI 0.13-0.43%), bowel disorders (without IBD) 11.74% vs. 4.5% (95% CI 5.72-6.68%), CNS/cranial anomalies 12.45% vs. 1.19% (95% CI 9.41-10.38%), diabetes mellitus type I (DM1) 0.79% vs. 0.34% (95% CI 0.3-0.6%), muscular dystrophy 0.47% vs 0.05% (95% CI 0.26-0.49%), sleep disorders 1.12% vs. 0.14% (95% CI 0.79-1.14%). Autoimmune disorders (excluding DM1 and IBD) were not significantly different at 0.67% vs. 0.68% (95% CI -0.14-0.13%). Three of the studied comorbidities increased significantly when comparing ages 0-17 vs 18-34 with p<0.001: Schizophrenia (1.43% vs. 8.76%), diabetes mellitus type I (0.67% vs. 2.08%), IBD (0.68% vs. 1.99%) whereas sleeping disorders, bowel disorders (without IBD) and epilepsy did not change significantly.
  
  
  CONCLUSIONS
  The comorbidities of ASD encompass disease states that are significantly overrepresented in ASD with respect to even the patient populations of tertiary health centers. This burden of comorbidities goes well beyond those routinely managed in developmental medicine centers and requires broad multidisciplinary management that payors and providers will have to plan for.
authors.affiliation: Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America. Isaac_kohane@harvard.edu
authors.forename: Isaac S
authors.initials: IS
authors.lastname: Kohane
authors.forename: Andrew
authors.initials: A
authors.lastname: McMurry
authors.forename: Griffin
authors.initials: G
authors.lastname: Weber
authors.forename: Douglas
authors.initials: D
authors.lastname: MacFadden
authors.forename: Leonard
authors.initials: L
authors.lastname: Rappaport
authors.forename: Louis
authors.initials: L
authors.lastname: Kunkel
authors.forename: Jonathan
authors.initials: J
authors.lastname: Bickel
authors.forename: Nich
authors.initials: N
authors.lastname: Wattanasin
authors.forename: Sarah
authors.initials: S
authors.lastname: Spence
authors.forename: Shawn
authors.initials: S
authors.lastname: Murphy
authors.forename: Susanne
authors.initials: S
authors.lastname: Churchill
mesh_terms: D000293:Adolescent; D000328:Adult; D001900:Boston; D002648:Child; D002659:Child Development Disorders, Pervasive / Q000453:epidemiology*; D002675:Child, Preschool; D015331:Cohort Studies; D015897:Comorbidity; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D015995:Prevalence; D012744:Sex Ratio