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The Capital Region of Denmark - a part of Copenhagen University Hospital
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Autism comorbidities show elevated female-to-male odds ratios and are associated with the age of first autism diagnosis

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OBJECTIVE: To investigate the association between the comorbidity rates in autism and sex, birth year and the age at which autism was first diagnosed and compare the relative impact of each.

METHOD: Using the Danish National Patient Registry, cumulative incidences up to the age of 16 for 11 comorbid conditions (psychosis, affective disorders, anxiety disorders, conduct disorder, eating disorders, obsessive-compulsive disorder, attention-deficit hyperactivity disorder, epilepsy, tic disorders, sleep disorders or intellectual disability) were calculated for individuals with autism (N = 16,126) and non-autism individuals (N = 654,977). Individuals were further stratified based on the age at the first autism diagnoses and comorbid diagnoses up to the age of 16 were compared.

RESULTS: Most comorbidities were significantly associated with birth year and sex. Female/male odds ratios for 8 of 11 comorbid conditions were up to 67% higher than the corresponding odds ratios in the non-autism population, including conditions that are generally more common in males than in females as well as conditions that are more common in females. All comorbidity rates were significantly associated with the age at the first autism diagnosis, which was a stronger predictor than sex and birth year for 8 conditions.

CONCLUSIONS: Comorbidity rates for females exceed what would be expected based on the sex ratios among non-autistic individuals, indicating that the association between autism and comorbidity is stronger in females. Comorbidity rates are also highly dependent on the age at the first autism diagnosis, which may contribute to autism heterogeneity in research and clinical practice.

Original languageEnglish
JournalActa Psychiatrica Scandinavica
Volume144
Issue number5
Pages (from-to)475-486
Number of pages12
ISSN0001-690X
DOIs
Publication statusPublished - Nov 2021

    Research areas

  • autism, comorbidity, heterogeneity, sex bias

ID: 67031325