BACKGROUND/OBJECTIVES Little is known about the timing and risk factors for developing depression among autistic youth. We tested the hypotheses that depression incidence occurs at higher rates and younger ages in autistic vs nonautistic youth and that known depression risk factors in the general population would predict current depression among autistic youth. METHODS We used nationally representative survey data from a cross-section of United States households with children aged 0 to 17 years. We built a logistic regression model estimating the interaction between age and having autism when predicting depression. With the autistic subpopulation, we built a best-fit model of predictors for depression. RESULTS In the logistic regression model predicting depression incidence, autism, age, and other relevant covariates significantly predicted current depression; autism and age significantly interacted such that the increased rate of depression for autistic vs nonautistic youth widens as age of the children increases. We found statistically significant predictors of depression within autistic youth: female sex (adjusted odds ratio aOR for male relative to female youths, 0.31), multiple adverse childhood experiences (aOR, 2.94), higher frequency of being bullied (aOR, 7.94), higher intellectual ability (aOR for moderate/severe intellectual disability ID relative to no ID, 0.46), higher severity of anxiety symptoms (aOR, 20.24), and older age (aOR, 1.26). CONCLUSIONS Overall, autistic children displayed depression at an earlier age than nonautistic children, with a steady increase through adolescence. Depression prevention efforts are likely to be most impactful if geared toward those whose identities, life experiences, symptoms, and environments put them at higher risk depression.
Kuhn et al. (Wed,) studied this question.
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