Prevalence of Depressive Disorders in Individuals with Autism Spectrum Disorder: a Meta-Analysis
Substantial uncertainty exists about the prevalence of depressive disorders in individuals with autism spectrum disorder (ASD). This meta-analysis quantitatively summarized studies that assessed the lifetime and current prevalence of unipolar depressive disorders in children, adolescents, and adults with ASD. We also examined demographic, methodological, and study moderators. This meta-analysis adhered to PRISMA guidelines. A total of 7857 articles were identified through 5 databases (PubMed, Web of Science, PYSCInfo, CINAHL, ProQuest Dissertations and Theses), forward searches, and backward searches. Two reviewers independently screened articles and extracted data. Sixty-six articles met inclusion criteria. Results indicated that the pooled lifetime and current prevalence was 14.4% (95% CI 10.3–19.8) and 12.3% (95% CI 9.7–15.5), respectively. Rates of depressive disorders were highest among studies that used a standardized interview to assess depressive disorders (lifetime = 28.5%, 95% CI 20.1–38.8; current = 15.3%, 95% CI 11.0–20.9) and required participants to report on their own depressive symptoms (lifetime = 48.6%, 95% CI 33.3–64.2; current = 25.9%, 95% CI 17.0–37.3). Rates were also higher in studies that included participants with higher intelligence. Lifetime, but not current, prevalence was positively associated with age and the proportion of the sample that was White. In conclusion, we found that the rates of depressive disorders are high among individuals with ASD. Compared to typically developing individuals, individuals with ASD are 4-times more likely to experience depression in their lifetime. These results suggest that individuals with ASD should be regularly screened and offered treatment for depression.
KeywordsAutism spectrum disorder Depressive disorders Comorbid Prevalence Meta-analysis
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
Meta-analyses are exempt from research ethics board review because the data is collected from publically available information.
Because the study did not involve interaction with participants, informed consent was not required.
- Achenbach, T. M., McConaughy, S. H., & Howell, C. T. (1987). Child/adolescent behavioral and emotional problems: Implications of cross-informant correlations for situational specificity. Psychological Bulletin, 101(2), 213–232. https://doi.org/10.1037/0033-2909.101.2.213 CrossRefPubMedGoogle Scholar
- Billstedt, E., Gillberg, C., & Gillberg, C. (2005). Autism after adolescence: Population-based 13- to 22-year follow-up study of 120 individuals with autism diagnosed in childhood. Journal of Autism and Developmental Disorders, 35, 351–360. https://doi.org/10.1007/s10803-005-3302-5 CrossRefPubMedGoogle Scholar
- Borenstein, M., Rothstein, D., & Cohen, J. (2005). Comprehensive meta-analysis: A computer program for research synthesis [computer software]. Englewood: Biostat.Google Scholar
- Breslau, J., Javaras, K. N., Blacker, D., Murphy, J. M., & Normand, S. L. T. (2008). Differential item functioning between ethnic groups in the epidemiological assessment of depression. The Journal of Nervous and Mental Disease, 196(4), 297. https://doi.org/10.1097/NMD.0b013e31816a490e CrossRefPubMedPubMedCentralGoogle Scholar
- Duval, S. (2005). The trim and fill method. In H. R. Rothstein, A. J. Sutton, & M. Borenstein (Eds.), Publication bias in meta-analysis: Prevention, assessment and adjustments (pp. 127–144). Hoboken: Wiley.Google Scholar
- Gotham, K., Brunwasser, S. M., & Lord, C. (2015). Depressive and anxiety symptom trajectories from school age through young adulthood in samples with autism spectrum disorder and developmental delay. Journal of the American Academy of Child & Adolescent Psychiatry, 54(5), 369–376. https://doi.org/10.1016/j.jaac.2015.02.005 CrossRefGoogle Scholar
- Hoy, D., Brooks, P., Woolf, A., Blyth, F., March, L., Bain, C., et al. (2012). Assessing risk of bias in prevalence studies: Modification of an existing tool and evidence of interrater agreement. Journal of Clinical Epidemiology, 65(9), 934–939. https://doi.org/10.1016/j.jclinepi.2011.11.014 CrossRefPubMedGoogle Scholar
- Johnson, S. A., Filliter, J. H., & Murphy, R. R. (2009). Discrepancies between self-and parent-perceptions of autistic traits and empathy in high functioning children and adolescents on the autism spectrum. Journal of Autism and Developmental Disorders, 39(12), 1706–1714. https://doi.org/10.1007/s10803-009-0809-1 CrossRefPubMedGoogle Scholar
- Joshi, G., Wozniak, J., Petty, C., Martelon, M. K., Fried, R., Bolfek, A., et al. (2013). Psychiatric comorbidity and functioning in a clinically referred population of adults with autism spectrum disorders: A comparative study. Journal of Autism and Developmental Disorders, 43(6), 1314–1325. https://doi.org/10.1007/s10803-012-1679-5 CrossRefPubMedGoogle Scholar
- Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., et al. (2003). The epidemiology of major depressive disorder: Results from the National Comorbidity Survey Replication (NCS-R). The Journal of the American Medical Association, 289(23), 3095–3105. https://doi.org/10.1001/jama.289.23.3095 CrossRefPubMedGoogle Scholar
- Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 593–602. https://doi.org/10.1001/archpsyc.62.6.593 CrossRefPubMedGoogle Scholar
- Kessler, R. C., Birnbaum, H., Bromet, E., Hwang, I., Sampson, N., & Shahly, V. (2010). Age differences in major depression: Results from the National Comorbidity Survey Replication (NCS-R). Psychological Medicine, 40(2), 225–237. https://doi.org/10.1017/S0033291709990213 CrossRefPubMedGoogle Scholar
- Koenen, K. C., Moffitt, T. E., Roberts, A. L., Martin, L. T., Kubzansky, L., Harrington, H., et al. (2009). Childhood IQ and adult mental disorders: A test of the cognitive reserve hypothesis. American Journal of Psychiatry, 166(1), 50–57. https://doi.org/10.1176/appi.ajp.2008.08030343 CrossRefPubMedGoogle Scholar
- Kraper, C. K., Kenworthy, L., Popal, H., Martin, A., & Wallace, G. L. (2017). The gap between adaptive behavior and intelligence in autism persists into young adulthood and is linked to psychiatric co-morbidities. Journal of Autism and Developmental Disorders, 47(10), 3007–3017. https://doi.org/10.1007/s10803-017-3213-2 CrossRefPubMedGoogle Scholar
- Merikangas, K. R., He, J. P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., et al. (2010). Lifetime prevalence of mental disorders in US adolescents: Results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 49(10), 980–989. https://doi.org/10.1016/j.jaac.2010.05.017 CrossRefGoogle Scholar
- Riolo, S. A., Nguyen, T. A., Greden, J. F., & King, C. A. (2005). Prevalence of depression by race/ethnicity: Findings from the National Health and nutrition examination survey III. American Journal of Public Health, 95(6), 998–1000. https://doi.org/10.2105/AJPH.2004.047225 CrossRefPubMedPubMedCentralGoogle Scholar
- Wingate, M., Kirby, R. S., Pettygrove, S., Cunniff, C., Schulz, E., Ghosh, T., et al. (2014). Prevalence of autism spectrum disorders among children aged 8 years: Autism and developmental disabilities monitoring network, 11 sites, United States, 2010. Morbidity and Mortality Weekly Surveillance Summaries, 63, 1–22.Google Scholar
- World Health Organization. (2017). Autism spectrum disorders: Fact sheet. Retrieved from: http://www.who.int/mediacentre/factsheets/autism-spectrum-disorders/en.