Autism Spectrum Disorder: Incidence and Time Trends Over Two Decades in a Population-Based Birth Cohort
We retrospectively identified autism spectrum disorder (ASD) incident cases among 31,220 individuals in a population-based birth cohort based on signs and symptoms uniformly abstracted from medical and educational records. Inclusive and narrow research definitions of ASD (ASD-RI and ASD-RN, respectively) were explored, along with clinical diagnoses of ASD (ASD-C) obtained from the records. The incidence of ASD-RI, ASD-RN, and ASD-C increased significantly from 1985 to 1998, then ASD-RI and ASD-RN plateaued while the rate of ASD-C continued to increase during 1998–2004. The rising incidence of research-defined ASD may reflect improved recognition and documentation of ASD signs and symptoms. Although the frequency of threshold ASD symptoms stabilized, the rate of ASD-C continued to increase, narrowing the gap between clinical ascertainment and symptom documentation.
KeywordsAutism spectrum disorder Incidence Epidemiology Time trends
The authors wish to acknowledge Dr. Leonard T. Kurland for his vision in initiating the Rochester Epidemiology Project and Dr. Robert C. Colligan for his insight, enthusiasm, and collegiality across his 47 years of research in developmental disabilities at the Mayo Clinic. We also thank study coordinators Ms. Candice Klein and Mr. Tom Bitz and other members of the team for data collection, Ms. Sondra Buehler for assistance in manuscript preparation, and Independent School District No. 535 for their cooperation and collaboration.
SKK, SMM and RGV conceived of the study, participated in its design and coordination, supervised all aspects of the study and drafted the manuscript; RES, JDP, ALW, and CBS participated in the design and interpretation of the data; and CBS and ALW participated in the design of the study and performed the statistical analysis. All authors have read and approved the final manuscript.
This study was funded by research Grants from the National Institutes of Health, Public Health Service (MH093522 and AG034676).
Compliance with Ethical Standards
Conflict of interest
The authors declare that they have no conflict of interest.
Medical research involving human subjects includes research on identifiable human material or identifiable data. All procedures performed in studies involving human subjects were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required. This article does not contain any studies with animals performed by any of the authors.
This retrospective study of medical records data did not involve any participant contact.
- American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders. In Text Revision (DSM-IV-TR) (4th Edition). Washington, DC: American Psychiatric Publishing.Google Scholar
- Atladottir, H. O., Gyllenberg, D., Langridge, A., Sandin, S., Hansen, S. N., Leonard, H., et al. (2015). The increasing prevalence of reported diagnoses of childhood psychiatric disorders: A descriptive multinational comparison. European Child and Adolescent Psychiatry, 24(2), 173–183. https://doi.org/10.1007/s00787-014-0553-8.CrossRefPubMedGoogle Scholar
- Baio, J., Wiggins, L., Christensen, D. L., Maenner, M. J., Daniels, J., Warren, Z., et al. (2018). Prevalence of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveillence Summaries, 67(6), 1–23. https://doi.org/10.15585/mmwr.ss6706a1.CrossRefGoogle Scholar
- Barbaresi, W. J., Katusic, S. K., Colligan, R. C., Pankratz, V. S., Weaver, A. L., Weber, K. J., et al. (2002). How common is attention-deficit/hyperactivity disorder? Incidence in a population-based birth cohort in Rochester, Minn. Archives of Pediatrics and Adolescent Medicine, 156(3), 217–224.CrossRefPubMedGoogle Scholar
- Barbaresi, W. J., Katusic, S. K., Colligan, R. C., Weaver, A. L., & Jacobsen, S. J. (2005). The incidence of autism in Olmsted County, Minnesota, 1976–1997: Results from a population-based study. Archives of Pediatrics and Adolescent Medicine, 159(1), 37–44. https://doi.org/10.1001/archpedi.159.1.37.CrossRefPubMedGoogle Scholar
- Beighley, J. S., Matson, J. L., Rieske, R. D., Jang, J., Cervantes, P. E., & Goldin, R. L. (2013). Comparing challenging behavior in children diagnosed with autism spectrum disorders according to the DSM-IV-TR and the proposed DSM-5. Developmental Neurorehabilitation, 16(6), 375–381. https://doi.org/10.3109/17518423.2012.760119.CrossRefPubMedGoogle Scholar
- Bishop, D. V., Whitehouse, A. J., Watt, H. J., & Line, E. A. (2008). Autism and diagnostic substitution: Evidence from a study of adults with a history of developmental language disorder. Devopmental Medicine and Child Neurology, 50(5), 341–345. https://doi.org/10.1111/j.1469-8749.2008.02057.x.CrossRefGoogle Scholar
- Blumberg, S. J., Bramlett, M. D., Kogan, M. D., Schieve, L. A., Jones, J. R., & Lu, M. C. (2013). Changes in prevalence of parent-reported autism spectrum disorder in school-aged U.S. children: 2007 to 2011–2012. National Health Statistics Reports, 65, 1–11.Google Scholar
- California Department of Developmental Services. (2007). Autistic spectrum disorders: Changes in the California caseload, an update: June 1987–June 2007. Sacramento: California Health and Human Services Agency, Department of Developmental Services.Google Scholar
- Christensen, D. L., Baio, J., Braun, K. V., Bilder, D., Charles, J., Constantino, J. N., et al. (2016). Prevalence and characteristics of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2012. MMWR Surveillance Summaries, 65(2), 1–23.CrossRefGoogle Scholar
- Clark, L. A., Cuthbert, B., Lewis-Fernandez, R., Narrow, W. E., & Reed, G. M. (2017). Three Approaches to understanding and classifying mental disorder: ICD-11, DSM-5, and the National Institute of Mental Health’s Research Domain Criteria (RDoC). Psychological Science in the Public Interest, 18(2), 72–145. https://doi.org/10.1177/1529100617727266.CrossRefPubMedGoogle Scholar
- Frost, W. H. (1939). The age selection of mortality from tuberculosis in successive decades. American Journal of Hygiene, 30, 91–96.Google Scholar
- Hennekens, C. H., & Buring, J. E. (1987a). Cohort studies. In S. L. Mayrent (Ed.), Epidemiology of Medicine. Boston/Toronto: Little, Brown and Company.Google Scholar
- Hennekens, C. H., & Buring, J. E. (1987b). Measures of disease frequency and association. In S. L. Mayrent (Ed.), Epidemiology in Medicine. Boston/Toronto: Little, Brown and Company.Google Scholar
- Hoffman, K., Weisskopf, M. G., Roberts, A. L., Raz, R., Hart, J. E., Lyall, K., et al. (2017). Geographic patterns of autism spectrum disorder among children of participants in Nurses’ Health Study II. American Journal of Epidemiology, 186(7), 834–842. https://doi.org/10.1093/aje/kwx158.CrossRefPubMedPubMedCentralGoogle Scholar
- Hyman, S. E. (2010). The diagnosis of mental disorders: The problem of reification. Annual Review of Clinical Psychology, 6, 155–179. https://doi.org/10.1146/annurev.clinpsy.3.022806.091532.CrossRefPubMedGoogle Scholar
- Idring, S., Lundberg, M., Sturm, H., Dalman, C., Gumpert, C., Rai, D., et al. (2015). Changes in prevalence of autism spectrum disorders in 2001–2011: Findings from the Stockholm youth cohort. Journal of Autism and Developmental Disorders, 45(6), 1766–1773. https://doi.org/10.1007/s10803-014-2336-y.CrossRefPubMedGoogle Scholar
- Jensen, C. M., Steinhausen, H. C., & Lauritsen, M. B. (2014). Time trends over 16 years in incidence-rates of autism spectrum disorders across the lifespan based on nationwide Danish register data. Journal of Autism and Developmental Disorders, 44(8), 1808–1818. https://doi.org/10.1007/s10803-014-2053-6.CrossRefPubMedGoogle Scholar
- Katusic, S. K., Colligan, R. C., Myers, S. M., Voigt, R. G., Yoshimasu, K., Stoeckel, R. E., et al. (2017). What can large population-based birth cohort study ask about past, present and future of children with disorders of development, learning, and behavior? Journal of Epidemiology and Community Health, 71(4), 410–416. https://doi.org/10.1136/jech-2016-208482.CrossRefPubMedPubMedCentralGoogle Scholar
- Kawamura, Y., Takahashi, O., & Ishii, T. (2008). Reevaluating the incidence of pervasive developmental disorders: Impact of elevated rates of detection through implementation of an integrated system of screening in Toyota, Japan. Psychiatry and Clinical Neurosciences, 62(2), 152–159. https://doi.org/10.1111/j.1440-1819.2008.01748.x.CrossRefPubMedGoogle Scholar
- Keyes, K. M., Susser, E., Cheslack-Postava, K., Fountain, C., Liu, K., & Bearman, P. S. (2012). Cohort effects explain the increase in autism diagnosis among children born from 1992 to 2003 in California. International Journal of Epidemiology, 41(2), 495–503. https://doi.org/10.1093/ije/dyr193.CrossRefPubMedGoogle Scholar
- Kim, Y. S., Fombonne, E., Koh, Y. J., Kim, S. J., Cheon, K. A., & Leventhal, B. L. (2014). A comparison of DSM-IV pervasive developmental disorder and DSM-5 autism spectrum disorder prevalence in an epidemiologic sample. Journal of the American Academy of Child and Adolescent Psychiatry, 53(5), 500–508. https://doi.org/10.1016/j.jaac.2013.12.021.CrossRefPubMedPubMedCentralGoogle Scholar
- Kurland, L. T., Elveback, L. R., & Nobrega, F. T. (1970). Population studies in Rochester and Olmsted County, Minnesota, 1900–1968. In I. I. Kessler & M. I. Levin MI. (Eds.), The Community as an Epidemiologic Laboratory (pp. 47–70). Baltimore: John’s Hopkins University Press.Google Scholar
- Lingren, T., Chen, P., Bochenek, J., Doshi-Velez, F., Manning-Courtney, P., Bickel, J., et al. (2016). Electronic health record based algorithm to identify patients with autism spectrum disorder. PloS One, 11(7), e0159621. https://doi.org/10.1371/journal.pone.0159621.CrossRefPubMedPubMedCentralGoogle Scholar
- Lord, C., Petkova, E., Hus, V., Gan, W., Lu, F., Martin, D. M., et al. (2012). A multisite study of the clinical diagnosis of different autism spectrum disorders. Archives of General Psychiatry, 69(3), 306–313. https://doi.org/10.1001/archgenpsychiatry.2011.148.CrossRefGoogle Scholar
- Lundstrom, S., Reichenberg, A., Anckarsater, H., Lichtenstein, P., & Gillberg, C. (2015). Autism phenotype versus registered diagnosis in Swedish children: Prevalence trends over 10 years in general population samples. BMJ. 350, h1961. https://doi.org/10.1136/bmj.h1961.
- Maenner, M. J., Rice, C. E., Arneson, C. L., Cunniff, C., Schieve, L. A., Carpenter, L. A., et al. (2014). Potential impact of DSM-5 criteria on autism spectrum disorder prevalence estimates. JAMA Psychiatry, 71(3), 292–300. https://doi.org/10.1001/jamapsychiatry.2013.3893.CrossRefPubMedPubMedCentralGoogle Scholar
- May, T., Sciberras, E., Brignell, A., & Williams, K. (2017). Autism spectrum disorder: Updated prevalence and comparison of two birth cohorts in a nationally representative Australian sample. British Medical Journal Open, 7(5), e015549. https://doi.org/10.1136/bmjopen-2016-015549.CrossRefGoogle Scholar
- Miller, J. S., Bilder, D., Farley, M., Coon, H., Pinborough-Zimmerman, J., Jenson, W., et al. (2013). Autism spectrum disorder reclassified: A second look at the 1980s Utah/UCLA Autism Epidemiologic Study. Journal of Autism and Developmental Disorders, 43(1), 200–210. https://doi.org/10.1007/s10803-012-1566-0.CrossRefPubMedPubMedCentralGoogle Scholar
- Office of Autism Research Coordination (OARC) National Institute of Mental Health and Thomson Reuters, Inc., on behalf of the Interagency Autism Coordinating Committee (IACC). IACC/OARC Autism Spectrum Disorder Research Publications Analysis Report: The Global Landscape of Autism Research, July 2012. Retrieved from the Department of Health and Human Services Interagency Autism Coordinating Committee website. Retrieved September 19, 2018 http://iacc.hhs.gov/publiations-analysis/july2012/index.shtml.
- Polyak, A., Kubina, R. M., & Girirajan, S. (2015). Comorbidity of intellectual disability confounds ascertainment of autism: Implications for genetic diagnosis. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics, 168(7), 600–608. https://doi.org/10.1002/ajmg.b.32338.CrossRefGoogle Scholar
- Posserud, M. B., Lundervold, A. J., & Gillberg, C. (2006). Autistic features in a total population of 7-9-year-old children assessed by the ASSQ (Autism Spectrum Screening Questionnaire). Journal of Child Psychology and Psychiatry and Allied Disciplines, 47(2), 167–175. https://doi.org/10.1111/j.1469-7610.2005.01462.x.CrossRefGoogle Scholar
- R Core Team (2017). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
- Raz, R., Weisskopf, M. G., Davidovitch, M., Pinto, O., & Levine, H. (2015). Differences in autism spectrum disorders incidence by sub-populations in Israel 1992–2009: A total population study. Journal of Autism and Developmental Disorders, 45(4), 1062–1069. https://doi.org/10.1007/s10803-014-2262-z.CrossRefPubMedPubMedCentralGoogle Scholar
- Rocca, W. A., Yawn, B. P., Sauver, St, Grossardt, J. L., B. R., & Melton, L. J. 3rd (2012). History of the Rochester Epidemiology Project: Half a century of medical records linkage in a US population. Mayo Clinic Proceedings, 87(12), 1202–1213. https://doi.org/10.1016/j.mayocp.2012.08.012.CrossRefGoogle Scholar
- Schieve, L. A., Rice, C., Yeargin-Allsopp, M., Boyle, C. A., Kogan, M. D., Drews, C., et al. (2012). Parent-reported prevalence of autism spectrum disorders in US-born children: An assessment of changes within birth cohorts from the 2003 to the 2007 National Survey of Children’s Health. Maternal and Child Health Journal, 16(Suppl 1), 151–157. https://doi.org/10.1007/s10995-012-1004-0.CrossRefGoogle Scholar
- Smith, I. C., Reichow, B., & Volkmar, F. R. (2015). The effects of DSM-5 criteria on number of individuals diagnosed with autism spectrum disorder: A systematic review. Journal of Autism and Developmental Disorders, 45(8), 2541–2552. https://doi.org/10.1007/s10803-015-2423-8.CrossRefPubMedGoogle Scholar
- St Sauver, J. L., Grossardt, B. R., Leibson, C. L., Yawn, B. P., Melton, L. J. 3rd, & Rocca, W. A. (2012a). Generalizability of epidemiological findings and public health decisions: An illustration from the Rochester Epidemiology Project. Mayo Clinic Proceedings, 87(2), 151–160. https://doi.org/10.1016/j.mayocp.2011.11.009.CrossRefGoogle Scholar
- St Sauver, J. L., Grossardt, B. R., Yawn, B. P., Melton, L. J., Pankratz, J. J., Brue, S. M., et al. (2012b). Data resource profile: The Rochester Epidemiology Project (REP) medical records-linkage system. International Journal of Epidemiology, 41(6), 1614–1624. https://doi.org/10.1093/ije/dys195.CrossRefPubMedPubMedCentralGoogle Scholar
- St Sauver, J. L., Grossardt, B. R., Yawn, B. P., Melton, L. J. 3rd, & Rocca, W. A. (2011). Use of a medical records linkage system to enumerate a dynamic population over time: The Rochester epidemiology project. American Journal of Epidemiology, 173(9), 1059–1068. https://doi.org/10.1093/aje/kwq482.CrossRefPubMedPubMedCentralGoogle Scholar
- Yeargin-Allsopp, M., Boyle, C., van Naarden-Braun, K., & Trevathan, E. (2008). The epidemiology of developmental disabilities. In P. J. Accardo (Ed.), Capute & Accardo’s neurodevelopmental disabilities in infancy and childhood, Third Edition: Volume I: Neurodevelopmental diagnosis and treatment (pp. 61–104). Baltimore: Paul H. Brookes Publishing Co.Google Scholar
- Zablotsky, B., Black, L. I., Maenner, M. J., Schieve, L. A., & Blumberg, S. J. (2015). Estimated prevalence of autism and other developmental disabilities following questionnaire changes in the 2014 National Health Interview Survey. National Health Statistics Report, 87, 1–20.Google Scholar