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Brief Report: Gender and Age of Diagnosis Time Trends in Children with Autism Using Australian Medicare Data

Abstract

Recent evidence suggests the male predominance in Autism Spectrum Disorder (ASD) may be decreasing. Secondary analyses of Australian Medicare data (paediatrician/child psychiatrist items for diagnosing ASD before age 13) were used (N = 73,463 unique children from 1-July-2008 to 30-June-2016). Cumulative incidence of ASD in 4-year-olds in 2015/2016 was 1.10% [95% CI 1.06–1.14], males 1.66% [95% CI 1.60–1.72] and females 0.51% [95% CI 0.47–0.55]. New diagnoses significantly increased in older (5–12 years) males and females but not younger (0–4 years) children, from 2010/2011 to 2015/2016. The M:F ratio decreased in older children (4.1–3.0), but not significantly in younger children (4.2–3.5). Identification of older males and females is contributing to the increased in ASD in Australia and proportionally more older females are being diagnosed.

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References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5). Washington, DC: American Psychiatric Publications.

    Book  Google Scholar 

  • Australian Bureau of Statistics (ABS). (2013). Census of population and housing: Socio-economic indexes for areas (SEIFA), Australia–data only. Canberra, ACT, Australia: ABS. Retrieved from http://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa2011?opendocument&navpos=260.

  • Bent, C. A., Barbaro, J., & Dissanayake, C. (2017). Change in autism diagnoses prior to and following the introduction of DSM-5. Journal of Autism and Developmental Disorders, 47(1), 163–171.

    Article  Google Scholar 

  • Christensen, D. L., Bilder, D. A., Zahorodny, W., Pettygrove, S., Durkin, M. S., Fitzgerald, R. T., … Yeargin-Allsopp, M. (2016). Prevalence and characteristics of autism spectrum disorder among 4-year-old children in the autism and developmental disabilities monitoring network. Journal of Developmental & Behavioral Pediatrics, 37(1), 1–8.

    Article  Google Scholar 

  • Coo, H., Ouellette-Kuntz, H., Lloyd, J. E., Kasmara, L., Holden, J. J., & Lewis, M. S. (2008). Trends in autism prevalence: Diagnostic substitution revisited. Journal of Autism and Developmental Disorders, 38(6), 1036–1046.

    Article  Google Scholar 

  • Daniels, A. M., & Mandell, D. S. (2014). Explaining differences in age at autism spectrum disorder diagnosis: A critical review. Autism, 18(5), 583–597.

    Article  Google Scholar 

  • Fombonne, E. (2003). Epidemiological surveys of autism and other pervasive developmental disorders: An update. Journal of Autism and Developmental Disorders, 33(4), 365–382.

    Article  Google Scholar 

  • Fombonne, E. (2009). Epidemiology of pervasive developmental disorders. Pediatric Research, 65(6), 591–598.

    Article  Google Scholar 

  • Hansen, S. N., Schendel, D. E., & Parner, E. T. (2015). Explaining the increase in the prevalence of autism spectrum disorders: The proportion attributable to changes in reporting practices. JAMA Pediatrics, 169(1), 56–62.

    Article  Google Scholar 

  • King, M., & Bearman, P. (2009). Diagnostic change and the increased prevalence of autism. International Journal of Epidemiology, 38(5), 1224–1234.

    Article  Google Scholar 

  • Loomes, R., Hull, L., & Mandy, W. P. L. (2017). What is the male-to-female ratio in autism spectrum disorder? A systematic review and meta-analysis. Journal of the American Academy of Child & Adolescent Psychiatry, 56, 466–474

    Article  Google 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. BMJ Open, 7(5), e015549.

    Article  Google Scholar 

  • Mazurek, M. O., Handen, B. L., Wodka, E. L., Nowinski, L., Butter, E., & Engelhardt, C. R. (2014). Age at first autism spectrum disorder diagnosis: The role of birth cohort, demographic factors, and clinical features. Journal of Developmental & Behavioral Pediatrics, 35(9), 561–569.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Randall, M., Sciberras, E., Brignell, A., Ihsen, E., Efron, D., Dissanayake, C., & Williams, K. (2016). Autism spectrum disorder: Presentation and prevalence in a nationally representative Australian sample. Australian & New Zealand Journal of Psychiatry, 50(3), 243–253.

    Article  Google Scholar 

  • Rutherford, M., McKenzie, K., Johnson, T., Catchpole, C., O’Hare, A., McClure, I., … Murray, A. (2016). Gender ratio in a clinical population sample, age of diagnosis and duration of assessment in children and adults with autism spectrum disorder. Autism, 20(5), 628–634.

    Article  Google Scholar 

  • Webb, S. J., Jones, E. J., Kelly, J., & Dawson, G. (2014). The motivation for very early intervention for infants at high risk for autism spectrum disorders. International Journal of Speech-Language Pathology, 16(1), 36–42.

    Article  Google Scholar 

  • Zwaigenbaum, L., Bauman, M. L., Choueiri, R., Kasari, C., Carter, A., Granpeesheh, D., … Fein, D. (2015). Early intervention for children with autism spectrum disorder under 3 years of age: Recommendations for practice and research. Pediatrics, 136(Supplement 1), S60–S81.

    Article  Google Scholar 

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Acknowledgments

Medicare data was provided by the Australian Government Department of Human Services. The findings and views reported in this article are those of the authors and should not be attributed to the Department of Human Services. The authors alone are responsible for the content and writing of the paper. We wish to thank the William Collie Trust, University of Melbourne, and the Lorenzo and Pamela Galli Charitable Trust, for their support of authors Dr May and Professor Williams.

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TM and KW conceived of the study, participated in its design and coordination and drafted the manuscript; TM performed the statistical analysis. All authors read and approved the final manuscript.

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Correspondence to Tamara May.

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Authors Tamara May and Katrina Williams declare that they have no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors. This study used a publicly available pre-existing, non-identifiable data set.

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May, T., Williams, K. Brief Report: Gender and Age of Diagnosis Time Trends in Children with Autism Using Australian Medicare Data. J Autism Dev Disord 48, 4056–4062 (2018). https://doi.org/10.1007/s10803-018-3609-7

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Keywords

  • Autism spectrum disorder
  • Incidence
  • Sex differences
  • Gender differences
  • Male to female ratio