Brief Report: Gender and Age of Diagnosis Time Trends in Children with Autism Using Australian Medicare Data
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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.
KeywordsAutism spectrum disorder Incidence Sex differences Gender differences Male to female ratio
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.
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.
Compliance with Ethical Standards
Conflict of interest
Authors Tamara May and Katrina Williams declare that they have no conflict of interest.
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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