Review
What Is the Male-to-Female Ratio in Autism Spectrum Disorder? A Systematic Review and Meta-Analysis

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Objective

To derive the first systematically calculated estimate of the relative proportion of boys and girls with autism spectrum disorder (ASD) through a meta-analysis of prevalence studies conducted since the introduction of the DSM-IV and the International Classification of Diseases, Tenth Revision.

Method

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The Medline, Embase, and PsycINFO databases were searched, and study quality was rated using a risk-of-bias tool. Random-effects meta-analysis was used. The pooled outcome measurement was the male-to-female odds ratio (MFOR), namely the odds of being male in the group with ASD compared with the non-ASD group. In effect, this is the ASD male-to-female ratio, controlling for the male-to-female ratio among participants without ASD.

Results

Fifty-four studies were analyzed, with 13,784,284 participants, of whom 53,712 had ASD (43,972 boys and 9,740 girls). The overall pooled MFOR was 4.20 (95% CI 3.84–4.60), but there was very substantial between-study variability (I2 = 90.9%). High-quality studies had a lower MFOR (3.32; 95% CI 2.88–3.84). Studies that screened the general population to identify participants regardless of whether they already had an ASD diagnosis showed a lower MFOR (3.25; 95% CI 2.93–3.62) than studies that only ascertained participants with a pre-existing ASD diagnosis (MFOR 4.56; 95% CI 4.10–5.07).

Conclusion

Of children meeting criteria for ASD, the true male-to-female ratio is not 4:1, as is often assumed; rather, it is closer to 3:1. There appears to be a diagnostic gender bias, meaning that girls who meet criteria for ASD are at disproportionate risk of not receiving a clinical diagnosis.

Section snippets

Method

We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews.

Overview

Figure 1 depicts the process by which studies were identified. Fifty-four met the inclusion criteria, consisting of 13,784,284 participants, 53,712 of whom were diagnosed with ASD (43,972 boys and 9,740 girls). Details of each study, including total risk-of-bias score, are presented in Table S1 (available online). Fourteen studies were conducted in North America, with 11 taking place in the United States21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 and 3 in Canada.32, 33, 34 Twenty-four were

Discussion

We conducted the first meta-analysis of the ASD male-to-female ratio based on a systematic review of epidemiologic prevalence studies reported according to PRISMA guidelines. The overall weighted MFOR (4.20; 95% CI 3.84–4.60), derived from 54 prevalence studies, was consistent with DSM-5’s assertion that among diagnosed cases, there are 4 boys for every girl on the autism spectrum.1 However, there was significant and very substantial variability among the 54 studies, which calls into question

References (83)

  • X. Sun et al.

    Parental concerns, socioeconomic status, and the risk of autism spectrum conditions in a population-based study

    Res Dev Disabil

    (2014)
  • E. Fernell et al.

    Autism spectrum disorder diagnoses in Stockholm preschoolers

    Res Dev Disabil

    (2010)
  • J. Isaksen et al.

    Observed prevalence of autism spectrum disorders in two Norwegian counties

    Eur J Paediatr Neurol

    (2012)
  • J.P. Huang et al.

    Prevalence and early signs of autism spectrum disorder (ASD) among 18-36 month old children in Tianjin of China

    Biomed Environ Sci

    (2014)
  • D.C. Lai et al.

    Gender and geographic differences in the prevalence of autism spectrum disorders in children: analysis of data from the national disability registry of Taiwan

    Res Dev Disabil

    (2012)
  • D.H. Skuse et al.

    Social communication competence and functional adaptation in a general population of children: preliminary evidence for sex-by-verbal IQ differential risk

    J Am Acad Child Adolesc Psychiatry

    (2009)
  • K. Dworzynski et al.

    How different are girls and boys above and below the diagnostic threshold for autism spectrum disorders?

    J Am Acad Child Adolesc Psychiatry

    (2012)
  • J.C. McPartland et al.

    Sensitivity and specificity of proposed DSM-5 diagnostic criteria for autism spectrum disorder

    J Am Acad Child Adolesc Psychiatry

    (2012)
  • Diagnostic and Statistical Manual

    (2013)
  • W. Mandy et al.

    Annual research review: the role of the environment in the developmental psychopathology of autism spectrum condition

    J Child Psychol Psychiatry

    (2016)
  • S. Kopp et al.

    Girls with social deficits and learning problems: autism, atypical Asperger syndrome or a variant of these conditions

    Eur Child Adolesc Psychiatry

    (1992)
  • S. Bargiela et al.

    The experiences of late-diagnosed women with autism spectrum conditions: an investigation of the female autism phenotype

    J Autism Dev Disord

    (2016)
  • E. Fombonne

    Epidemiology of pervasive developmental disorders

    Pediatr Res

    (2009)
  • F. Icasiano et al.

    Childhood autism spectrum disorder in the Barwon region: a community based study

    J Paediatr Child Health

    (2004)
  • MRC Review of Autism Research: Epidemiology and Causes

    (2001)
  • F.R. Volkmar et al.

    Sex-differences in pervasive developmental disorders

    J Autism Dev Disord

    (1993)
  • M. Rutherford et al.

    Gender ratio in a clinical population sample, age of diagnosis and duration of assessment in children and adults with autism spectrum disorder

    Autism

    (2016)
  • K.O. McGraw et al.

    Forming inferences about some intraclass correlations coefficients

    Psychol Method

    (1996)
  • M. Lipsey et al.

    Practical Meta-Analysis

    (2001)
  • J.P.T. Higgins et al.

    A re-evaluation of random-effects meta-analysis

    J R Stat Soc Ser A Stat Soc

    (2009)
  • R.M. Harbord et al.

    A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints

    Stat Med

    (2006)
  • W.J. Barbaresi et al.

    The incidence of autism in Olmsted County, Minnesota, 1976-1997 results from a population-based study

    Arch Pediatr Adolesc Med

    (2005)
  • J. Bertrand et al.

    Prevalence of autism in a United States population: the Brick Township, New Jersey, investigation

    Pediatrics

    (2001)
  • Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network, six sites, United States 2000

    MMWR Surveill Summ

    (2007)
  • Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network, 14 sites, United States 2002

    MMWR Surveill Summ

    (2007)
  • Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network, United States, 2006

    MMWR Surveill Summ

    (2009)
  • Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network, 14 sites, United States, 2008

    MMWR Surveill Summ

    (2012)
  • Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network, 11 sites, United States, 2010

    MMWR Surveill Summ

    (2014)
  • M.D. Kogan et al.

    Prevalence of parent-reported diagnosis of autism spectrum disorder among children in the US, 2007

    Pediatrics

    (2009)
  • G.C. Windham et al.

    Birth prevalence of autism spectrum disorders in the San Francisco Bay area by demographic and ascertainment source characteristics

    J Autism Dev Disord

    (2011)
  • M. Yeargin-Allsopp et al.

    Prevalence of autism in a US metropolitan area

    JAMA

    (2003)
  • Cited by (0)

    Dr. Loomes was supported by Health Education England.

    The authors thank Vyv Huddy, PhD, of the UCL Research Department of Clinical, Educational and Health Psychology, for his support with planning and conducting the meta-analysis.

    Disclosure: Drs. Loomes and Mandy and Ms. Hull report no biomedical financial interests or potential conflicts of interest.

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