Published online April 3, 2006
PEDIATRICS Vol. 117 No. 4 April 2006, pp. 1438-1439 (doi:10.1542/peds.2005-2911)

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COMMENTARY

Diagnostic Substitution and Changing Autism Prevalence

Paul T. Shattuck, PhD

Waisman Center, University of Wisconsin, Madison, Wisconsin

Abbreviations: MR, mental retardation

I am grateful to the editor of Pediatrics for selecting my article on diagnostic substitution in US special education for comment and doubly honored that Dr Newschaffer,¹ an esteemed epidemiologist and autism researcher, rendered that commentary. Newschaffer explores some of the limitations of my analyses including reliance on aggregate-level associations to make the case for diagnostic substitution, the inability to disentangle cohort effects in these data, and an incomplete discussion of the magnitude of association between changes in autism prevalence and corresponding changes in the prevalence of other categories. I have acknowledged and explored most of these limitations in my discussion and will not reiterate those points here. However, there are 2 comments to which I would like to briefly reply.

First, although the article perhaps can be fairly criticized for neglecting to detail the magnitude of effects in some of the regression models more thoroughly, it would be a mistake to conclude that the magnitude of effects in any given model is negligible. In fact, the magnitude of association between growing autism prevalence and the corresponding decrease in the prevalence of other categories is quite substantial. One of the ways to evaluate the adequacy of a model such as this is to compare observed values against values predicted by the model. For instance, the 2003 autism prevalence predicted by the mental retardation (MR) model in Table 2 of the article is 2.9 per 1000 (based on analysis of the residuals), whereas the actual observed autism prevalence in the same year was 3.1 per 1000, representing a very close match between observed and predicted outcomes. Regression models aside, one can also consider the actual magnitude of change in prevalence for one category as compared with another, as I did for examining the difference between changes in combined autism, other health impairments, traumatic brain injury, and developmental delay prevalence versus changes in combined learning disabilities and MR prevalence from 1994 to 2003. A similar comparison can be made between just autism and MR. The observed aggregate MR prevalence among 6- to 11-year-olds in special education declined by 2.8 per 1000 from 1994 to 2003, whereas autism prevalence increased by 2.6 per 1000. This indicates that, in the aggregate, total decline in MR prevalence could have offset the total increase in autism prevalence almost 1-for-1. Of course, this nationally aggregated calculation masks variability among states and cohorts.

Second, Newschaffer concludes with a plea to turn from the intractable, and perhaps unanswerable, question of whether autism's true prevalence has increased over the past 2 decades toward a greater prospective focus on conducting epidemiologic and genetic research related to autism. I agree that we may never be able to fully understand the dynamics behind historical changes in autism prevalence and of course agree that we need more research into etiology. However, autism diagnosis is based on observing behavior rather than clearly identifiable biological markers, diagnostic agreement among clinicians is not perfect,^2,3 black children tend to be identified later than white children,⁴ and clinicians have reported a willingness to give a diagnosis of autism for children with ambiguous symptoms if they know it will result in the child obtaining more services.⁵ Therefore, I also believe that we need to continue complementing research into etiology with careful examination of the sociopolitical context wherein processes of identification, referral, diagnosis, and intervention occur for children with autism and their families. Questions related to equity, efficacy, effectiveness, quality, and efficiency in services for children are important in their own right.

	FOOTNOTES

 
Accepted Nov 30, 2005.

Address correspondence to Paul T. Shattuck, PhD, 533B Waisman Center, University of Wisconsin, 1500 Highland Ave, Madison, WI 53705. E-mail: shattuck{at}waisman.wisc.edu

The author has indicated he has no financial relationships relevant to this article to disclose.

	REFERENCES

TOP REFERENCES

 

1. Newschaffer C. Changing autism prevalence [commentary]. Pediatrics. 2006;117 :1436 –1437[Free Full Text]
2. Klin A, Lang J, Cicchetti DV, Volkmar FR. Brief report: interrater reliability of clinical diagnosis and DSM-IV criteria for autistic disorder—results of the DSM-IV autism field trial. J Autism Dev Disord. 2000;30 :163 –167[CrossRef][Web of Science][Medline]
3. Mahoney WJ, Szatmari P, MacLean JE, et al. Reliability and accuracy of differentiating pervasive developmental disorder subtypes. J Am Acad Child Adolesc Psychiatry. 1998;37 :278 –285[CrossRef][Web of Science][Medline]
4. Mandell DS, Listerud J, Levy SE, Pinto-Martin JA. Race differences in the age at diagnosis among Medicaid-eligible children with autism. J Am Acad Child Adolesc Psychiatry. 2002;41 :1447 –1453[CrossRef][Web of Science][Medline]
5. Skellern C, Schluter P, McDowell M. From complexity to category: responding to diagnostic uncertainties of autistic spectrum disorders. J Paediatr Child Health. 2005;41 :407 –412[Medline]

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