Diagnostic Substitution for Intellectual Disability: A Flawed Explanation for the Rise in Autism.

García-Villamisar et al. (2017) pulled U.S. special-education counts from IDEA. They looked state-by-state at autism (ASD) and intellectual disability (ID) labels from 2000-2010.

They asked a simple question: when autism numbers went up, did ID numbers go down? If they did, it would support the idea that kids once called ID are now called autistic.

The big states that drive national totals showed flat ID prevalence while autism kept climbing. The mirror-image swap just wasn’t there.

The authors conclude that diagnostic substitution—switching an ID label to an ASD label—cannot explain the autism surge.

Watt et al. (2026) looked at the same IDEA file and saw the opposite: a 331 % ASD jump paired with a 64 % ID drop. The two papers contradict, but they used different age brackets and year ranges; tiny method choices flip the answer.

Hé lène et al. (2007) had already shown that earlier detection, not new cases, pushed numbers up. García-Villamisar et al. (2017) add that those extra cases are probably not recycled ID labels.

Lai et al. (2013) found both ASD and ID rising together in Taiwan. That pattern matches D et al.’s U.S. finding and extends it across the Pacific—suggesting global trends rather than local coding games.

When you see a child with an autism label, do not assume ID has been ruled out. Flat ID rates mean many kids still carry both diagnoses or remain mislabelled. Always run full cognitive and adaptive tests. Update your file review checklist: look for past ID eligibility, re-test if scores are old, and write goals that target the true deficit—whether it’s social, cognitive, or both.

Diagnostic substitution is the reclassification of the same children under a different label over time. Applied to autism, the hypothesis is that many children who would once have been diagnosed with intellectual disability (ID) are now diagnosed with autism spectrum disorder (ASD) instead, as diagnostic criteria, awareness, and services have changed.

If that were the whole story, then part of the sharp rise in autism prevalence would not reflect a true increase in autism, only a shift in how the same children are counted. Testing the idea means checking whether ID prevalence fell as ASD prevalence rose, and whether the two changes line up.

Substitution is a real phenomenon in some places and periods, so the useful question is not whether it ever happens, but whether it is large enough to explain the overall autism increase.

The authors analyzed United States special-education data collected under the Individuals with Disabilities Education Act from 2000 to 2011, broken down by state and by each age from 6 to 17. When all states and ages were pooled together, diagnostic substitution looked plausible, because national ID counts fell as ASD counts rose.

But the disaggregated data told a different story. The nationwide decline in ID prevalence was driven mainly by about 15 states that together account for only about one-fourth of the U.S. school population. In the more populous states, ID prevalence stayed relatively constant while ASD prevalence climbed sharply.

Because ID did not decline in most places where autism rose, the pattern does not support diagnostic substitution as the explanation for the increase. The apparent link only emerged when aggregation hid the state-level detail.

This study is a caution against reading prevalence trends from pooled national totals. Aggregation can create a relationship that vanishes once you look within states, which is exactly what happened with the substitution hypothesis here.

For clinicians and researchers, the practical point is that the autism increase cannot be dismissed as mere relabeling of intellectual disability. Substitution may contribute in specific places, but it is a partial and local effect, not a general explanation for rising autism rates.