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Most investigators now think of the “autism epidemic” as a statistical composite generated by three overlapping forces:
Below is the evidence for each category and the share of the observed rise that the best studies attribute to it.
• Broader diagnostic criteria
– The category expanded from “infantile autism” in DSM-III (1980) to a heterogeneous “autism spectrum” that in DSM-IV (1994) added Asperger’s and PDD-NOS, then was consolidated in DSM-5 (2013). Each revision lowered the symptom threshold and raised prevalence estimates [13].
• Diagnostic substitution and re-labeling
– In California 1987-1994, 24 % of new ASD cases came from children who would previously have received an intellectual-disability label, and 56 % from other non-autism categories [5].
• Better screening, more services, and greater public awareness
– U.S. schools, pediatricians (universal screening recommended since 2007) and insurance coverage now actively look for ASD, so milder cases that once stayed invisible are counted [1][7].
• Changes in administrative reporting
– A population-based analysis of 1990–2010 birth cohorts concluded that 60 % (95 % CI, 48-71 %) of the rise was explained by changes in recording practices alone [4].
Taken together, these factors explain at least one-half and quite possibly most of the increase in diagnosed prevalence.
• Older parents
– Each 10-year increase in paternal age raises autism odds by ~20 %, and fathers ≥ 40 have roughly double the risk [9]. Maternal age ≥ 35 adds another 30 % relative risk [12]. Average parental ages have risen steadily since the 1980s, so age alone can account for an estimated 4-13 % of the prevalence growth [2].
• Improved survival of high-risk births
– Very pre-term infants (< 32 weeks) have ASD rates around 7 % versus 1–2 % in term births; rising survival of these infants contributes a few additional percentage points [10].
• Urbanisation, assortative mating among people with sub-clinical autistic traits, and smaller families may also incrementally increase true case numbers, but the effect sizes are small [15].
Comprehensive reviews find some reproducible associations (e.g., heavy prenatal valproate exposure, extreme air pollution peaks, organophosphate pesticides), but the overall evidence base is inconsistent and effect sizes are modest to moderate [8]. Large twin studies continue to show that heritability remains high (64-91 %) and has not changed across birth cohorts, implying that any new environmental causes are either weak or rare so far [3][6].
Notably, large epidemiologic studies repeatedly find no association between vaccines and autism; the idea does not survive controlled analysis and is rejected by the scientific literature [1][7].
Putting the pieces together
• U.S. prevalence rose from roughly 0.5 / 1 000 births in the 1960s to 28 / 1 000 (1 in 36) among 2012 births monitored by the CDC [7].
• Aggregate studies that adjust for known diagnostic and reporting artifacts usually explain 50–80 % of that rise; demographic changes explain another 10–25 %.
• The remaining fraction—if any—could reflect unidentified environmental factors or residual measurement error, but current data cannot cleanly separate the two.
In short, the rise in autism diagnoses is mostly a mirror of how, and how hard, we look for autism, amplified modestly by later parenthood and the survival of medically fragile infants. A large, rapid increase in biologically new autism is neither necessary nor well-supported by existing evidence.
Sources
[1] Arnold Kling, “On RFK, Jr. on Autism.” Emphasises that broadened definitions and better detection, not vaccines, drive the numbers. https://arnoldkling.substack.com/p/on-rfk-jr-on-autism
[2] Jill Escher, “Getting Real About Autism’s Exponential Explosion,” NCSA. Argues that diagnostic change explains much but insists some real increase remains, pointing to parental age and environmental factors. https://www.ncsautism.org/blog//autism-explosion-2024
[3] Colvert et al., “Heritability of Autism Spectrum Disorders: A Meta-Analysis of Twin Studies.” Finds heritability 64–91 %, stable across cohorts. https://acamh.onlinelibrary.wiley.com/doi/full/10.1111/jcpp.12499
[4] Hansen et al., “Explaining the Increase in the Prevalence of Autism Spectrum Disorders: The Proportion Attributable to Changes in Reporting Practices,” JAMA Pediatrics. Estimates ~60 % of the rise due to reporting. https://pubmed.ncbi.nlm.nih.gov/25365033/
[5] King & Bearman, “Diagnostic Change and the Increased Prevalence of Autism,” Int. J. Epidemiology. Shows diagnostic substitution accounts for a large share of California’s increase. https://pubmed.ncbi.nlm.nih.gov/19737791/
[6] Robinson et al., “Etiology of Autism Spectrum Disorders and Autistic Traits Over Time,” JAMA Psychiatry. Confirms stable heritability across birth years; little evidence for new environmental effects. https://pubmed.ncbi.nlm.nih.gov/32374377/
[7] Centers for Disease Control and Prevention, “Data and Statistics on Autism Spectrum Disorder.” Provides prevalence time-series and documents improved surveillance. https://www.cdc.gov/autism/data-research/index.html
[8] Bölte et al., “Environmental Risk Factors for Autism: An Evidence-Based Review,” Molecular Autism. Finds only limited, inconsistent environmental evidence. https://pubmed.ncbi.nlm.nih.gov/28331572/
[9] Reichenberg et al., “Advancing Paternal Age and Autism,” Arch. Gen. Psychiatry. Quantifies paternal-age effect. https://pubmed.ncbi.nlm.nih.gov/16953005/
[10] Agrawal et al., “Prevalence of ASD in Preterm Infants: A Meta-analysis,” Pediatrics. Shows elevated risk in very pre-term children. https://pubmed.ncbi.nlm.nih.gov/30076190/
[11] Croen et al., “The Changing Prevalence of Autism in California,” JADD. Early evidence of diagnostic growth in state data. https://pubmed.ncbi.nlm.nih.gov/12108622/
[12] Gardener et al., “Advancing Maternal Age Is Associated With Increasing Risk for Autism,” J. Am. Acad. Child & Adolescent Psychiatry. Meta-analysis of maternal age effect. https://pubmed.ncbi.nlm.nih.gov/22525954/
[13] Lord & Jones, “Update on Diagnostic Classification in Autism,” Current Opinion in Psychiatry. Reviews how DSM revisions altered prevalence. https://pmc.ncbi.nlm.nih.gov/articles/PMC4929984/
[14] Emil O. W. Kirkegaard, “What’s the deal with autism rates?” Blog analysing data and agreeing that most of the rise is diagnostic. https://www.cremieux.xyz/p/whats-the-deal-with-autism-rates
[15] NY Times Opinion (23 Jun 2025) “Why Autism Rates Increased.” Summarises consensus: measurement dominates, demographics contribute, environment unclear. https://www.nytimes.com/2025/06/23/opinion/why-autism-rates-increased.html