Let the speculation begin about why autism rates have increased!
Is it in the water? The air? The genes? The blood? The food?
News reports about higher rates of autism were widespread in early December of 2021. Many reports seem sensational, even if not alarming. I'd like to take a look at those reports...But, let's get the facts, first.
At the root of the current reports is a publication from 1 December 2021 by the U.S. Center for Disease Control and Prevention; Let's start there. That report indicated that
• About 1 in 44 children has been identified with autism spectrum disorder (ASD) according to estimates from CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network. [Read article]
• ASD is reported to occur in all racial, ethnic, and socioeconomic groups. [Read article]
• ASD is more than 4 times more common among boys than among girls. [Read article]
• About 1 in 6 (17%) children aged 3–17 years were diagnosed with a developmental disability, as reported by parents, during a study period of 2009-2017. These included autism, attention-deficit/hyperactivity disorder, blindness, and cerebral palsy, among others. [Read summary]
As the bullets show, there is a lot of content in this CDC report. It’s noteworthy, for example, that it reflects a previously not-found balance among ethnic groups. In this post, I want to focus primarily on the estimates of identification rates.
One can find posts about the CDC's findings plastered on lots (and lots) of sites around the Intertubes. Some are probably more credible than others. Here is a just a selection (Note: I didn't use a systematic method to select the items in the following catalogue; I just snagged a few so I could illustrate the range of interpretations).
Lindsey Tann of the Associated Press reported about the increased identification rate under the headline, “New data suggests [sic] 1 in 44 US children affected by autism”
The eminent Johns Hopkins School of health touted its participation in the research effort.
The widely read “WebMD” weighed in with a post about “record-breaking autism rates!”
MedScape, another presumably reputable medical source, provided “Record-Breaking Autism Rates Reported With New CDC Criteria.”
Autism Speaks, advanced a treatment under the heading, “CDC estimate on autism prevalence increases by nearly 10 percent, to 1 in 54 children in the U.S.”
Yahoo, citing PRNewswire, reported that “Autism Prevalence is Now 1 in 44, Signifying the Eighth Increase in Prevalence Rates Reported by the CDC Since 2000.”
[If someone is looking for an interesting side project, consider identifying a representative sample of these press reports and compare the wording used across them. Then, see if you can identify the source that they used to get that wording. Of course, pretty much all of them mention the CDC, but did they draw on the original?]
What data are the CDC using to publish its findings, findings that led to these news reports?
Well, the data are pretty well established...it's the spin that matters! The CDC reported about work by the Autism and Developmental Disabilities Monitoring Network (ADDM). ADDM collects data from 11 sites around the US. Each site periodically reports the number of cases in its catchment area. That is, the ADDM sites collect their data and push their observations up to the ADDM central group. The ADDM Network adds up all the data from the sites and reports them, usually with a good degree of statistical analysis. For example, do the data reflect increases? Hos do the reports differ by gender? Age group? Etc.
Here's how the CDC described the report:
Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD. This report focuses on the prevalence and characteristics of ASD among children aged 8 years in 2018 whose parents or guardians lived in 11 ADDM Network sites in the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. In 2018, children met the case definition if their records documented 1) an ASD diagnostic statement in an evaluation (diagnosis), 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code.
So, the ADDM data don't precisely tell how many kids actually have autism. Those data tell how many cases have been diagnosed by diagnosticians in those 11 states. [There’s a great opportunity to wander off into understanding prevalence, incidence, and such, but I’m staying on the path here; for those who would like to wander, start by reading Forness et al. (2011) and McKenzie et al. (2016).] Ideally, diagnoses would be based on some objective data (e.g., if a male individual has > 10,000 white blood cells per milliliter of blood, that's a strong indicator of infection). Diagnosis of autism, even when instruments such as ADOS-2 (Lord et al., 2012) are used, has a more subjective character; the diagnostician must make judgements. There's room for diagnosticians to use “clinical judgement.” Take a look at the National Institutes for Health (2020) description of the criteria for identifying autism in the section of this post headed by “Souces.”
What's the evidence of changes over time? To analyze increases over time, one (or the ADDM network team) needs data collected repeatedly over many years using the same data collection methods. What was the number of identifications in Site 1 in 1960, in Site 1 in 1970, in Site 1 in 1980? ...in Site 1 in 2018? What was the number of identifications in Site 2 in 1960, in Site 2 in 1970, in Site 2 in 1980? ...in Site 2 in 2018? What was the number of identifications in Site 9 in 1960, in Site 9 in 1970, in Site 9 in 1980? ...in Site 9 in 2018?
Suppose for a moment, that the diagnostic criteria used at Site 1 are different from those used at Site 2? They may be quite similar, differing just a little, but the rate of diagnosis would probably vary between the two sites. In fact, the 11 sites in the ADDM study report different prevalence, as reflected in the following figure:
Further, suppose that the diagnostic criteria used in 1960 differ from the criteria used in 2020. Yep, the identification rates would probably differ.
The ADDM takes steps to correct for such problems, of course. For example, the report noted difference identification rates based on whether cases were diagnosed using an ICD code, special education category, or a clinical diagnosis. (Fascinating! The different colors in the preceding bar graph reflect different identification methods; also, though, see the CDC slide deck for a venn diagram.)
But knowing this potential for variation, we have to be sure to consider each measurement as essentially a snapshot of of how many children were identified at that time in that area. Any comparisons across time or location need to be tempered by such knowledge.
The U. S. CDC described the the ADDM system carefully. Note the caution in the characterization of it that I quoted previously. See how it says “children aged 8 years,” “In 2018,” “met the case defintion if...?”
Changes over time
But, who can resist? If we have those data, we can plot a graph showing rates at different times. That is we can show that in the 1960s, autism was diagnosed quite rarely. In 2020, it is diagnosed much more frequently...maybe 1 child out of 40-some in the 2018 data. And that's a helluva a lot more than the 1 child in 150 in the data for the year 2000. Here's one such graph, as published by Autism Speaks:
In fact, the graph pretty accurately represents the change over time (i.e., “growth”) in the rate at which autism is diagnosed. And that linear trend is emphasized by including the red line with an arrow. But the graphic doesn't tell anything about whether the same diagnostic standards were used in identifying cases. So, caveat reader!
Personal side light here. In the 1960s, I worked directly with some children who had been identified as having “autism.” Others with whom I worked were said to have “childhood schizophrenia.” Still others were labelled “Educationally Handicapped.”
The children (5-12 years of age) identified as having autism had severe communication, social, and behavioral problems. They simply didn't speak in an understandable way or show understanding of verbal directions. They rarely engaged in intra-human interactions. They spent a lot of their time self-stimulating (e.g., rocking) and, sadly, injuring themselves (banging their heads, biting their wrists, etc.).
Some other children in our classrooms had different behavior. They could speak words as clearly as a bell rings, but the words were nonsense—echoes of what seemed to be previously heard conversations. They were not as socially isolated as some more severely involved children, but they still would spend time on the playground, for example, talking while there was no one to listen, wiggling their fingers, and strutting about in stereotypic ways.
Were the children in the latter group “autistic?” We debated variations on the term: “Autistic-like?” “Autistoid?” And, note that Asperger's Syndrome wasn't even in the mix then.
Of course, as my career has progressed, what was once called autism has come to be known by some as "Level 3 autism" The other two levels are less severed, but still require some special support. And, popularly, all three are ordered along a range that is popularly called "the spectrum" that it ranges from Level 1 to Level 3 in support requirements.
Back to the chase here: Do these data mean that more children are catching autism these days? Nope.
These data show that diagnosticians are catching more cases. Indeed, the data probably reflect greater sensitivity, greater responsiveness on the part of diagnosticians. The spectrum is getting wider, probably not at its severe end, but at the Level 1 end.
Now, is in the food, blood, genes…? Who knows. First let’s just reflect on how we know rates are increasing!
Forness, S. R., Freeman, S. F., Paparella, T., Kauffman, J. M., & Walker, H. M. (2012). Special education implications of point and cumulative prevalence for children with emotional or behavioral disorders. Journal of Emotional and Behavioral Disorders, 20(1), 4-18. https://doi.org/10.1177%2F1063426611401624
Lord, C., Rutter, M., DiLavore, P. C., Risi, S., Gotham, K., & Bishop, S. L. (2012). Autism Diagnostic Observation Schedule (2nd ed.). Western Psychological Services. https://www.wpspublish.com/ados-2-autism-diagnostic-observation-schedule-second-edition
Maenner M. J., Shaw K. A., Bakian A. V., Bilder, D. A., Durkin, M. S., Esler, A., Furnier, S. M., Hallas, L., Hall-Lande, J., Hudson, A., Hughes, M. H., Patrick, M., Pierce, K., Poynter, J. N., Salinas, A., Shenouda, J., Vehorn,A., Warren, Z., Constantino, J. N.,...Cogswell, M. E. (2021, 3 December). Prevalence and characteristics of autism spectrum disorder among children aged 8 years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018. Morbidity and Mortality Weekly Surveillance Summaries, 70(11), 1–16. http://dx.doi.org/10.15585/mmwr.ss7011a1
McKenzie, K., Milton, M., Smith, G., & Ouellette-Kuntz, H. (2016). Systematic review of the prevalence and incidence of intellectual disabilities: Current trends and issues. Current Developmental Disorders Reports, 3, 104–115. https://doi.org/10.1007/s40474-016-0085-7
National Institutes for Health. (2020, 29 June). "Diagnostic Criteria for 299.00 Autism Spectrum Disorder"
To meet diagnostic criteria for ASD according to DSM-5, a child must have persistent deficits in each of three areas of social communication and interaction (see A.1. through A.3. below) plus at least two of four types of restricted, repetitive behaviors (see B.1. through B.4. below [not copied here—JohnL]).
Persistent deficits in social communication and social interaction across multiple contexts, as manifested by the following, currently or by history (examples are illustrative, not exhaustive; see text):
Deficits in social-emotional reciprocity, ranging, for example, from abnormal social approach and failure of normal back-and-forth conversation; to reduced sharing of interests, emotions, or affect; to failure to initiate or respond to social interactions.
Deficits in nonverbal communicative behaviors used for social interaction, ranging, for example, from poorly integrated verbal and nonverbal communication; to abnormalities in eye contact and body language or deficits in understanding and use of gestures; to a total lack of facial expressions and nonverbal communication.
Deficits in developing, maintaining, and understand relationships, ranging, for example, from difficulties adjusting behavior to suit various social contexts; to difficulties in sharing imaginative play or in making friends; to absence of interest in peers.