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Dr. Bob Sears on 1 in 36 Autism Rate

Ask_Dr_Sears_Trusted_Resource_For_ParentsFrom Pediatrician Dr. Bob Sears on the AskDrSears website:

The Centers for Disease Control just released their latest findings about autism:

  • In 2014 the rate of autism was 1 in 45 children
  • In 2015 it rose slightly to 1 in 43
  • In 2016, the number jumped up to 1 in 36 kids

For boys, the rate is 1 in 28. For girls, it’s 1 in 80.

The survey also found that the number of children diagnosed with any developmental disability increased from 1 in 17 kids to 1 in 14 – about 7% of all children.

It’s important to know that there are two ways in which the CDC researches autism rates. They originally began by gathering surveillance data on reported cases of autism from about 11 different states. They collected data on all 8 year old children who were diagnosed with autism, and extrapolated that to give a nationwide rate. That’s where the numbers 1 in 150, then 1 in 110, then 1 in 68 came from. The main drawback is that it took many years to research and report data this way, and the information is very old by the time we get it. For example, for kids born in 2004, the CDC had to wait until they were are 8 years old (2012), then take two years to gather the data on diagnosis rates, then publish it. So, we didn’t learn the rate of autism in these kids until 10 years after they are born.

Now the CDC has added a second method: the National Health Interview Survey. This nationwide parent survey tabulates health information on a variety of topics, and it gives us an immediate look at the rate of autism in kids now. And this is where these new numbers came from.

What I find unusual about the CDC report is that it states “there was not a statistically significant change in the prevalence of children ever diagnosed with autism spectrum disorder from 2014 to 2016.” However, the report shows it increased from 1 in 45 to 1 in 36. By trying to say that there is no significant increase, is the government hoping to reassure people that autism isn’t a significant problem? That the rising number of children with autism isn’t something that anyone has to worry about? Are they trying to avoid a panic?

Families affected by autism have long been waiting for our medical and governmental communities to step up and treat this rise as the single most significant pediatric health challenge of our time. After all, every other single medical condition with a rate of 1 in 36 gets billions in funding to solve (and most of these conditions are much less common). For autism, we’ve left most of the bill to each individual family so far.

Is it time we take autism seriously as a nation? Or do we all just keep assuming our own children and grandchildren will be among the 35 out of 36 who don’t have autism and look the other way?

Read the CDC National Health Interview Survey here

For more information on autism, visit our autism page.

Dr. Bob


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John Stone

I don’t understand why the US government is left making projections about this - surely they have the ability to track all the cases. Admittedly there are rather a lot of them, but whose fault is that?


Reading is Fundamental,

I am pretty sure that you are aware there are better solutions than that.

If you want to compare two different questionaires, you give the tests to two representative samples of the population you plan on testing, and then do a paired t test.

If for some reason being able to compare your rates to previous years accurately isn't even worth the effort to do that, then you add the new question that specifically asks about autism , to the old questionaire, so you are effectively mentioning autism twice. Not perfect, but extremely cheap.

If for some reason you want to make sure you have a semi-plausible out when rates that you wanted to stay stable show an increase, then you do neither of those things.

And after what you describe as a massive undertaking, we are still left with the question as to why the data describing boys rates of autism by year was somehow not put into the data tables.

The trouble is, that as John Stone points out, the people really exist, and statisticians can't wave a magic wand the way they can with numbers, to make actual people go away..

An inaccurate study, or one that can't be used to compare rates to previous years, isn't just marking time while people save face and quietly change things to prevent further harm. Instead, people look at studies, take them at face value, don't read the fine print, and then make policy decisions ( like adding more vaccines during pregnancy) and can't understand why the rates of autism keep increasing because a scientist they trusted told them everything is fine.

Numbers on paper translate into real peoples lives.

John Stone

Reading Is Fundamental

The trouble is we can quibble about this or that but autism is swamping the population: it has been gathering pace for three decades and our governments just don't care, even as it becoming economically unsustainable.

Reading Is Fundamental
If you felt that a health condition was important to track, and you wanted to change the words on the questionaire, *( which is what they did, asked a specific question about autism diagnosis instead of including it in a question that listed other disorders too) wouldn't you run a comparison with both questionaires to indicate whether changing the wording on the questionaire actually caused any significant difference in responses or not?

You mean do the NHIS twice? No, I wouldn't. It's a massive undertaking. The technical aspects are set out in excruciating detail, e.g., here for 2014 (see p. 52). The variable CCONDL06 has been replaced by the variable AUTISM. Do you have any specific complaint about the wording of the item?

Dennis Picknett

1 in 36 is just 'business as normal' as Mary Holland says. So it's ALWAYS been 1 in 36, since the dawn of time, eh? And it's all down to our new-found razor-sharp powers of observation which were hitherto sadly absent.
The question is, can we expect our observational powers to increase further? They certainly appear to be on an upward exponential curve. Extrapolating to 2032 would give us such fabulous observational powers that we could detect 1 in 2 ASD ratio. Problem is, why isn't our new sensitivity also revealing a host of other conditions we've been blind to all along? And why aren't we seeing exponential increases in heart disease, lung cancer, osteoarthritis, scabies and ingrowing toenails?


Hi Greg,

Thanks for your kind words ( and I am not a statistician, so please anyone else chime in!). Yes, adding the numbers up it does seem like there is some overlap between the three categories. I also suspect that environmental and vaccine injury harm is going to show up in multiple ways, not all of them related to autism.
My personal belief in the good faith/integrity of these studies went out the window with the confession by Dr Thompson that data was dumped in trash cans to hide significance.Hard to get past that.

What actually really strikes me about the data though, is what is not included.
A couple of questions for RIF.
If you felt that a health condition was important to track, and you wanted to change the words on the questionaire, *( which is what they did, asked a specific question about autism diagnosis instead of including it in a question that listed other disorders too) wouldn't you run a comparison with both questionaires to indicate whether changing the wording on the questionaire actually caused any significant difference in responses or not?

Why would they not do that? It's pretty basic science.

Now let us imagine for a moment that a scientist was seriously interested in finding out whether an increase was significant or not. They would want to look at what happened to the sub population that showed the most increase, wouldn't they?
(Boys, specific races.)
Because girls have a lower rate of autism, you could expect that girls would reduce the chance of finding significance when the two groups were combined. So , why would you not release the specific data showing the rates of just boys for 2014, 2015, and 2016. It had to have been obtained to get the data on the tables. So why wasn't it included on the 5 pages of tables that you provided for us?
Why would the specific groups that are most likely to be able to prove significance over the three year period only be listed with an overall 2014-2016 combined rate? Why no breakdown year by year? They were that concerned with saving virtual paper?

It comes across as questionable, imo. Would you have designed a study that specifically did not provide a table showing data on the most effected groups by year? Would you yourself, designing a study, have combined girls and boys if you wanted to identify whether an increase in the rate of boys was significant? Maybe this table is somewhere else. In which case, it would be a pretty important one, don't you agree?

By the way, there does appear to be a linear trend. It just hasn't reached the level of 95% significance yet.

In terms of your comment that nothing has changed, so why would the rates have changed, you might want to consider the differences in the immunization schedule over the years.
What recommendations have changed for pregnant women during the time period that would have effected these kids?
Well, in 2006, the CDC strengthened the recommendation for a flu shot in pregnancy. (Kids who would have been approx 8 and under in 2014, 10 and under in 2016 ) By the way, that is a class C risk category shot for pregnant women.
Then in 2011, the TDAP shot in pregnancy after 20 weeks was also recommended, (kids who would be approx 3 years old in 2014, approx 5, 4, and 3 in 2016) Also a class C pregnancy risk category shot.
2008, I think is when it a double dose of influenza was required in a child's first year. ( approx 6 year olds in 2014,)
Many states have also made it much harder even for families who have previously suffered from vaccine injury to refuse shots for their kids.

Also, more and more of the people giving birth will be the first generation of highly vaccinated ( and the first generation who have had to process high injected amounts of aluminium) in the U.S. Will their children already be more susceptible to autoimmune and health problems as a result? We already know environmental toxins given to the mother and father can effect ongoing generations in other animals.

Even if the rates never increased from the current rates or even the 2011 rates, that is still a huge portion of the population, isn't it? Of course given the happy go lucky way they continue to add immune system insults to new babies, regardless of family history, one has to wonder what rates we may be looking at in the future.


I guess that the people inside the government agencies do not lead, but follow.
So, here we are. Many of the general population - and that is what it takes many of us so painfully, slowly beginning to believe differently and thus dragging the kicking and screaming people along - that was suppose to lead.

Jeannette Bishop

I guess this is the leadership persona of the CDC when they have an epidemic that is not easily assigned to vaccination for treatment (or perhaps rather highly suspected if not demonstrated by research at this point to involve a vaccination role).

Imagine a three year survey finding an increase in Guillain-Barre outcomes post influenza-like infections from 1 case for every 45 infections to 1 in 36 and instead of plastering these results all over the corporate media, screaming for increased uptake in the flu shot, pneumonia shots, and calling for funding for several other vaccines in development, they settle on the statistical significance, or lack thereof, in their survey.

Pediatricians waiting for marching orders from on high need to catch on to the fact that they're not going to get appropriate direction from the federal agencies, particularly in this matter, and parents assuming that all this infrastructure protects your babies, need to catch on, too, and probably run from most pediatricians generally, unless willing to risk being enlightened the way most of us here have been enlightened.

John Stone

I can’t remember what year it was at the beginning of the last decade when the UK Department of Health sent me the latest article by Eric Fombonne arguing that the rise in autism was an artefact of altering criteria, when it was perfectly apparent to those of us struggling for services on the ground that the rise in autism was a rise in autism. I wrote to them that it was a false argument while unknown to me Mark Blaxill was writing an extremely similar critique of it on the other side of the Atlantic (better, of course). They can always point to inadequate or inconsistent methodology but in the real world they can’t make the problem go away.

John Stone


Yes, sampling methods may change but the trend continues to steeple - for instance in Scotland the figure went up from I in 86 in 2011 to 1 in 51 in 2016. These are absolute figures, in the sense that they are number of pupils in the system divided by the number of pupils with an ASD diagnosis, not projections. However, the position is worse than it looks because many children at the younger end will still lack a diagnosis. Indeed, we know the diagnostic and support services are breaking down from the influx. The stories, where they are reported focus perversely on the lack of services and not on the unprecedented scale of the influx. In London, as I was pointing out in May, in 5 boroughs they had services to diagnose 750 children a year but suddenly they had 1500 cases: that could be 10,000 cases a year for the whole of London with a birthrate of 90k. While these extraordinary events happen it is scarcely a defence of the bureaucracy that we don't know all the answers because they employ weak or inconsistent methodology.

Reading Is Fundamental
RIF is saying compare the three data points only from 2014, 2015 , and 2016. As Dr Taught O'logy is pointing out, we have data going from before then and given what that looks like, it is extremely likely that compared to 2013 data, we have indeed had a significant increase.

Yes, but the reason these three NHIS estimates were presented was because they were obtained with uniform methodology, and the question to hand re Dr. Bob was whether the current report showed a significan linear trend (no) or absolute increase (extract a p-value for the CI overlap).

Do you really think that ASD had a sudden spike from 1 in 80 during the period from 2011 to 2013 to 1 in 43 a year later? What happened aside from sampling method? Why did "Other developmental delay" show the opposite? Why is the baseline flat?

John Stone


Perhaps, it is the wrong way to look at it. If the CDC wants to find out about something it finds out. If the study method was too blunt to find out whether autism had really risen by half a percent among schoolchildren in two years they are not really trying. If they really wanted to know about it they would find out in 5 minutes about every single case. Ed Yazbak put it memorably in his article eleven years ago "The CDC, Spinach and Autism"

The just continue to ruthlessly waste time as the position gets daily worse.


Hi Hera,

Further to my last comment about the CDC's disingenuity with this survey, are they also misleading suggesting they found a significant increase in kids diagnosed with other disabilities that weren't autism, when it's actually a significant increase in autistic kids being diagnosed with additional disabilities?

John, if you get a chance, let me know if I am thinking things correctly.  I am finding a further problem with this survey.

I already mentioned how perplexing it is for the CDC to claim with this survey there was no significant increase in autism prevalence over the three years (2014-2016) when the actual rate went from 1 in 45 in 2014 to 1 in 36 in 2016, yet a significant increase for other disabilities is claimed when the actual increase went from 1 in 17 in 2014 to a mere 1 in 14 in 2016.  Yet, what does the claim that there was a significant increase in other disabilities really mean?  Taken at face value it seems to be suggesting that that there was a significant increase in kids being diagnosed with other disabilities -- AND WHO DIDN'T HAVE AUTISM.  Reviewing the survey, I found a certain 'quibble' in the data that leads me to question this leap, particularly the emphasised clause.

Consider, for example, a survey where parents were interviewed to report on the health outcomes of 100 kids:  In the first year of the survey, of 100 kids, 2 were found to have autism, and 3 kids were diagnosed with other disabilities that weren't autism.  Repeating the survey in the second year, 3 kids were diagnosed with autism and 9 were diagnosed with other disabilities that weren't autism.  Is it then not accurate to conclude that there was a significant increase in kids being diagnosed with autism -- AND WHO DIDN'T HAVE AUTISM?

It would be wrong to jump to that conclusion if further perusing the data it was found that the kids being diagnosed with other disabilities also had autism.  In that case, the proper conclusion would be that there was a significant increase in autistic kids being diagnosed with other disabilities.  Consider when we re-examine this hypothetical survey's data it is found that in year one the tally for total kids with a disability is 4, and in the second year it is 6.  Yet, how can this be?  In the first year there are 2 autistic kids, and 3 with other disabilities so the total should be 5 -- not 4!.  Likewise in the second year, there are  3 kids with autism and 9 with other disabilities, so the total should be 12 -- not 6. 

The answer to this puzzle is the categories are not exclusive, and there is overlapping going on.  The same kids that were found to have autism were the same kids being diagnosed with other issues.  It's not a case of there being a significant increase in kids who didn't have autism being diagnosed with other issues, but healthcare officials 'significantly' slapping more autistic kids with other diagnosis over the years.

Reviewing the actual CDC survey, the data seems to suggest this overlapping, and indicating that the categories are also not exclusive.  For instance, for 2014 it reports percentages of 2.24 kids diagnosed with autism, 1.10 diagnosed with intellectual disabilities, 3.57 diagnosed
with 'Other development delay', and the total it provides for 'Developmental disability' which it describes as a composite for all the disabilities is 5.76. Yet, how can this be?  Adding the categories separately the total or 'composite' should be 6.91.  This seems to  indicate that there is overlapping of the categories, they're not exclusive! Some of the kids that were diagnosed with autism were the same ones being found to have other issues.  This same pattern can be found for 2015 and 2016.

Interestingly, the previous survey that reported the 1 in 45 prevalence rate, specified that the category of 'other developmental delay' included kids diagnosed with autism and other issues.  The overlapping was acknowledged.  Things, however, remains murky with this current survey.  The overlapping is not acknowledged and I don't know whether it was accounted for.  On the surface it appears as yet another example of the CDC attempting to mislead -- and in this case pointing to a bogus finding that's really not what it's implied to be.  



Thanks so much Hera!  Your explanation seems to be in line in with what I was thinking.  A few threads down I also wrote to John discussing the effect that sample size also plays into this.  I consider that the CDC may be guilty of two disingenuous strikes, first, what you're pointing out that they're claiming no significant increase in autism rates over the three years (2014 -2016), and while ignoring the 2013 figures that does indeed suggest a significant increase trend. Second, they fail to address that even for the period from 2014-2016 the finding of no significant increase may have merely been due from the small size.  On this point, let me know if my thinking below is correct.

John, I am not an expert on statistics and I hope someone will correct me if I am thinking this wrong, but I think the CDC is using statistical terminology to confuse and suggest that there was no overall increase in autism rates over those three years, and when that wasn't the case -- there was. Consider that the term 'significant' has a precise statistical definition, which is a 'real' effect that is not due from chance.  Significant results are contingent on sample size.  The larger the sample size, the more likely you are to get a significant result. 

How does this pertain to study?  It means there was an increase, just that the sample size was not large enough to determine whether it was a significant one, not occurring due to  chance.  Yet, this is a far cry from saying there wasn't.  Consider the example where you walk outside and calculate an autism rate for the first 100 kids that you run into at 3 in 100.  Your sample size may be too small to say that that result is significant, but it doesn't mean there is no result.  You could repeat the exercise with a million kids -- a sample size large enough to obtain a significant finding -- and still end up with a rate of 3 autistic kids per 100.

For kids with 'any disability' they were likely dealing with a large enough sample size, and, hence, a significant result was yielded.  Yet, strictly speaking, again, we're not talking about the size of the increase or whether it is greater than the one for increasing autism rates -- but whether it was significant.


Hi Greg;

I haven't done statistics for a while, so if anyone else wants to correct or add to this that would be great.
From the data Reading is Fundamental( hope its ok if I shorten this name to RIF) added

2014 2.24 (1.90–2.63)
2015 2.41 (2.01–2.85)
2016 2.76 (2.29–3.29)
We can see that the average 2.24 (2014) 2.41 (2015) 2.76 (2016) is going up every year, which is suggestive.
However, when statisticians give an average, what they actually say is that the average may not represent the true figure, so they say that they are 95% certain that the real number lies between a stretch of numbers .
For example, in 2014, they are 95% sure that the real number is between 1.90 and 2.63.
In 2016, they are 95% sure that the real number lies between 2.29 and 3.29

So theoretically , say if the "real" number is 2.30, that would still lie between the ranges for both years.
However, you can have an overlap of as much as 25% in the two ranges, and still have a statistically significant increase. It requires some math to work out if it is significant or not.

RIF is saying compare the three data points only from 2014, 2015 , and 2016. As
Dr Taught O'logy is pointing out, we have data going from before then and given what that looks like, it is extremely likely that compared to 2013 data, we have indeed had a significant increase.

And indeed this article from cdc .gov indicates that the rates have increased to a level that achieves statistical significance from 2013.
From the article;

The estimated ASD prevalence was
2.24% (1 in 45) in 2014, while
averaging 1.25% (1 in 80) from 2011
through 2013—a significant increase
(p < 0.001)

So, while I haven't done the math to say if between 2014-2016 there was a statistically significant increase in autism rates, we can certainly say that between 2013 and 2016 there has been a statistically significant increase.
Hope this is helpful/useful.

Dr Taught O’Logy

Reading is Fundamental

You are confusing yourself. I see no compelling evidence that trend hasn’t continued upwards as it has done every year for the last 30 years. It may be that the data isn’t definitive but it is what it points to - you can make out that it is uncertain but you can’t make out it is level.

Greg@Reading Is Fundamental

Reading Is Fundamental,

I am also quite puzzled at how the CDC can claim no significant increase. I am sure I am not the only one here who is not an expert on statistic. I think many here would appreciate it if you could walk us through the statistics and how it pertains to CI and the finding of no significant increase.

Reading Is Fundamental
Three data points?

Yes, the 2014, 2015, and 2016 NHIS results, unless you want to reanalyze the raw data, in which case you need to understand the original analysis. Note also that the 2014 and 2016 CIs do overlap; it's the sample estimates that don't. The question, if this is what one wants to point at, is formal quantification of significance.

I think a p-value can be extracted from the CIs and SEs by means of an unpaired t-test, but I can't do it on the spur of the moment. You could just E-mail them, as could have Dr. Bob.

Dr Taught O'Logy

Reading Is Fundamental

Well, there is overlap in those too - albeit less - but there more or less has to be because you are dealing with a 15 year cohort from which two years have been removed at one end and two years added at the other, so 13 years are the same albeit they will likely have accumulated new diagnoses. It is a way of measuring which greatly slows the detection of changes in trend.

Three data points? What about all those other data points going back 30 years?

Reading Is Fundamental
Wrong. Of course there is overlap between the three years (there would have to be an almost impossible jump for there not to be) but the 2016 figure is outside the range of 2014, and vica versa.

No, there would not have to be an "almost impossible jump": Note "Other developmental delay" and "Developmental disability." In any event, the point is whether there's a significant linear trend (and there are only three data points). Compare here.


As an old school mate of mine told me last summer
It is our kids, we don't want to tell others that there is something wrong with them to other people.

This is after I picked up on a small little comment that most people would have let go. That is all it took for him to open up. What a horrible time he has had with his son.

So there is 1 out of 36 kids through out our community and parents hate to say there is something wrong with their kids. So, the CDC has used parental love and pride ot keep the lid on just how bad it really is.

Dr Taught O'Logy

Reading is Fundamental

Wrong. Of course there is overlap between the three years (there would have to be an almost impossible jump for there not to be) but the 2016 figure is outside the range of 2014, and vica versa.

Angus Files

And then how much disabled kids/adults are costing ...

Pharma For Prison


Reading Is Fundamental

"What I find unusual about the CDC report is that it states 'there was not a statistically significant change in the prevalence of children ever diagnosed with autism spectrum disorder from 2014 to 2016.'"

This again? There wasn't. The data table is sitting right there:

The confidence intervals overlap. If Dr. Bob can't figure this out, maybe he should do some remedial work on basic statistics.

Hans Litten

Posted by: Mary S. Holland | December 15, 2017 at 10:16 AM

They are all going to prison for this damn outrage.

Mary S. Holland

This new study on autism prevalence from the CDC is important. Thanks to Dr. Sears for writing about it and to AoA for republishing it.

With 1 in 36 children with an ASD diagnosis, it's obvious that this condition is affecting virtually every classroom and community in the country. And yet, with the issue becoming ever more relevant, the publicity about the escalating rate has all but disappeared. 1 in 500 was news; 1 in 150 was news; 1 in 68 was news; but 1 in 36 is business as usual.

The government and media's apparent lack of concern about rising autism rates has always been shocking to all who read Age of Autism. But the latest silence almost defies comprehension. As Anne Dachel and other instructive writers here so frequently ask, when will the public conversation start? 1 in 20? 1 in 15? 1 in 10? 1 in 5? 1 in 2? Never? It's hard to comprehend.


Yes, the FedGov, and especially the CDC, has a vested interest in NOT admitting the seriousness and extent of rising autism rates. The rate of increase is already so high, that there's no profit in saying it's higher than it is, or even admitting it's as bad as it is. What seems clear to me, as an interested, fairly well-informed observer, is that *SOME* vaxxed kids develop a type of auto-immune response, which results in a type of brain inflammation, which leads to an ASD "diagnosis". The trend in both FedGov, and CDC, is mandatory forced vaxxing, which profit$ both PhRMA, and the FedGov/CDC. And which will lead to inevitable higher autism rates. No, they do NOT care about your children. Please stop fooling yourself that they do. If they truly cared, why is there so little legitimate research going on....????....
(c)2017, Tom Clancy, Jr., *NON-fiction

bob moffit

'What I find unusual about the CDC report is that it states “there was not a statistically significant change in the prevalence of children ever diagnosed with autism spectrum disorder from 2014 to 2016.”

If memory serves me right .. Dr William Thompson .. who has been denied ANY hearing by Congress .. explained how easy it WAS .. (the cynic in me believes it still IS) .. for the CDC to claim there was "no statistically significant change in the prevalence of BLACK children"

Just curious .. since it is claimed .. "for boys, the rate is 1 in 28. For girls, it’s 1 in 80 .. and .. developmental disability increased from 1 in 17 kids to 1 in 14"

If Dr Thompson's information is correct and black children are at "significantly higher risk" of autism .. are any efforts by the CDC to examine if a particular "race" of boys and girls that either confirms or denies Dr. Thompson's allegations?

In other words .. is the rate of 1 in 28 boys the same for black boys" as a group?

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