Long-time readers will recall the epidemiologist fallacy is a shotgun marriage of the ecological fallacy and wee p-values. Make that and/or confidence intervals.
For confidence intervals are equivalent to p-values in use and interpretation. Meaning they should not be used, just as p-values should never be used.
The ecological fallacy is to conclude X is a cause of Y when X has not been measured. You’d think such a thing never happens. After all, what scientist would say, or hint, “I conclude pesticides cause autism, but I never measured pesticide exposure”? Sounds silly, n’est-ce pas?
Enter the paper “Prenatal and infant exposure to ambient pesticides and autism spectrum disorder in children: population based case-control study” in BMJ by Ondine S von Ehrenstein and a bunch of others.
First comes the record search:
2961 individuals with a diagnosis of autism spectrum disorder based on [DSMV IV], including 445 with intellectual disability comorbidity, were identified through records maintained at the California Department of Developmental Services and linked to their birth records. Controls derived from birth records were matched to cases 10:1 by sex and birth year.
That’s fine, more or less. But this is not:
Data from California state mandated Pesticide Use Reporting were integrated into a geographic information system tool to estimate prenatal and infant exposures to pesticides (measured as pounds of pesticides applied per acre/month within 2000 m from the maternal residence). 11 high use pesticides were selected for examination a priori according to previous evidence of neurodevelopmental toxicity in vivo or in vitro (exposure defined as ever v [sic] never for each pesticide during specific developmental periods).
Let me translate. A highly inaccurate guessing machine said “This much of this pesticide was used within 2km of this person’s home address, even though people aren’t always around their home address.”
Then von Ehrenstein said, or rather implied, “That guess is the exposure.”
Enter the regression models to “control” for this exposure, among other things:
Risk of autism spectrum disorder was associated with prenatal exposure to glyphosate (odds ratio 1.16, 95% confidence interval 1.06 to 1.27)…diazinon (1.11, 1.01 to 1.21), malathion (1.11, 1.01 to 1.22), avermectin (1.12, 1.04 to 1.22)… For autism spectrum disorder with intellectual disability, estimated odds ratios were higher (by about 30%) for prenatal exposure to glyphosate (1.33, 1.05 to 1.69)…; exposure in the first year of life increased the odds for the disorder with comorbid intellectual disability by up to 50% for some pesticide substances.
Now everybody, and I mean absolutely everybody, even the most ardent die-hard frequentist ideologue, treats confidence intervals as Bayesian credible intervals. Which is to say, nobody treats confidence intervals according to frequentist theory. The reason is simple. Because the only thing you are allowed to say about any confidence interval is “either the true value of the parameter lies within or it does not.” Which is a useless tautology.
However, since nobody uses confidence intervals as confidence intervals, but instead all use them as credible intervals, it is unfair to criticize confidence intervals as confidence intervals. Let’s instead criticize them as credible intervals.
We can ignore here the “control” of their models for other things, though it’s very important (because no control of any kind took place). Let’s just look at the non-exposure-exposure. Risk of autism was associated with prenatal exposure to glyphosate with a 95% interval 1.06 to 1.27.
That is an estimate for a parameter in a model, but everybody takes it to be the risk of autism. What we really want is the probability of autism given the risk. What we got is a remark about a non-existent parameter in a model, the confidence (or credibility) of which is necessarily higher than in the probability.
Meaning, even if the exposure is real, we should not be as confident about developing autism as the interval leads us to believe.
Unfortunately, without the data I can’t tell you what the non-exposure-exposure probability would be, but I’m guessing—and it’s only a wild guess—that it’s not too different than the probability of autism without the non-exposure-exposure. It will be higher, but not a lot higher.
That is before taking account of the non-exposure-exposure. The exposure was only a guess, meaning there is uncertainty in actual exposure, an uncertainty that ought to be accounted for in the model, but which was not. This means that the difference between the non-exposure-exposure probability and the non-exposure-non-exposure probability is even smaller still, and possibly non-existent.
Meaning we can’t such much of anything about pesticides and autism.
In order to become the epidemiologist fallacy the charge of cause must have been made. Was it? Yes, indirectly. First by having discussions in the paper of how exposure might cause autism, and second by concluding this:
Findings suggest that an offspring’s risk of autism spectrum disorder increases following prenatal exposure to ambient pesticides within 2000 m of their mother’s residence during pregnancy, compared with offspring of women from the same agricultural region without such exposure.
To say “the” risk increases (as if risk existed) is to hint with a heavy wink-wink that pesticides indeed were implicated as a cause.
Even though they were never measured. Any other measure that was highly correlated with the exposure guess—say, distance from grocery stores, a proxy of being near a farmer’s field—would give the similar results, even though it would be obvious grocery stores were not causing autism.
The real question is, “Do pesticides cause autism?” I have no idea. I wouldn’t say no. I wouldn’t want my kid or me exposed to them. But I make that judgement without the evidence from this paper, which is unhelpful and misleading—even though the mistakes made are extremely common.
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Do they mention anywhere in the paper that glyphosate isn’t a pesticide but an herbicide? It’s the main ingredient in Round-Up.
Prof Briggs, Your post comes at a propitious time. Just yesterday I received from a university I teach at their magazine. Front cover: GLOBAL CRISIS. Environmental pollution claims more than 9 million lives a year. In the article, “In 2015, pollution and the diseases it can cause–cancer, stroke, heart and lung disease…attention disorders, autism..are estimated to have cost the world about $4.6 trillion and killed 9 million people.” Another: ‘fatalities attributed to indoor air pollution claim–7 million a year..” (so 7 ex 9 million are tent and hut fatalities?)
You get the picture.
I went looking for evidence. A doctor mentioned in the piece is Philip Landrigan, an epidemiology guru. An Oct 9, 2017 article in WaPo cites the same numbers, as well as the same doctor, and was probably at least partly a source for the magazine piece. How lies get spread, right?
I was tempted to pen a sardonic letter to the writer of the magazine article, you know, you say person X died of a heart attack, but person X, in your telling, died from pollution. Can you tell me how you or anyone in your coven isolated the particular variable? The murk! It would be like talking to a committed rock.
Keep up the good work in what I sometimes feel is a losing battle. In the end, irrationality almost always wins out. Fight on!!!
Any study can prove anything if the grant is sufficiently large.
For fun, I’ve taken to addressing any “X causes autism” argument with a counter of “How do you know that Autism isn’t simply the next step on our evolutionary journey?”
Yeah, its a specious and silly argument … but you’d be amazed how many people it shuts up.
I’m still waiting for the epidemiologists to explain how talcum powder causes ovarian cancer. I want to know the causal mechanism and etiology. I can’t find it.
Glyphosate is a herbicide as opposed to a pesticide. There is a difference.
Glyphosate works systemically after topical application and is neutralised when it hits the soil, unlike other herbicides which poison soil.
Invaluable for pernicious weeds, (its primary use.)
Nicotinoids are a problem because they are broad spectrum and are toxic to all animal life in high doses.
Not so much causing autism as just plain death.
Autism is being used by all and sundry as a vague unknown terror because the disease itself is not understood or defined properly. Macimum advantage is taken by all interested parties.
I have worked with young children with sever autism and there is no doubt that there is something very profoundly wrong with those individuals.
Much of what is being diagnosed as autism seems to me to be an unfortunate label for a combination of poor maternal parenting and just simple, old fashioned developmental and behavioural problems.
Some highly intelligent boys, for example, are diagnosed as having problems because they are wrongly placed with children of mixed abilities where they become disruptive or fail to gel with the other children.
If everybody’s suddenly being diagnosed with autism then something else is probably going on.
‘maXimum’, sorry, and ‘severeE.
Some dyslexia, or typos.
God bless you for using “non-exposure-exposure”.
Where did some of our first antibiotics come from? Fungi. You all do realize that every plant and every animal makes “toxins”; where a toxin is a conditional thing. Dose and route make both the medicine and the poison.
Our host is correct about medicine. It is run by humans and humans are nothing if not subject to fads.
Oh, just what is the “N” in NADP? ;p
Joy – You’ve hit upon the real problem. Psychologists invent new disorders in order to charge become famous and charge fees for treatment. They de-list obvious mental disorders when it becomes politically fashionable so to do.
It’s rather obvious that the psychological profession is, on the whole, insane when it is not merely corrupt.
June 25, 2019 at 11:20 am
RE – Talc and ovarian cancer.
The chemical composition of talc is very close to that of asbestos. That is probably not why talc “causes” cancer, though. What causes it appears to be the asbestos that is often found in mineral deposits of talc, and which is a natural contaminant of the talc.
But then, maybe talc may make a contribution, as well?
And, if it doesn’t, the trick is to find talc that contains no asbestos.
(relying on a company’s assurance may not be a sufficient guarantee)