Is comfirmation bias essential to anti-fluoride “research?”

Anti-fluoride propagandists like Declan Waugh and Paul Connett avidly scan the scientific literature looking for anything they can present as evidence for harmful effects of community water fluoridation (CWF). Sometimes they will even do their own “research”  using published and on-line health data looking for any correlations with CWF, or even just with fluoride levels in drinking water.

Several years ago an activist going under the nom de plume “Fugio” posted images showing correlations of mental retardation, adult tooth loss and ADHD with the incidence of CWF in the US. These images are simply the result of “research” driven by confirmation bias and data dredging.They prove nothing. Correlation is not proof of a cause. And no effort was made to see if other factors could give better correlations.

I go through Fugio’s examples below – partly because I noticed one of their images surfacing recently on an anti-fluoridation Facebook page as “proof” that CWF causes tooth loss. But also because they are just more examples of the type of limited exploratory analysis used in two recently published papers – Peckham et al., (2015) (discussed in my article Paper claiming water fluoridation linked to hypothyroidism slammed by experts) and Malin and Till (2015) (discussed in my articles More poor-quality research promoted by anti-fluoride activistsADHD linked to elevation not fluoridation and Poor peer-review – a case study).


This figure is essentially the same as that reported by Malin & Till (2015). In fact, I wonder if Fugio (who posted December 2012) is the unattributed source of Malin & Till’s hypothesis. Fugio chose the ADHD data for 2007 and fluoridation data for 2006 whereas Malin and Till (2015) concentrated mainly on fluoridation data for 1992 which had the highest correlation with ADHD figures.

I won’t discuss this further here – my earlier article ADHD linked to elevation not fluoridation shows there are a number of other factors which correlate with ADHD prevalence just as well or better than CWF incidence does and should have at least been considered as confounding if not the main factors. I found a model using mean elevation, home ownership and poverty only (no CWF included) explained about 48% of the variation whereas their model using CWF and mean income explained only 22-31% of the variation. And when these confounder factors were considered the correlation of ADHD with CWF was not statistically significant.

In other words we could do a far better job of predicting ADHD prevalence without involving CWF.

Water Fluoridation and Adult Tooth Loss

Fugio posted a figure showing a correlation of adult tooth loss with CWF incidence in 2008. It was statistically significant explaining 11% of the variation. But quite a few other factors display better correlations with adult tooth loss. For example, the data for smoking by itself explains 66% of the variation (see figures below).


Checking out correlations with a range of factors I found a model involving only smoking and longitude  explaining  about 74% of the variation. The contribution from CWF was not significant statistically – it added nothing to this model.

Water Fluoridation and Mental Retardation

Fugio found a better relationship between CWF in 1992 and mental retardation in 1993 – a correlation explaining 19% of the variation. Apparently the concept of “mental retardation” was later abandoned as there do not appear to be any more recent statistics.

But again, if Fugio had not stopped there he/she would have found a number of other factors with better correlations. I give an example in the figure where state educational level (% Bachelors Degree in 1993) explained 50% if the variation. This correlation is negative as we might expect.


 Again I used multiple regression analysis to derive a model involving educational level (% with Bachelors degree in 1993), poverty in 1993 and mean state elevation which explained 69% of the variation. No statistically significant contribution from CWF occurred.


I am not suggesting here that the factors I identified have a causal effect. Simply that they give better correlations  than CWF. These and similar confounding factors should have been considered by Fugio and Malin and Till (2015).

My purpose is to show that this sort of exploratory analysis of easily available data can easily produce results for anti-fluoride activists who are searching for some “sciency” looking arguments to back up  their position. Provided they don’t look too deeply, stop while they are ahead and refuse to consider the influence of other factors.

Unfortunately poor peer review by some journals is allowing publication of work that is no better than this. Peckham et al (2015) did nothing to check out other factors except gender in their correlations of hypothyroidism with CWF. The glaring omission was of course dietary iodine which is known to have a causative link with hypothyroidism. (I could not find US data for hypothyroidism so was unable to check out Peckham et al’s hypothesis for the US.) Malin and Till (2015) included only socioeconomic status (as indicated by income) in their analysis despite the fact that ADHD is known to be related to a number of factors like smoking and alcohol intake.

As I keep saying, when it comes to understanding the scientific literature it really is a matter of “reader beware.” It’s easy to find papers supporting one’s pet obsession if you are not critical and sensible with your literature searches. And it is important not to take at face value the claims of activists who clearly rely on confirmation bias when they explore the literature.

20 responses to “Is comfirmation bias essential to anti-fluoride “research?”

  1. Fugio was prolific on line during the PDX fluoridation referendum campaign. Sadly, he and his won with Portland voters.


  2. Yes Ken, there are apparent biased arguers and fabricators in many fields.
    Have you come across James Randi?

    Fugio is showing a much wider variation in MR between states whose number of fluoridated towns is around 55% or greater. Some of it could be “explained” by more states being above 55%. I would expect more variation if the number of states is greater in the 5% range.

    Also states where there is less mental retardation may be choosing less fluoridation.

    Would it be more helpful to limit our comments to studies where multiple regression has been performed?


  3. Soundhill, have you not noticed  that in contrast to the anti-fluoriationists I have been  checking multiple regressions  and these show no correlation with fluoridation?

    Sent from Samsung Mobile


  4. Ken but I have been waiting to see matters like lime levels attended to. This shows a place where fluoride is negatively correlated to lime.

    An interesting point, in Christchurch the shallower aquifers can have more fluoride, maybe fed by rain washing the Ravensdown fluoride chimney output?

    I think a water supply lime, vitamin D, vitamin K2 study would be useful to combine with fluoride/fluoridation.

    Note that fluoridation does not just mean the level of fluoride.

    Like dental amalgam removal is touted to have a benefit but what about studies which look into the effect of all the chelation and nutrition that are often done with it?


  5. You are rambling again  Brian. Only a fool “waits” while ignoring all the available data and then accuses others of not doing multiple regressions.

    Sent from Samsung Mobile


  6. Ken what I mean is that you seem to be often accusing those who do simple correlations which may or not have causal effect by doing other simple correlations which may or may not have causal effect.

    I think if you are doing multiple regressions you would be better to
    give the results each time.

    Your mental retardation/batchelor’s degree correlation example, where you say education explains 50%. If that is a multiple regression figure could you please say (again?) what variables were being regressed together?

    For it seems obvious that increased mental retardation would reduce the number of batchelors degrees.

    I note that MSOF has diverged from just promoting fluoridation, which may show some dental benefit, to promoting tax on sugar. The idea is to add effects. Some effect plus some effect. But in the claim of reducing some of the claimed effects of fluoridation you do not seem to be willing to consider additive small negative effects which may be worse for the tail of the distributions.

    Simply because something shows a better correlation does not mean the lesser correlation can be dismissed. It is like a cat crossing the road which cannot understand the speed of approach of vehicles. Cats that run very fast may be luckier, but not as luckier as ones that cross at night or when the road is not busy. Running very fast may or may not increase survival but the fact that an empty road helps more should not remove the need to consider running speed.

    Brian Sandle


  7. “I think a water supply lime, vitamin D, vitamin K2 study would be useful to combine with fluoride/fluoridation.”

    Go ahead and do it then, soundhill. Or look at lime levels yourself. No-one will stop you. Once you’ve done them then you won’t have to wait any longer.

    The results are extremely unlikely to change the scientific consensus that overwhelmingly demonstrates the benefits and safety of CWF.


  8. Stuartg, CWF may have adverse effects for the tails of the distribution.

    And do you realise that CWF now is different from a few years back?

    A good scientist wants to know what is happening. Just because vaccines help many that should not mean attempts to reduce vaccine injury payouts should only be based on power of lawyers. Shouldn’t there be attempts to improve targeting. not just by age? I suppose you are used to system which accepts iatrogenic disease and tries to avoid payouts.

    Brian Sandle


  9. Brian, you are indulging in naive straw clutching while demonstrating poor comprehension. I should not have to repeat what I have been saying in my articles.

    1: I have i ticked Peckham et al (2015) and Malin and Till (2015) for not properly considering confounding factors and relying on rather weak, but statistically significant, correlations. I have shown that there are a number of factors explaining far more of the variation than does fluoridation. That is not offering these factors as causes in the way they claim for fluoridation as I continually stress the correlation is not causation. It purely demonstrates the inadequacy of their approach.

    2: I have done multiple regression in each case – you poor comprehension means you have not seen my description of these. In each case I offered a model which explains a relatively large amount of the variation – but more important pointed out the fluoridation cannot explain any of the variation when these factors factors are included. This lack of any correlation at all for fluoridation does rather suggest that there is no causal effect involving fluoride – no matter how much you wish there were or the number of straws you grasp.

    3: Finally, I have included links to sources of the data I used. You are welcome to play a play with it yourself.

    But please read what I have written before making these senseless criticisms.



  10. soundhill,

    Vaccines, “vaccine injury”, lawyers, iatrogenic disease, payouts? And this relates to CWF – how?

    I guess you are trying to change the subject to avoid saying that you are not prepared to do the work that you are ” waiting” to see appear.

    Why don’t you do the work yourself? That is, if it’s so important to you?


  11. Ken could you say what date you included the data links?


  12. Stuartg, what about the safety of the tails of the distribution?


  13. Most of the basic links are in my article in ADHD, Brian. Use google if you want different years, just like I did.



  14. soundhill,

    What about you doing the work yourself rather than “waiting”?


  15. Thanks Ken, I see the coloured links work. Leaving out Hawaii and Alaska I get a Spearman Rank Order Correlation between longitude and altitude of -0.7441, p<0.000001, using Vassarstats. I am looking for how to relate the vitamin D producing UVB to latitude, and altitude, and when I do so I shall use the ranking of that instead.

    I think the altitude figure may be more powerful than the latitude, going by your correlation to latitude for me, thanks.

    Your graph of relation of smoking to loss of 5 or fewer teeth is rather interesting. If I understand it, with 10% smoking, only 30% lose less than 6 teeth, but with 25% smoking 55% lose less than 6 teeth.

    Perhaps the smoke, like fluoride in water, is disabling acetylcholinesterase, and increasing duration of protective salivary flow.
    Brian Sandle


  16. Ken, you wrote: “Malin and Till (2015) concentrated mainly on fluoridation data for 1992 which had the highest correlation with ADHD figures.”

    Ken, as I have had to say to Stuartg, “optimum fluoridation” and CWF are terms which are used in a very misleading fashion by pro-fluoridationsists. They try to make out that “it” is just great, when in fact that “it” has very different meaning over the years.

    “Of the population with artificially fluoridated water in 1992, more than two-thirds had a water fluoride concentration of 1.0 mg/L, with almost one-quarter having lower concentrations and about 5% having concentrations up to 1.2 mg/L (CDC 1993)”

    And you in your AHDH article use the 2010 figures, by which time fluoridation strength will have considerably reduced. 0.7mg/L is now the recommended US figure.

    It would be interesting to try to get data as to what proportion of the ADHD sufferers came from 1.2mg/L levels, almost twice today’s figure.

    Also you need to acknowledge effects in pregnancy. Diabetes in pregnancy is found to increase autism somewhat, and it takes a few years for autism to show after pregnancy/birth.

    You may be sceptical of this journal, but an article in it has been cited by a number of authors for various reasons, so I do not think it can be just wiped away quickly.

    Rats on high fluoride levels suffered more if they had had diabetes induced in them.

    I ask again that the tails of distributions are attended to so that minorities are not made to suffer for the supposed “good” of the majority.

    Those with diabetes in pregnancy are a minority. Those with autistic offspring as a result of diabetes in pregnancy are a further minority. And I ask if there may be a further minority affected by 1.2mg/L fluoridation in that situation.

    Since vitamin D is known to help ward off diabetes, then the longitude/alttitude UVB factor could be working.

    One factor of poverty may be that of dwelling in apartments where less UVB sunlight is available.

    And I say again your educational attainment relation could be working in reverse to what you suggest.

    Brian Sandle


  17. Brian, you can fiddle with the data as much as you like but the fact remains that in a multiple regression of the ADHD data there is no statistically significant relationship to CWF, even with the 1992 data. You are clutching at imaginary straws.

    “Optimum” concentrations of F in drinking water are defined in the NRC report you link to:

    ” 1 The term optimally fluoridated water means a fluoride level of 0.7-1.2 mg/L; water fluoride levels are based on the average maximum daily air temperature of the area (see Appendix B). “

    That is the way I use it – you are the one misleading, not me.

    Read my articles again, Brian. I am not suggesting anything about educational attainment. I pointed out that correlation does not mean causation – and have not speculated on causes. That would require other evidence.

    One thing for sure, though, is that fluoridation is irrelevant. It cannot be involved in causes if there is no significant relationship with fluoridation. And that is the fact in multiple regressions.



  18. Ken that optimum reference applies to the year 2002.
    Great they put in air temperature to be taken into account when dosing since people drink more in hot climates. But any medically trained people should have in their minds that a symptom of diabetes is drinking more water. So the diabetic may be more frequently suppressing acetylcholinesterase with fluoride.

    Your smoking mention could have more attention. You give data for states(?) which have 25% smokers losing less teeth, and even less than states where the smoking percentage is smaller. Is that correct? I hypothesise then that passive smoking may be having an effect. That a small amount of smoke and or nicotine breathed by non-smokers suppresses their acetycholinesterase sufficiently to increase salivary flow but not enough over all the population to increase tooth loss which nicotine is supposed to do when you compare smokers and non-smokers.

    If we consider the numbers of diabetic pregnant women to be not very great then they will not have a big pull on a correlation, or significance. Therefore should they bear suffering for the gain of everyone else?

    Let’s be decent and do some studies on minorities.


  19. Brian, why don’t you be “decent” and do some studies in minorities?



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