Category Archives: SciBlogs

Not just another rat study

A new high-quality study of the effect of fluoride on the memory and learning behaviour of rats has produced definitive results. Anti-fluoride campaigners had great hopes this study would bring an end to community water fluoridation (CWF) – but their hopes have been dashed.

The study showed no effect of fluoride on the memory, learning and motor skills of rats thus reinforcing the consensus that CWF is safe

Animal experiments are commonly used to investigate possible health effects of chemicals like fluoride. This enables strict research protocols without the ethical problems faced by human studies. Consequently, there have been a large number of investigations of the effect of fluoride on animals. Some of these have suggested harmful effects. The US anti-fluoride activist organisation, the Fluoride Action Network (FAN) lists 45 studies “where mice or rats treated with fluoride were found to suffer impairments in their learning and/or memory abilities” (see FLUORIDE AFFECTS LEARNING & MEMORY IN ANIMALS).

FAN claims these and similar studies as irrefutable evidence that CWF is harmful – particularly in their major campaign claiming CWF lowers IQ and should be stopped. However, a more scientific assessment is far less dogmatic.

The US National Toxicity Program (NTP) examined published research of potential neurological effects from fluoride exposures in experimental rodent animals in a systematic review published in 2016 (see Systematic literature review on the effects of fluoride on learning and memory in animal studies). They found many of the studies had limitations due to confounding in the learning and memory assessments and there was a lack of discrimination between motor and learning skills. Very few of the studies were made at drinking water concentrations relevant to CWF and the evidence for adverse effects was “low to moderate,” and weakest for animals during their developmental phase.

The NTP concluded further research was needed and undertook laboratory studies with rodents to fill the research gaps it had identified. Those studies are now complete and have been published in a research paper:

McPherson, C. A., Zhang, G., Gilliam, R., Brar, S. S., Wilson, R., Brix, A., … Harry, G. J. (2018). An Evaluation of Neurotoxicity Following Fluoride Exposure from Gestational Through Adult Ages in Long-Evans Hooded Rats. Neurotoxicity Research. Neurotoxicity Research.

The laboratory experiment

The authors used four treatments for the rats:

  • G1: Fed standard rodent chow;
  • G2: Fed low-fluoride chow;
  • G3: Fed low-fluoride chow + drinking water with 10 ppm F;
  • G4 Fed low-fluoride chow + drinking water with 20 ppm F.

Effects of drinking water F were determined by comparing results for G3 and G4 with G2.

The drinking water fluoride concentrations still seem high (compared with the recommended level of 0.75 ppm for CWF) but are lower than used in most earlier studies (often around 100 ppm). However, the basis for these choices was the use of the US secondary drinking water standard (2 ppm) and US UPA maximum contaminant level (4 ppm) and “the conventional wisdom that a 5-fold increase in dose is required to achieve comparable human serum levels.” However, this “wisdom” is debated as blood serum levels fluctuate.

These drinking water concentrations are still far higher than the recommended optimum level for CWF (0.75 ppm) so the results should be seen as more related to the defined upper limits than to CWF itself.

Behavioural assessments

A range of behavioural assessments was made. These included:

“motor, sensory, or learning and memory performance on running wheel, open-field activity, light/dark place preference, elevated plus maze, pre-pulse startle inhibition, passive avoidance, hot-plate latency, Morris water maze acquisition, probe test, reversal learning, and Y-maze.”

The purpose of using such a wide range was to overcome deficiencies of the measurements made in earlier studies and to fill in gaps. Animals at the developmental stage were included as most earlier studies had been made with adult rats.

“No significant differences observed”

One of the most commonly used phrases in this paper as the results are presented and discussed is that there were “no significant differences observed across groups.”

The authors note in their abstract that they “observed no exposure-related differences” in any of the behavioural tests listed above.

This result is important. The study is authoritative. The chosen experimental protocols resulted from an extensive systematic review of the earlier work which identified gaps and deficiencies. A very wide range of behavioural tests was used. And the experimental plans were discussed very widely before the experiments began.

We can conclude, therefore, that rodent experiments are unlikely to show behavioural effects related to fluoride exposure at the concentrations which, the authors argue, are relevant to the recommended maximum drinking water standard (2 ppm) and maximum contaminant level (4 ppm) for humans. The argument that this result is relevant to humans is strengthened by the possibility that ““the conventional wisdom that a 5-fold increase in dose is required” to make results relevant for humans may be inflated.

The argument is further strengthened for humans as the recommended drinking water fluoride concentrations for humans is even lower than the maximum drinking water standard and the maximum contaminant level.

Other assessments

The researchers also analysed thyroid hormones and examined collected tissues. They reported:

“No exposure-related pathology was observed in the heart, liver, kidney, testes, seminal vesicles, or epididymides.”


No evidence of neuronal death or glial activation was observed in the hippocampus at 20 ppm F.”

In fact, the only statistically significant effects they found were a “mild inflammation in the prostate gland” and “evidence of mild fluorosis in adults” at 20 ppm F (treatment G4). Remember this level corresponds to the maximum contaminant level for humans and dental fluorosis has also been reported for humans at that concentration.

The anti-fluoride spin

Several years ago I discussed the planned NTP work and the reaction of anti-fluoride campaigners to it in my article Fluoride and IQ – another study coming up.

These campaigners seemed ecstatic about the planned NTP work, although I did comment:

“You wouldn’t think the anti-fluoride crowd would welcome such a careful analysis of the poor-quality articles they promote”

However, Fluoride Free NZ revealed the spin they placed on the NTP document describing the systematic review and the planned work in their press release at the time (see Fluoride-Brain Studies Set to Expose Fluoridation Damage):

“Results could mean the end to fluoridation world-wide, and definitely should put a halt to any plans to start fluoridation in places not currently fluoridated.

Because it is now well established that fluoride affects the brain, the NTP plans to conduct new animal studies to determine the lowest dose at which this damage occurs. They also plan to do a systematic review of all the existing scientific literature. To date, there have been 314 studies that have investigated fluoride’s effects on the brain and nervous system. These include 181 animal studies, 112 human studies, and 21 cell studies.”

I commented on this:

“The confirmation bias and dogmatic agenda stick out like a sore thumb – don’t expect these people to accurately report this study’s findings.”

Well, it seems that these campaigners are still stuck in dumb shock of the denial phase as they have yet to make any comment on these research results. When they do get around to overcoming their speechlessness they are going to be hard put to reconcile this denial with their earlier hopes for the research findings.

There is no way this study can be used to argue for “the end to fluoridation worldwide” or that there “definitely should” be “a halt to any plans to start fluoridation in places not currently fluoridated.

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Anti-fluoridationist Paul Connett misrepresents NZ data

Slide 110 from Paul Connett’s presentation prepared for his planned meeting at Parliament Buildings last February

Here is another post in my series critiquing a PowerPoint presentation of Paul Connett – a leading US anti-fluoridation activist.

Paul prepared this for a meeting in New Zealand Parliament buildings last February. Although only three MPs turned up his presentation is important as it summarises almost all the arguments used by anti-fluoridation activists.

Connett claims NZ data shows fluoridation ineffective

Connett argues the evidence community water fluoridation (CWF) is effective in reducing tooth decay is weak. He covers this in slides 96-110 but in this post I will deal only with the New Zealand evidence he uses (slides 108-110).  Paul’s presentation can be downloaded for those wishing to look at it in detail – see Prof Paul Connett Power Point Presentation to Parliament 22nd Feb 2018.

The total New Zealand evidence Connett presents for this is a graphic obtained from his NZ offsiders, Fluoride Free NZ (FFNZ):

We know how unreliable FFNZ is as a source and the data is obviously cherry-picked. But what is the truth? What do the NZ School Dental statistics really say about the oral health of children in NZ?

I have covered this before – FFNZ misrepresentation of the MoH data is an annual event occurring each time the Ministry of Health adds its annual summary of the data to their web pages.

For a change, here is a breakdown and discussion of the 2016 data prepared by Environmental Health Indicators NZ in association with Massey University:

“Children in fluoridated areas generally have better oral health”

“Children living in communities with fluoridated drinking-water generally had better oral health than children living in non-fluoridated communities.

In 2016, around 60 percent of 5-year-olds were caries-free in their primary teeth. Rates were similar in fluoridated communities (60 percent) and non-fluoridated communities (60 percent) (Figure 1).

More Māori and Pacific Island 5-year-olds were caries-free in fluoridated communities than in non-fluoridated communities in 2016. The largest difference can be seen for Māori children.

5-year-olds had on average 1.8 decayed, missing or filled primary teeth in 2016. Children living in fluoridated communities had less decayed, missing or filled teeth than children living in non-fluoridated communities (Figure 2).

This difference is particular large for Māori children. 5-year old Māori children had on average 2.5 decayed, missing or filled teeth in fluoridated communities compared to 3.3 decayed, missing or filled teeth in non-fluoridated communities in 2016.”

I am unable to embed the Environmental Health Indicators NZ graphs, but they are essentially the same I presented in my article Anti-fluoridationists misrepresent New Zealand dental data – an annual event so I reproduce that section of the article below:

What does the new data really say?

Let’s look at a summary of the data – for 5-year-olds and year 8 children – and for the different ethnic groups listed – Māori, Pacific Island and “other”(mainly Pakeha and Asian).  You can download the spreadsheets contain the data from the MoH web page – Age 5 and Year 8 oral health data from the Community Oral Health ServiceWe will look at the % of these children that a free from caries as well as the mean decayed, missing and filled teeth (dmft and DMFT) for each group.


Notice the FFNZ cherry picking? Yes, the “Total” figures show very little difference but if they had dared look at different ethnic groups their argument would not have looked so great. Fluoridation appears to be associated with an improvement of dental health from about 6% (for “Other”) to 23% (for Māori)

Year 8 children

You can see why  FFNZ chose the 5-year-olds instead of year 8 children. Even the misleading data for the “Total” group suggests an almost 20% improvement of dental health in fluoridated areas.  Fluoridation appears to be associated with an improvement of dental health from about 18% (for “Other”) to 30% (for Māori).

What’s the problem with the 2009 Oral Health Survey?

Anti-fluoride activists love to hate this survey because it concluded:

“Overall, children and adults living in fluoridated areas had significantly lower lifetime experience of dental decay (ie, lower dmft/DMFT) than those in non-fluoridated areas. There was a very low overall prevalence of moderate fluorosis (about 2%; no severe fluorosis was found), and no significant difference in the prevalence of moderate fluorosis (or any of the milder.

“These findings support international evidence that water fluoridation has oral health benefits for both adults and children. In addition, these findings should provide reassurance that moderate fluorosis is very rare in New Zealand, and that the prevalence of any level of fluorosis was not significantly different for people living in fluoridated and non-fluoridated areas.”

Yes, it covers only the period up to 2008 and it would be good to get more recent high-quality data from a similar study.

But Connett’s accusation of “cherry-picked data” is simply wrong – and dishonest. In fact, scientific principles were used to obtain a representative sample for the survey – recognising that oral health is strongly influenced by ethnic, regional and fluoridation differences.

The methods used are explained in 22 pages of the report –  MoH. (2010). Our Oral Health Key findings of the 2009 New Zealand Oral Health Survey

In contrast, the annual School Dental Data is simply a record of overall findings. There is no attempt to standardise diagnostic and reporting methods to the standard of the Oral Health Survey or scientific studies.

But, of course, it provides a lot of data which can be cherry-picked to support a specific argument or confirm a bias. FFNSZ and Paul Connett have ignored all the known ethnic, social and regional differences in their cherry-picking. Consequently, their reported “findings” do not have credibility.


I think it is somewhat disrespectful of Paul Connett to include such a shonky bit of misrepresentation in a presentation prepared for members of parliament. It is also disrespectful in that he relies on his scientific qualifications, his Ph. D. to give “respectability” to a scientific argument which is so easily shown to be false.

Surely our members of parliament deserve something better than this.

Although, even with members of parliament, I guess the old adage “reader (or listener) beware” applies. Sensible MPs will not accept such assurances at face value and will seek out adive=ce on such matters from their officials and experts.

I guess we should feel pretty confident that most of our MPs are sensible in this repect. The fact they did not turn up to a meeting to hear someone well-known for misrepresenting the science is telling – and this despite the fact that anti-fluoride activists were exerting strong pressure on MPs to attend.

Politicians have experienced, and learned from, excessive lobbying, pressuring and untruthful submissions precisely because of their targeting by anti-science activist groups like FFNZ. They know this is why local councils wanted the central government to take over fluoridation decisions.

I suspect our parliamentary politicians are a little more mature than our local body politicians and now  treat such organised campaigns like water off a duck’s back.

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Anti-fluoridationists rejection of IQ studies in fluoridated area.

US anti-fluoride activist Paul Connett claims studies cannot detect an IQ effect from fluoridated water because total fluoride intake is the real problem – but still campaigns against community water fluoridation. Image credit: MSoF “Activist Spouts Nonsense – The Evidence Supports Fluoridation”

This is another article in my critique of the presentation Paul Connett prepared to present to a meeting at Parliament in February.

I deal with his coverage of the studies of IQ effects where community water fluoridation (CWF) is used. There are now actually three such studies (Broadbent et al. 2015, Barberio et al. 2017  and  Aggeborn & Öhman 2016), but Connett pretends there is only one – the Broadbent et al. (2015) New Zealand study.

Maybe because it was the first one to provide evidence challenging his extrapolation of the fluoride/IQ studies (see The 52 IQ studies used by anti-fluoride campaigners) results in areas of endemic fluorosis to areas where CWF is used. It is also the study which seems to have resulted in the most hostility from anti-fluoride campaigners.

So here I will just be sticking with his criticism of the New Zealand study Broadbent et al (2015):

Slide 76 from Paul Connett’s presentation prepared for his February meeting at  parliament buildings

Broadbent’s findings do not “negate all other human studies”

Paul allows emotion to get the better of him as no one is suggesting this at all. The studies Connett refers to are all from areas of endemic fluorosis (see  The 52 IQ studies used by anti-fluoride campaigners), not from areas of CWF.

Broadbent et al (2015) simply concluded that their “findings do not support the assertion that fluoride in the context of CWF programmes is neurotoxic.”  That is a modest statement and Broadbent et al. (2015) simply do not draw any conclusions about the studies Connett relies on. But, of course, Connett is upset because this and similar studies just do not support his attempt to extrapolate results from areas of endemic fluorosis to areas of CWF.

The health problems suffered by people in areas of endemic fluorosis are real and it is right they should be studied and attempts made to alleviate them. But this has absolutely nothing to do with CWF.

“Fatally flawed” charge is itself fatally flawed

Again, Paul has allowed emotions to get the upper hand. It is possible, and necessary, to critique published papers – but critiques should be evidence-based and realistic. Paul’s “fatally flawed” charge (slides 77 & 78) simply displays how much this paper has put his nose out of joint.

But let’s look at the specific “flaws” Paul (and other critics associated with the Fluoride Action Network) claim.

The two villages mindset: Paul alleges that the Broadbent et al (2015) study “essentially compared two groups.” He is stuck in the mindset of most of his 52  studies from areas of endemic fluorosis (see  Fluoride & IQ: The 52 Studies). The mindset of simply comparing the IQ levels of children in a village suffering endemic fluorosis with the IQ levels of children in a village not suffering endemic fluorosis. This simple approach can identify statistically significant differences between the villages but provides little information on causes. For example, most of these studies used drinking water fluoride as a parameter but there could be a whole range of other causes related to health problems of fluorosis.

Professor Richie Poulton, current Director of the Dunedin Multidisciplinary Health and Development Research Unit

In contrast, Broadbent et al. (2015) used “General Linear models to assess the association between CWF and IQ in childhood and adulthood, after adjusting for potential confounders.” The statistical analysis involved includes accounting for a range of possible risk-modifying factors besides CWF., This was possible because the study was part of the Dunedin Multidisciplinary Health and Development Study. This is a highly reputable long-running cohort study of 1037 people born in 1972/1973 with information covering many areas.

The fluoride tablets argument: Connett and other critics always raise this issue – the fact that “In New Zealand during the 1970s, when the study children were young, F supplements were often prescribed to those living in unfluoridated areas.” Often they will go further to claim that all the children in the unfluoridated area of this study were receiving fluoride tablets – something they have no way of knowing.

But the fact remains that fluoride tablets were included in the statistical analysis. No statistically significant effect was seen for them.  Overlap of use of fluoride tablets with residence in fluoridated or unfluoridated areas will have occurred and their influence would be reflected in the results found. Presumably, the effect would be to increase the confidence intervals. As the critics, Menkes et al. (2014), say “comparing groups with overlapping exposure thus compromises the study’s statistical power to determine the single effect of CWF.”  I agree. But this does not negate the findings which are reported with the appropriate confidence intervals (see below).

The point is that the simplistic argument that effects of fluoride tablets were ignored is just not correct. Their effect is reflected in the results obtained.

Potential confounders: Many poor quality studies have ignored possible confounders, or considered only a few. This is a general problem with these sort of studies – and even when attempts are made to include all that the researchers consider important a critic can always claim there may be others – especially if they do not like the results. Claims of failing to consider confounders can often be simply the last resort of armchair critics.

In this case, there is no actual reported association to be confounded (unlike my identification of this problem with the Malin & Till 2015 ADHD study – see Perrott 2017). However, Osmunson et al. (2016) specifically raised possibilities of confounding by lead, manganese, mother’s IQ and rural vs urban residence. Mekes et al. (2014) also raised the rural vs urban issue as well as a possible effect from breastfeeding reducing fluoride intake by children in fluoridated areas.  In their response, Broadbent et al (2015b & 2016) reported that a check showed no significant effect of lead or distance from the city centre and pointed out that manganese levels were too low to have an effect. Broadbent et al (2015b) also reported no significant breastfeeding-fluoride interaction occurred.

Numbers involved: Connett claims the study was fatally flawed because “it had very few controls: 991 lived in the fluoridated area, and only 99 in non-fluoridated” (Slide 77). But the numbers are simply given by the longer term Dunedin study themselves – they weren’t chosen by Broadbent and his co-workers. That is the real world and is hardly a “fatal flaw.”

The 95% confidence intervals

Yes, statisticians always love to work with the large numbers but in the real world, we take what we have. Smaller numbers mean less statistical confidence in the result – but given that Broadbent et al (2015) provides the results, together with confidence intervals, it is silly to describe this as fatally flawed. These were the results given in the paper for the parameter estimate of the factors of interest:

Factor Parameter estimate 95% Confidence interval p-value
Area of residence -0.01 -3.22 to 3.20 .996
Fluoride toothpaste use 0.70 -1.03 to 2.43 .428
Fluoride tablets 1.55 -0.38 to 3.49 .116

Connett did not refer to the confidence intervals reported by Broadbent et al (2015). However, Grandjean and Choi (2015) did describe them as “wide” – probably because they were attempting to excuse the extrapolation of “fluoride as a potential neurotoxic hazard” from areas of endemic fluorosis to CWF.

The argument over confidence intervals can amount to straw clutching – a “yes but” argument which says “the effect is still there but is small and your study was not large enough to find it.” That argument can be never ending but it is worth noting that Aggeborn & Öhman (2016) made a similar comment about wide confidence intervals for all fluoride/IQ studies, including that of Broadbent et al. (2015).  Aggeborn & Öhman (2016) had a very large sample (almost 82,000 were involved in the cognitive ability comparisons) and reported confidence intervals of -0.18 to 1.03 IQ points (compared with -3.22 to 3.20 IQ points reported by Broadbent et al 2015). Based on this they commented, “we are confident to claim that we have estimated a zero-effect on cognitive ability.”

The “yes but” argument about confidence intervals may mean one is simply expressing faith in an effect so small as to be meaningless.

Total fluoride exposure should have been used: Connett says (slide 77) “Broadbent et al did not use the proper measure of fluoride exposure. They should have used total F exposure.  Instead, they used only exposure from fluoridated water.” Osmunson et al. (2016) make a similar point, claiming that the study should not have considered drinking water fluoride concentration but total fluoride intake. They go so far as to claim “the question is not whether CWF reduces IQ, but whether or not total fluoride intake reduces IQ.”

This smacks of goalpost moving – especially as the argument has specifically been about drinking water fluoride and most of the studies they rely on from areas of endemic fluorosis specifically used that parameter.

In their response to this criticism Broadbent et al (2016) calculated estimates for total daily fluoride intake and used them in their analysis which “resulted in no meaningful change of significance, effect size, or direction in our original findings.”

It’s interesting to note that Connett and his co-workers appear to miss completely the point about “wide” confidence intervals made by Grandjean and Choi (2015). Instead, they have elevated their argument to the claim that fluoride intake is almost the same in both fluoridated and unfluoridated areas so that any study will not be able to detect a difference in IQ. Essentially they are claiming that we are all going to suffer IQ deficits whether we live in fluoridated or unfluoridated areas.

This is the central argument of their paper – Hirzy et al (2016). However, the whole argument relies on their own estimates of dietary intakes – a clear example where motivated analysts will make the assumptions that fit and support their own arguments. This argument also fails to explain why the Dunedin study found lower tooth decay in fluoridated areas.

Last time I checked the anti-fluoride campaigners, including Connett, were still focusing on CWF – fluoride in drinking water. One would think if they really believed their criticism that they would have given up that campaign and instead devoted their energies to the total fluoride intake alone.


All studies have limitations and of course, Broadbent et al. (2015) is no exception. However, the specific criticisms made by Connett and his fellow critics do not stand up to scrutiny. Most have been responded to and shown wrong – mind you this does not stop these critics from continuing to repeat them and disregard the responses.

I believe the relatively wide confidence intervals could be a valid criticism – although it does suggest a critic who is arguing for very small effects. A critic who may always find the confidence intervals still exclude their very small effect – no matter how large the study is.

In effect, the narrow confidence intervals reported by Aggeborn & Öhman (2016) should put that argument to rest for any rational person.


Aggeborn, L., & Öhman, M. (2016). The Effects of Fluoride In The Drinking Water

Barberio, A. M., Quiñonez, C., Hosein, F. S., & McLaren, L. (2017). Fluoride exposure and reported learning disability diagnosis among Canadian children: Implications for community water fluoridation. Can J Public Health, 108(3),

Broadbent, J. M., Thomson, W. M., Ramrakha, S., Moffitt, T. E., Zeng, J., Foster Page, L. A., & Poulton, R. (2015). Community Water Fluoridation and Intelligence: Prospective Study in New Zealand. American Journal of Public Health, 105(1), 72–76.

Broadbent, J. M., Thomson, W. M., Moffitt, T., Poulton, R., & Poulton, R. (2015b). Health effects of water fluoridation: a response to the letter by Menkes et al. NZMJ, 128(1410), 73–74.

Broadbent, J. M., Thomson, W. M., Moffitt, T. E., & Poulton, R. (2016). BROADBENT ET AL. RESPOND. American Journal of Public Health, 106(2), 213–214.

Grandjean, P., Choi, A. (2015). Letter: Community Water Fluoridation and Intelligence. Am J Pub Health, 105(4).

Hirzy, J. W., Connett, P., Xiang, Q., Spittle, B. J., & Kennedy, D. C. (2016). Developmental neurotoxicity of fluoride: a quantitative risk analysis towards establishing a safe daily dose of fluoride for children. Fluoride, 49(December), 379–400.

Malin, A. J., & Till, C. (2015). Exposure to fluoridated water and attention deficit hyperactivity disorder prevalence among children and adolescents in the United States: an ecological association. Environmental Health, 14.

Menkes, D. B., Thiessen, K., & Williams, J. (2014). Health effects of water fluoridation — how “ effectively settled ” is the science? NZ Med J, 127(1407), 84–86.

Osmunson, B., Limeback, H., & Neurath, C. (2016). Study incapable of detecting IQ loss from fluoride. American Journal of Public Health, 106(2), 212–2013.

Perrott, K. W. (2017). Fluoridation and attention deficit hyperactivity disorder – a critique of Malin and Till ( 2015 ). Br Dent J.

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A conference paper on the maternal neonatal urinary fluoride/child IQ study has problems

Image credit: Do new mothers doing a Ph.D. get enough support?

The anti-fluoride movement has certainly mobilised over the neonatal maternal urinary fluoride study which reported an association with child IQ. They see it as the best thing since sliced bread and believe it should lead to the end of fluoridation worldwide.

They also seem to be putting all their eggs in this one basket and have started a campaign aimed at stopping pregnant women from drinking fluoridated water (See Warning to Pregnant Women: Do Not Drink Fluoridated Water).

So I was not surprised to see a newsletter this morning from the Fluoride Action Network reporting another output from this study – a conference paper (most likely a poster) presented at the  3rd Early Career Researchers Conference on Environmental Epidemiology. The meeting was in Freising, Germany, on 19-20 March 2018.

I had been aware of the poster for the last week so had expected FAN to gleefully jump on it and start promoting it in their campaigns.

Here is a link to the abstract:

Thomas, D., Sanchez, B., Peterson, K., Basu, N., Angeles Martinez-Mier, E., Mercado-Garcia, A., … Tellez-Rojo, M. M. (2018). Prenatal fluoride exposure and neurobehavior among children 1-3 years of age in Mexico. Occupational and Environmental Medicine, 75(Suppl 1), A10–A10.

It’s only an abstract and it may be some time before a formal paper is published, if at all. Posters do not get much in the way of peer review and often not followed by formal papers.  So I can’t say much about the poster at this stage as I never like to make an assessment of studies on the basis of abstracts alone.

But, in this case, I have Deena Thomas’s Ph.D. thesis which was the first place the work was reported. If you are interested you can access it from this link:

Thomas, D. B. (2014). Fluoride exposure during pregnancy and its effects on childhood neurobehavior: a study among mother-child pairs from Mexico City, Mexico. University of Michigan.

I will wait for a formal paper before properly critiquing the poster, but at the moment I find a big discrepancy between the Thesis conclusions and the conclusions presented in the poster abstract.

Thesis conclusions

In her work, Deena Thomas used the Mental Development Index (MDI) which is an appropriate way of determining neurobehavioral effects in young children.

She concluded in her thesis (page 37):

“Neither maternal urinary or plasma fluoride was associated with offspring MDI scores”

And (page 38):

“This analysis suggests that maternal intake of fluoride during pregnancy does not have a strong impact on offspring cognitive development in the first three years of life.”

And further (page 48):

“Maternal intake of fluoride during pregnancy does not have any measurable effects on cognition in early life.”

So – no association found of child MDI score with maternal neonatal urinary F concentrations.

Poster conclusions

But the poster tells a different story.

The abstract concluded:

“Our findings add to our team’s recently published report on prenatal fluoride and cognition at ages 4 and 6–12 years by suggesting that higher in utero exposure to F has an adverse impact on offspring cognitive development that can be detected earlier, in the first three years of life.”

So her conclusions reported in her thesis are exactly the opposite of the conclusions reported in her conference poster!

What the hell is going on?

The data

Obviously, I do not have access to the data and she does not provide it in her thesis. But from her descriptions of the data in her thesis and her poster perhaps we can draw some tentative conclusions.

The table below displays the data description, and a description of the best-fit line determined by statistical analysis, in her thesis and her poster.

Information on data Thomas Ph.D. Thesis Conference abstract
Number of mother/child pairs 431 401
Maternal Urinary F range (mg/L) 0.110 – 3.439 0.195 – 3.673
Mean maternal urinary F (mg/L) 0.896 0.835
Model β* -0.631 -2.40
Model p-value 0.391 – Not significant
95% CI for β -4.38 to -0.40

*β is the coefficient, or slope, of the best-fit line


Apparently at least 30 data pairs have been removed from her thesis data to produce the dataset used for her poster. Perhaps even some data pairs were added (the maximum urinary F value is higher in the smaller data set used for the poster).

This sort of change in the data selected for the statistical analysis could easily swing the conclusion from no effect to a statistically significant effect. So the reasons for the changes to the dataset are of special interest.

Paul Connett claims this poster “strengthens” the findings reported in the Bashash paper.  He adds:

“This finding adds strength to the rapidly accumulating evidence that a pregnant woman’s intake of fluoride similar to that from artificially fluoridated water can cause a large loss of IQ in the offspring.”

But this comes only by apparently removing the conflicting conclusions presented in Deela Thomas’s Ph.D. thesis. We are still left with the need to explain this conflict and why a significant section of the data was removed.

To be clear – I am not accusing Thomas et al. (2018) of fiddling the data to get the result they did. Just that, given the different conclusions in her thesis and the poster,  there is a responsibility to explain the changes made to the dataset.

From the limited information presented in the poster abstract, I would think the scatter in the data could be like that seen in the Bashash et al. (2017) paper. The coefficient of the best fit line (β) is relatively small and while the 95% CI indicates the fit is statistically significant its closeness to zero suggest that it is a close thing.

However, let’s look forward to getting better information on this particular study either through correspondence or formal publication of a research paper.

Other articles on the Mexican study

Fluoride, pregnancy and the IQ of offspring,
Maternal urinary fluoride/IQ study – an update,
Anti-fluoridation campaigners often use statistical significance to confirm bias,
Paul Connett “updates” NZ MPs about fluoride?
Paul Connett’s misrepresentation of maternal F exposure study debunked,
Mary Byrne’s criticism is misplaced and avoids the real issues

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The 52 IQ studies used by anti-fluoride campaigners

Slide number 30 from Paul Connett presentation prepared for a talk at NZ Parliament buildings in February 2018.

Continuing my critique of the presentation prepared by Paul Connett for his much-publicised meeting at Parliament Building in February. The meeting attracted only three MPs but his presentation is useful as it presents all the arguments anti-fluoride campaigners rely on at the moment.

My previous articles on this presentation are Anti-fluoride activist commits “Death by PowerPoint” and Paul Connett’s misrepresentation of maternal F exposure study debunked.

In this article, I deal with the argument presented in the slide above. it is an argument repeated again and again by activists. Connett has posted a more detailed list of these studies and his description of them in Fluoride & IQ: The 52 Studiesat the Fluoride Action Network website.

Studies in areas of endemic fluorosis

All the 52 studies comment refers to are from regions of endemic fluorosis in countries like India, China, Mexico and Iran where dietary fluoride intake is above the recommended maximum level. People in these areas suffer a range of health problems and studies show cognitive deficits as one of them. However, a quick survey of Google Scholar shows this concern is well down the list (See Endemic fluorosis and its health effects). Only 5% of the Google Scholar hits related to health effects of endemic fluorosis considered IQ effects.

People in high fluoride areas where fluorosis is endemic suffer a range of health problems. Credit: Xiang (2014)

In, most, but not all, cases the major source of fluoride in the diet is drinking water with high fluoride levels (above the WHO recommended 1.5 mg/L). Paul Connett’s logic is simply to extrapolate to low drinking water fluoride concentrations typical of community water fluoridation (CWF). However, we do not see the other health effects like severe dental fluorosis, skeletal fluorosis, etc., where CWF is used.

His logic also ignores the possibility that cognitive deficits may result from other health problems common in areas of endemic fluorosis. Problems such as premature births and low birth weight, skeletal fluorosis or even the psychological effect of unsightly teeth due to severe dental fluorosis.

Comparing “high” fluoride villages with “low” fluoride villages

This approach is simplistic as it simply compares a population suffering fluorosis with another population not. Yes, the underlying problem is the high dietary intake (mainly from drinking water) in the high fluoride villages – but that does not prove fluoride in drinking water is the direct cause of a problem. The examples discussed above, eg., low birth weights or premature births, could be the direct cause.

It is easy to show statistically significant differences of drinking water fluoride and a whole host of fluorosis related diseases between two villages but that, in itself, does not prove that drinking water fluoride is the direct cause. Nor does it justify extrapolating such results to other low concentrations situations typical of CWF.

Paul Connett’s logic ignores the fact that in most of these studies the “low” fluoride villages (which the studies were treating as the control or normal situations where IQ deficits did not occur) had drinking water fluoride concentrations like that used in CWF. It also ignores, or unjustly attempts to dismiss) studies which show no cognitive deficits related to CWF.

A low fluoride concentration study showing an IQ effect

After making a big thing about the large numbers of studies and being challenged by the high fluoride concentrations involved Connett normally goes into a “yes, but” mode and attempts to transfer that credibility of “large numbers” to the very few studies which report effects at low fluoride concentrations.

He usually makes a big thing of the study by Lin et al (1991):

Lin Fa-Fu, Aihaiti, Zhao Hong-Xin, Lin Jin, Jiang Ji-Yong, M. (1991). THE RELATIONSHIP OF A LOW-IODINE AND HIGH- FLUORIDE .ENVIRONMENT TO SUBCLINICAL CRETINISM lN XINJIANG. Iodine Deficiency Disorder Newsletter, 24–25.

Connett claims this study shows a lower IQ when the drinking water F concentration was 0.88 ppm, but the areas suffered from iodine deficiency which is related to cognitive deficits.

The study I reviewed recent by Bashash et al (2017) (see Paul Connett’s misrepresentation of maternal F exposure study debunked) is also on Connett’s list. He doesn’t mention, however, that while an association of child IQ with prenatal maternal urinary fluoride was reported the paper also reported there was no observed association of child IQ with child urinary fluoride concentrations.

Studies not showing an effect

Connett lists 7 studies which showed no effect on IQ. One of these was the well-known Broadbent et al., (2014) study from New Zealand, which he, of course, proceeds to debunk in an irrational and not very truthful manner.

He does not mention the studies from Canada (Barberio et al. 2017 ) and Sweden (Aggeborn & Öhman 2016) which also show no effect of CWF on IQ.

The 6 other studies listed are all Chinese, and not translated. Interesting because Connett’s Fluoride Action Network invested money and time into translating obscure Chinese papers that could support their argument of harm. They obviously did not bother translating those papers which did not confirm their bias.


So, Connett’s 52 studies are rather a waste of time. Based in areas of endemic fluorosis their findings are not transferable to areas where CWF is used. The quality of most papers is low and, usually, the studies are simply a comparison of two villages, one where fluorosis is endemic and the “control” village where it isn’t but drinking water concentrations are like that used in CWF.

Connett simply is not able to properly evaluate, or in some cases even consider, studies which show no effect of fluoride on IQ or were made in areas where CWF exists and no effects are shown.

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Why is it so difficult to get an open discussion on fluoridation?

Yes, I know – everyone’s mind is already made up so participants just talk past each other. People’s positions on this and similar issues have become a matter of identity – people are driven by emotions, not information.

But, the information is there – and while I agree many people are driven by emotions they often attempt to use that information to support their positions. In a sense, the information acts as a proxy for their real driving force – their emotions.

Nevertheless, I have always considered a good-faith scientific exchange on issues like this is possible. I believe the exchange I had with Paul Connett, a US anti-fluoride campaigner, four years ago was a good example of what is possible (see Fluoride Debate or download Connett & Perrott (2014) – the pdf document of the exchange).

So, I always look for the chance to repeat that discussion – and I thought that might happen with my recent articles discussing the Mexican maternal prenatal urinary F/child IQ study. Why, because my recent article Paul Connett’s misrepresentation of maternal F exposure study debunked got a response from Mary Byrne, National Coordinator of Fluoride Free New Zealand. I posted her article as Anti-fluoride group coordinator responds to my article.

I responded to that with Mary Byrne’s criticism is misplaced and avoids the real issues and again I offered her a right of reply.

But no response. In fact, she refuses to answer any of my emails.

OK, I can take a hint – but then I see her claiming on Facebook (see image above) that SciBlogs would not allow this discussion! Would not allow “exposure to both sides!” This is patently untrue and she is completely misrepresenting SciBlogs and me.

Note: SciBlogs is a collection of New Zealand science bloggers. My science-oriented blogs usually appear there by syndication.

The email exchange

So it is worth actually looking at the email exchange where Mary requested publication of her article and we responded. Please note the dates and times and excuse the low magnifications. Here are the emails in sequence:

11 March, 12:51 pm: Mary Byrne requests SciBlogs publish her response to my article.
11 March, 1:06pm: After internal passing on the email, Peter Griffin sends it to me.

Pretty quick service. Remember this was a Sunday.

My response was also pretty quick (considering I usually have my daily power nap at that time). I didn’t have to do much thinking about the issue (please excuse my verbosity).

11 March, 2.11 pm

Mary Byrne did not reply so I went ahead anyway and interpreted the original request to mean that a right of reply post on my blog was acceptable. Her article was posted on Tuesday, March 13 (I already posted on Monday and like to spread posts throughout the week) – Anti-fluoride group coordinator responds to my article. I emailed Mary to let her know her article was posted and I would respond to it.

I posted my promised response to her article on Wednesday, March 14th – Mary Byrne’s criticism is misplaced and avoids the real issues and sent Mary an email to let her know – once again offering her another right of reply.

So, Mary’s claim of SciBlogs not allowing exposure from both sides is completely false.

Incidentally, I have emailed Mary asking her to correct that misrepresentation. She has ignored my email, as she ignored all the other emails I have sent her about this issue. The misrepresentation is still on the Fluoride Free NZ Facebook page.

So, I do not expect Mary to continue this exchange, unfortunately. And I do regret she has chosen to misrepresent the situation in the way she has.

But I guess it is just another case of misrepresentation by an anti-fluoridation activist.

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Mary Byrne’s criticism is misplaced and avoids the real issues

Image credit: BuildGreatMinds.Com

First, thanks to Mary Byrne and FFNZ for this response (see Anti-fluoride group coordinator responds to my article). Hopefully, this will help encourage some good faith scientific discussion of the issues involved in my original article (Paul Connett’s misrepresentation of maternal F exposure study debunked). I am pleased to promote such scientific exchange.

I will deal with the issues Mary raised point by point. But first, let’s correct some misunderstandings. Mary claimed I am a “fluoride promoter” and had “sought to discredit the study via his blog posts and tweets.”

  1. I do not “promote fluoride.” My purpose on this issue has always been to expose the misinformation and distortion of the science surrounding community water fluoridation (CWF). I leave promotion of health policies to the health experts and authorities.
  2. I have not “sought to discredit the study.” The article Mary responded to was a critique of the misrepresentation of that study by Paul Connett – not an attack on the study itself. This might become clear in my discussion below of the study and how it was misrepresented.

The study

The paper we are discussing is:

Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., … Hernández-avila, M. (2016). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico.Environmental Health Perspectives, 1, 1–12.

Anti-fluoride activists have leaped on it to promote their cause – Paul Connett, for example, claimed it should lead to the end of community water fluoridation throughout the world! But this is not the way most researchers, including the paper’s authors, see the study. For example, Dr. Angeles Martinez-Mier, co-author and one of the leading researchers,  wrote this:

1. “As an individual, I am happy to go on the record to say that I continue to support water fluoridation”
2. “If I were pregnant today I would consume fluoridated water, and that if I lived in Mexico I would limit my salt intake.”
3.  “I am involved in this research because I am committed to contribute to the science to ensure fluoridation is safe for all.”

Was the reported association statistically significant?

Mary asserts:

“Perrott claims that the results were not statistically significant but his analysis is incorrect.”

That is just not true. I have never claimed their reported association was not statistically significant.

I extracted the data they presented in their Figures 2 and 3A and performed my own regression analysis on the data. This confirmed that the associations were statistically significant (something I never questioned). The figures below illustrating my analysis were presented in a previous article (Maternal urinary fluoride/IQ study – an update). These results were close to those reported by Bashash et al., (2017).

For Fig. 2:

My comment was – “Yes, a “statistically significant” relationship (p = 0.002) but it explains only 3.3% of the variation in GCI (R-squared = 0.033).”

For Fig 3A:

My comment was – “Again, “statistically significant” (p = 0.006) but explaining only 3.6% of the variation in IQ (R-squared = 0.0357).”

So I in no way disagreed with the study’s conclusions quoted by Mary that:

” higher prenatal fluoride exposure, in the general range of exposures reported for other general population samples of pregnant women and nonpregnant adults, was associated with lower scores on tests of cognitive function in the offspring at age 4 and 6–12 y.”

I agree completely with that conclusion as it is expressed. But what Mary, Paul Connett and all other anti-fluoride activists using this study ignore is the real relevance of this reported association. The fact that it explains only about 3% of the IQ variance. I discussed this in the section The small amount of variance explained in my article.

This is a key issue which should have been clear to any reader or objective attendee of Paul Connett’s meeting where the following slide was presented:

Just look at that scatter. It is clear that the best-fit line explains very little of it.  And the 95% confidence interval for that line (the shaded area) does not represent the data as a whole. The comments on the statistical significance and confidence intervals regarding to the best-fit line do not apply to the data as a whole.

Finally, yes I did write (as Mary quotes) in my introductory summary that “the study has a high degree of uncertainty.” Perhaps I should have been more careful – but my article certainly makes clear that I am referring to the data as a whole – not to the best fit line that Connett and Mary concentrate on. The regression analyses indicate the uncertainty in that data by the low amount of IQ variance explained (the R squared values) and the standard error of the estimate (about 12.9 and 9.9 IQ points for Fig 2 and  Fig 3A respectively).

The elephant in the room – unexplained variance

Despite being glaringly obvious in the scatter, this is completely ignored by Mary, Paul Connett and other anti-fluoride activists using this study. Yet it is important for two reasons:

  • It brings into question the validity of the reported statistically significant association
  • It should not be ignored when attempting to apply these findings to other situations like CWF in New Zealand and the USA.

Paul Connett actually acknowledged (in a comment on his slides) I was correct about the association explaining such small amount of the variance but argued:

  • Other factors will be “essentially random with respect to F exposure,” and
  • The observed relationship will not be changed by the inclusion of these other factors.

I explained in my article Paul Connett’s misrepresentation of maternal F exposure study debunked how both these assumptions were wrong. In particular, using as one example the ADHD-fluoridation study I have discussed elsewhere (see Perrott, 2017). I hope Mary will refer to my article and discussion in her response to this post.

While ignoring the elephant in the room – the high degree of scattering, Mary and others have limited their consideration to the statistical significance and confidence intervals of the reported association – the association which, despite being statistically significant, explains only 3% of the variation (obvious from the slide above.

For example, Mary quotes from the abstract of the Bashash et al., (2017) paper:

“In multivariate models we found that an increase in maternal urine fluoride of 0.5mg/L (approximately the IQR) predicted 3.15 (95% CI: −5.42, −0.87) and 2.50 (95% CI −4.12, −0.59) lower offspring GCI and IQ scores, respectively.”

I certainly agree with this statement – but please note it refers only to the model they derived, not the data as a whole. Specifically, it applies to the best-fit lines shown in Fig 2 and Fig 3A as illustrated above. The figures in this quote relate to the coefficient, or slope, of the best fit line.

Recalculating from 0.5 mg/L to 1 mg/L this simply says the 95% of the coefficient values, or slopes, of the best fit lines resulting from different resampling should be in the range  -10.84 to -1.74 CGI (Fig 2) and -8.24 to 1.18 IQ (Fig 3A).

[Note – these are close to the CIs produced in my regression analyses described above – an exact correspondence was not expected because digital extraction of data from an image is never perfect and a simple univariate model was used]

The cited CI figures relate only to the coefficient – not the data as a whole. And, yes, the low p-value indicates the chance of the coefficient, or slope, of the best-fit line being zero is extremely remote. The best fit line is highly significant, statistically. But it is wrong to say the same thing about its representation of the data as a whole.

This best-fit line explains only 3% of the variance in IQ – and a simple glance at the figures shows the cited confidence intervals for that line simply do not apply to the data as a whole.

The misrepresentation

That brings us back to the problem of misrepresentation. We should draw any conclusions about the relevance of the data in the Bashash et al., (2017) study from the data as a whole – not just from the small fraction with an IQ variance explained by the fitted line.

Paul Connett claimed:

“The effect size is very large (decrease by 5-6 IQ points per 1 mg/L increase in urine F) and is highly statistically significant.”

But this would only be true if the model used (the best-fit line) truly represented all the data. A simple glance at Fig 2 in the slide above shows that any prediction from that data with such a large scatter is not going to be “highly statistically significant.” Instead of relying on the CIs for the coefficient or slope of the line, Connett should have paid attention to the standard error for estimates from the data as a whole given in the Regression statistics of the Summary output. – For Fig. 2, this is 12.9 IQ points. This would have produced an estimate of “5-6 ± 36 IQ points which is not statistically significantly different to zero IQ points,”  as I described in my article

Confusion over confidence intervals

Statistical analyses can be very confusing, even (or especially) to the partially initiated. We should be aware of the specific data referred to when we cite confidence intervals (CIs).

For example, Mary refers to the CI values for the coefficients, or slopes, of the best fit lines.

Figs 2 and 3A in the Bashash et al., (2017) paper include confidence intervals (shaded areas) for the best fit lines (these take into account the CIs of the constants as well as the CIs of the coefficients). That confidence interval describes the region of 95% probability for where the best-fit line will be.

Neither of those confidence intervals applies to the data as a whole as a simple glance at Figs 2 and 3A will show. In contrast, the “prediction interval” I referred to in my article, does. This is based on the standard error of the estimate listed in the Regression statistics. Dr. Gerard Verschuuren demonstrated this in this figure from his video presentation.

Mary is perfectly correct to claim “it is the average effect on the population that is of interest” – but that is only half the story as we are also interested in the likely accuracy of that prediction. The degree of scatter in the data is also relevant because it indicates how useful this average is to any prediction we make.

Given the model described by Bashash et al., (2017) explained only 3% of the IQ variance, while the standard error of the estimate was relatively large, it is misleading to suggest any “effect size” predicted by that model would be “highly significant” as this ignores the true variability in the reported data. When this is considered the effect size (and 95% CIs) is actually “5-6 ± 36 IQ points which is not statistically significantly different to zero IQ points,”

Remaining issues

I will leave these for now as they belong more to a critique of the paper itself (all published papers can be critiqued) rather than the misrepresentation of the paper by Mary Byrne and Paul Connett. Mary can always raise them again if she wishes.

So, to conclude, Mary Byrne is correct to say that the model derived by Bashash et al., (2017) predicts that an increase of “fluoride level in urine of 1 mg/L could result in a loss of 5-6 IQ points” – on average. But she is wrong to say this prediction is relevant to New Zealand, or anywhere else, because when we consider the data as a whole that loss is “5-6 ± 36 IQ points.”

I look forward to Mary’s response.

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Anti-fluoride group coordinator responds to my article

Image credit: Debate. The science of communication.

My recent article Paul Connett’s misrepresentation of maternal F exposure study debunked got some online feedback and criticism from anti-fluoride activists. Mary Byrne, National coordinator Fluoride Free New Zealand, wrote a response and requested it is published on SciBlogs “in the interests of putting the record straight and providing balance.”

I welcome her response and have posted it here. Hopefully, this will satisfy her right of reply and help to develop some respectful, good faith, scientific exchange on the issue.

I will respond to Mary’s article within a few days.

Perrott wrong. New US Government study does find large, statistically significant, lowering of IQ in children prenatally exposed to fluoride

By Mary Byrne, National coordinator Fluoride Free New Zealand.

While the New Zealand Ministry of Health remains silent on a landmark, multi-million-dollar, US Government funded study (Bashash et al), and the Minister of Health continues to claim safety based on out-dated advice, fluoride promoter Ken Perrott has sought to discredit the study via his blog posts and tweets.

Perrott claims that the results were not statistically significant but his analysis is incorrect.

The conclusion by the authors of this study, which was published in the top environmental health journal, Environmental Health Perspectives, was:

In this study, higher prenatal fluoride exposure, in the general range of exposures reported for other general population samples of pregnant women and nonpregnant adults, was associated with lower scores on tests of cognitive function in the offspring at age 4 and 6–12 y.”

Perrott states the study has “a high degree of uncertainty”. But this contrasts with the

statistical analysis and conclusion of the team of distinguished neurotoxicity researchers from Harvard, the University of Toronto, Michigan and McGill. These researchers have written over 50 papers on similar studies of other environmental toxics like lead and mercury.

RESULTS: In multivariate models we found that an increase in maternal urine fluoride of 0.5 mg/L (approximately the IQR) predicted 3.15 (95% CI: −5.42, −0.87) and 2.50 (95% CI −4.12, −0.59) lower offspring GCI and IQ scores, respectively.

The 95% CI is the 95% Confidence Interval which is a way of judging how likely the results of the study sample reflect the true value for the population. In this study, the 95% CIs show the results are highly statistically significant. They give a p-value of 0.01 which means if the study were repeated 100 times with different samples of women only once could such a large effect be due to chance.

Perrott comes to his wrong conclusion because he has confused Confidence Intervals with Prediction Intervals and improperly used Prediction Intervals to judge the confidence in the results. A Prediction Interval is used to judge the confidence one has in predicting an effect on a single person, while a Confidence Interval is the proper measure to judge an effect on a population. In epidemiological studies, it is the average effect on the population that is of interest, not how accurately you can predict what will happen to a single person.

Despite the authors controlling for numerous confounders, Perrott claimed they did not do a very good job and had inadequately investigated gestational age and birth weight.

Once again Perrott makes a fundamental mistake when he says that the “gestational period < 39 weeks or > 39 weeks was inadequate” and “The cutoff point for birth weight (3.5 kg) was also too high.”

Perrott apparently did not understand the Bashash paper and mistook what was reported in Table 2 with how these covariates were actually treated in the regression models. The text of the paper plainly states:

“All models were adjusted for gestational age at birth (in weeks), birthweight (kilograms)”

Thus, each of these two variables were treated as continuous variables, not dichotomized into just two levels. Perrott’s criticism is baseless and reveals his misunderstanding of the Bashash paper.

Perrott states that the results are not relevant to countries with artificial fluoridation because it was done in Mexico where there is endemic fluorosis. But Perrott is wrong. The study was in Mexico City where there is no endemic fluorosis. Furthermore, the women’s fluoride exposures during pregnancy were in the same range as found in countries with artificial fluoridation such as New Zealand.

The study reports that for every 0.5 mg/L increase of fluoride in the urine of the mothers there was a statistically significant decrease in average IQ of the children of about 3 IQ points. It is therefore correct to say that a fluoride level in urine of 1 mg/L could result in a loss of 5 – 6 IQ points. This is particularly relevant to the New Zealand situation where fluoridation is carried out at 0.7 mg/L to 1 mg/L and fluoride urine levels have been found to be in this range2.

There is no excuse for Health Minister, David Clark, to continue to bury his head in the sand. This level of science demands that the precautionary principle be invoked and fluoridation suspended immediately.

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Paul Connett’s misrepresentation of maternal F exposure study debunked

Title slide for Paul Connett’s presentation to parliament

Anti-fluoride campaigners are misrepresenting a recent Mexican study claiming its findings should cause governments around the world to abandon community water fluoridation (CWF). Their claims are unwarranted because the study has a high degree of uncertainty. Activists are misrepresenting the accuracy of the studies findings. Because Mexico has areas of endemic fluorosis the study itself is not relevant to CWF.

Misrepresentation of the Mexican study was a central argument used by US anti-fluoride activist Paul Connett in his recent New Zealand speaking tour. This is shown in the Powerpoint presentation he prepared for his meeting at parliament buildings last month (see Anti-fluoride activist commits “Death by PowerPoint”).

It may have not been used in the end as only 3 MPs turned up. But, given his status in the anti-fluoride movement, this presentation will present the current strongest arguments against CWF. It is therefore worth critiquing his presentation whether it was given or not.

In this article, I will concentrate on Paul’s presentation of the Mexican study and may deal with other arguments used in the presentation in later articles. The paper reporting the study is:

Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., … Hernández-avila, M. (2016). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico.Environmental Health Perspectives, 1, 1–12.

In Connett’s mind, the study’s results are so overwhelming we should immediately stop fluoridation throughout the world! This was the first and main argument he presented. His title slide and slide no. 10 introducing the study demonstrates the importance to him.

Slide No. 10 introducing Connett’s presentation of the Bashash et al (2017) study.

I have critiqued this study in previous articles – readers can find them at:

Fluoride, pregnancy and the IQ of offspring,
Maternal urinary fluoride/IQ study – an update,
Anti-fluoridation campaigners often use statistical significance to confirm bias and
Paul Connett “updates” NZ MPs about fluoride?

Paul is clearly aware of these articles because he included a note in his presentation about them. I am honoured (it is the only comment in the presentation) and pleased he has made an effort to engage with my critique.

This is what he says:

“Ken Perrott and those who follow him will claim that the wide degree of scatter in the data means the findings of this study are unreliable.  That is an incorrect interpretation of this graph and the study.  The effect size is very large (decrease by 5-6 IQ points per 1 mg/L increase in urine F) and is highly statistically significant.  The fact that urine F can only explain a small amount of the variation of IQ does not invalidate the finding.  Rather, it is a reflection that there are many other factors that affect IQ, most of which are essentially random with respect to F exposure.  For example, individual genetics plays a huge role in IQ (it explains 80% or more of variation in IQ), therefore it would not be possible for F to explain more than the small remaining portion of variation in IQ.  Most studies of other developmental neurotoxins like Pb and Hg find very similar low correlation coefficients, yet there is no debate that their findings are valid.”

This comment provides me with a basis for a more detailed discussion of his use of the study.

The small amount of variance explained

Connett acknowledges my point that the observed relationship with urinary fluoride can explain only a very small amount of the variation in IQ – only 3%. A bit hard to deny considering the high degree of scatter in the data which is obvious even in the slides Connett uses:

Slide 20 where Connett reproduces Fig 2 from the Bashash et al. paper.

But he claims that this:

“does not invalidate the finding. Rather, it is a reflection that there are many other factors that affect IQ, most of which are essentially random with respect to F exposure.”

Here he is, of course, referring to his own “finding” or conclusion – not the authors.

Notice his assumptions:

  • Other factors will be “essentially random with respect to F exposure,” and
  • The observed relationship will not be changed by the inclusion of these other factors.

Those are huge assumptions. And they are wrong.

Here is a relevant example illustrating the danger of such assumptions – the association between ADHD prevalence and extent of fluoridation observed by Malin & Till (2015). Their association was able to explain between 22% and 31% of the variance in ADHD, depending on the specific data used. Far more than the 3% for the Bashash et al., (2017) study.

Yet, when other risk-modifying factors were included, in this case, mainly altitude, the significant association with fluoridation disappeared. A model including altitude, but not fluoridation, explained 46% of the variability in ADHD (see Perrott 2017 and a number of articles in this blog).

In this case, the incidence of fluoridation was correlated with altitude – fluoridation was simply acting as a proxy for altitude in the Malin & Till (2015) association. So much for Connett’s assurance that other factors “are essentially random with respect to F exposure.”

Other studies have found an association between symptoms of fluorosis and cognitive deficiencies. Choi et al., (2015), for example, reported an association of child cognitive deficits with severe dental fluorosis, but not with water F concentration. But there is a relationship between fluoride exposure and fluorosis prevalence – ie. fluorosis is not random with respect to F exposure. If the health effects resulting from fluorosis are the prime cause of the cognitive deficiency, the inclusion of fluorosis incidence in the multiple regression could produce a model where there is a statistically significant association with fluorosis but not with fluoride expose. That is, the urinary fluoride values could be simply acting as a proxy of fluorosis incidence.

A similar non-random association of premature births and low birth weight could occur because these problems do occur in areas of endemic fluorosis. These could be two of the health issues related to fluorosis but fluoride intake may not be the prime cause (see Premature births a factor in cognitive deficits observed in areas of endemic fluorosis?).

Connett is completely wrong to assume that other risk-modifying factors not considered in the Bashash study would necessarily be random with respect to fluoride exposure. And he is wrong to assume that inclusion of these factors would not change the association of child IQ with mothers’ urinary fluoride reported in the paper.

Notably, the Bashash et al (2017)study did not include any measure of fluorosis as a risk-modifying factor – despite the fact that Mexico has areas of endemic fluorosis. I believe its consideration of gestation period <39 weeks or >39 weeks was inadequate (the normal average period is 40 weeks). The cutoff point for birth weight (3.5 kg) was also high.

The size of the IQ effect

We only have the data in the Bashash et al., (2017) study to go with here and the associations they report are valid for that data. But what about the calculations Connett makes from the reported association.

For example, Connett declares:

” The effect size is very large (decrease by 5-6 IQ points per 1 mg/L increase in urine F) and is highly statistically significant.”

Let’s test this claim – using the association represented in Fig 2 from Bashash, which is the figure Connett and other anti-fluoride activists are using (his slide 20 above).

Firstly, we need to calculate prediction intervals from the data (see Confidence and prediction intervals for forecasted values). The shaded region in the figure used by Connett (Fig 2 in Bashash et al., 2017) represents the confidence interval – the region where there is a 95% probability that a best-fit line for the data lies. The region for the prediction intervals is much larger and Connett may be confused because he has interpreted the confidence interval wrongly. Yet, the prediction intervals are the important measure when considering the effect size.

Here are my graphs for the confidence interval and the prediction interval using data I digitally extracted from the paper (see Maternal urinary fluoride/IQ study – an update).

Let’s consider the predicted values of “child IQ” for urinary F concentrations of 0.5 and 1.5 mg/L.

Urine F (mg/L) Predicted value Lower Higher
0.5 99.8 74.4 125.2
1.5 93.0 67.5 118.4

The prediction intervals are very large. This means the real value for “child IQ” at a urine F value of 0.5 mg/L has a 95% probability of being in the range 74.4 – 125.2. The corresponding range for a urine F concentration of 1.5 mg/L is 67.5 – 118.4. When Connett claims that an increase of 1 mg/mL in mother’s urinary F produces a drop of 5 – 6 IQ points he actually means a drop of 5 – 6 ± 26 IQ points which is not statistically significantly different to zero.

The best-fit line for the data may be statistically significant – but Connett is wrong to say this about his predicted effect of urinary F on child IQ. In fact, over the whole range of urinary F measured there is a 95% probability that IQ remains at 100.

Connett’s claim of a “highly statistically significant” effect size is completely false. If he had simply and objectively looked at the scatter in the data points he would not have made that mistake.

Comparing maternal urinary F levels to other countries

Connett makes an issue of the similarity of maternal urinary F levels found in this Mexcian study to levels found elsewhere. One is tempted to say – so what? After all, I showed above that his claim of a “highly statistically significant” drop in child IQ with increases in maternal urinary F is completely wrong.

He does compare the urine F levels reported by Bashash et al., (2017) with some New Zealand data (Brough et al., 2015) and finds them to be very similar. Interestingly, Brough et al., (2015) reported their urinary F values as indicating fluoride intakes were inadequate for the women concerned. They certainly did not indicate toxicity.

The comparison does highlight for me one of the inadequacies in the Bashash (2017) paper – the inadequate measurements of urinary F. Whereas Borough et al., (2015) used the recommended 24-hr urine collection technique, the data used by Bashash et al (2017) relied on spot rather than 24 hr measurements. These spot measurements were only made once or twice during the pregnancy of these women.

Yes, these were the only F exposure measurements Bashash et al., (2017) had to work with but they are far from adequate.


Paul Connett, as a leader of the anti-fluoridation movement, is completely wrong about the Bashash et al., (2017) study. It will not lead to the end of community water fluoridation throughout the world – nor should it.

He has attempted to ignore, or downplay, the high scatter in the data and the low explanatory power of the relationship between children’s IQ and maternal F exposure found in the study (only 3%). His denial that this relationship may disappear when other more important risk-modifying factors are included is also wrong – as other examples clearly show.

Connett’s presentation of a size effect (5-6 IQ points with a 1 mg/L increase in F exposure) as “highly statistically significant” is also completely wrong. In fact, this size effect is more like 5 – 6 ± 26 IQ points which is not significantly different to zero.

The misrepresentation of this study by Paul Connett and other anti-fluoridation activists demonstrates, once again, that their claims should never be accepted uncritically. This is just one more example of the way their ideological and commercial interests drive them to misrepresent scientific finding.

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Paul Connett “updates” NZ MPs about fluoride?

Data from Bashash et al., (2017). Despite a statistically significant relationship of child IQ with mothers prenatal urinary fluoride, this explains only about 3% of the huge scatter in the data.

I haven’t followed the latest speaking tour of Paul Connett – organised by the local Fluoride Free NZ organisation. But I watched a TV interview with him this morning and came away thinking he is skating on very thin ice – scientifically. He has put all his eggs in one basket – promoting a Mexican study as the be-all and end-all of scientific research which should lead to the immediate ceasing of community water fluoridation.

Paul is a leader of the anti-fluoride activist group the Fluoride Action Network and appears to love visiting New Zealand during our summer (and his winter). Local campaigners seem to idolise him – and rely heavily on him as a self-declared  “world expert on fluoridation.” But this idol has feet of clay (don’t they all?).

In fact, Paul has no original research on fluoride and is simply presenting a biased picture of the scientific literature on the subject., He relies heavily on his academic status and qualifications to give his biased views respectability.

But back to the Mexican study. Paul is referring to this paper:

Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., … Hernández-avila, M. (2016). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico.Environmental Health Perspectives, 1, 1–12.

I have written about this study in some detail in my articles:

Here I will simply return to the poor explanatory power of fluoride for the children’s IQ measured in the study.

The graph above is a plot of the data from the paper – child IQ compared with the pre-natal urinary fluoride levels of the mothers.

Now, Paul describes this study as “rigorous” and relies heavily on it. But despite a statistically significant relationship, the huge scatter in the data really stands out.

In fact, this relationship explains only about 3% of this scatter! It probably only appears because the researchers did not include any proper risk-modifying factors in their regression analysis.

Well, Paul is making a big thing of speaking to New Zealand MPs tonight to “update” them on this latest research. Rather smug because it implies the research is his – when it isn’t.

But this research does not “prove” what Connett implies. It is not as rigorous as he claims. And it is certainly not an argument to stop community water fluoridation in New Zealand.

Note: Paul Connett and I had a scientific exchange on the fluoridation issue four years ago. Interested readers can download the full text from Researchgate –  The fluoride debate.

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