Tag Archives: IQ

When scientists get political: Lead fluoride-IQ researcher launches emotional attack on her scientific critics

age credit: Science and Politics – Skeptically.org

It seems impossible to keep politics out of science. It’s a pity because politics can end up forcing science to produce the results desired by politicians. When this happens the ideal aim of science – the pursuit of objective knowledge – can get lost.

We rightly disapprove of external political and commercial influences on science. But there is another insidious form of politics derived from ego, personal ambition and the promotion of research by institutes and individual researchers. This is very often driven by the competition for research funding – the loudest researcher gets the grant. These days this is a real problem – the classical introverted scientist, no matter how bright, is often at a complete disadvantage when it comes to the fight over research funding.

In my own career, I have seen excellent researchers driven to redundancy simply because they did not have the political skills to fight for research funds. And at the same time, I have seen mediocre scientists, often producing poor quality or even misleading science, get those funds – simply because of their ambition and political skills.

These thoughts came flooding back to me as I read the new opinion piece by Christine Till, the leader of the research group that published several of the recent fluoride-IQ/ADHD and similar papers that I have critiqued here. Papers that have been heavily promoted by the authors and Till’s institute as well as the anti-fluoride/anti-vaccination crowd and, at the same time, extensively critiqued by the scientific community.

The citation  for her article is:

Till, C., & Green, R. (2020). Controversy: The evolving science of fluoride: when new evidence doesn’t conform with existing beliefs. Pediatric Research.

Unfortunately, the article is not a reply to critics or a good faith scientific engagement with the scientific issues. It is simply an attack on those who have made honest and respectful critiques. An attack which attributes unjust motives to her critics and comes close to personal.

Attempt to close down science by personal attacks

I discussed some of these issues before in my articles Scientific integrity requires critical investigation – not blind acceptance and Fluoridation science and political advocacy – who is fooling who?

In this case, I was concerned about the way  Dr William Ghali, one of the promoters of  Christine Till’s work, attacked and attempted to belittle scientific colleagues who were indulging in the normal peer-review process of critiquing published papers which they considered had faults. Nothing new about that scientific critique – it goes on all the time. It is expected by authors and, in the end, it helps to improve the science. I Personally think such critique should be welcomed by researchers.

If the opponents of scientific exchange like Dr Ghali are successful in their attempt to prevent such scientific debate then we are all losers. How can we trust scientific findings that are protected from scrutiny?

This is what is wrong with the opinion piece by Till and Green cited above. Instead of entering into a good-faith scientific exchange with their critics they attribute motives and biases to them. Even accusing them of attempting to prevent the progress of science. They accuse critics of a “tendency to ignore new evidence,” of  “overt cognitive bias” and of promoting  a “polarized fluoride debate.”

But, in fact, these critiques have come because the “new evidence” is not being ignored but is being evaluated. It is being critically considered. The article more or less admits this when it says “critics attacked the methodology of the study [Green et al (2019] and discounted the significance of the results.

True, the so-called “fluoride debate” is polarised. After all, it is being promoted by anti-fluoride/anti-vaccination activists who are attempting to prevent or remove, a health policy known to benefit children. Till & Green may be unhappy that they have not been able to win over the scientific community with their paper but it is hardly honest to reject the critiques of the paper by calling them “attacks” or by claiming they “ignore” the evidence.

An admission the paper had difficulties

The article admits the  Green et al (2019) paper had difficulties right from the beginning. It took three attempts before a journal would accept it for consideration. Even then it ended up having “several additional rounds of review by the JAMA editors until we eventually reached a compromise.” This gives some substance to my speculation of problems in the review process which lead to the unprecedented publication of an editor’s note – a political action  I have never seen before (see If at first you don’t succeed . . . statistical manipulation might help).

They acknowledge that even their colleagues in environmental epidemiology “were initially sceptical.” And so they should have been – all new research should be reviewed sceptically and critically.

Refusing to engage scientifically

But the annoying thing is that these authors attempt to write off the scepticism and critical review of the wider scientific community as being due to “experts” (yes in quotes), “who held strong beliefs . .” This despite the fact that in the published critiques it is not “strong beliefs” which were presented, but detailed consideration of the methodology and statistical analyses used in the original paper.

All these critiques were made respectfully – and often with thanks to the Green et al (2019) for their new work. Yet Till and Green accuse these reviewers of making “vitriolic comments and claims with little scientific basis” – a comment which is, in itself, disrespectful to those who took time to make their critiques. They resort to smearing two of the reviews (by the UK-based Science Media Centre and Dr Berezow, a specialist from the American Council on Science and Health) by accusations these bodies are “both heavily funded by the pharmaceutical and food and beverage industries.” This funding smear is commonly used by anti-science activists who attempt to discredit scientific findings or analysis but refuse to consider the science itself.

They say of these two reviews that they claim “the results are driven by outliers” – yet a simple search shows that this comment simply does not appear in the cited reviews.  The critique of Dr Berezow from the American Council on Science and Health does not include either of the words “outlier” or “driven.”

The only reference to “outliers” in the Science Media Centre review was by Dr Oliver Jones, Associate Professor of Analytical Chemistry, RMIT University who wrote:

“The authors state that an increase of 1 milligram per liter (1 mg/L) increase in fluoride was associated with a 4.49 point lower IQ score but fluoride intake appears to have been below 1 mg/L for most people in the study, even for those with fluoridated water, and nearly everyone (bar a few outliers) had a fluoride intake of less than 2 mg/L (which multiple previous studies have shown is safe) . There is also a Lot of variation in the data – which makes drawing firm conclusions/ predictions from it difficult.”

A valid criticism which needed a response – not a smear.

My search for the word “driven” produced these two comments:

Dr Joy Leahy, Statistical Ambassador, Royal Statistical Society, wrote:

“if a woman is living in an area with fluoridated water during pregnancy, then her child is likely to grow up drinking this same fluoridated water. Therefore, it is difficult to say whether any association found is driven by the fluoride consumption in pregnancy, or an assumed fluoride consumption in the infant after birth.”

Prof Rick Cooper, Professor of Cognitive Science, Birkbeck, University of London, said:

“a significant decrease in IQ was found only in boys – girls showed a non-significant increase in IQ. The negative effect was driven by a small number of boys whose mothers had extreme levels of fluoride exposure, but even these children had IQ in the normal range.”

These are valid points that again deserve a scientific response yet Till & Green describe them as “vacuous claims exemplify attempts to manipulate the scientific evidence and manufacture doubt.”

We all support using new knowledge to adjust policies

Till & Green attempt to claim the high moral ground by asserting:

“Science advances by continuously challenging old ideas and adjusting our beliefs as new knowledge emerges, even if this new evidence conflicts with conventional wisdom or is inconvenient.”

Of course, this is true and I think it is dishonest of them to pretend this is not also the position of those who critiqued their paper. These reviewers were interested in looking at the new results, evaluating them and seeing how relevant they are. Seeing if they do indeed require us to adopt new thinking.

After all, look at what Dr Berozow, one of the critics they smeared by implying he was influenced by industry funding  and was falling back on “vitriolic comments” and “vacuous claim”, says in introducing his critique:

“The investigation by Green et al into the effect of maternal consumption of fluoride on the IQ of children is important. It is always wise to constantly evaluate and reevaluate long-standing public health practices in the light of new evidence.”

Till & Green are simply resorting to attributing motive and asserting their critics are not open to new knowledge as a way of avoiding facing up to the valid criticisms made by experts who reviewed and critiqued their work.

Confirmation bias – the pot calls the kettle black

We all suffer from confirmation bias and scientists (including Till & Green) are not immune. It is well understood that scientists are the last people to recognise problems in their own work. That is why peer review and open critique of scientific reports is so essential. But, in line with the whole approach of this opinion piece, Till & Green attempt to present a picture that only their critics suffer from this problem. They say:

“We typically fret about subtle biases, like recall bias and unmeasured confounding, but confirmation bias, the tendency to ignore or debunk data that does not conform to what we believe, is arguably a much larger problem.”

I find their attempt to belittle concerns about “unmeasured confounding” rather ironic. After all, this was the problem with Till’s original fluoride-ADHD work (which she used to win research grants for her later fluoride research) that I highlighted in Perrott (2018) Fluoridation and attention deficit hyperactivity disorder – a critique of Malin and Till (2015).

I am aware that Till has read my paper in its pre-publication and published forms but studiously ignores it. For example, the ADHD paper of Riddell et al (2109), which she co-authored, simply does not include Perrott (2018) in its discussion and continues to present Malin & Till (2105) as authoritative despite the obvious flaw that it ignored important confounders, and when these are considered their claim of a relationship between fluoridation and ADHD prevalence proved to be false.

So much for her attribution of confirmation bias to others – when she is obviously guilty of it in this case by ignoring “data that does not conform, to what [she] believes.”

The Till & Green opinion piece is unwise

Till & Green seem to have simply reacted emotionally to the reviews and critiques the Green et al (2019) paper received. They, of course, had the right – even the obligation – to respond scientifically to the reviews. But I believe their response in this article is unwise, maybe even professionally damaging,  and they should not have committed these emotional outbursts to print. After a cooling down period, it is possible they will withdraw the article – and that would be best for them in the end.

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New study touted by anti-fluoridation campaigners actually indicates fluoridation is safe

Children used in this study were from Lintingkou town (a normal-fluoride/control area) and Dakoutun town (a high-fluoride area) in Baodi district of Tianjin, China. The towns are 25 km apart.

Anti-fluoridation activists on social media seem to cite any scientific article about fluoride which they think will show it harmful. They usually rely only on information in the article title or abstract. This means they are often wrong as the articles may not be at all relevant to the low fluoride concentrations used in water fluoridation. Perhaps they should stop for a minute and actually read the articles they cite.

The other day @NYSCOF, the twitter account for the New York State Coalition Opposed to Fluoridation, Inc (a small antifluoridation activist group in New York) promoted a new Chinese study as part of its campaign against community water fluoridation (CWF). It claimed: “Children’s IQ was lower when water and urinary fluoride levels were high compared to a low fluoride group.” But the fact this is a Chinese study should have warned the honest reader that the “high” fluoride group lived in an area of endemic fluorosis and data for them is irrelevant to CWF.

In fact, some of the data in their paper are relevant to CWF – the data for the “low fluoride” control group where children were exposed to drinking water concentrations less than 1 mg/L (CWF aims to maintain a drinking water fluoride concentration of about 0.7 or 0.8 mg/L). It’s worth looking at that data to see if child IQ is related to fluoride exposure at that level.

The take-home message is that it isn’t.

Here is the citation for the new study:

Zhao, Q., Tian, Z., Zhou, G., Niu, Q., Chen, J., Li, P., … Wang, A. (2020). SIRT1-dependent mitochondrial biogenesis supports therapeutic effects of resveratrol against neurodevelopment damage by fluoride. Theranostics, 10(11), 4822–4838.

Two different communities

The children (8-12 year-olds) in this study came from two different communities in the Baodi district of Tianjin, China – see the map above. They are Lintingkou town, where drinking water fluoride concentrations were “normal,” and Dakoutun town, which is in an area of endemic fluorosis and the drinking water fluoride concentrations are high (about 1 to 3.5 mg/L). The towns are about 25 km apart and will clearly have a number of differences which could be relevant to the IQ of children. Possible confounders like this were not considered in the study.

People living in areas of endemic fluorosis suffer a range of health and socioeconomic effects which could influence child IQ

The figure below from the paper illustrates the ranges of drinking water F and urinary F for the children studied (30 in each of the “low” and “high” fluoride groups).

Only the data for the “control” group are relevant to CWF. Unfortunately, the authors chose to plot the IQ data for the two groups on the same graph and concluded that this showed a “fluoride-caused intellectual loss in children” – see their graph below.

But, their conclusion is wrong. When we look at the data for the “control” and “high fluoride” groups separately that simple conclusion is clearly unwarranted.  In fact, there is no statistically significant relationship (p<0.05) of child IQ with urinary F for either the “low” or the “high” group – see the graph below which uses digitally extracted data from the above figure. Data points for the”low” fluoride group are green and those for the “high” fluoride group are red.

This shows how statistical analyses like regression analyses can produce misleading results if the data is not considered properly. It is simply misleading to include two separate populations like this in a regression analysis without considering the whole range of possible confounders.

There is no relationship between child IQ and urinary fluoride in either population. All the regression analysis shows is that there is a difference between the two towns – and that is simply shown by the average values of IQ in those towns. The average child IQ in Lintingkou town is 112.4 while in Dakoutun town it is 98.5.

While these IQ values seem pretty good (usually the average IQ for a population is 100) the lower value for Dakoutun town is not surprising considering that the population living in areas of endemic fluorosis suffer a whole range of health and social problems.

The biochemical data has the same problem

The paper itself is a real hodgepodge of separate studies involving child IQ, levels of mitochondrial biogenesis signalling molecules, experiments with rats and with in vitro cell cultures. I do not have the expertise to critique the biochemical, cell culture and rat behavioural techniques used. However, the presentation of the biochemical data for the children suffers the same problems as the presentation of the IQ data.

The authors claim that there is a significant positive relationship between the silent information regulator 1 (SIRT1) and child urinary F, and significant negative relationships of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and mitochondrial transcription factor A (TFAM) with child urinary F. But they simply lumped the data for the two towns together. When the data for the two groups are considered separately there are no statistically significant relationships for these biochemical measures in either of the two groups – see figures below. Again, data points for the “low” fluoride group are green and those for the “high” fluoride group are red.

Conclusions

Yet against anti-fluoride campaigners are promoting a study that they probably haven’t even bothered reading. They are using results for an area of endemic fluorosis to argue against CWF. Worse, they are completely ignoring the data in this and similar studies which show no relationship between child IQ and fluoride exposure at fluoride levels relevant to CWF.

Note

The Twitter account @NYSCOF promoting this specific study is very active and is connected with the Fluoride Action Network (FAN) through Carol Kopf –  the media officer for both the New York State Coalition Opposed to Fluoridation, Inc. (NYSCOF) and FAN. Ironically, she uses the slogan “I Am a Force for Science” on her Twitter image.

Sometimes I drop a reply to her posts – in this case pointing out: “And no loss of IQ at F concentrations relevant to community water fluoridation. These studies show CWF safe.”

My comment will not change Carol Kopf’s mind, of course, but others may read it and understand. Mind you, it’s inevitable that other anti-fluoride activists see my comments and react in stupid ways. For example, one of the Fluoride Free NZ leaders, Kane Kitchener, posted this reply:

“Ken, you’ve been exposed too long by Hamilton’s Fluoridated water. Too much reduction in IQ to see it.”

It really is pointless attempting to discuss science with these people.

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New review finds fluoride is not a developmental neurotoxicant at exposure levels relevant to fluoridation

Proper consideration of the best science shows community water fluoridation does not have a negative effect on child IQ. Image credit: Africa Studio / Shutterstock.com

A new extensive review of the scientific literature has concluded that fluoride is not a human developmental neurotoxicant at the current exposure levels in Europe. This is of course just as valid for New Zealand, the USA and other countries which use community water fluoridation (CWF).

Forty-one pages long, it’s a very extensive and detailed review. The full text can be downloaded  and its citation is:

Guth, S., Hüser, S., Roth, A., Degen, G., Diel, P., Edlund, K., … Thomas, H. (2020). Toxicity of fluoride: critical evaluation of evidence for human developmental neurotoxicity in epidemiological studies, animal experiments and in vitro analyses. Archives of Toxicology. 2020 May 8.

The anti-fluoridation crowd won’t be happy with this review. They have tended to have things their own way as they have argued that fluoridation is harmful to child IQ using irrelevant studies from endemic fluorosis areas where people suffer a range of health effect from overexposure to fluoride and other contaminants. Anti-fluoride campaigners have also misrepresented and misused recent studies from areas where fluoride exposure is lower.

So this review is timely because it critically examines all the recent studies and identifies their limitations. It identified 23 relevant epidemiological studies published between January 2012 and August 2019. One of these examined an association between fluoride exposure and school performance. The other 22 examined possible relationships with IQ.

Limitations of fluoride-IQ studies

The authors reported that:

“So far, almost all studies investigating the effect of fluoride intake on intelligence were performed in relatively poor, rural communities, e.g., in China, Iran, and Mongolia, where drinking water may contain comparatively high levels of fluoride (‘exposed population’), whereas the ‘reference populations’ often had access to water that was fluoridated at the recommended level.”

Figure 1: People in endemic fluorosis area sufferer a range of health problems – studies from these areas are not relevant to CWF

This means that anti-fluoride campaigners usually rely on studies which actually show no effect at F intake levels relevant to CWF. They base their arguments on the known negative health effects at high fluoride intake (people in areas of endemic fluorosis suffer a range of health problems) but ignore, or cover-up the fact the data actually does not show any harmful effects at levels similar to that experienced by people in areas of CWF.

Figure 2: Drinking water concentrations reported by Duan et al. (2018) from “high F” and “low F” villages compared with tap water F in areas of CWF

Figure 2 above shows this using data from 26 studies reported in the review of Duan et al. (2018). Here the blue range represents the drinking water concentration range for the control groups where no health problems were reported, or it was assumed none occurred (that is why it was a control group). The green range represents drinking water fluoride concentration common in areas of CWF.

We should be drawing our conclusions about the possible effects of CWF from the blue range of data – not the red range.

Confounding effects

Guth et al (2020) stress that most studies they considered ignored many confounding effects.  For example:

” . .rural regions with unusually high or unusually low fluoride in drinking water may be associated with a less developed health-care system, as well as lower educational and socioeconomic status. Furthermore, in these regions the overall nutritional status and the intake of essential nutrients may be lower and the exposure to environmental contaminants such as lead, cadmium, mercury, or manganese may be higher—factors that are also discussed to have a potential impact on intelligence”

Only two of the studies were from areas using CWF – Broadbent et al (2015) and Green et al (2019) – and their conclusions were different. Guth et al (2020) considered these two studies in detail.

Both studies were limited by the lack of IQ data for mothers – parental IQ is a strong confounder for child IQ studies. But Guth et al (2020) are quite critical of the lack of consideration of confounders in the Green et al (2019) study:

Green et al. (2019) did not consider breastfeeding and low birth weight as possible confounders (both factors significantly associated with IQ in the study of Broadbent); they considered some of the relevant confounders (city, socioeconomic status, maternal education, race/ethnicity, prenatal secondhand smoke exposure), but did not adjust for others (alcohol consumption and further dietary factors, other sources of fluoride exposure, exact age of children at time point of testing). Furthermore, the study (Green et al. 2019) did not include assessment of children’s postnatal fluoride exposure via, e.g., diet, fluoride dentifrice, and/or fluoride tablets, which is considered to be a noteworthy limitation.”

Problems like poor consideration of confounders, contradictory results and the vague results reported by Green et al (2019) (no overall effect of fluoridation on child IQ, a statistically significant relationship of drinking water F concentration with male child IQ but not with female child IQ) caused Guth et al (2020) to conclude:

“The available epidemiological evidence does not provide sufficient arguments to raise concerns with regard to CWF in the range of 0.7–1.0 mg/L, and to justify the conclusion that fluoride is a human developmental neurotoxicant that should be categorized as similarly problematic as lead or methylmercury at current exposure levels.”

To repeat – this review is very detailed and thorough. Unlike the recent review of Grandjean (2019) (Developmental fluoride neurotoxicity: an updated review) which was superficial and somewhat biased (Grandjean is well known for his opposition to CWF) it made a detailed assessment of problems like the poor consideration of confounders or important risk-modifying factors and the concentration on poor quality studies from areas of endemic fluorosis.

Hopefully, policymakers will read this new review and take its conclusions into account.

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Anti-fluoridation propaganda now relies on only four studies. 6: Incestuous relationship of these studies

A Fluoride Action Network (FAN) propaganda video where Paul Connett urges listeners to consider only four studies when considering the possible harmful effects of fluoridation.

Paul Connett, director of the Fluoride Action Network (FAN), now claims “You only have to read four studies…” to come to the conclusion that community water fluoridation (CWF) is bad for your health. He wants you to ignore all the other research – which is just bad science.

But this is even worse than it looks because these four studies are hardly independent. They basically represent the work of one or two groups and weaknesses in the studies indicate the groups are basically “torturing” data to produce relationships which confirm their likely biases against CWF. The same researchers appear as authors on most of the published papers from these studies.

But that is not all. There is evidence of an “old boy/girl network” operating within these research groups where journal peer reviewers are selected from the same groups.

It’s called “taking in each other’s laundry.”

For earlier articles in this series see:

In this article, I discuss the incestuous relationship of the studies promoted by Connett and show these researchers have links to anti-fluoride activism.

Links between the four studies

One indication of the lack of independence of these studies is the fact that the papers have common authors. The figure below reveals these links between the studies via their authors with the names in red being authors on more than one of the papers.

The above diagram indicates the four studies came from no more than 2 groups.

Martinez-Meir is common to both groups – probably because her laboratory was responsible for the analysis of maternal urinary fluoride.

Christine Till has been responsible for several of these studies as she obtained funding on the back of the flawed Malin & Till (2015) study (see Leader of flawed fluoridation study gets money for another go).

Till and Lanphear appear to have responsibility for formulating and designing these studies.

So it is wrong to see these as completely independent studies. They will all be influenced by the biases of the groups involved and the links shown in the figure above suggest coordination in publishing their research findings.

This becomes more apparent when we look at the journals involved in publishing some of this work and the peer reviewers used.

Links with peer reviewers

Unfortunately, very few journals make available the names of peer reviewers or the contents of their reviews. A pity, as I would like to understand better the controversy that seemed to erupt during the journal review of the Green et al (2019) paper, for example. (This controversy resulted in an unprecedented brief statement from the Editor and an opinion piece by David Bellinger promoting the paper – see If at first you don’t succeed . . . statistical manipulation might help).

However, some of the researchers have published their fluoride work in the journal Environmental Health which in recent years has published peer reviewer names and the contents of their reviews. So let’s look at papers published by the authors Connett is promoting where this peer review information is available. They were all published in Environmental Health and are:

This diagram illustrates some of the papers and the reviewers and links the authors and reviewers.

Note: The extra papers considered in the figure are:

Yes, it’s a real network and perhaps it’s not necessary to follow the details of each link. We can see, though, that authors on these papers often appear as journal peer reviewers of other papers from these research groups.

I suspect this situation may be more common in science publishing than we realise – especially as journals now often ask authors to suggest possible reviewers and to specifically name researchers they do not want to review their work.

I think that is bad for the quality of published research. It’s easy to see that in a network like this peer review is done within the groupthink (or bias) that exists in such a network. I raised this problem when commenting on the peer review of an earlier paper from the network – Malin & Till (2015) – in my articles Poor peer-review – a case study and Poor peer review – and its consequencesIn this case, the reviewers were fixated on chemical toxicity as the reason for health problems so did not consider all the other possible factors that might be responsible for the prevalence of ADHD diagnoses. They, therefore, missed completely possible regional effects which were at the time shown as important (see Perrott 2018).

This author/peer-reviewer network is particularly bad in situations like this where a controversial or even flawed paper gets approval simply because of the common biases of authors and peer reviewers.

Links with anti-fluoride campaigners

Notice in the figure above that two of the reviewers for Grandjean’s paper are members of FAN – senior members at that. While their contribution to improving the paper was probably minimal (Spittle’s comment – “The review capably considers recently available information and is highly pertinent to the public health” was worthless) the fact these reviewers were selected by the journal (and possibly by the author who is also the Chief Editor of the journal) indicates some influence.

These links indicate some sort of “under the table” influence and linking of researcher with FAN which probably explains why FAN often seems to have early information about upcoming publications which enable them to launch timely propaganda pieces.

Journals used for publication

Environmental Health is open access and a pay-to-publish journal. Pay-to-publish is becoming more common but many researchers steer away from these journals because they tend to have a reputation that payment encourages publication of bad research. On the positive side (as I said above) the open access policy, in this case, helps us see when the peer reviewers are and understand the problems I have discussed.

A relevant aspect of the author-peer-reviewer network, in this case, is the involvement of journal editors in the network as shown by this diagram.

NOTE: See notes for previous figure.

Phillipe Grandjean is also the author of Grandjean et al (2019) which appeared in the previous figure. I have written about his specific biases regarding fluoride in the past (see Special pleading by Philippe Grandjean on fluoride) and it is notable that as Editor in Chief of Environmental Health he refused to even consider for publication my paper critiquing Malin & Till (2015) (see Fluoridation not associated with ADHD – a myth put to rest).

David Bellinger is linked to the Bashash et al (2018a) study, not as an author, but as the note in the paper says:

“David Bellinger collaborated on the design and execution of this study’s cognitive testing.”

So it’s not surprising to see him authoring a promotion of the Green et al (2019) paper – although the inclusion of that promotion and the special note from the journal’s editor in that issue of the journal is very unusual.

Conclusions

The lack of independence in these four studies really reinforces the danger of limiting one’s reading. It’s not just a matter of restricting reading to four papers – its a matter of restricting information sources to one (or perhaps two) research groups influenced by the same groupthink and biases.

Group thinking and bias within research groups are not new. Nor is it a surprise that journals can be influenced by such group thought and bias and that this influences their acceptance of papers for publication. But if you are aware of the problem then you realise the need not to restrict your reading in the way that Connett is suggesting.

If anything, Connett’s statement is an admission that the overall findings of scientific studies on this issue do not support his case. He admits that all the studies anti-fluoride activists had been relying on in the past suffer from relating only to high fluoride concentrations. His plea people now restrict their reading to only four studies which really limits information sources to one or perhaps two research groups with a bias against CWF, is aimed at censoring the wider information availble.

Even more reason for readers to beware. One should never restrict information sources in the way Connett is suggesting.

See also:

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Anti-fluoridation propaganda now relies on only four studies. 4: Till et al (2020)

Paul Connet, head of the anti-fluoride propaganda group, Fluoride Action Network, claims that the IQ of children bottle-fed in fluoridated areas drops by 9 points. But he misrepresented the research. There is no observable effect.

For earlier articles in this series see:

Part 1: Anti-fluoridation propaganda now relies on only four studies. 1: Bashash et al (2018).

Part 2: Anti-fluoridation propaganda now relies on only four studies. 2: Green et al (2019).

Part 3: Anti-fluoridation propaganda now relies on only four studies. 3: Riddell et al (2019).

Paul Connett, director of the Fluoride Action Network (FAN), now claims “You only have to read four studies…” to come to the conclusion that community water fluoridation (CWF) is bad for your health. As I said in the first article in this series that is simply bad science. One should not ignore all the other relevant studies – and anyway, these four studies do not say what Connett claims.

In this article, I discuss the fourth study Connett recommends. It’s citation is:

Till, C., Green, R., Flora, D., Hornung, R., Martinez-mier, E. A., Blazer, M., … Lanphear, B. (2020). Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environment International, 134(September 2019), 105315.

Till et al (2020)

Finally, according to Connett:

“The fourthcame in 2020, when it was reported that children who were bottle-fed in fluoridated communities in Canada lost up to 9 IQ points compared to those in non-fluoridated communities.”

This claim is just not true as Table 5 below shows. There is no significant difference in IQ (FSIQ) of children, who had been bottle-fed as babies, between fluoridated (mean IQ 106.1) and unfluoridated (mean IQ 106.8) areas. The only difference Till et al (2020) saw between fluoridated and unfluoridated areas was a significant increase of verbal IQ (VIQ – a subset of FSIQ) for breastfed children in fluoridated areas compared with non-fluoridated areas, and a significant decrease in performance IQ (PIQ a subset of FSIQ) for formula-fed babies in fluoridated areas compared with non-fluoridated areas.

Table 5. Influence of fluoridation on the IQ, VIQ and PIQ of children breastfed or formula-fed as babies found by Till et al (2020)(* indicates statistically significant difference)

Connett appears to have not read the Till et al (2020) paper, or misunderstood it. Perhaps his misunderstanding is derived from the relationships of cognitive measurements with drinking water F – although the relationships are not statistically significant for IQ (FSIQ) (see Table 6 below).

Then perhaps he is grasping at the straws offered by separating the IQ measurements into subsets – VIQ and PIQ. There were no significant relationships for VIQ but there are for the relationships of PIQ to drinking water F for both breastfed and formula-fed children. In fact a decrease of almost 8 PIQ points per 0.5 mg/L water fluoride concentration increase (which the authors argue is the increase seen with fluoridation).

Table 6: Relationships of cognitive measures with exposure to fluoride for children breastfed or formula-fed as babies reported by Till et al (2020)

This study has all the hallmarks of a desperate search for significant relations by using other measures of cognitive ability and fluoride exposure when the main relationship (that of FSIQ and CWF) proves not to be statistically significant. This approach, which statisticans are critical of, is common with most of the studies Connett relies on for his current claims.

There is also the problem that the authors in  their abstract, and of course the anti-fluoride activists promoting the paper, basically ignore most of the relationships because they are not statistically significant and report only the significant ones – and even then often incorrectly (as does Connett who uses the term IQ inappropriately).

Connett is wrong. His claim that “bottle-fed in fluoridated communities in Canada lost up to 9 IQ points compared to those in non-fluoridated communities” is just plain wrong. In fact, the mean IQ values for bottle-fed children in fluoridated areas of Canada was 106.1 and in non-fluoridated areas was 106.8 according to this study.

Tomorrow I will discuss other studies Connett purposely ignores and attempts to cover up because he cannot construe them as supporting his anti-fluoride narrative – see Anti-fluoridation propaganda now relies on only four studies. 5: Don’t censor yourself.

See also:

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Anti-fluoridation propaganda now relies on only four studies. 1: Bashash et al (2018)

This is the advice from the very top of the anti-fluoride movement – Paul Connett, director of the Fluoride Action Network (FAN). Don’t worry about reading  up on all the scientific information “You only have to read four studies…”

Of course – that is bad science. To ignore all the other information and rely just on four studies. But it is also bad science as those specific studies were chosen by Paul Connett because he believes they confirm his bias that community water fluoridation (CWF) is bad for you (they don’t actually). He consistently ignores studies which contradict his bais. But it is also bad science because these studies are weak and their results contradictory. Connett is simply into confirmation bias. He uses misrepresentation and mistaken interpretation of these studies to support his claims.

Connett acknowledges problems with high fluoride studies

Connett admits in his Fluoride Action Network (FAN) Bulletin from March 24, 2020:  “You only have to read four studies…” that “Many of the earlier studies were in places with elevated natural fluoride levels.” Yes – they are overwhelmingly from areas of endemic fluorosis, mainly in China, where health problems are very common and obvious. They have no relevance to community water fluoridation (CWF) – but this did not stop Connett, FAN and the whole anti-fluoride movement using them in their propaganda opposing a safe, effective and economic health policy known to reduce child tooth decay.

Then he goes on to claim:

“There is now very strong evidence that fluoride damages both the fetal and infant brain at the levels used in artificially fluoridated areas.”

“You only have to read four studies to realize that deliberately adding fluoride to drinking water unnecessarily endangers children’s brains.”

Let’s be scientific about it and have an objective and critical look at the specific studies Connett now relies on. I will discuss each of these four studies in separate articles. Here is my critique of the first one – Bashash et al (2017)

Bashash et al (2017)

The citation for this paper is:

Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., … Hernández-avila, M. (2017). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico. Environmental Health Perspectives, 125(9).

Connett says:

“The first* came in Sept 2017 with a groundbreaking study from Mexico City. This study found a strong association between the amount of fluoride women were exposed to during pregnancy and lowered IQ in their offspring.”

Don’t take Connett’s word for this – read the paper and actually look at and consider the data.

Table 1 illustrates results from Bashash et al (2018) and from Thomas (2014) and Thomas et al (2013, 2014 & 2018): These all used the same or similar data from the ELEMENT database. The red triangles represent statistically significant relationships. All other relationships are not statistically significant.

Table 1: Summary of data from papers using the Mexican ELEMENT database. Red triangles indicate a statistically significant relationship.

Note: The coefficients were obtained from linear regression of full-scale child intelligence quotient (IQ), general cognitive index for the child (GCI) or mental development index of the child (MDI) against urinary fluoride for the child (UF) or prenatal urinary fluoride for the mother (MUF), adjusted in some cases using urine specific gravity (MUFsg) or urine creatinine concentrations (MUFcr). Bars represent the 95% confidence intervals of coefficients of the change of cognitive measure with an increase in fluoride measure. The red triangles represent statistically significant relationships. All other relationships are not statistically significant.

No relationship of child IQ with child urinary F:

Connett does not mention that there is no significant relationship of child IQ with fluoride exposure as measured by the child urinary F (UFsg) and he is also silent about the Thomas (2014) thesis which also showed no relationship of child MDI with child UF – although when Thomas (2014) separated data by sex she found a statistically significant positive relationship of IQ with UF for males.

Relationships with maternal prenatal urinary F – but very weak:

Yes, there are significant relationships of child IQ (6 – 12-year-olds) or child GCI (4-year-olds) with MUF – but contrary to Connett’s claim these relationships are far from “strong.” (Thomas did not find a significant relationship of MDI with  MUF for children of ages 1 to 3  but reported – in a conference poster paper Thomas et al 2018 – a statistically significant relationship for MUF corrected using creatinine concentrations – see  A conference paper on the maternal prenatal urinary fluoride/child IQ study has problems).

These figures from Bashash et al (2017) illustrate how scattered the data is:

While statistically significant the reported relationships are extremely weak – explaining only about 3.6% of the variance in IQ and 3.3% of the variance in GCI (see Maternal urinary fluoride/IQ study – an update). The large standard error of the regressions (9.8 for IQ and 12.9 for GCI) also indicate that the estimates of IQ change (-5.0) and GCI change (-6.3) for an increase of MUF of 1 mg/L  have no predictive value (see Maternal urinary fluoride/IQ study – an update).

Connett is very wrong to claim that “This study found a strong association . . .” It simply didn’t.

Tomorrow I will discuss the second study Connett now relies on – Green et al (2019) – see Anti-fluoridation propaganda now relies on only four studies. 2: Green et al (2019).

See also:

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Another embarrassment for anti-fluoride campaigners as neurotoxic claim found not to be justified

Anti-fluoride campaigners have made the classic mistake of promoting claims based on a draft report. Now peer reviewers have found the claim unjustified and the report will be rewritten. But will the anti-fluoride brigade stop making the claim?

Anti-fluoride campaigners have just lost another of their propaganda claims with the release of a US National Academies of Science (NAS) peer review of the recent National Toxicity Program’s (NTP) draft monograph discussing fluoride exposure and neurotoxicity.

Ever since the release of this draft last October anti-fluoride campaigners have been making hay out of this statement on page 2 of the draft (and repeated several times in its text):

“Conclusions: NTP concludes that fluoride is presumed to be a cognitive neurodevelopmental hazard to humans.”

In general, these campaigners have presented this conclusion as a finding of the NTP, even though the draft includes this statement on every page:

“This DRAFT Monograph is distributed solely for the purpose of pre-dissemination peer review under the applicable information quality guidelines. It has not been formally disseminated by NTP. It does not represent and should not be construed to represent any NTP determination or policy.”

In a clear case of counting eggs before they hatch, the anti-fluoride campaigners now face the embarrassment of losing this claim because the NAS peer reviewers have found the conclusion is not supported by the evidence presented in the draft report. The NAS press release announcing the results of their peer review clearly says:

It “does not find that NTP has adequately supported its conclusion that “fluoride is presumed to be a cognitive neurodevelopmental hazard to humans.”

For readers wanting more detail these are the relevant documents:

Anti-fluoride activists response to the NAS peer review

The peer review has been out for only a few days and the anti-fluoride propagandists on social media have already denounced it (without reading it in most case) as only one committee’s opinion. Or they have indulged in the straw-clutching of quoting the NAS peer review’s sentence after the one that found the conclusion fo the NTP report was not supported. This says.

“The committee emphasized its finding does not mean that the NTP’s conclusion is incorrect; rather, further analysis or reanalysis is needed to support conclusions in the monograph.”

Perfectly normal for a scientific assessment and, in this case, a bit of a face-saver for the NTP (in many of its details the NAS peer review is quite scathing). And if the NTP has done a reasonable job of accessing the literature we all know that no “further analysis or reanalysis” will magically support the draft claim.

But, as an indication of the embarrassment of these people the “authoritative” comment on the peer review from Paul Connett, leader of the anti-fluoride US activist group Fluoride Action Network (FAN) almost reads like an endorsement of the peer review. Despite FAN having originally stressed the faulty NTP draft conclusion that “fluoride is presumed to be a cognitive neurodevelopmental hazard to humans” Connett does not even mention the NAS finding in his press release (see Federal report finding fluoride lowers IQ of children reviewed by National Academy of Sciences.“) Strangely he quotes: “The NAS emphasized its finding ‘… does not mean that the NTP’s conclusion is incorrect.'” without even saying what that conclusion was.

The rest of Connett’s comments amount to spin – putting a brave face on his disappointment at this major loss. His claim that “The NAS suggestions should strengthen the draft report’s conclusion that fluoride is a presumed neurotoxin in children” is fanciful given that the material reviewed by the NTP simply does not support this claim.

He is also attempting diversion with his claim “The NAS review has been misinterpreted by fluoridation defenders. The NAS did not independently review the scientific evidence but instead limited itself to comments on whether the NTP clearly and thoroughly explained their methods” The fact is very few comments have been made by “fluoridation defenders” yet – the peer review has been public for only a few days – barely enough time for busy scientists to get around to reading it. And I have not seen a single person claim that the NAS peer reviewers “independently reviewed the evidence.”

What was required of the peer review?

The peer review report makes their action and purpose very clear. They were not tasked with making an independent review of the literature but their job went a lot further than limiting themselves to “comments on whether the NTP clearly and thoroughly explained their methods”

The NTP Project Information document Peer Review of the NTP Monograph on Systematic Review of Fluoride Exposure and Neurodevelopmental and Cognitive Health Effects) provided a list of requirements for the peer reviewers who were asked to address the following questions:

  • Has the systematic review protocol been followed and modifications appropriately documented and justified?
  • Does the monograph accurately reflect the scientific literature?
  • Are the findings documented in a consistent, transparent, and credible way?
  • Are the report’s key messages and graphics clear and appropriate?  Specifically, do they reflect supporting evidence and communicate effectively?
  • Are the data and analyses handled in a competent manner?  Are statistical methods applied appropriately?
  • What other significant improvements, if any, might be made in the document?
  • Does the scientific evidence in the NTP Monograph support NTP’s hazard category conclusions for fluoride in children and adults?”

The NAS peer reviewers clearly answered the last question with an emphatic No! This is not changed by the desperate straw clutching of propagandists who quote the (inevitable and polite) qualification that a further “further analysis or reanalysis” might provide support. Nor is it changed by Connett simply refusing to acknowledge or comment on that very important finding of the peer review committee.

Other findings of the NAS peer reviewers

The NAS peer review report is quite extensive (it’s 48 pages long) and covers several other important issues besides its rejection of the main conclusion. Issues related to how good the original protocol was and how closely it was followed, bias resulting from incomplete consideration of all the findings (negative as well as positive) and selection in the literature considered, issues related to statistical analysis and presentation, and problems with accounting for the range of different fluoride exposure measures and outcome parameters.

I might return to some of these issues later as I think they are relevant to other reviews in this area – especially the recent review of Grandjean (2019) – Developmental fluoride neurotoxicity: an updated review. This has similar faults – and some extra faults of its own.

But it is clear that in it’s current form the draft NTP report is not credible. Its conclusion is flawed and there are a number of other problems. It will have to be extensively rewritten to take the peer reviewers comments into account. I look forward to the new, and hopefully much better, version.

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What are the recent fluoride-IQ studies really saying about community water fluoridation?

Scaremongering graphic currently being promoted by Declan Waugh who is well known for misrepresenting the fluoride science

This graphic is typical of current anti-fluoride propaganda. It is scare-mongering, in that it is aimed at undermining community water fluoridation (CWF) which is accepted by health and scientific authorities as safe and effective. It relies on citations of recent research to give an impression of scientific credibility – but it misrepresents that research.

In fact, this research has produced confusing and contradictory results based on very weak relationships. Instead of the cherry-picking commonly indulged in by anti-vaccination and anti-fluoridation groups like this, all the findings in these studies must be considered. In this article, I have attempted to graphically present all these findings in one place. This makes clear how weak the evidence these activist groups rely on is and why it does not provide a basis for reviewing the current acceptance of CWF.

I have given below all the reported findings from the recent research (including the citations given by Declan Waugh in the above graphic). There is a lot here (I have not cherry-picked as the anti-fluoride activists do) so I present the findings graphically to provide a complete overview without the boring job of trying to understand  detailed text. My apologies for the length of this article.

NOTE: I recommend readers refer to the cited papers for more details on methodology and definitions of the cognitive measures and F-exposure measures.

Does fluoridation influence IQ?

The answer provided by these modern studies is clearly no. Remember, these studies use data from areas where CWF is used or where drinking water concentrations are similar. They are quite different from the studies (previously relied on by anti-fluoridation activists) from areas of endemic fluorosis where fluoride intake is much higher and where many health problems result.

All the comparisons from fluoridated and unfluoridated areas in these studies are presented in Figure 1 below. The bars represent the standard deviations for the data sets and the data points are the means. A * indicates differences are statistically significant.

Figure 1:  Comparison of IQ results in fluoridated and non0-fluoridated areas

The only statistically significant differences are for verbal IQ (VIQ) of 3-4 year-olds breastfed as babies (where the VIQ of children in fluoridated areas is higher) and for performance IQ (PIQ) of the same group (where the PIQ of children in fluoridated areas is lower). Till et al (2020) had to dig deep, use multiple measures of the cognitive score and subdivide the children into groups, to find an occasional difference. And these differences are contradictory.

I discussed the Till et al (2020) study which reported these occasional differences in Anti-fluoride propagandists appear not to read the articles they promote.

What about the relationships between IQ and measures of F intake?

Anti-fluoride propagandists ignore the data presented in Figure 1 above (and reported in the papers involved) and instead rely on cherry-picked relationships between measures of cognitive ability and various measures of fluoride exposure. Yes, some of these relationships, but only a small proportion, are statistically significant. But, importantly, none of these explain more than a few percents of the variation of the cognitive measure used.

Figure 2 below displays all the results from all the recent studies where linear regressions were used. The coefficient represents the size of the effect (eg., the change in IQ for every 1 mg/L increase of F exposure measure like drinking water F or maternal urinary F) and the bars represent the 95% confidence levels. The statistically significant (p<0.05) relationships are represented by red points while the green data points represent nonsignificant results.

Figure 2: Relationships of cognitive measures with exposure to fluoride obtained by linear regression analyses

Footnote: UF – concurrent urinary fluoride of the child. UFsg – UF adjusted using the specific gravity of urine. MUF – maternal prenatal urinary fluoride. MUFcr MUF – adjusted using urinary creatinine concentration. MUFsg – MUF adjusted using urine specific gravity. FSIQ – Full-Scale IQ. VIQ – Verbal IQ. PIQ – performance IQ. MDI – Mental development index.

Figure 3 below displays the results obtained by Barberio et al (2017) using logical regression of learning disabilities in children aged 3-12 years on urinary fluoride (UF), specific gravity adjusted urinary fluoride (UFsg), and creatinine adjusted urinary fluoride (UFcr). The data used was from two cycles of the Canadian Health Measures Survey (CHMS).

Findings for logical regression of ADHD and ADD on urinary fluoride are also included.

Figure 3: Relationships of cognitive measures with exposure to fluoride obtained by logical regression analyses

There are a lot of reported relationships in these two figures but only a few are statistically significant. Even these are contradictory – Thomas (2014) and Santa-Marina (2019) found positive coefficients while Bashash et al (2017), Thomas (2018), Green et al (2019) and Till et al (2020) reported some negative relationships. Barberio et al (2017) found a positive relationship for the data from combined CHMS cycles but this disappeared when UFsg or UFcr was used. Most of the reported relationships are not statistically significant.

Moving from nonsignificant to significant by adjusting urinary-F figures

This is illustrated by the evolution of the way the results are presented for the Thomas (2014) study which is related to the Bashash et al (2017) study. In this thesis and early conference reports (Thomas et al 2013 & Thomas et al 2014), She did not find any statistically significant relationships of child IQ with maternal urinary F (MUF) or maternal blood plasma F. But she did report a statistically significant relationship with MUFcr in her last conference paper (Thomas et al 2018).

So what happened?

There appears to be a change in the actual mother-child pairs used as indicated by the numbers and this sort of data selection can easily push a nonsignificant relationship into significance – especially when the relationship is so weak (see A conference paper on the maternal prenatal urinary fluoride/child IQ study has problems).

The other factor is that in the 2018 conference paper she has adjusted the MUF figures using creatinine concentration. Use of individual urinary fluoride measures, especially spot samples rather than a 24-hr collection, is a problem and is not a good measure of F exposure. Adjustment of urinary F using specific gravity or creatinine concentration is often used to improve the measure but this is problematic because creatinine concentration is influenced by a range of other factors.  The adjusted MUF figures may actually be acting as a proxy for one of these other factors. This is why Barr et al (2005) recommended that:

“ For multiple regression analysis of population groups, we recommend that the analyte concentration (unadjusted for creatinine) should be included in the analysis with urinary creatinine added as a separate independent variable. This approach allows the urinary analyte concentration to be appropriately adjusted for urinary creatinine and the statistical significance of other variables in the model to be independent of effects of creatinine concentration.”

This is not done by any of the authors of these recent papers where urinary fluoride was used.

Thomas (2014) also reported a positive relationship of concurrent child urinary F (UF) with a cognitive measure, but not for girls. This seems to have been ignored in later reports – and by Bashash et al (2017) which used the same data but only reported the non-significant result for all children.

Till et al (2020) found that only relationships with PIQ were statistically significant. It is not clear why this happened considering no significant relationships were found for FSIQ or VIQ. It’s interesting that Till et al (2019) initially did not report the PIQ results and instead relied on a significant relationship of FSIQ with water F in children formula-fed as babies. Maybe the PIQ measurement is considered unreliable in practice. This finding was also heavily promoted by ant-fluoride campaigners – despite the fact that adjustment for other factors made this relationship nonsignificant (see Anti-fluoride propagandists appear not to read the articles they promote).

Most anti-fluoride campaigners have stuck with the initial FSIQ relationship – although a few who may have read the paper are now cherry-picking the PIQ relationships and ignoring the others.

What about fluoride and ADHD?

Three of these recent studies used linear regression when considering ADHD – but those of Malin & Till (2015) (claimed to be the first study to suggest an effect of fluoridation on ADHD) and Perrott (2018) are important. Not because one of the studies is mine – but because they illustrate a basic problem with correlation studies.

Even when multiple regression is used to adjust for covariants or other possible risk-modifying factors the investigation may miss an important risk-modifying factor. Not only does correlation not prove causation – the “significant” relationships themselves may be false when important risk-modifying factors are not included in the multiple regressions.

This happened with the Malin & Till (2015) study which reported statistically significant relationships of the extent of fluoridation in US states with ADHD prevalence. However, when the mean state elevation was included in the multiple regression of exactly the same data by Perrott (2018) the relationship with fluoridation extent disappeared (this had a p-value of 0.269 whereas those for Malin & Till 2015 were <o.o5). See Figure 4 below.

Figure 4: The effect of including other important risk-modifying factors on reported significant relationships

Figure 5 below shows the data reported by Bashash et al (2018) for the linear regression of a range of ADHD symptoms against urinary fluoride (UFcr).

Figure 5: Relationships of ADHD symptoms with exposure to fluoride obtained by linear regression analyses

The relationships were statistically significant for only four of the ten symptoms considered. Those relationships were very weak, explaining only a few per cent of the variance in ADHD prevalence (see Fluoridation and ADHD: A new round of statistical straw clutching).

The logistical regression results reported by Riddell et al (2019) for ADHD diagnosis and SDQ subscale score Urinary fluoride (UFcr) are given in Figure 6 below.

Figure 6: Relationships of ADHD diagnoses  with exposure to fluoride obtained by logistical regression analyses

I discussed Riddell et al (2019) in my article ADHD and fluoride – wishful thinking supported by statistical manipulation?

This is another case where authors found unpromising results (no significant relationship for UFsg for example) and searched for other measures. It is also interesting that the significant relationships for water F and CWF status disappeared for younger children when age separation was used. The large confidence intervals in most cases indicate a large scatter in the data and very weak relationships.

I should also mention here the nonsignificant relationships reported by Barberio et al (2017) for ADHD and ADD (see Figure 3 above). These just underline how significant relationships are not common in these recent studies when looked at overall.

Update: Fluoride and sleep disturbances

Strictly, sleep disturbances don’t come under the classification of cognitive effects but a recent paper on fluoride and sleep disturbances is being promoted by anti-fluoride campaigners and should, therefore, be included here. For the sake of completeness.

I discussed the paper, Malin et al (2019), in my article Sleep disorders and fluoride: dredging data to confirm a bias. All the findings reported in that paper, and the supplementary files, are presented in Figure 7 below.

The authors report relationships of a range of sleep disorders against two measures of fluoride exposure – blood plasma-F and tap water-F. None of the relationships with blood plasma were significant (most had a p-value of 1.0). I discussed these in Sleep disorders and fluoride: dredging data to confirm a bias. and made the point that that bedtime and waketime were likely to be related to residence and the tap water F was simply acting as a proxy for regional location.

But again we see the use of a large number of measures for a “disorder’ and very few statistically significant relationships which are probably better explained by other factors than fluoride.

Conclusion

Considering all the findings together of the recent studies relevant to community water fluoridation and cognitive factors shows the results are weak, conflicting, and contradictory. This is probably not surprising considering the nature of the data (the studies were basically exploratory using existing databases – not designed experiments). Although adjustments were made for other possibly important factors this does not mean those really important ones (like the relationship of ADHD prevalence to elevation) were included. All the statistically significant relationships found were very weak – explaining a small proportion of the variance in the cognitive measure.

This is the sort of picture one might expect from exploratory studies using a large number of cognitive factors and measure of fluoride exposure. While these results may be useful in suggesting possible hypotheses to check in future better-designed experiments they are not sufficiently coherent to inform social health policy.

These recent studies do not provide sufficient evidence for revision of community water fluoridation policies because of possible effects on cognitive abilities. Anti-fluoride activists have only been able to use these studies in their scaremongering propaganda by cherry-picking results and ignoring the weakness of the relationships they cite.

References

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), 229.

Barr, D. B., Wilder, L. C., Caudill, S. P., Gonzalez, A. J., Needham, L. L., & Pirkle, J. L. (2005). Urinary creatinine concentrations in the U.S. population: Implications for urinary biologic monitoring measurements. Environmental Health Perspectives, 113(2), 192–200.

Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., … Hernández-avila, M. (2017). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico. Enviromental Health Perspectives, 1, 1–12.

Bashash, M., Marchand, M., Hu, H., Till, C., Martinez-Mier, E. A., Sanchez, B. N., … Téllez-Rojo, M. M. (2018). Prenatal fluoride exposure and attention deficit hyperactivity disorder (ADHD) symptoms in children at 6–12 years of age in Mexico City. Environment International, 121(August), 658–666.

Broadbent, J. M., Thomson, W. M., Ramrakha, S., Moffitt, T. E., Zeng, J., Page, L. A. F., & Poulton, R. (2015). Community water fluoridation and intelligence: Prospective study in New Zealand. American Journal of Public Health, 105(1), 72–76.

Green, R., Lanphear, B., Hornung, R., Flora, D., Martinez-Mier, E. A., Neufeld, R., … Till, C. (2019). Association Between Maternal Fluoride Exposure During Pregnancy and IQ Scores in Offspring in Canada. JAMA Pediatrics, 1–9.

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(1), 17.

Malin, A. J., Bose, S., Busgang, S. A., Gennings, C., Thorpy, M., Wright, R. O., … Arora, M. (2019). Fluoride exposure and sleep patterns among older adolescents in the United States : a cross-sectional study of NHANES 2015 – 2016. Environmental Health, 1–9. Retrieved from https://link.springer.com/article/10.1186/s12940-019-0546-7

Perrott, K. W. (2018). Fluoridation and attention deficit hyperactivity disorder a critique of Malin and Till (2015). British Dental Journal, 223(11), 819–822.

Riddell, J. K., Malin, A., Flora, D., McCague, H., & Till, C. (2019). Association of water fluoride and urinary fluoride concentrations with Attention Deficit Hyperactivity Disorder in Canadian Youth. Submitted to Environment International, 133(May), 105190.

Santa-Marina, L., Jimenez-Zabala, A., Molinuevo, A., Lopez-Espinosa, M., Villanueva, C., Riano, I., … Ibarluzea, J. (2019). Fluorinated water consumption in pregnancy and neuropsychological development of children at 14 months and 4 years of age. Environmental Epidemiology, 3.

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.

Thomas, D., Hu, H., Basu, N., Sanchez, B., Bellinger, D., Schnaas, L., … Tellez-Rojo, M. M. (2013). A prospective study of prenatal exposure to fluoride and neurobehavior : preliminary analyses. Environmental Health Perspectives.

Thomas, D., Hu, H., Basu, N., Martinez-Mier, E. A., Sanchez, B., Bellinger, D., … Tellez-Rojo, M. M. (2014). Urinary Fluoride in Pregnant Women and Prenatal Fluoride Exposure and Mental Development Index ( MDI ) in 1-3 Year Old Infants from Mexico City, Mexico. Environmental Health Perspectives, 1(Icc), 2–3.

Thomas, D., Sanchez, B., Peterson, K., Basu, N., Angeles Martinez-Mier, E., Mercado-Garcia, A., … Tellez-Rojo, M. M. (2018). OP V – 2 Prenatal fluoride exposure and neurobehavior among children 1–3 years of age in Mexico. Environmental Contaminants and Children’s Health, 75(Suppl 1), A10.1-A10.

Till, C., Green, R., Flora, R., Hornung, R., Martinez-Mier, E., Blazer, BFarmus, L., … Lanphear, B. (2019). Fluoride Exposure from Infant Formula and Child IQ in a Canadian Birth Cohort. Environmental Epidemiology, 3.

Till, C., Green, R., Flora, D., Hornung, R., Martinez-mier, E. A., Blazer, M., … Lanphear, B. (2020). Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environment International, 134 (September 2019), 105315.

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Anti-fluoride propagandists appear not to read the articles they promote

Anti-fluoride activists are rubbing their hands in glee over what they claim is “yet another study” showing fluoride harms the brains of children. But their promotion relies on IQ relationships which the paper’s authors acknowledge disappearing when outliers or other factors are considered. And they completely ignore other relationships which indicate much larger effects and are not influenced by outliers or other factors.

Why ignore this gift from the paper? I can only conclude these anti-fluoride campaigners don’t actually read the papers they promote.

Mind you, the paper is rather confusing. But the data, relating to formula-fed infants, is hardly surprising. It’s from the same group that has produced multiple studies along the same line – and suffers from the same weakness the other studies do.

The paper citation is:

Till, C., Green, R., Flora, D., Hornung, R., Martinez-mier, E. A., Blazer, M., … Lanphear, B. (2020). Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environment International, 134(September 2019), 105315.

Multiple parameters measured

This research group appears to be taking the approach of searching existing databases using multiple parameters – in the hope of finding significant differences or trends. And then interpreting significant trends as evidence for a cause.

The problem is that the p-value, used to judge significance, gets pretty meaningless when multiple attempts are made on the same data like this, although there are statistical procedures for correcting the final p-values to get a more meaningful measure. But, more importantly, p-values are pretty meaningless even at the best of times – remember correlation is not evidence for causation and should never be used that way.

Don’t be fooled by a statistically significant relationship. Low p-values, even high R-squared values should not be used as evidence of causation. Data from Spurious Correlations.

The parameters used in this paper are full-scale IQ (FSIQ) verbal IQ (VIQ), performance IQ (PIQ) for the cognitive parameters. Fluoridation, water fluoride concentration and estimated fluoride intake were used as the fluoride parameters.

Looks very much like they were “spreading their bets” by using a range of parameters.

Difference between breast-fed and formula-fed infants

The difference they reported between breastfed (BF) and formula-fed infants are unsurprising. These differences were only significant for maternal education, HOME total score (a measure of the child’s home environment), full-scale IQ (FSIQ),  verbal IQ (VIQ), water fluoride concentration and estimated fluoride intake. Parental attitudes to breastfeeding are probably expected to change with education. Breast-feeding has previously been reported to result in children with higher IQs and, however poor the F intake estimate, it would obviously be higher where the water is fluoridated.

IQ difference between fluoridated and unfluoridated areas

The data extracted from the paper’s Table 1 also shows that the VIQ of breastfed children is statistically higher in fluoridated areas. and the PIQ of formula-fed children is statistically higher in non-fluoridated areas. There were no statistically significant differences in FSIQ between children in fluoridated and unfluoridated areas irrespective of the feeding method.

So, just using the mean values of the cognitive measures there were no statistically significant effects of fluoridation of FSIQ, VIQ for formula-fed children and PIQ for breastfed children.

However, child VIQ was greater in fluoridated areas for breastfed children and lower in fluoridated areas for formula-fed children.

Digging difference out of trends

The authors repeat the same method they used in Green et al., (2019) where although mean values showed no effects of fluoridation they used trends from linear regressions to imply there were effects (see If at first you don’t succeed . . . statistical manipulation might help).

In all their promotion of the paper, the anti-fluoride campaigners refer only to the data for FSIQ – the figures they cite make clear that their term IQ is referring solely to FSIQ. This is strange as the story is very poor for FSIQ and I would have thought they would concentrate on PIQ where effects are larger and not influenced by others or other factors as FSIQ is.

But, let’s look at the FSIQ story – at least the paper provides a figure enabling extraction of data for an independent analysis. The figure below is from the paper’s Figure 1 showing the relationships of FSIQ to drinking water fluoride concentration for breastfed (BF) and formula-fed (FF) babies.

The paper claimed a statistically significant (p<0.05) relationship for formula-fed (FF)(B=-8.80 [-16.34,-0.92]) but not for breastfed (BF) babies.

I can’t get the same result with the data I digitally extracted from the figure (about 90% of data points) The extracted data showed for For FF: B=-2.07 (-11.17, 7.04), p=0.6 and for BF B=1.92 (-6.74, 10.59).

The difference surprises me. I am aware I was able to extract only about 90% of the data points (n=354 compared with the paper’s 398) but would not have expected such a large difference in regression result. I would dearly like someone to duplicate this as a check.

These were the results I obtained using the data I digitally extracted from Figure 1 in Till et al., (2020).

Perhaps this is just another indication that the relationship is very weak.

But, Importantly, the IQ relationships were not significant when outliers and covariate effects were included. Till et al., (2020) found the significant relationship they reported for FF disappeared when the 2 low IQ outliers were removed. The regression without the outliers was B=-6.28 (-13.98, 1.42), no p-value given. The relationship also disappeared when maternal urinary fluoride (MUF) was included as a covariate. But before I get the response this proves that MUF, rather than FF is the determining factor, Till also reported (in the supplementary data) that “MUF was not significantly associated with FSIQ score (B = -0.54, 95% CI: -3.04, 0.90, p = .28).” 

Why concentrate on FSIQ instead of PIQ?

The authors include only a figure for FSIQ plotted against water concentration. This seems strange as the quoted relationship disappears when the 2 outliers are excluded or covariates included in the regression.

In contrast, the relationship of PIQ with water concentration is statistically significant for both breastfed and formula-fed infants and remained significant when controlled for maternal; urinary fluoride or when the 2 outliers are removed. (The authors could not find any statistically significant relationships for VIQ). The effect size was also much larger than that found (before adjustment) for FSIQ.

Whereas the B value for the relationship of FSIQ with water fluoride before adjustment was -8.8 IQ points per 1 mg/L water fluoride the equivalent coefficients for PIQ were:

Formula-fed children: B=-18.52 (-27.54, -9.52);
Breastfed children: B=-12.38 (-20.90, -3.88)

These B coefficients were a little smaller when adjustments were made for the 2 outliers or for maternal urinary fluoride but they were still statistically significant (p,0.05).

So, why no figure for PIQ vs water fluoride? I would have thought such a figure would be far more important for the paper than the included one for FSIQ (where the relationship became non-significant when adjustments were made). Data extracted from a PIQ figure would also have enabled determination of how much of the PIQ variance was explained by water fluoride. Although, the very large 95% confidence interval range suggests to me that very little of the PIQ is actually explained by water fluoride. I think the strange data presentation may have been a result of attemtps to confirm a bias.

The anti-fluoride people have talked about IQ (meaning FSIQ) rather than PIQ in their promotion of the study. Perhaps they have not actually read the paper. They seem not to realise that the relationship they rely on disappears when considered properly.

And it is not just a convenient shorthand. For example, The Fluoride Action Network press release says:

“A study published this week found a large decrease in the IQ of children who had been fed infant formula reconstituted with fluoridated tap water, compared to formula-fed children living in unfluoridated areas. The study by a research team based at York University, Toronto, followed a large cohort of Canadian mother-child pairs through age 3-4 years and found an average drop of over 4 IQ points for children in fluoridated areas.”

The local Fluoride Free NZ (FFNZ) press release also makes clear they are referring to FSIQ:

“children lose 4.4 IQ points for every 0.5 mg fluoride added to their drinking water if they are formula-fed rather than breast-fed.”

They clearly refer to the FSIQ relationship where B=-8.8 (or -4.40 for  0.5 mg/L water fluoride concentration).

Did these anti-fluoride people not get past the paper abstract or the press release put out by the authors?

Fluoride intake

The study also included a calculated measure of fluoride intake from formula. The calculation is questionable and was not significantly related to VIQ or FSIQ. However, the relationship with PIQ was significant even after adjustment – although the large 95% confidence interval suggests it did not explain much of the variance in PIQ. I digitally extracted data for the PIQ – F intake figure (their Figure 1B) and regression analysis indicated F-intake explained only about 1.5% of the PIQ variance. (Unfortunately, I was unable to extract more than 78% of the data as a large number of data points seemed to coincide. This is probably inevitable with the method they used to estimate F intake).

Problems with the Till group

I find it interesting that the authors specifically express their coefficient B values for 0.5 rather than the normal 1.0 mg/L water fluoride because they wish to relate their relationship to water fluoridation. They write:

“To aid interpretation, we divided all regression coefficients by 2 so that they represent the predicted IQ difference per 0.5 mg/L of fluoride in tap water or 0.5 mg fluoride from formula; 0.5 mg/L corresponds to the approximate difference between mean water fluoride level in fluoridated versus non-fluoridated regions in our sample.”

This suggests to me the group has a preoccupation of finding fault with community water fluoridation.

Mind you, I had already come to this conclusion because, when taken together,  papers coming from this group report relationships that are always weak and very often contradictory. If a relationship isn’t significant when maternal urinary fluoride is used, they switch to water fluoride. If that is not successful they use a non-verified fluoride intake measurement of their own invention. They seem to be searching for any relationship which will confirm their bias.

The truth is that in these and similar studies the data is often not very good (no one should be using spot urine F tests for example) and the relationships found are always very weak. The results are usually confused because of the different parameters used and also the results are often contradictory. For example, data will sometimes show an increase in IQ with fluoridation or drinking water fluoride (see the table above, A conference paper on the maternal prenatal urinary fluoride/child IQ study has problemsWhat do these mother-child studies really say about fluoridation?, and The anti-fluoride brigade won’t be erecting billboards about this study).

The authors also seem to be very willing to make exaggerated claims linking their weak results to health policies and often seem to work in collusion with some anti-fluoride activist organisations and people. For example, Bruce Lanphear, one of the coauthors on the Green et al., (20219) paper, is serving pro bono as an expert witness for the Fluoride Action Network and other antifluoride groups in a current legal case.

Despite this apparent bias and the weakness of the data in these papers, they should stand on their own merit instead of the reputation (good or bad) of the authors. It is up to interested readers to critically examine the data and make their own decisions about the reliability of the claims being made.

However, this does require readers to actually read the papers and think critically about them. It appears to me that most anti-fluoride campaigners never do this but simply rely on newsletters and press releases coming from “Head Office – the Fluoride Action Network.

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The anti-fluoride brigade won’t be erecting billboards about this study

If FFNZ really put their faith in “Top Medical Journals” they would now be amending their billboards to recognise new research results. Image from FFNZ but updated to agree with the latest research.

Just imagine it. If the local anti-fluoride group Fluoride Free NZ (FFNZ) really put their faith in “Top Medical Journals” they would now be erecting billboards encouraging pregnant women to drink fluoridated water because a new study shows a positive relation of child cognitive abilities with prenatal maternal urinary fluoride.

The study has been reported at a recent conference – this is the citation and links to an abstract:

Santa-Marina, L., Jimenez-Zabala, A., Molinuevo, A., Lopez-Espinosa, M., Villanueva, C., Riano, I., … Ibarluzea, J. (2019). Fluorinated water consumption in pregnancy and neuropsychological development of children at 14 months and 4 years of age. Environmental Epidemiology, 3.

This appears to be research using Spanish data and the abstract reports that a number of cognitive measures for children aged 4 – 5 years-old are positively related to their mother’s prenatal urine fluoride concentrations:

“At the age of 4-5 years, an increase of 1 mg/l in the level of fluoride in urine during pregnancy (mean level of 1st and 3rd trimesters) was related to a higher score on the perceptual-manipulative scale of 4.44 (0.13, 0.75) points. Taking into account the window of prenatal exposure, at week 32 the level of fluorine was associated with an increase of 4.11 (0.28, 7.94) points in verbal function, 3.57 (-0.03, 7.18) in perceptive-manipulative and 3.97 (0.29, 7.65) in general cognitive.”

And the researchers concluded:

“Prenatal exposure at the levels found in fluorinated drinking water may exert a beneficial effect on the development at 4 years of age. At low doses, fluoride could present a dose-response pattern with a beneficial effect.”

Compare this with the report of a negative effect taken from the abstract of Green et al., (2019) – the study FFNZ relies on for their current scaremongering propaganda:

“A 1-mg/L increase in MUFSG was associated with a 4.49-point lower IQ score (95%CI, −8.38 to −0.60) in boys, but there was no statistically significant association with IQ scores in girls (B = 2.40; 95%CI, −2.53 to 7.33).” [MUFSG is an abbreviation for maternal urinary F cocnetration].

And Green et al., (2019) concluded:

“In this study, maternal exposure to higher levels of fluoride during pregnancy was associated with lower IQ scores in children aged 3 to 4 years. These findings indicate the possible need to reduce fluoride intake during pregnancy.”

So there you go. You can happily erect a billboard to promote either message depending on your own bias and your desire to confirm that bias. You can scaremonger and attempt to frighten mothers and pregnant women. Or you can do the opposite – perhaps even scaremongering to warn mothers that they must drink fluoridated water – or warn them not be taken in by activists who only wish to reduce your child’s opportunities in later life.

My take on this.

I have yet to see the full paper reporting this study and look forward to its publication. But I am not looking to confirm a bias – I simply want to see the data and subject it to the same sort of scientific critique I have made for the Green et al (2019) paper.

My initial response is that the reported relationship will be weak (going on the confidence intervals given). So I am sure that many of the criticisms I made of Green et al., (2019) will also apply to Santa-Marina et al., (2019).

But I think this situation with conflicting results from different research groups – both relying on weak statistical relationships – is the sort of result we can expect from analysis of unsatisfactory weak data. Sensible readers should be aware of this and not be swayed by single studies – especially studies using very weak relationships.

Unfortunately, activists do not have such scientific ethics – they will simply use the data and studies supporting their propaganda and biases. And they will claim these studies are of high quality and the best thing since sliced bread. On the other hand, these activists will attempt very hard to discredit the new study and I wonder if they will be able to see the irony of using arguments that could equally be used against the Green et al., (2108) study they promote.

More serious is the confirmation bias that goes on in the scientific community and the way authors like those involved in the Green et al., (2019) paper make statements promoting their work which are then used by activists to promote scaremongering messages.

I do not know enough about the research group involved in the Santa-Marina et al., (2019) study but, from their record, the other research group headed by Christine Till seem to be driven to confirm their bias against community water fluoridation and this is motivating them to extract weak relationship from poor data.

See my critiques of papers from Christine Till’s group:

Conclusion

I hope that this new study is reported in the media with the same interest the Green et al., (2109) study was. But I also hope the situation is used to get the message across that this sort of study should not be used to inform public policy. And that we should not be taken in by the scaremongering promotion of these sort of weak studies by anti-fluoride activists.

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