Tag Archives: Canada

What do these mother-child studies really say about fluoridation?

A list of indicators of bad science – many of these are found in articles promoted by anti-fluoride activists.

Anti-fluoride activists have been pouring money into a scaremongering campaign warning pregnant women not to drink fluoridated water. They claim fluoride will lower the IQ of their future child.

Fluoride Free NZ (FFNZ)  launched this campaign on the back of the recent publication of Canadian research on fluoride intake by pregnant women and child IQ (see Ground Breaking New Study – Top Medical Journal – Fluoridated Water Lowers Kids’ IQs). Now they are responding to criticisms of this paper by claiming it is supported by other research and claim a list of 6 papers support their claim that pregnant women drinking fluoridated water may be harming the IQ of their children.

Image used by FFNZ as part of their appeal for finance to support billboards and newspaper advertising promoting their false scaremongering claim.

None of these studies actually support the FFNZ claim. Let’s consider each of the six studies listed by the Fluoride Action Network (FAN) – but first, look at this data from the “New Study – Top Journal” mentioned by FFNZ:

This is from Table 1 in  Green et al., (2019). There are no statistically significant differences in the IQ o children whose mothers lived in either fluoridated or nonfluoridated areas during their pregnancy. So the FFNZ claim is completely false.

The Fluoride Action Network (FAN) Bulletin Several In Utero Fluoride/IQ Studies Should Provoke A Nation-Wide Fluoridation Moratorium initially list 5 studies but expanded this to 6 studies in an article posted by Ellen Connett the same day – The 6 Mother-Offspring Fluoride Studies. Here is the list (descriptions are from the FAN articles):

  • Green et al.,  (2019). Largest study with 512 mother-offspring. Lower IQ in children 3- 4 years of age.
  • Bashash et al., (2017). Longest study. 299 mother-offspring pairs in Mexico. Lower IQ in children 4 and 6-12 years of age.
  • Thomas et al., (2018). 401 mother-offspring pairs in Mexico. Lower IQ in children 1-3 years of age Only the abstract has been published.
  • Valdez Jiménez (2017). Lower IQ between the ages of 3-15 months with 65 mother-offspring pairs in Mexico.
  • Li et al., (2004). Significant differences in the neonatal behavioral neurological assessment score in 91 offspring aged 1-3 days old.
  • Chang et al., (2017). Reported significant differences in the mental development index and psychomotor development index of the offspring at 3, 6, 9, and 12 months of age.

I will consider these in three groups and include some relevant theses.

The Chinese studies from areas of endemic fluorosis

These describe data from areas of endemic fluorosis in China. They are irrelevant to community water fluoridation as the drinking water fluoride concentrations are much higher and people in these areas suffer a range of health problems including severe skeletal and dental fluorosis. Remember, the optimum levels of fluoride recommended for community water fluoridation are generally below 1 mg/L and WHO recommends drinking water concentrations should be lower than 1.5 mg/L.

People in areas of endemic fluorosis suffer a range of health problems

Li, J., Yao, L., Shao, Q. L., & Wu, C. Y. (2008). Effects of high fluoride level on neonatal neurobehavioral development. Fluoride, 41(2), 165–170.

This is one of the generally poor quality studies FAN got translated to assist their campaign. They are generally published in Fluoride, an anti-fluoride journal.

It compared children from villages with drinking water concentrations of  1.7–6.0 mg/L with a control group from villages with drinking water concentrations of 0.5–1.0 mg/L.

Chang A, Shi Y, Sun H, Zhang L. (2017) Analysis on the Effect of Coal-Burning Fluorosis on the Physical Development and Intelligence Development of Newborns Delivered by Pregnant Women with Coal-Burning Fluorosis.

Another one of the poor quality papers  FAN got translated but they have made only the abstract and a brief abstract available on their site. I cannot find a full test or even abstract anywhere else. It compares two groups:

“A total of 68 newborns delivered by pregnant women from coal-burning endemic fluorosis areas in this region were selected as an observation group, and 50 full-term newborns delivered by normal healthy pregnant women were selected as a control group. “

Both papers report statistically significant differences in some measurements between the two groups but that is to be expected for areas of endemic fluorosis and especially where coal-burning creates health problems. Of course, this is all irrelevant to community water fluoridation as only the control groups are likely to be drinking water with similar fluoride concentrations.

Mexican study from an area of endemic fluorosis

The paper is:

Valdez Jiménez, L., López Guzmán, O. D., Cervantes Flores, M., Costilla-Salazar, R., Calderón Hernández, J., Alcaraz Contreras, Y., & Rocha-Amador, D. O. (2017). In utero exposure to fluoride and cognitive development delay in infants . Neurotoxicology

This study found a relationship of child cognitive deficits with maternal prenatal urinary fluoride but, again, it is not relevant to community water fluoridation. The authors acknowledge that the study was done in an area of endemic fluorosis.  About 90% of the drinking water samples in the study contained fluoride above the World Health recommended maximum of 1.5 mg/l and the Fluoride in the mothers’ urine was also high – with the mean concentration for all the mothers of 1.9 mg/l  for the 1st trimester, 2.0 mg/l for the 2nd and 2.7 mg/l for the 3rd trimester. Urinary fluoride concentrations as high as 8.2 mg/l were found. This compares with a mean value for urinary F of 0.65 mg/L for pregnant women residents in areas with low levels of F in drinking water (0.4 to 0.8 mg/l – similar to that recommended in community water fluoridation).

I have written about this study in my post Premature births a factor in cognitive deficits observed in areas of endemic fluorosis? There I speculated that the effect of fluoride on cognitive deficits may be indirect because of the observede higher incidence of prematurity and low birth rate.

The Bashash study

I have separated these from the Green et al., (2019) study although they both report relationships between maternal prenatal urinary fluoride and the IQ of offspring and many of the authors are common to both studies  Bashash is the senior author on the paper reporting data from Mexico city and Green on the paper reporting data for Canada.

There are really three citations for this study. The main paper:

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), 8–10.

A conference poster:

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. https://doi.org/10.1136/oemed-2018-ISEEabstracts.23

And Deena Thomas’s Ph. D. thesis which also reported data from the study:

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.

The anti-fluoride activists have waxed lyrical about the reported negative relationship of child IQ with maternal prenatal urinary F concentrations but they are clutching at statistical straws as, in fact, the relationship is very weak – explaining only a few percent of the IQ variance. I explained this in my post Fluoride, pregnancy and the IQ of offspring, and described several other problems (correlation is not evidence of causation, information about the mothers is scant with no indication if they lived in areas of endemic fluorosis, possible important risk-modifying factors were not considered as confounders, urinary fluoride is not a good indicator of fluoride intake by individuals, and there was no association of child IQ to child urinary fluoride).

When data has this much scatter the marginal statistical significance of relationship are easily altered by tweaking the data. (Fig 3a from Bashash et al., 2017).

It is easy to be misled by marginal statistically significant relationships when considering data with such a high scatter. This is illustrated by the conclusions of one of the authors, Deena Thomas, in her Ph. D. thesis that:

“Neither maternal urinary or plasma fluoride was associated with offspring MDI scores” [page 37);

“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.” [page 38];

“Maternal intake of fluoride during pregnancy does not have any measurable effects on cognition in early life.” [page 48].

Yet, in the conference poster  based on her thesis she 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.”

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

I suggest in my article A conference paper on the maternal prenatal urinary fluoride/child IQ study has problems that the different conclusions in the poster resulted from the fact that at least 30 mother-child pairs were removed from the data set used in her thesis (the thesis consider 431 mother-child pairs but the poster considered only 401 pairs). Perhaps even some data pairs were added (the maximum urinary F value is higher in the smaller data set used for the poster).

In her thesis, Deena Thomas also reported: “concurrent urinary fluoride exposure has a strong positive impact on cognitive development among males aged 6-15 years.” [page 54]. The relationship was not significant for females. But the actual paper, Bashash et al., (2017), concluded “there was not a
clear, statistically significant association between contemporaneous children’s urinary fluoride . . . and IQ. “

I have discussed the Mexican maternal prenatal urinary fluoride- IQ study in more detail in the following articles:

A draft of my article critiquing the Bashash et al., (2017) paper, “Predictive accuracy of a model for child IQ based on maternal prenatal urinary fluoride concentration” is also available online. I have also discussed another paper from this study (Bashash et al., 2018) which reported a weak relationship of ADHD prevalence with maternal urinary fluoride in my article Fluoridation and ADHD: A new round of statistical straw clutching.

Green et al., paper/thesis

This study is actually the only one that included people exposed to community water fluoridation – hence the relevance of the data I presented in the introductory table which showed no effect. But the study it is basically the same as that of Bashash et al (2017) except it involved Canadian mother-child pairs and most of the criticism of Bashash et al., (2018)  are relevant to the Green et al., (2019) study which has been reported in the following forms:

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.

Green, R. (2018). Prenatal Fluoride Exposure and Neurodevelopmental Outcomes in a National Birth Cohort (MSc thesis, Graduate Program in Psychology York University Toronto, Ontario). 

My original critique included a conclusion that the reported negative relationship of child IQ with maternal prenatal urinary F concentration was extremely weak. I found that it explained only 1.3% of the child IQ variance using data extracted from the figures. Subsequently Rivka Green claimed an R-squared value of 4.7% which is still very low (we can reject her claim that it was “quite high” as simple promotion of her work).

For further discussion of the Green et al (2019) study see my articles:

A problem of self-promotion and confirmation bias

Science and the scientific literature are, of course, not immune to self-promotion and confirmation bais and I think the maternal urinary fluoride-child IQ studies show this. I discussed this in If at first you don’t succeed . . . statistical manipulation might help as well as pointing out that these scientific politics are amplified by activist propaganda.

This is a pity because such confirmation bias and self-promotion may result in important information being overlooked. I discussed this in  my article A more convincing take on prenatal maternal dietary effects on child IQ which referred to another paper from the Mexican maternal urinary fluoride study which showed a relationship of child IQ with maternal nutrition:

Malin, A. J., Busgang, S. A., Cantoral, A. J., Svensson, K., Orjuela, M. A., Pantic, I., … Gennings, C. (2018). Quality of Prenatal and Childhood Diet Predicts Neurodevelopmental Outcomes among Children in Mexico City. Nutrients, 10(8), 1093.

Again the relationships reported were weak, but the negative relationship of child IQ with poor prenatal maternal nutrition explains 11.2% of the variance in child IQ – much better than the data for prenatal maternal urinary fluoride (which explained only 3% of the variance).

Conclusions

So what do these mother-child studies say about community water fluoridation and IQ?

Well, nothing really – except that the only study which compared fluoridated and non-fluoridated areas showed absolutely no effect.

But this will not stop activists (and unfortunately self-promoting scientists and their institutions) from making unwarranted claims. Their propaganda relies on unsupported “authority” opinion and misrepresentation. This violates many of the rules in my first image above.

It tries to present correlation as proof of causation, misinterprets results, promotes unsupported conclusions, selectively reports the data and findings, and expands these unsupported conclusions way beyond the small sample sizes used.

This is just bad science!

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Biostatistical problems with the Canadian fluoride/IQ study

There are insights in there somewhere. Image Credit: DATA ANALYTICS COMES TO THE LEGAL PROFESSION

There has been widespread scientific criticism of the recently published Canadian fluoride-IQ study of Green et al., (2019). Most recently Dr. René F. Najera (a Doctor of Public Health, an epidemiologist and biostatistician) has critiqued the statistical analysis. He finds a number of faults and concludes by hoping “public health policy is not done based on this paper:”

 “It would be a terrible way to do public health policy. Scientific discovery and established scientific facts are reproducible and verifiable, and they are based on better study designs and stronger statistical outcomes than this. “

Dr. Najera’s critiques the biostatistics is in his article The Hijacking of Fluorine 18.998, Part Three. This follows his previous critique (Part 1 and Part 2) of the epidemiological issues which I reviewed in Fluoridation – A new fight against scientific misinformation.

Dr. Najera starts by stressing the important role of biostatistics in epidemiological studies. After all the planning and measurement:

“.. we hand off the data to biostatisticians, or we do the work with biostatisticians. Doing this assures us that we are measuring our variables correctly and that all associations we see are not due to chance. Or, if chance had something to do with it, we recognize it and minimize the factors that lead to chance being a factor in and of itself.”

I agree completely. In my experience statisticians play a critical role in research and should be involved even at the planning stage. Further, I think the involvement of experienced biostatisticians is invaluable. Too often I see papers where the authors themselves relied on their own naive statistical analyses rather than calling on experience. Perhaps they are being protective of their own confirmation bias.

The specific study Dr. Najera critiques is:

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.

For my other comments on the Candian fluoride/IQ research see:

No comparison group

One problem with this study is that a number of mother-child pairs were excluded and, in the end, the sample used was not representative of the Canadian population. Najera summarises the “main finding of the study as “that children of mothers who ingested fluoride during pregnancy had 4 IQ points lower for each 1 mg of fluoride consumed by the mother:”

“If you’re asking yourself, “Compared to whom?” you are on the right track. There was no comparison group. Women who did not consume tap water or lived outside a water treatment zone were not included, and that’s something I discussed in the previous post. What the authors did was a linear regression based on the data, and not much more.”

In fact, while the sample used was unrepresentative the study did compare the IQs of children whose mothers had lived in fluoridated and nonfluoridated areas. There was no statistically significant difference – an important fact which was not discussed at all in the paper. This table was extracted from the paper’s Table 1.

What about that regression?

While ignoring the mean values for fluoridated and nonfluoridated areas the authors relied on regression analyses to determine an effect.

But if you look at the data  in their Figure 3A reproduced below you can see problems:

“. . . you can see that the average IQ of a child for a mother consuming 1.5 mg of fluoride is about 100. You also see that only ONE point is representing that average. That in itself is a huge problem because the sample size is small, and these individual measurements are influencing the model a lot, specially if their value is extreme. Because we’re dealing with averages, any extreme values will have a disproportionate influence on the average value.”

Several scientific commenters on this paper have noted this problem which is important because it should have been dealt with in the statistical analysis:

“When biostatisticians see these extreme values popping up, we start to think that the sample is not what you would call “normally distributed.” If that is the case, then a linear regression is not exactly what we want to do. We want to do other statistical analyses and present them along with the linear regressions so that we can account for a sample that has a large proportion of extreme values influencing the average. Is that the case with the Green study? I don’t know. I don’t have access to the full dataset. But you can see that there are some extreme values for fluoride consumption and IQ. A child had an IQ of 150, for example. And a mother consumed about 2.5 milligrams of fluoride per liter of beverage. Municipal water systems aim for 0.7 mg per liter in drinking water, making this 2.5 mg/L really high.”

No one suggests such outliers be removed from the analyses (although the authors did remove some). But they “should be looked at closely, through statistical analysis that is not just a linear regression.”

This is frustrating because while the authors did not do this they hint that it was considered (but do not produce results)  when they say:

“Residuals from each model had approximately normal distributions, and their Q-Q plots revealed no extreme outliers. Plots of residuals against fitted values did not suggest any assumption violations and there were no substantial influential observations as measured by Cook distance. Including quadratic or natural-log effects of MUFSG or fluoride intake did not significantly improve the regression models. Thus, we present the more easily interpreted estimates from linear regression models.”

As Dr. Najera comments, this is “.. worrisome because that is all they presented. They didn’t present the results from other models or from their sensitivity analysis.”

Scientific commenters are beginning to demand that the authors make the data available so they can check for themselves. My own testing with the data I extracted from the figure does show that the data is not normally distributed. Transformation produced a normal distribution of the data but the relationship was far weaker than for a straight linear regression. Did the authors reject transformations simply because they  “did not significantly improve the regression models?”

That suggests confirmation bias to me.

Confidence intervals

In their public promotions, the authors and their supporters never mention confidence intervals (CIs)- perhaps because the story does not look so good when they are considered. Most of the media coverage has also ignored these CIs.

A big thing is made for the IQ score of boys dropping by 4.49 points with a 1 mg/L increase in  mother’s urinary fluoride, but:

“Based on this sample, the researchers are 95% confident that the true drop in IQ in the population they’re studying is between 0.6 points and 8.38 points. (That’s what the 95% CI, confidence interval, means.)”

In other words:

“In boys, the change is as tiny as 0.6 and as huge as 8.38 IQ points.”

For girls the change:

“is between -2.51 (a decrease) and 7.36 (an increase). It is because of that last 95% CI that they say that fluoride ingestion is not associated with a drop in IQ in girls. In fact, they can’t even say it’s associated with an increase. It might even be a 0 IQ change in girls.”

Dr. Najera asks:

“Is this conclusive? In my opinion, no. It is not conclusive because that is a huge range for both boys and girls, and the range for girls overlaps 0, meaning that there is a ton of statistical uncertainty here. “

This is why the epidemiological design used by the authors is worrying. For example:

” The whole thing about not including women who did not drink tap water is troubling since we know that certain drinks have higher concentrations of fluoride in them. If they didn’t drink tap water, what are the odds that they drank those higher-fluoride drinks, and what was the effect of that?”

This comes on top of the problems with the regression models used.

Transformation to normalise the data and inclusion of other important facts may have produced a non-significant relationship and there would be no need for this discussion and speculation.

What about those other important factors?

Green et al (2019) included other factors (besides maternal urinary fluoride) in their statistical model. This “adjustment” helps check that the main factor under consideration is still statistically significant when other factors are included. In this case, the coefficient (and CIs) for the linear association for boys was reduced from -5.01  (-9.06 to -0.97) for fluoride alone to -4.49 (-8.38 to -0.60) when other considered factors were included. In this case, the other factors included race/ethnicity, maternal education, “city”, and HOME score (quality of home environment).

Dr. Najera questions the way other factors, or covariates, were selected for inclusion in the final model. He says:

“The authors also did something that is very interesting. They left covariates (the “other” factors) in their model if their p-value was 0.20. A p-value tells you the probability that the results you are observing are by chance. In this case, they allowed variables to stay in their mathematical model if the model said that there was as much as a 1 in 5 chance that the association being seen is due to chance alone. The usual p-value for taking out variables is 0.05, and even that might be a little too liberal.

Not only that, but the more variables you have in your model, the more you mess with the overall p-value of your entire model because you’re going to find a statistically significant association (p-value less than 0.05) if you throw enough variables in there. Could this be a case of P Hacking, where researchers allow more variables into the model to get that desired statistical significance? I hope not.”

Good point. I myself was surprised at the use of such a large p-value for selection. And, although the study treats fluoride as the main factor and inclusion of the other factors reduces the linear coefficient for maternal urinary fluoride, I do wonder why more emphasis was not put on these other factors which may contribute more to the IQ effect than does fluoride.

Perhaps this paper should have concentrated on the relationship of child IQ with race or maternal education rather than with fluoride.

Padding out to overcome the poor explanation of IQ variance

Another point about the inclusion of these covariates. As well as possible improving the statistical significance of the final model they may also make the model look better in terms of the ability to explain the variance in IQ (which is very large – see figure above).

In my first critique of the Green et al (2019) paper (If at first you don’t succeed . . . statistical manipulation might help) I pointed out that the reported relationship for boys, although statistically significant, explained very little of the variance in IQ. I found only 1.3% of the variance was explained – using data I had digitally extracted from the figure. This was based on the R-squared value for the linear regression analysis.

Unfortunately, the authors did not provide information like R-squared values for their regression analysis (poor peer review in my opinion) – that is why I, and others, were forced to extract what data we could from the figures and estimate our own. Later I obtained more information from  Green’s MA thesis describing this work (Prenatal Fluoride Exposure and Neurodevelopmental Outcomes in a National Birth Cohort). Here she reported an R-squared value of 4.7%. Bigger than my 1.3% (my analysis suffered from not having all the data) but still very small. According to Nau’s (2017) discussion of the meaning of R-squared values (What’s a good value for R-squared?), ignoring the coefficient determined by Green et al (2019) (5.01) and relying only on the constant in the relationship would produce a predicted value of IQ almost as good (out by only about 2%).

That is, simply taking the mean IQ value (about 114.1 according to the figure above) for the data would be almost as good as using the relationship for any reasonable maternal urinary fluoride value and OK for practical purposes.

But look at the effect of including other factors in the model. Despite lowering the coefficient of the relationship for fluoide it drastically increases the R-squared value. Green reported a value of 22.0% for her final model. Still not great but a hell of a lot better than 4.7%.

Perhaps the inclusion of so many other factors in a multiple regression makes the final model look much better – and perhaps that perception is unjustly transferred to the relationship with fluoride.

Are other more important factors missed?

Almost certainly – and that could drastically alter to conclusions we draw from this data. The problem is that fluoride can act as a proxy for other factors. City location and size are just one aspect to consider.

In my paper Fluoridation and attention deficit hyperactivity disorder a critique of Malin and Till (2015), I showed inclusion of altitude as a risk-modifying factor completely removed any statistical significance from the relationship between ADHD prevalence and fluoridation – despite the fact Malin & Till (2015) had reported a significant relationship with R-squared values over 30%!

Malin & Till (2015) reported these relationships as statistically significant. However, when altitude was included in the multiple regressions by Perrott (2018) no significant relationships were fluoridation were found.

So you can see the problem. Even though authors may list a number of factors or covariates they “adjusted” for, important risk-modifying factors may well be ignored in such studies. This is not to say that inclusion of them “proves” causation any more than it does for fluoride. But if their inclusion leads to the disappearance of the relationship with fluoride one should no longer claim there is one (reviewers related to the group involved in the Green et al., 2019 study still cite Malin & Till 2015 as if their reported relationship is still valid).

In effect, the authors acknowledge this with their statement:

“Nonetheless, despite our comprehensive array of covariates included, this observational study design could not address the possibility of other unmeasured residual confounding.”

Summary

Dr. Najera summarises his impression of the Green et al (2019) study in these words:

“The big idea of these three blog posts was to point out to you that this study is just the latest study that tries very hard to tie a bad outcome (lower IQ) to fluoride, but it really failed to make that case from the epidemiological and biostatistical approaches that the researcher took, at least in my opinion. Groups were left out that shouldn’t. Outliers were left in without understanding them better. A child with IQ of 150 was left in, along with one mother-child pair of a below-normal IQ and very high fluoride, pulling the averages in their respective directions. The statistical approach was a linear regression that lumped in all of the variables instead of accounting for different levels of those variables in the study group. (A multi-level analysis that allowed for the understanding of the effects of society and environment along with the individual factors would have been great. The lack of normality in the distribution of outcome and exposure variables hint at a different analysis, too.)”

Pretty damning!

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An evidence-based discussion of the Canadian fluoride/IQ study

Dr. Christopher Labos and Jonathan Jarry discuss the recent Canadian fluoride/IQ research. They provide an expert analysis of the paper and its problems. Click on image to go to podcast.

The critical debate about the recent Candian fluoride/IQ study is continuing. Dr. Christopher Labos and Jonathan Jarry of The Body Of Evidence group discussed the research in their recent Podcast. The subject is appropriate because, as their website says:

“The Internet allows fantasies to thrive, but your health (and wallet) should not be the target of nonsense. There is a body of evidence out there, and Dr. Christopher Labos and Jonathan Jarry are staring it right in the face.

Through a podcast, a shared blog, and videos (and even appearances on the radio and in person), they explore what reproducible evidence has to say on important medical topics, and how scientific thinking shouldn’t be the sole purview of researchers. The bickering is just the cherry on top.”

The discussion is in Podcast 053 – Smart Drugs and Fluoride. The section on the Canadian fluoride/IQ study starts at 30 minutes and is 10 minutes long.

It’s a very thorough discussion going into a range of problems with these sort of studies and problems with the particular study. It raises the issue of differing results obtained by similar studies (eg the Mexican study did not report differences between boys and girls although the Canadian study did see Paul Connett’s misrepresentation of maternal F exposure study debunked and other articles here). They also discuss important factors the Canadian study ignored

Clearly, there is a lot wrong with the Canadian study – or at least a lot of factors that a sensible reader should take into account.

An important issue is the ethics of publishing controversial studies like this. In particular, the authors should have been aware that their results would be used by anti-fluoride activists to scaremonger in their campaign against community water fluoridation (that is certainly happening in New Zealand). And the most effective scaremongering is raising fears about children. Christopher and Jonathan suggest that in such a situation the authors should have been responsible enough to do further work to eliminate doubts or at least present their findings in a more qualified way. The authors should have been more diligent considering the way their findings were going to be used by activists.

The fact that this was not done suggests to me that other factors, such as professional ambition and pressure form immediate peers and their institution came into play (see Politics of science – making a silk purse out of a sow’s ear).

They also finish with a discussion of the nature of IQ tests and suggest that the differences claimed by the researchers are rather meaningless given that the average IQ of the children in the study were above average.

There is a very strong message here for the non-specialist. In cases like this, one should never simply accept the initial claims because they can be highly motivated. Christopher and Jonathan recommend that non-specialists should wait several days for the more balanced views to be published. There are plenty of experts out there who can provide this balance – they just have to be given time to actually read the paper, work out what the data means and how that compares with the claims made by authors.

For other comments on the Candian fluoride/IQ research see:

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More expert comments on the Canadian fluoride-IQ paper

The Green et al (2019) fluoride/IQ is certainly controversial – as would be expected from its subject (see If at first you don’t succeed . . . statistical manipulation might help and Politics of science – making a silk purse out of a sow’s ear). Anti-fluoride campaigners have been actively promoting it as the best thing since sliced bread. But it has not received the same glorification from most experts.

The UK Science Media Centre published a list of reactions from experts (see expert reaction to study looking at maternal exposure to fluoride and IQ in children) and they are worth reading. Also, there are comments from Dr F. Perry Wilson presented in the video above.

Wilson raises some very valid criticisms, a few of which (such as the weakness of the reported relationship) I have dealt with. He also brings attention to how even that weak relationship appears to be strongly affected by extreme values (particularly the few high values for maternal urinary fluoride).

He says:

But as you can see from the scatter plot, the effect was really small—about 1.5 IQ points for moving between the 25th and 75th percentiles of urinary fluoride.”

This is from the data presented in the paper’s Table 2. This low value was not really discussed by the authors who instead promoted an effect of 4.5 IQ points using data covering the whole range, including the unrealistically high urinary F values.

I have already commented in the previous articles on how weak the child IQ – maternal Urinary Fluoride relationship is and how it has no predictive value (see If at first you don’t succeed . . . statistical manipulation might help and Politics of science – making a silk purse out of a sow’s ear). Also, as the mean IQ values for all children and separately for boys and girls are not affected by the residence of mothers in fluoridated and unfluoridated areas it is likely that even this weak relationship is anomalous.

However to return to Dr F. Perry  I have reproduced the transcript of his talk below as he does make a number of valid points worth considering.


Welcome to Impact Factor, your weekly dose of commentary on a new medical study. I’m Dr F. Perry Wilson.

Usually, as studies come across my desk, I say, “Oh, that one is interesting” and dig in to see if it’s worth spending a few minutes of your time on. This week, I saw this study appearing in JAMA Pediatrics and just thought, “Oh no.”

This is one of those studies that I just knew would blow up, and probably for the wrong reasons.

Despite robust evidence that fluoridation of water reduces the incidence of cavities in kids, it has long been a bugaboo of conspiracy buffs, ranging from General Jack D. Ripper to Alex Jones.

No one ever seems to complain about chlorinating water, but whatever.

In any case, the argument that fluoridation is a secret communist plot has never held water, but several prior medical studies have documented a link, however small, between fluoride exposure and lower IQ in children. But all of those prior studies were flawed in one way or another, most often because the exposure was orders of magnitude higher than what is seen in the fluoridated water supply.

Enter JAMA Pediatrics, with what is really the best study to date of the effect of fluoride on IQ. Five hundred and twelve mother-child pairs from Canada were recruited during pregnancy and followed until the kids were around 3-4 years of age. At three points during pregnancy, the moms had their urinary fluoride concentrations measured. These measurements were averaged, and the researchers report that moms with higher levels had kids with lower IQs.

This held up even after adjusting for city, maternal education, race, child sex, and a score that measures the quality of the home environment.

Yikes, right? Is fluoridation causing a process of “dumbening”? Is “dumbening” even a word?

Hold up. It’s caveat time.

First, this was not a randomized trial. No one was giving these moms fluoride or regulating what they drank, so confounders could be a major issue. I’m particularly worried about socioeconomic factors that may be linked to fluoridated water consumption and also children’s IQ.

But there’s potentially a bigger problem. The plausible mechanism for neurotoxicity of fluoride in utero is that blood fluoride crosses the placenta and gets into the fetus’ developing brain. Like this.


But blood fluoride wasn’t measured. Urine fluoride was. Now, as a nephrologist, this piques my interest because urine fluoride is not a perfect proxy for blood fluoride.


The authors know this. They realize, for example, that more dilute urine will have a lower fluoride concentration, and they “correct” this problem by dividing urinary fluoride by urine specific gravity.


But this introduces a new variable. Assuming that fluoride has no effect on a child’s IQ, you could get results that look like this if moms with more dilute urine tend to have kids with lower IQs.

But wait, there’s more. Fluoride is freely filtered at the glomerulus, but it is reabsorbed in the renal tubules. This is a pH-dependent process,[2] with more reabsorption occurring when the pH is lower. That means that women with higher urinary pH (due to a more vegetarian diet or just prolonged fasting) will, on average, have higher urinary fluoride levels.


Another confounder, this one unaccounted for.

Does the presence of possible confounders invalidate the study? Of course not, but these factors remind us to interpret results like this very carefully, especially when the documented benefits of fluoridation rest on much firmer scientific footing than the possible harms.

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Politics of science – making a silk purse out of a sow’s ear

Anti-fluoride activists have some wealthy backers – they are erecting billboards misrepresenting the Canadian study on many New Zealand cities – and local authorities are ordering their removal because of their scaremongering.

Many New Zealanders are concerned at the scaremongering by anti-Fluoride activists lately. Media commenters have criticised misleading advertisements placed in national and local newspapers by Fluoride Free New Zealand (FFNZ). And local authorities have ordered some of the billboards erected by FFNZ to be taken down because of their scaremongering (see Anti-fluoride billboard removed).

A misleading advertisement anti-fluoride activists are inserting in many New Zeland newspapers. Media commentators believe newspapers must allow space for the experts to present the true science listen to Gavin Ellis, Nine to Noon, Sept. 3).

I can fully understand anti-fluoride activists taking advantage of current interest in the recently published Canadian fluoride/IQ study (see If at first you don’t succeed . . . statistical manipulation might help). They are, after all, an advocacy group, well known for their misrepresentation of the science, and they have rich backers in the alternative health industry (see Big business funding of anti-science propaganda on health and Anti-fluoridationists go to Supreme Court – who is paying for this?) to finance this expensive advertising.

As always its a matter of “Reader Beware.”  In this day and age readers are well-advised to take what they see on billboards and in newspapers (particular advertisements) with large dollops of salt.

“Sexy” science

But what disturbs me is the role the personal ambition of scientists and institutional advocacy, the politics of science, has played in this unfortunate misrepresentation and advocacy of the Canadian study.

This is not an isolated case. Scientific researchers with any experience know of many examples where individual scientists have misrepresented or exaggerated their findings because of personal ambition and institutes have gone along with this to obtain kudos (and money). We all know of young scientists who have behaved in this way, effectively promoting their poor science, risen through the ranks and, before long, exited research to take high-paying roles in science administration. More honest researchers are often scathingly critical of such ambition – especially as we often have to put up with these people manipulating funding and distorting scientific directions when they later become administrators. At the same time, we respect the honest researchers who often plod away, making slow but real progress, but not seeking, or getting, full public recognition for their work – because it is not “sexy” enough.

Yes, I like most researchers, have experienced administrators demanding that we make our research more “sexy.” These same administrators have never expressed the desire we make out research more honest, more professional or more effective (except in terms of winning publicity and unthinking funds).

Relying on “authority” statements while ignoring real data

Interestingly, in this current round of scaremongering the anti-fluoride activists do not reproduce data from the studies. There are no graphs, for example. Perhaps the real-life data is so scattered it would expose their claims of specific values of harm as fantasy.

According to an FFNZ post, the IQ of children in this study would have dropped by 4.5 points, from 114.1 where mother’s urinary F concentration (MUF) was 0 mg/L to 109.6 when the MUF was 1 mg/L. But look at the figure below. Very few of the data points near a MUF of 1 mg/L are actually near 109.6. They vary from about 75 to 125! No wonder they do not reproduce the figure from the paper to support their claim.

Instead, they rely on the approach of quoting the statements of “authorities,” some of the authors and others who have commented favorably on the research.

Yes, the authors did state they had found an association (for boys) with a best-fit line (the blue line above) showing an IQ decline of 4.49 points for an increase in MUF of 1 mg/L. But clearly this is meaningless when the very high scatter of the data is considered – it has no predictive value. This is because the claimed IQ reduction represents only the best fit line, the very weak association of IQ with MUF they reported. An association so weak that it refers only to 1.3% of the data (see If at first you don’t succeed . . . statistical manipulation might help).

OK, perhaps I can be accused of ignoring the stated variability of the reported relationship (although so have the anti-fluoride campaigners). Green et al (2019) described the relationship in the abstract of their paper this way:

“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.”

As a predictor that is saying that 95% of IQ values for boys at a MUF of about 1 mg/L should be in the range 105.7 to 113.5. Again, simply not true (look at the figure above). In fact, this relationship refers only to the best fit line and the blue zone in the figure above indicates where this line could go 95% of the time.

So this “authority” statement about the reported relationship is simply of no practical value as it applies to only 1.3% of the data. It is meaningless and it’s irresponsible for the authors and other “authority” spokespeople to refer to this relationship in the way they have without mentioning how weak it is.

The “authority” statements and those of the authors themselves are doubly worse because they ignore the fact that there is no statistically significant difference for the IQs of all children and separately the boys and girls, for mothers who lived in fluoridated and unfluoridated areas during their pregnancy. The data showing this is in Table 1 of the paper (and presented below) so it is strange that the authors did not discuss this in their paper at all.

Mean IQ of children whose mothers drank fluoridated or unfluoridated water during pregnancy (SD =  11.9 – 14.7)

Nonfluoridated Fluoridated
All children 108.07 108.21
Boys 106.31 104.78
Girls 109.86 111.47

Shameless advocacy by scientists and institutions

Scientists are only human and it’s perhaps not surprising that authors of these and similar studies will exaggerate the importance of their finding and remain silent about deficiencies in their studies. After all, self-promotion of this sort, especially if it gets widespread industry and public attention, can only be good for their careers.

One of the authors, Cristine Till is reported as saying:

“At a population level [4.5 IQ points, SC], that’s a big shift. That translates to millions of IQ levels lost” [reported by CNN]

And:

“We would feel an impact of this magnitude at a population level because you would have millions of more children falling in the range of intellectual disability, or an IQ of under 70, and that many fewer kids in the gifted range…We recommend that women reduce their fluoride intake during pregnancy.” [Reported by NPR]

And:

“Four and a half IQ points is of substantial societal and economic concern…We’re talking a magnitude that’s comparable to what we’re talking about when we talk about lead exposure. You would have millions of more children falling into the range of intellectual disability with IQ scores of less than 70, and that many fewer kids in the gifted range.” [Reported by WebMD]

Looking at the graph we can clearly see that at the population levels there are not these huge losses in IQ. She omits the fact that the relationship they report is extremely weak. Her statement is misleading – but she no doubt feels its good for her career. She also omits the fact shown by their own Table 1 that there is no difference in IQ fo children whose mothers lived in fluoridated or unfluodiated areas.

And then we get promotion of these misrepresentations by other scientists – apparently independent of the authors but a closer look shows them to be linked.

This from  Phillipe Grandjean:

“This is an excellent study,”  . . . CDC has to come out and look at the risk-benefit ratio again, because they can’t continue relying on studies that were carried out decades ago.” (Reported by Washington Post]

Grandjean frequently makes these sort of comments on studies which can be interpreted as supporting anti-fluoride positions. He is even a bit of a go-to spokesperson for the Fluoride Action Network (FAN) and his bias is clear, despite his professional standing. As the chief editor for Environmental Health he would not allow my critique of the Malin & Till (2015) ADHD study to be considered for publication (see Fluoridation not associated with ADHD – a myth put to rest). My critique was later reviewed and accepted by a different journal but ethically it should have been published by the journal which published the original Malin & Till (2015) paper.

Grandjean was one of the people I commented on in my articles about the poor peer review of the Malin & Till paper (see Poor peer-review – a case study and Poor peer review – and its consequences). So was David Bellinger – a subeditor who dealt with the Malin & Till (2105) paper. Bellinger, coincidentally, wrote a supportive opinion piece on the Green et al (2019) paper in the issue of JAMA  Pediatrics which published the Green et al paper.

It amazes me sometimes how incestuous journal editors, paper authors and peer reviewers cna be.

Don’t get me wrong. there was also quite a widespread criticism of the Green et al (2019) paper in the scientific community. Hopefully, some of these critics will contribute critiques of the paper to the journal. Also, hopefully the journal editor will allow these critiques to be published (although, as I point out in If at first you don’t succeed . . . statistical manipulation might help the editor seems only to be welcoming debate on these findings if it is in the public media).

The point, of course, is that activist anti-fluoride organisations like FAN and FFNZ never quote those critics. they simply quote the apparently “authoritative” figures who have praised the paper or promoted the misinformation described above. Thes misleading quotes from authors, institutes and “authority” supporters are simply mana from heaven to the FAN and FFNZ activists.

Dangers of science politics allied with ideologically-motivated advocacy

Problems with the politics of science occur all the time. That is why I always suggest readers should look at papers, even those in the most reputable journal, critically and intelligently. Importantly, one should look at the actual data where possible to check that it is portrayed properly in the discussion, conclusions and abstract. Otherwise, it is easy to be misled by ambitious authors, public relations press releases from institutions and “independent” scientific commenters.

Also, only the most naive reader accepts information in news articles and adverts as necessary gospel truth. The sensible reader approaches the media and advertising critically.

However, in this case, I think people have a right to be far more concerned about the misinformation – both that presented by authors, their institutes and their colleagues, and the way it is presented to us by the media and advertising. This is because the worst sort of fear-mongering is involved – playing on our love for our children and inherent wishes to do anything to protect them.

So I support the concern expressed by people in the media, the suggestion that such advertising should be accompanied by more informed articles, and the actions of local authorities in ordering the offending billboards be taken down. I passionately believe in free speech and defend the rights of even those I think wrong to partake of this – to express their opinions. But when the wellbeing and health of children and their parents are compromised by that free speech I think there is a case for it to be limited.

After all, there are other avenues, especially one which enable claims to be challenged properly, where that free speech can continue without creating harm.

Science reporters should be more responsible

I can’t finish without airing a concern I have about science reporters. In a sense, they are in a privileged position because the subjects they deal are credible because science is involved. Science does have a reputation for getting to the truth and being objective.

Privilege is also conferred on these reporters because they continually cite and quote experts – people of “authority” because of their education and scientific positions.

But surely an experienced science reporter is aware of the problems of politics in science – the role of ambition and search for fame which can lead to misrepresentations or at least over-glorification of the subjects being reported by the researchers involved. They must also surely be aware that different schools of thought within the scientific community can lead to biased presentations.

It’s not good enough for science reporters to simply quote authors and biased researchers. Surely they have an obligation to do some checking on the credibility of the claims being made. Why not read the full papers rather than rely on an abstract or an author’s claim? Further, and more importantly, why not cast a critical eye over the evidence reported in the paper and the data if it is there? Surely most science reports have some scientific and statistical skills.

I realise reporters have deadlines. In this case, some of the “authorities” commenting on the paper had been given prior access – a bit unfair for other reporters. It is tempting to go with what one has and not delay an article by indulging in critical analysis. But reporters should also think responsibly. Misinformation, in this case, is being used to promote dangerous scaremongering. That scaremongering should not be assisted by negligent reporting.

I am saddened that hardly any reporters quote the important information from the paper – that presented in the paper’s Table one and the table above. Differences in IQ of children whose mothers lived in fluoridated or unfluoridated areas are not different – or more correctly the differences (changes of +0.14 points for all children, -1.53 points for boys and + 1.61 points for girls when fluoridation is involved) are not statistically significant.  OK, the authors and their promoters were silent about that data – but a good reporter should have picked it up.

On the other hand, most science reporters ignored the actual data and went with the quotes. So instead of the data in the table above a misleading IQ change of 4.5 points for boys was presented as the main message. With absolutely no evaluation of how weak the relationship used to obtain that figure is.

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If at first you don’t succeed . . . statistical manipulation might help

Anti-fluoride campaigners are promoting yet another new study they claim shows community water fluoridation lowers children’s IQ. For example, the Fluoride Free NZ (FFNZ) press release Ground Breaking Study – Fluoridated Water Lowers Kid’s IQs which claims the study confirms“our worst fears, linking exposure to fluoridated water during pregnancy to lowered IQ for the developing child.”

Yet the study itself shows no significant difference in children whose mothers lived in fluoridated or unfluoridated areas during pregnancy. Here is the relevant data from Table 1 in the paper:

Mean IQ of children whose mothers drank fluoridated or unfluoridated water during pregnancy (SD =  11.9 – 14.7)

Nonfluoridated Fluoridated
All children 108.07 108.21
Boys 106.31 104.78
Girls 109.86 111.47

The differences between fluoridated and nonfluoridated are not statistically significant.

The paper has just been published and is:

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.

Surprisingly the authors do not discuss the data in the table above. Its as if the data didn’t exist, despite being given in their Table 1. I find this surprising because their discussion is aimed at finding a difference – specifically, a decrease in child IQ due to fluoridation – and surely these mean values must be relevant. Were the authors embarrassed by these figures because they did not show the effect they wanted?

So how did they manage to find an effect they could attribute to fluoride, or fluoridation, despite the mean values above? They basically resort to statistical manipulation – and this has opened up an intense controversy about the paper.

An unprecedented “Editor’s Note”

The journal editor, Dimitri A. Christakis, published a note alongside the paper (see Decision to Publish Study on Maternal Fluoride Exposure During Pregnancy), together with a piece in the Opinion section by David C. Bellinger (see Is Fluoride Potentially Neurotoxic?). This opinion piece is described as an editorial although Bellinger is not an editor of the journal or on the Editorial Board.

This is, in my experience, completely unprecedented. Editor’s don’t comment on the quality of papers or the refereeing process and I can only conclude that within the journal editorial board and those who reviewed the paper there were sharp differences about its quality and whether it should be published. While an editorial may sometimes bring attention to an article, in this case, it is likely that Bellinger was one of the reviewers of the paper and he is expressing his viewpoint on it and supports its publication.

Christakis writes “The decision to publish this article was not easy.” He goes on to imply the journal supports publication “regardless of how contentious the results may be.”  But surely there is no need to defend a good quality paper in this way just because the results may be “contentious.”

Interestingly, FFNZ interpreted the publication of the Editor’s note as making the publication of the paper more “impactful” not realising that the Note is probably not positive for the paper as it reveals controversy over the paper’s quality and whether it was worthy of publication. FFNZ also chose to describe Bellinger’s comments in his opinion piece as representing the views of the authors. However, it would be inappropriate for an editor to make such comments.

I think Bellinger has his own biases and preferences which lead him to advocate for papers like this. I commented on Bellinger’s role in the review of another paper promoting an anti-fluoride perspective in my articles Poor peer-review – a case study and Poor peer review – and its consequences.

A large amount of controversy

I am surprised at the degree of controversy around this paper – and it’s loudness. The fact that it started on the same day the paper was made public reveal various actors have had access to the paper and have been debating it for some time.  This could have been stoked by the unorthodox statistical analysis used and contradictions in the findings.

But it appears this controversy had gone far wider than the journal editors and reviewers of the paper because of the immediate reactions from anti-fluoride organisations like the Fluoride Action Network (see BREAKING: GOVERNMENT-FUNDED STUDY LINKS FLUORIDATED WATER DURING PREGNANCY TO LOWER IQS IN OFFSPRING), some leading Newspapers,  professional bodies (see AADR Comment on Effect of Fluoride Exposure on Children’s IQ Study) and the UK Science Media Centre which published a reaction from experts article (see expert reaction to study looking at maternal exposure to fluoride and IQ in children).

This suggests to me a large degree of lobbying. Not only from activists and anti-fluoride scientists or reviewers. But also from authors and their institute. I am not really surprised as I have often seen how politics, activism, commercial interests, and scientific ambitions will coordinate in these situations.

How to discover an effect from a nonsignificant difference

So how do we get from the data in the table above – showing no statistically significant difference between fluoridated and unfluoridated areas – to a situation where the authors (who don’t refer to that data in their discussion) say:

“higher levels of fluoride exposure during pregnancy were associated with lower IQ scores in children measured at age 3 to 4 years. These findings were observed at fluoride levels typically found in white North American women. This indicates the possible need to reduce fluoride intake during pregnancy.”

In their press releases and statements to media, where they are not constrained by a journal’s need for evidence and objectivity, they come out even more vocally against community water fluoridation.

Well, it appears to me, by statistical manipulation. One of the Science Media experts referred to above, Prof Thom Baguley, wrote:

“First, the claim that maternal fluoride exposure is associated with a decrease in IQ of children is false. This finding was non-significant (but not reported in the abstract). They did observe a decrease for male children and a slight increase in IQ (but non-significant) for girls. This is an example of subgroup analysis – which is frowned upon in these kinds of studies because it is nearly always possible to identify some subgroup which shows an effect if the data are noisy. Here the data are very noisy.”

It appears the authors found a significant effect of child sex on IQ so made a decision to do a subgroup analysis – of boys and girls – and this produced a significant association of IQ with maternal urinary fluoride for the boys. This resort to subgroup analysis may have, in itself, produced a misleading significant relationship.

Adam Krutchen, Biostatistics PhD student at the University of Pittsburgh, also illustrates how the relationship with child sex has confused the analysis. He comments on the data that he managed to extract from the paper’s Figure 3:

“There were drastic sex-specific IQ differences in the children, which is of course strange. We shouldn’t expect anything like that to happen. This difference is very significant. There’s also some outlier extremely low IQ values among the male children.”

He is saying that his regression analysis showed a strong effect of child sex on IQ. This is quite irrespective of maternal urinary F or drinking water F. However, once that effect of child sex is taken into account he found no relationship of child IQ with maternal urinary F. He says:

“with such a significant effect of sex on IQ, does fluoride have any remaining relationship? The answer is a resounding no in the digitized data.”

It appears that including child sex difference in the regression analysis produces the finding that there is no significant relationship of fluoride to child IQ after taking into account the significant relationship of IQ with child sex. But when the data is divided into subgroups and analysed separately (a technique statisticians “frown on” “because it is nearly always possible to identify some subgroup which shows an effect if the data are noisy”) a significant relationship of IQ with maternal urinary fluoride can be produced for boys (but not girls).

Interestingly, a second part of the Green et al., (2019) study investigated a relationship of child IQ with unverified estimated fluoride intake by the pregnant mothers. The estimation method was not verified so may be questionable). No sex difference appeared in that data set.

How strong are the reported relationships

Perhaps it is not necessary to go any further. Perhaps the data for mean IQ in the table above is sufficient to show there is no effect of fluoride on IQ. Or perhaps the critique of the analysis of subgroups used is sufficient to make the reported conclusions suspect.

However, perhaps a comment on the weakness of the relationships reported by Green et al is useful – if only because I took the trouble to digitally extract the data from the figures in the paper and do my own regression analyses on the data.

Of course, digital extraction does not get all the data – even if only because the points may merge. In this case, I managed to extract 410 data points from Figure 3A which showed the relationships of child IQ with the maternal urinary F concentrations during pregnancy. This is quite a bit smaller than the 512 data pairs the authors reported in their Table 1 and suggests to me they had not plotted all their data. However, the values for means and coefficients obtained by my own regression were very similar to those reported by Green et al., (2019).

The authors reported a significant (p=0.02) negative relationship of boy’s IQ with maternal urinary F. They do not discuss how strong that relationship is – although the wide scatter of data points in the figures suggest it is not strong. My regression analysis showed the relationship explained only 1.3% of the variance in IQ. I do not think that is worth much. With such low explanatory power, I think the authors overstate their conclusions.

I think this is another case of placing far too much reliance on p-values and ignoring other results of the statistical analysis. I discussed this in a previous article – see Anti-fluoride activists misrepresent a new kidney/liver study).

Conclusions

I think this paper has been overblown. It has problems with its statistical analyses as well as other limitations referred to in the paper. I do not think it should have been published in its present form – surely reviewers should have picked up on these problems. I can only conclude that intense arguments occurred within the journal’s editorial board and amongst reviewers – and most probably more widely amongst institutes and activist groups. In the end, the publication decision was most likely political.

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Flaw and porkie in anti-fluoride report claiming a flaw in Canadian study

Anti-fluoride group, Fluoride Action Network, ironically stamps their own critique of the Calgary fluoridation cessation study as “debunked.”

Anti-fluoride campaigners have launched another attack on a Canadian fluoridation cessation study. They claim it is flawed – but there is a huge flaw in their own critique.

I discussed their original attack in February last year (see Anti-fluoridationist’s flawed attacks on Calgary study). But this new attack is based on a published critique of the original study. I think that is good progress – the anti-fluoride campaigners have made a detailed critique and published it in the journal which published the original paper. The original authors have then responded. This is how things should be done.

Timeline

For those of you with the interest and time who want to go into the details, the original study was published in:

McLaren L, Patterson S, Thawer S, Faris P, McNeil D, Potestio M, Shwart L. (2016) Measuring the short-term impact of fluoridation cessation on dental caries in Grade 2 children using tooth surface indices. Community Dent Oral Epidemiol 2016.

The anti-fluoride critique was recently published in:

Neurath, C., Beck, J. S., Limeback, H., Sprules, W. G., Connett, M., Osmunson, B., & Davis, D. R. (2017). Limitations of fluoridation effectiveness studies: Lessons from Alberta, Canada. Community Dentistry and Oral Epidemiology, (October 2016), 1–7.

The response from the original authors was then published in:

McLaren, L., Patterson, S., Thawer, S., Faris, P., McNeil, D., & Potestio, M. (2017). Fluoridation cessation: More science from Alberta. Community Dentistry and Oral Epidemiology, (October), 1–3.

Other data which have been used in the critique and which I will use here can be found in:

McLaren, L., McNeil, D. A., Potestio, M., Patterson, S., Thawer, S., Faris, P., … Shwart, L. (2016). Equity in children’s dental caries before and after cessation of community water fluoridation: differential impact by dental insurance status and geographic material deprivation. International Journal for Equity in Health, 15(1), 24.

And:

McLaren, L., Patterson, S., Thawer, S., Faris, P., McNeil, D., Potestioa, M. L., & Shwart. L. (2017). Exploring the short-term impact of community water fluoridation cessation on children’s dental caries: a natural experiment in Alberta, Canada. Public Health, 146, 56–64.

Most of the authors of the critique are listed as members of the Fluoride Action Network (FAN) team and I can understand that FAN would feel proud that their critique was published. However, I feel their press release was rather underhand to imply the original study is:

“seriously flawed science  . . . Citizens should be concerned that their tax dollars have funded this biased work.”

And that the work was funded by state and public bodies:

“whose policy is to promote fluoridation.”

But let’s look at the critique itself – because it has some pretty big flaws itself.

What did the original study find?

My article, Anti-fluoridationist’s flawed attacks on Calgary study describes the details of this study. But briefly, it showed that child tooth decay increased in the Canadian city of Calgary after cessation of fluoridation. It used a comparison fluoridated city (the nearby and similar sized city of Edmonton) – and just as well because tooth decay also increased in that city during that time. However, there was still an increase in tooth decay in Calgary after cessation of fluoridation even after correction for the increase due to other factors apparent in Edmonton.

What did the critique claim?

A number of the criticisms are debatable and relatively minor.

How suitable was Edmonton as a comparison city? Neurath et al., (2017) claim it wasn’t suitable (but did not suggest a better alternative). McLaren et al., (2017) claim there is “no better comparison community for Calgary than Edmonton.”

Confounding – Neurath claims consideration of confounding factors was inadequate. McLaren et al., (2017) refer to extra data in two other papers and describes their consideration of several likely confounding factors like public health programmes and use of sealants. Whether the correct factors or sufficient factors were considered is always a bone of contention between authors and critics and, in the end, available data and funding decides.

Study design – Neurath et al., (2017) argue for randomised controlled trials. McLaren et al. (2017) point out that in studies of social programmes one must go with what exists. They say:

“While we agree with the value of stronger designs, one must be thoughtful about evaluation of public health measures, which by definition are complex and context-dependent. We used the best available
data and design for our circumstances”

Data ignored?

But Neurath et al (2017)’s major criticism is that some important data was ignored. And they claim that when that data is included the conclusions are not valid.

Of course, the FAN authors are stretching things quite a bit. The original study was based on data for tooth surfaces – the decay, extracted and filled tooth surfaces (defs). This was used as it is more sensitive than the tooth data itself – the decayed missing and filled teeth (deft).

Data for defs were only available for the 2004/05 and 2014/15 surveys. Unfortunately, there were no defs data for the pre-cessation period closer to the time of cessation (2011). That is the sort of problem researchers face when dealing with existing surveys and existing social programmes.

But the bright sparks at FAN latched on to the fact there was a survey with deft data in Calgary closer to the cessation time – 2009/2010. The fact that there was no equivalent survey for Edmonton didn’t hold them back – they proceeded to imply the 2009/2010 data had been purposely held back, despite McLaren making clear she could not use that data for Calgary in the absence of similar data for Edmonton. That would have negated the requirement for a comparison city and the existing data surely shows that requirement was very wise.

So Neurath et al., (2017) chose to ignore the obvious requirement for a comparison city and proceeded to argue their case on the Calgary data alone. They argued the study was “fatally flawed” and that “key data [was] omitted.” The argument implied the study was somehow fraudulent and that the authors had hidden the 2009/2010 survey data – despite the fact this data is used in another of their papers!

Neurath et al., (2017) pretend that a comparison city is not really necessary – relying only on the tooth data (deft) for Calgary they argue that as 50% of the increased in tooth decay had occurred between the 2004/05 and 2009/10 surveys then the increases seen after cessation of fluoridation was due to the same trend (see their Figure 1 below). They argued this proved that cessation of fluoridation had no effect. Ignoring completely the Edmonton data.

So, an obvious flaw in their critique – but wait, there is more! They actually go so far as to falsify data.

Falsifying a “correction factor”

Not satisfied with the plots in Figure 1B they found a way to make the data look even worse for McLaren et al. (2015). They came up with a “correction” factor to convert the deft data for 2009/2010 survey into defs data. Here is their Figure 2 using the “converted” deft data

Looks bad, doesn’t it?

However, the trick is in the way the conversion factor is calculated. They “used the ratio of defs to deft in the 2013/2014 survey to make the conversion.” The table below for subset (dmft>0) data they used shows this produces a conversion factor of 2.41 – big enough to dramatically push the 2009/10 data point right up so that it is sitting on the Edmonton “trend line” in their Figure 2 above.

But they could have equally used the ratio of defs/deft in the 2004/2005 survey to make the conversion. That produces a much lower conversion factor of 1.63 – which is not at all consistent with their claim “when we applied this conversion [2.41] to the 2004/2005 Calgary survey, where both deft and defs are known, the calculated defs was very close to the known defs.”

In fact, it may have been more appropriate to take the average conversion factors from the two available surveys. In the figure below I have done this (green data point) and compared this with the use of the conversion factors from the 2004/05 survey (purple data point) and that from the 2004/15 survey used by Neurath et al (yellow data point).

I guess this shows the danger of making these sort of adjustments – especially when there is a bias to confirm. And also that readers should beware of vague assertions of the sort:

“when we applied this conversion [2.41] to the 2004/2005 Calgary survey, where both deft and defs are known, the calculated defs was very close to the known defs.”

Conclusion

The McLaren et al., (2017) study has its limitations, limitations admitted and described by the authors. But, it is the FAN critique of Neurath et al., (2017) rather than the original study, that is fatally flawed. Flawed because of confirmation bias and a porky.

1: They ignored the necessary use of a comparison city and assumed the increase in tooth decay in Calgary was linear over the time between the two surveys McLaren at al used.

2: The use of any correction factor would be questionable but Neurath et al., (20127) clearly used a biased value to suit their argument. Further, they purposely misrepresented their correction factor by implying a similar value would have been obtained from the 2004/2005 survey data. Completely wrong.

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Local anti-fluoride activists tell porkies yet again

FFNZ confuses lack of low fluoride studies on rats with human studies

Well, I suppose that’s not news. A bit surprising, though, because they are claiming the absence of research on fluoridation and IQ – which sort of conflicts with the previous attempts to actually condemn and misrepresent the actual research on fluoridation and IQ.

Fluoride Free NZ’s (FFNZ) face book page is claiming:

Would you be interested to know that no studies have been conducted on fluoridated water at 0.7ppm to determine whether there is IQ reduction? The National Toxicology Program are currently completing research to fill this gap. You would have thought that they would have done this in the 1950s before starting the fluoridation program wouldn’t you?

There have actually been three recent studies from three different countries which have specifically investigated the claim of an effect of fluoridation on IQ – and, unsurprisingly, all threes studies showed there was no effect.

Here are those studies:

New Zealand

Broadbent, J. M., Thomson, W. M., Ramrakha, S., Moffitt, T. E., Zeng, J., Foster Page, L. A., & Poulton, R. (2014). Community Water Fluoridation and Intelligence: Prospective Study in New Zealand. American Journal of Public Health, 105(1), 72–76.

In fact, anti-fluoride activists in the US, as well as New Zealand, have campaigned against this study. Their major criticism is that the study also included the effect of fluoride tablet use. They argue that this makes the unfluoridated control group useless because many participants will have consumed fluoride tablets. However, they ignore the fact that the statistical analysis corrected for this but still found no statistically significant difference in IQ of children and adults from fluoridated and unfluoridated areas.

Sweden

Other critics of the Broadbent et al. (2014) study have raised the issue of experimental power because of the numbers of people in the study. This could be a valid issue as it would determine the minimum effect size capable of being detected. Aggeborn & Öhman (2016) made that criticism of Broadbent et al., (2016) and all other fluoride-IQ studies. Their study is reported at:

Aggeborn L, Öhman M. (2016) The Effects of Fluoride in the Drinking Water. 2016.

Aggeborn & Öhman (2016) used much larger sample size than any of the other studies – over 81,000 observations compared with around 1000 or less for the commonly cited studies. It was also made on continually varying fluoride concentrations using the natural fluoride levels in Swedish drinking waters (the concentrations are similar to those in fluoridated communities), rather than the less effective approach of simply comparing two villages or fluoridated and unfluoridated regions. The confidence intervals were much smaller than those of other cited fluoride-IQ studies. This makes their conclusion that there was no effect of fluoride on cognitive measurements much more definitive. Incidentally, their study also indicated no effect of fluoride on the diagnosis of ADHD or muscular and skeleton diseases.

Canada

Another recent fluoridation-IQ study is that of Barbario (2016) made in Canada:

Barberio, AM. (2016). A Canadian Population-based Study of the Relationship between Fluoride Exposure and Indicators of Cognitive and Thyroid Functioning; Implications for Community Water Fluoridation. M. Sc. Thesis; Community Health Sciences, University of Calgary.

This study also had a large sample size – over 2,500 observations. This reported no statistically significant relationship of cognitive deficits to water fluoride.

Incidentally, Barberio (2016) also found there was no evidence of any relationship between fluoride exposure and thyroid functioning. That puts another pet claim of anti-fluoride campaigners to rest.

Animal studies

So much for NZFF’s claim that “no studies have been conducted on fluoridated water at 0.7ppm to determine whether there is IQ reduction.” But, just a minute, they are quoting the National Toxicology Program (NTP):

“No studies evaluated developmental exposure to fluoride at levels as low as 0.7 parts per million, the recommended level for community water fluoridation in the United States. Additional research is needed.”

But they omit the next sentence from the quote:

“NTP is conducting laboratory studies in rodents to fill data gaps identified in the systematic review of the animal studies.”

The NTP is discussing the research with animals, mainly rats, where effects of fluoride on the cognitive behaviour of the test animals have been reported but the fluoride concentrations are very high. And NTP’s assessment base on the review of the literature found only “a low to moderate level of evidence that the studies support adverse effects on learning and memory in animals exposed to fluoride in the diet or drinking water.” Hence the need for more research.

As part of the NTP’s research, which is currently underway, there are plans to extend studies to low fluoride concentrations more typical of that used in community water fluoridation.

The high concentrations used in animal studies is a major flaw in the anti-fluoride activist use of them to oppose community water fluoridation. For example, Mullinex et al (1995) (very commonly cited by anti-fluoride campaigners) fed test animals drinking water with up to 125 mg/L of fluoride (concentrations near 0.8 mg/L of fluoride are used in community water fluoridation).

While it is unlikely that the NTP research will find any significant effects of fluoride on the cognitive behaviour of rats at the low concentrations used in community water fluoridation the anti-fluoride campaigners have their fingers (and probably toes as well) crossed.

NTP will begin publishing the results of their new research next year (see Fluoride and IQ – another study coming up).

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More nails in the coffin of the anti-fluoridation myths around IQ and hypothyroidism

thyroid_fluoride

Large Canadian study finds no effect of fluoridation on thyroid health

A new Canadian study shows no relationship of cognitive deficits or diagnosis of hypothyroidism with fluoride in drinking water. This work is important because it counters the claims made by anti-fluoride campaigners. While the campaigners cite scientific studies to support their claims, those studies are usually very weak, or irrelevant because they involve areas of endemic fluorosis where drinking water fluoride concentrations are much higher than in situations where community water fluoridation (CWF) is used.

The study is reported in:

Barberio, A. M. (2016). A Canadian Population-based Study of the Relationship between Fluoride Exposure and Indicators of Cognitive and Thyroid Functioning; Implications for Community Water Fluoridation. MSc Thesis, University of Calgary

This new study is important as it has the advantages of using a large representative sample of the Canadian population, with extensive data validation and quality control measures. It also uses individual-level estimates of fluoride exposure on the one hand, and thyroid health and cognitive problems on the other.

Fluoride exposure was measured both by concentration in tap water for selected households and concentration in urine samples from individuals.

Thyroid health

The Canadian study found:

“Fluoride exposure (from urine and tap water) was not associated with impaired thyroid functioning, as measured by self-reported diagnosis of a thyroid condition or abnormal TSH level.”

This contradicts the conclusions from the population-level study of Peckham et al., (2015) which reported that fluoridation was correlated with the prevalence of hypothyroidism. That study is quoted extensively by anti-fluoridation activists but has been roundly criticised because it did not include the influence of confounders – particularly iodine which is known to influence thyroid health.

Barberio (2016) also suggests that the different recommended fluoride concentrations used for CWF in Canada and the UK, and the fact that the Peckham et al (2015) study did not involve individual measures, could also be factors in the different findings.

Cognitive functioning

The Canadian study reported:

“Fluoride exposure (from urine and tap water) was not associated with self-reported diagnosis of a learning disability.”

Barberio (2016) did also investigate a more detailed diagnosis for cognitive problems and found:

“Higher urinary fluoride was associated with having ‘some’ compared to ‘no’ cognitive problems . . . . however, this association:

  • Was weak;

  • Was not dose-response in nature; and

  • Disappeared when the sample was constrained to those for whom we could discern fluoride exposure from drinking water.”

I guess anti-fluoride activists might latch on to this last point regarding urinary fluoride but, at least as far as tap water fluoride is concerned, there was no relationship with learning difficulties.

Conclusion

So – yet another large-scale study contradicts anti-fluoridationist claims. It shows that CWF has no influence on cognitive problems or thyroid health.

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Another defeat for anti-fuoridation claims about arsenic

Anti-fluoride campaigners make a song and dance about contaminants, particularly arsenic, in fluoridation chemicals. However, a new study shows there is actually nothing to worry about – and, in fact, these campaigners should be more concerned with natural sources of arsenic, than with fluoridation chemicals.

The study is:

Peterson, E., Shapiro, H., Li, Y., Minnery, J. G., & Copes, R. (2015). Arsenic from community water fluoridation: quantifying the effect. Journal of Water and Health.

Past studies estimated the arsenic contribution to drinking water from fluoridation using the arsenic concentration of the fluoridation additives. This new study went further and compared the actual arsenic concentrations of  1329 paired raw water and treated drinking water samples. The samples were taken from 121 drinking water systems in Ontario, Canada.

The graph below compares the mean values of arsenic concentrations in raw water and treated water for both fluoridated (49%) and unfluoridated systems (51%).

Peterson

The data shows that even after treatment the concentration of arsenic due to natural sources is about 0.44 ppb. Fluoridation added a mere 0.07 ppb to this! (ppb = parts per billion = micrograms/litre = μg/L).

The authors concluded that fluoridation is associated with an extra 0.078 ppb compared with non-fluoridated systems when controlling for other factors (raw water concentrations, treatment processes and water source).

Let’s put these figures in context. The maximum acceptable value (MAV) for arsenic in drinking water is 10 ppb. So even the raw water mean concentration of 0.69 ppb (0.44 ppb after treatment) is safe. And the extra arsenic in fluoridated water is only 0.7% of the MAV!

Surely the sensible person will worry about natural sources of arsenic long before getting their knickers in a twist over the contribution from fluoridation.

I drew a similar conclusion from some New Zealand (Hamilton City) data in my article Fluoridation: putting chemical contamination in context. In that case, the contribution for arsenic from natural sources was much higher (around 30 ppb in the raw water – 3 times the MAV, and about 3 ppb in the treated water – a third of the MAV ).

New paper confirms previous studies

This new study confirms previous work based on the measured concentration of arsenic in fluoridating chemicals. That work produced regulations defining maximum permissible levels of contamination in water treatment chemicals. These are based on a maximum contribution of 1 ppb – 10% of the MAV.

Peterson et al., (2015) indicates the extra arsenic resulting from fluoridation is less that 10% of these standards. This is likely to be much less in Australia and New Zealand as the actual arsenic concentrations in the major fluoridating agent used, fluorosilicic acid, are much lower than those used in North America.

So – my message to anti-fluoridation campaigners is stop worrying about arsenic due to fluoridation. If you must worry then check out the concentration  of arsenic in your drinking water, and the raw water source, due to natural sources.

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