Category Archives: Health and Medicine

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!

Similar articles

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!

Similar articles

Fluoridation – A new fight against scientific misinformation

Anti-fluoride campaigners think a new Canadian fluoride IQ study is the best thing since sliced bread but the scientific critiques warn they are wrong. Photo Illustration by The Daily Beast/Getty

The new Canadian fluoride-IQ study has certainly created some sensational reporting. On the one hand, anti-fluoride campaigners are lauding the study as the best things since sliced bread and seem sure it will lead to the end of community water fluoridation. Mainstream media have featured the findings – although in most cases warn they are controversial and may be meaningless. As would be expected, alternative health media have been promoting it and repeating the anti-fluoridation arguments.

However, scientific commenters have mainly criticised the study and warned that even if the findings are valid it is just one study and it is far too early to consider stopping community water fluoridation – a health policy which is so far been seen as economical, safe and effective in helping fight tooth decay.

I strongly believe the scientific critiques are important. One should not rely on “authority” statements in such matters – especially statements from well known anti-fluoride activists. But we should also be aware that self-promotion by the authors and journal, and by the authors’ institutions, is also not a reliable indicator of the worth of a study.

In the end, the validity and worth of this study will depend on the data and methodology – and good scientific critiques will look at these, not the status of the journal, institutions or authors. And not the public statements being made to promote the findings.

Some interesting critiques are coming from Dr. René F. Najera who is a Doctor of Public Health, an epidemiologist and biostatistician. These are the very skills essential for a proper critique of the Canadian study.

The specific study Dr. Najera refers to 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:

The “shenanigans” of activists

In his first article, The Hijacking of Fluorine 18.998, Part One, Dr. Najera gives some background. He says:

“Time after time, epidemiological studies have shown that fluoridated water leads to less tooth decay. Less tooth decay leads to better health outcomes as poor oral health is a risk factor for a variety of conditions. At the same time, all of these studies failed to see any association between bad outcomes and fluoridation done correctly.”

And

” . . those people who were suspicious of putting fluoride in the water did what people who are suspicious of public health interventions often do: they heard of some bad outcome of ingesting fluoride (which is a compound made up of fluorine, the chemical element), amplified it, exaggerated it and showed it as the ultimate example of what fluoride consumption at any concentration can do to a person.”

He compares this to “the shenanigans of the anti-vaccine crowd” and concludes that:

“…just like we had to do in the late 1990s with the Wakefield Fraud “study” that was not a study, here we go fighting a new fight against misinformation…”

He concludes this because:

“In consultation with friends and colleagues, we found a lot to be worried about in the epidemiological design of the study and the biostatistical analysis of the resulting data… And, of course, of the conclusions reached by the authors and the press (with some help from the authors). “

Some epidemiological concerns

In his second article, The Hijacking of Fluorine 18.998, Part Two, Dr. Najera expresses his epidemiological concerns about the research. These include:

1: Unwarranted exclusion of some mother-child pairs:

“For example, some were excluded because they did not drink tap water or lived outside a water treatment zone. Wouldn’t you want to know if not drinking tap water or living outside a water treatment zone led to children with normal-to-high IQs compared to the others?

This raised flags with me because I don’t exclude someone from an outbreak investigation if they don’t have a desired exposure. In fact, I want to know if someone who is not exposed to something is less likely to develop the disease or have the condition I’m studying. It would be like saying that I don’t want women who live in air-conditioned apartments in a city included in a study on Zika because they are not likely to have been exposed to mosquitoes like women living in huts in the jungle.”

2: Overlap of groups:

“In the end, they had 369 mother-child pairs with mean urine fluoride (MUF) measurements, IQ measurements and water fluoride data and 400 mother-child pairs with fluoride intake and IQ measurements. But that’s 769 pairs when 610 children were originally considered? Yes, there is some overlap between the two groups. No big deal if they do their biostats right. (Spoiler alert for Part Three: They didn’t.)”

3: Urinary fluoride data questionable:

“They then used data on mean urine fluoride concentrations from spot (one-time) urine samples taken at different points in the mothers’ pregnancies, and they only accepted those who had been tested throughout (i.e. didn’t miss a test). The problem with this is that the standard to really know how much fluoride someone is exposed to — by testing their urine — is a 24-hour collection of urine. In that test, you have someone collect their urine for 24 hours and then we measure the fluoride (or a lot of other chemicals) in that sample. This is because urine concentrations of chemicals vary throughout the day. If you drink a lot of fluoridated water in the morning, then your urine is likely to have higher concentrations shortly thereafter than in the evening, when you’ve been drinking bottled water without fluoride. Or, if you worked out in the morning and drank energy drinks but stuck to only tap water in the evening, your urine fluoride will be different.”

Other scientific commenters have also been critical of the urinary fluoride data.  Dr F. Perry Wilson suggests that blood plasm fluoride would have been a far better indicator of fluoride intake (see More expert comments on the Canadian fluoride-IQ paper).

The World Health Organisation’s (WHO) recommendations on the monitoring total fluoride intake for populations also stress the need for 24-hour collection and warn that “urinary fluoride excretion is not suitable for predicting fluoride intake for individuals.” [WHO’s emphasis] (see Anti-fluoridation campaigner, Stan Litras, misrepresents WHO).

WHO recommends it only for monitoring fluoride intake of groups of people because of the large effects of individual diets (see Basic Methods for Assessment of Renal Fluoride Excretion in Community Prevention Programmes for Oral Health). But in this Canadian study, urinary fluoride values were used to estimate individual intake of fluoride.

4: Fluoride intake assessed via an unvalidated survey:

“This means that it is hard to know if the survey really measures what it is supposed to measure. Still, they used it, and it leaves the study wide open to recall bias, something you want to minimize as much as possible. And they would have minimized it if they used it a more valid survey, or a prospective design to their study.

First, what is a prospective design? Well, this is when you take a group of women and sign them up for the study, then you carefully measure their fluoride intake with more validated laboratory assays and questionnaires, and then you follow their children and measure their IQ periodically. You don’t do it all retrospectively with already collected data. But, sometimes, what you have is what you have.

Next, what is recall bias? Recall bias is this interesting phenomenon we see when we rely on people telling us their story in order to ascertain risks and outcomes of exposures. We epidemiologists have noticed that people who have bad outcomes tend to be more likely to remember significant exposures. For example, parents of children with birth defects are more likely to remember things like exposures to chemicals or a history of disease in the family. While parents of typical children don’t recall similar exposures as much because, well, they aren’t looking to connect any dots.

(You see this all the time in anti-vaccine circles, where parents of autistic children are more likely to recall bad reactions to vaccines in their children.)”

Dr. Najera also finds this methodology strange because “they multiplied the intake of certain drinks by some factors in order to estimate fluoride intake:”

“This complicates things because, as you saw above, they excluded women who were not in places where the water was being treated and women who didn’t consume tap water. But, come on, have you ever met someone who never consumed tap water? Do we not use tap water to cook foods all the time? What about that fluoride intake? And why just multiply for fluoride in beverages and not, say, that delicious Canadian cheese soup I’ve heard good things about?”

5: Problems with IQ testing of children:

“I’ve asked some friends of mine who are experts in childhood development, and they are skeptical of accurate measurements of IQ in children because children develop at different rates depending on a variety of variables. You may have seen this when you look at a classroom or a school play. Children are on a big spectrum of development, with milestones being really more like average moments.”

6: Sample not representative:

“The sample used in this study is not at all representative of all mothers and their children in Canada, not even close. As we saw in the paper, many women were left out of the study for a variety of reasons, and mother-child pairs were also excluded. I want to believe that there were good reasons for this, but I could not find them in the paper. The authors do mention that they wanted to look only at mothers consuming fluoride, but why not include those who were not expected or outright did not consume fluoride in order to really compare two populations of interest?”

Dr. Najera finishes with a general comment about the way other studies in the scientific literature are used to provide credibility to the findings;

“Finally, the authors mention other studies — some with rats, other purely environmental — where there is some association between fluoride intake and lowered IQ or some sort of negative impact to neurodevelopmental delay. The thing is, public health agencies around the whole world have been looking at these claims and not finding them to be true within their populations. “

I also find the practice concerning, especially as it is relatively common. I think it indicates confirmation bias – the authors making citations that they think support their findings (and purposely refraining from citing studies that don’t). I find this practice disingenuous because it never qualifies the citations with any reference to the applicability to the real-life situation of community water fluoridation. It never points out the high fluoride concentrations used in animal studies or the fact that many research articles on fluoride and child IQ have involved populations in areas of endemic fluorosis where health problems abound.

Dr. Najera is planning a third article discussing the biostatistical issues with the research – a very important issue I have commented on in previous posts. I look forward to it and will do a post on it in due course.

Similar articles

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:

Similar articles

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.

Similar articles

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.

Similar articles

Preempting the annual misrepresentation of NZ dental health data by anti-fluoride activists

Dental therapist Heather Dalton examines an Avondale College student in Auckland in 2010. Image credit: Te Ara: The Encyclopedia of NZ.

The latest NZ school dental service data again confirms that community water fluoridation is effective.  The data show benefits of up to about 30% improvement in oral health. But, anti-fluoride activists will, once again,  reject this evidence and instead cherry-pick the data to support their claims.

The NZ Ministry of Health (MoH) has posted the latest summary of child dental health collected by the dental health service. So it is time for local anti-fluoride activists to indulge in their annual activity of cherry-picking and misrepresentation to claim the data “proves” community water fluoridation (CWF) is ineffective (see my comment on last year’s misrepresentation – Anti-fluoridationists misrepresent New Zealand dental data – an annual event).

I haven’t seen this year’s expected press release from Fluoride Free NZ. I may have missed it or perhaps they haven’t got their A into G yet (although there is a bit of notice on their Facebook page). Nevertheless, I will post here my annual analysis of the data.

My comments are much the same as last year – the data has not really changed. But first an explanation of how the data should be used

Nature of the MoH dental health data

The published spreadsheets are simply records of dental health (% caries free and mean Decayed, Missing and Filled Teeth (DMFT and dmft) for 5-year-olds and year 8  children. There has been no selection of children to give representative data. Distortion due to ethnic and socioeconomic factors has not been taken into account.

Data are presented for all children – (Total), Maori, Pacific Island and “Other.” I have previously explained that the Total data is distorted by ethnic factors – different ethnic groups have differences in oral health, irrespective of fluoridation. In particular, the predominance of Pacific Island children in fluoridated areas distort the “Total” data – 85% live in fluoridated areas. Pacific Island children comprise about 15.1% of children in fluoridated areas but only about 3.2% of children in non-fluoridated areas.

Because Pacific Island children generally have poorer health they increase the value of dmft/DMFT and lower the value of caries-free % in the fluoridated areas in the Total figures. Therefore the “Other” figures are more reliable than the “Total” figures for interpretation.

The 2017 data

You can download the two spreadsheets, and the spreadsheets for earlier years, from the MoH website – Age 5 and Year 8 oral health data from the Community Oral Health Service). I will just give the overall New Zealand data for Māori and “Other” (this is all except Māori and Pacific Island).

As explained above the “Total” data is misleading because of ethnic effects and the data for Pacific Island is poor because only a small number resided in non-fluoridated areas.

5-Year Old Children

Clearly, the overall data suggest a benefit of fluoridation to Maōri and “other” children – about 14% for “Other” and 25% for Māori children (using the data for mean dmft).

Year 8 Children


Again the data suggests that fluoridation has been beneficial to Māori and “Other” children. The DMFT data suggest a benefit of about 30.5% for Māori and 26% for “Other” children.  Even the %Caries free data indicates benefits of about 16% and 11% for Māori and “Other” children respectively.

Changes over time

It’s worth considering more than one year. This overcomes, to some extent, variations in the data. It may also be helpful in assessing if the effectiveness of CWF is changing.

However, there is a proviso. Let’s not forget this is simply raw data from the school dental service. While I have corrected for ethnic differences I have no way of correcting for other differences. Socioeconomic effects may change over time. Another important factor is that, at least in some regions, dental health authorities are targeting children form non-fluoridated areas with extra treatments like fluoride tooth varnishes. Ideally, a controlled experiment would take all these factors into account.

I will just take one example – the DMFT data for year 8 children.

The table shows the mean values of %Caries free and DMFT of year 8 children over the periods 2005-2017 and 2013-2017.

Year 8 Children Māori “Other”

%Caries Free

Mean 2005-2017 24.2 13.4
Mean 2013-2017 15.6 8.8

MDFT

Mean 2005-2017 31.3 24.7
Mean 2013-2017 30.1 22.2

This data shows that the oral health of both Māori and “Other” children have improved over time irrespective fluoridation. But there is still a difference between fluoidated and unfluodiated areas indicating fluoridation is having a benefit over and above other factors contributiong to oral health improvement.

The differences due to fluoridation seem to be diminishing. However, my comments above are relevant here. This could be due to extra fluoride treatments targeting children from non-fluoridated areas.

It’s obviously a factor for health authorities to consider but limitations in this data should be kept in mind and other sources of information also considered.

Conclusions

Once again the MoH school dental service data show benefits from CWF. But don’t expect anti-fluoride activists to accept this. I expect they will indulge in their usual cherry-picking of the data to confirm their biases.

Fluoridation: Another study shows stopping fluoridation bad for child tooth decay

Stopping community water fluoridation in Alaska’s capital city, Juneau, caused an increase in child tooth decay

In the last week, Windsor in Ontario, Canada, voted to reinstate community water fluoridation (CWF) 5 years after it was stopped because of opposition. This time the City Council was swayed by the Windsor-Essex County Health Unit’s Oral Health 2018 Report which found the percentage of children with tooth decay or requiring urgent care increased by 51 per cent since fluoridation had stopped.

Now a new study reports similar increases in child tooth decay after stopping CWF in the Alaskan capital, Juneau. This paper reports the study results for Juneau:

Meyer, J., Maragaritis, V., & Mendelshon, A. (2018). Consequences of community water fluoridation cessation for Medicaid-eligible children and adolescents in Juneau, Alaska. BMC Oral Health, 18:215

Juneau – an ideal community for the study

Juneau maintains all the modern conveniences and standards expected of a capital city but has little in-and-out migration or travel from neighboring countries as it is accessible only by plane or sea. This reduces confounding effects due to population changes, only about 0.006% per year during the study period.

Use of fluoridated toothpaste is widespread and CWF was available to 96% of residents before it was stopped in January 2007.

The researchers compared child oral health data in 2003 (when children were exposed to optimum levels of fluoride: 0.7 – 1.2 mg/L) with that in 2012, 6 years after CWF ceased. During those six years, exposure to fluoride was suboptimum: <0.065 mg/L.

The data used for the study was from Medicaid dental claims records. This means the study population was made up of residents living at near poverty conditions. This limited confounding effects from higher-income groups.

Cessation of CWF resulted in increased child tooth decay

The findings were clear and statistically significant. The number of caries-related dental procedures increased after cessation of CWF.

For all children and adolescents (ages 0 – 18 years) the number of procedures increased by 16%. But binary logistic results indicated “the odds of a child or adolescent undergoing a dental caries procedure in 2003 was 25.2% less than that of a child or adolescent in the suboptimal CWF group.”

The effects of CWF were even greater for children aged 0 – 6 years who had never experienced the advantages of exposure optimum fluoride levels. The number of caries-related dental procedures in this group increased by 63%. However,  binary logistic results indicated “the odds of undergoing dental caries procedures under optimal CWF conditions was 51% less than that for a child of the same age in 2012 under suboptimal conditions.”

CWF cessation increased dental treatment costs

The researchers obtained dental costs from the Medicaid dental claims records so were able to make estimates of the effects of CWF on the financial costs to the community. After adjusting for inflation this data showed that the increased annual cost per person of ages 0 – 18 years due toi cessation of CWF increased by $162, a 47% increase. The corresponding increase for children 0 – 6 years was %303, a 111% increase.

Conclusions

While this study had several advantages over similar studies because of reduced confounding effects due to migration and socioeconomic factors this may also be seen as a limitation when trying o extend to findings to more socially heterogeneous communities. However the authors conclude it does provide stong evidence supporting:

“current evidence that even in modern conditions with widely available fluoride toothpaste, rinses, and professionally applied prophylaxis, CWF is associated with population benefits, including cost effectiveness and caries prevention.”

They also conclude from their results that:

“CWF cessation promoted a marked increase in the number of caries-related procedures and treatment costs for Medicaid-eligible children and adolescents aged 0–18 years. Additionally, the results indicated that children in the younger age group cohorts underwent more dental caries procedures than the older age group cohorts, who had benefited from early childhood exposure to optimal CWF.”

Similar articles

 

Protection of teeth by fluoride confirmed – yet again

 

Fluoride protects teeth from the attack of acid and microbes. Figure from Faidt et al., (2018)

The protective role of fluoride in teeth has been confirmed, yet again. A new study nicely demonstrates how incorporation of even a small amount of fluoride into the surface layer of teeth protects them from the acid attack which leads to tooth decay.

Researchers measured the ablation, or loss of surface material from hydroxyapatite before fluoridation and after fluoridation. It showed a clear difference due to inhibition of ablation by fluoride.

The research findings are published in:

Faidt, T., Friedrichs, A., Grandthyll, S., Spengler, C., Jacobs, K., & Müller, F. (2018). Effect of fluoride treatment on the acid-resistance of hydroxyapatite. Langmuir

Measuring ablation

Samples were etched with a sodium acetate buffer at pH 4.5 which simulated the effect of an acid attack on teeth resulting from the formation of acid when sugars are microbiologically decomposed in the mouth. The degree of ablation was measured using atomic force microscopy (AFM). Part of the sample surface was coated with a gold layer to prevent acid attack and give a reference surface.

Fluoridated surfaces, submerged for five minutes in a sodium acetate buffer at ph 6.0 cotnaining 500 mg/L of sodim fluoride, were compared with unfluoridated surfaces.

Results

Interestingly, the AFM height images showed there were two different areas of the hydroxyapatite surface when it came to ablation – a fast etching area and a slow etching area. The authors attributed this to the different orientations of crystallites in the hydroxyapatite sample. The image below is for an unfluoridated sample

Ablation of  fluoridated samples was quite different – no ablation occurred until after 330 seconds – the image below is for a fluoridated sample

The paper summarises the results for the fluoridated and unfluoridated surfaces and the different ablation rates due to crystallite orientation in this figure:

The crystallites that etched slowly (Z2) in the unfluoridated sample did not etch at all in the fluoridated sample. The more rapidly etching crystallites (Z1) did etch in the fluoridated sample but only after a delay.

The authors concluded that some of the fluoride in the surface layer of the fluoridated samples could eventually be removed by soaking in the acid buffer – but only after a delay. This was confirmed by an analysis of the surface concentrations of Ca, P, O and F using X-ray photoelectron spectroscopy (XPS) – see below:

Thickness of the fluoridated surface layer

The authors recall:

“In a former study, we revealed that the thickness of the HAp layer that can be loaded with fluoride is in the range of only a few nanometers (24, 25), even if loaded under optimal conditions (25). “

So – a very thin layer. One that some anti-fluoridation commenters claimed insufficient to give any protection. As the authors say

” the question arose whether such a thin layer would actually be capable of protecting the surface against acid attacks. “

But, their results definitely show that this thin layer does offer protection. I am sure critics will quickly point to the fact that the experimental study showed the removal of some of the fluoride after about 400 seconds. But this removal should be seen in the light of the dynamic system in the oral cavity where the pH of saliva is changing, dropping due to sugar decomposition and then rising again. The presence of fluoride, together with phosphate and calcium in saliva also leads to repair of areas where acid attack has occurred.

Conclusions

This experimental work confirms the protective role of fluoride in saliva for existing teeth – despite the fact that the fluoridated layer may be extremely thin – of the order of a few nanometers. While some of the fluoride in the surface layers is eventually removed the presence of fluoride in saliva helps replenish these layers and repair areas of acid attack.

The authors conclude their results provide:

“evidence that already thin and low concentrated fluoridated layers have a large effect on the acid resistance of HAp [hydroxyapatite]”

They combine these finding with results from a previous study of theirs showing fluoridation reduced adhesion forces of bacteria on hydroxyapatite (HAp) to finally conclude:

“the caries-preventive effect of fluoride is an interplay of at least two mechanisms: a reduction of the solubility and a reduction of the bacterial adhesion force.”

Hence the figure at the top of this article.

Similar articles

 

 

Fluoridation and ADHD: A new round of statistical straw clutching

“To clutch at straws – the act of reaching for a solution no matter how irrational or inconsequential.” Source: Advanced Vocabulary for English Language Learners

Anti-fluoridation activists are promoting a number of new scientific papers they argue support their campaigns. But one has only to critically read these papers to see they are clutching at straws. Their promotion relies on an unsophisticated understanding of statistics and confirmation bias.

I will look at one paper here – that of Bashash et al., (2018) which reports an association between maternal prenatal urinary fluoride and prevalence of child ADHD.

The paper is:

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.

I discussed an earlier paper  by these authors – Bashash et al., (2016) which reported an association between maternal neonatal IQ fluoride and child IQ – (also heavily promoted by anti-fluoride activists) in a number of articles:

Promotion of the new paper by anti-fluoride activists suffers from the same problems I pointed out for their promotion of the earlier paper. In particular it ignores the fact that the reported relationships (between maternal neonatal urinary fluoride and cognitive measure for children in Bashash et al., 2016, and prevalence of child  attention deficit hyperactivity disorder – ADHD – in Bashash et al., 2018) were very weak and explain only a very small amount of the variation. This raises the possibility that the reported weak relationships would disappear if significant risk-modifying factors were included in the statistical analyses.

Bashash, et al., (2018)

Whereas the earlier paper considered measures of cognitive deficits in the children the current paper considers various measurements related to ADHD prevalence among the children. These include parent rating scales (CRS-R). Three were ADHD-related scales from the Diagnostic and Statistical Manual of Mental Disorders (DSM) (Inattention Index, Hyperactivity-Impulsive Index and Total Index [inattentive and hyperactivity-impulse behaviours combined]). They also include several other indexes related to ADHD.

A number of computer-assisted indexes (CPT-II) were also determined.

Most indices were not significantly associated with maternal prenatal urinary fluoride. However, the authors reported statistically significant (p<0.05) relationships for indices of Cognitive Problems + Inattention, ADHD Index, DSM Inattention and DSM ADHD Total.

The data and the relationships were provided in graphical form – see figure below – taken from their Figure 2:

There is obviously a wide scatter of data points indicating that the observed relationships, although statistically significant, explain only a small part of the variation in the indices.

So, just how good are the relationships reported by Bashash et al., (2018) in explaining the variation in these ADHD-related indices? I checked this out by digitally extracting the data from the figures and using linear regression analysis.

Index

% Variance explained

Cognitive problems + Inattention 2.9%
ADHD Index 3.1%
DSM Inattention 3.6%
DSM ADHD Total 3.2%

In fact, these relationships are extremely weak – explaining only a few per cent of the observed variation in the ADHD related indices. This repeats the situation for the cognition-related indices reported on the Bashash et al., (2016) paper (see Maternal urinary fluoride/IQ study – an update).

The fact these relationships were so weak has two consequences:

  1. Drawing any conclusions that maternal neonatal fluoride intake influences child ADHD prevalence is not justified. There are obviously much more important factors involved that have not been considered in the statistical analysis.
  2. Inclusion of relevant risk-modifying factors in the statistical analysis will possibly remove any statistical significance of the relationship with maternal urinary fluoride.

Credible risk-modifying factors not considered

Bashash et al., (2108) do list a number of possible confounding factors they considered. These did not markedly influence their results. however, other important factors were not included.

Nutrition is an important factor. Malin et al., (2108) reported a signficant effect of nutrition on cognitive indices for a subsample of the mother-child pairs in this study (see A more convincing take on prenatal maternal dietary effects on child IQ).

Their statistical analyses show that nutrition could explain over 11% of the variation in child cognitive indices indicating that nutrition should have been included as a possible risk-modifying factor in the statistical analyses of Bashash et al., (2016) and Bashash et al., (2018). I can appreciate that nutrition data was not available for all the mother-child pairs considered in the Bashash et al., papers. However, I look forward to a new statistical analysis of the subset used by Malin et al., (2108) which includes prenatal maternal urinary fluoride as a risk-modifying factor and tests for relationships with child ADHD prevalence.

Could the reported weak relationship disappear?

Possibly. After all, it is very weak.

The problem is that urinary fluoride data could simply be a proxy for a more important risk-modifying factor. That is, urinary fluoride could be related to other risk modifying factors (eg. nutrition) so that the relationship with urinary fluoride could disappear when these other factors are included.

I illustrated this for a earlier reported relationship of child ADHD prevalence with extent of fluoridation in US states (see Perrott 2017 – Fluoridation and attention deficit hyperactivity disorder – a critique of Malin and Till (2015)). In  that case the relationship was much better than those reported by Bashash et al., (2016) and Bashash et al., (2018) – explaining 24%, 22% and 31% of the variance in ADHD prevalence for the years 2003, 2007 and 2011 respectively. The relationships are illustrated in their figure:

Relationships between water fluoridation (%) and child ADHD prevalence for 20013 (red triangles), 2007 (blue diamonds) and 2011 (purple circles). Malin & Till (2105)

Yet, when other risk-modifying factors (particularly mean state elevation) not considered by Malin & Till (2015) were included in the regression analyses there was no statistically significant influence from fluoridation prevalence. In this case fluoridation prevalence was related to altitude and was simply acting as a proxy for altitude in the Malin & Till (2015) regression.

Conclusion

As the authors admit, this study:

“was not initially designed to study fluoride exposure and so we are missing some aspects of fluoride exposure assessments (e.g., detailed assessments of diet, water, etc.).”

However, they do say these “are now underway” so I look forward with interest to the publication of a more complete statistical analysis in the future.

There are other problems with the data (for example the paucity and nature of the urinary fluoride measurements) and these are the sort of issues inevitably confronting researchers wishing to explore existing data rather than design experimental protocols at the beginning.

Readers should therefore always be hesitant in their interpretations of the results and the credibility or faith that they put on the conclusions of such studies. The attitude should be: “that is interesting – now let’s design an experiment to test these hypothetical conclusions.”

The problem is confirmation bias – the willingness to give more credibility to the findings than is warranted. Scientists are only human and easily succumb to such biases in interpreting their own work. But this is even more true of political activists.

The reported relationships are weak. Important risk-modifying factors were probably not included in the statistical analyses. The observed relationships may simply mean that urinary fluoride is acting as a proxy for a more important risk-modifying factor (like nutrition) and the weak relationship may disappear when these are considered.

So scientific assessment of this study will be extremely hesitant – interpreting it, at best, as indicating need for more work and better designed research protocols.

But, of course, political activists will lap it up. It confirms their biases. Political activist organisations like the Fluoride Action Network are heavily promoting this paper – as they did with the earlier Bashash et al., (2016) paper.

But they are simply clutching at straws – as they often are when using science (or more correctly  misrepresenting and distorting the science) to support their political demands.

Similar articles