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

Image credit: BuildGreatMinds.Com

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

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

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

The study

The paper we are discussing is:

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

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

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

Was the reported association statistically significant?

Mary asserts:

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

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

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

For Fig. 2:

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

For Fig 3A:

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

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

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

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

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

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

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

The elephant in the room – unexplained variance

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

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

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

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

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

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

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

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

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

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

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

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

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

The misrepresentation

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

Paul Connett claimed:

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

But this would only be true if the model used (the best-fit line) truly represented all the data. A simple glance at Fig 2 in the slide above shows that any prediction from that data with such a large scatter is not going to be “highly statistically significant.” Instead of relying on the CIs for the coefficient or slope of the line, Connett should have paid attention to the standard error for estimates from the data as a whole given in the Regression statistics of the Summary output. – For Fig. 2, this is 12.9 IQ points. This would have produced an estimate of “5-6 ± 26 IQ points which is not statistically significantly different to zero IQ points,”  as I described in my article

Confusion over confidence intervals

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

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

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

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

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

Given the model described by Bashash et al., (2017) explained only 3% of the IQ variance, while the standard error of the estimate was relatively large, it is misleading to suggest any “effect size” predicted by that model would be “highly significant” as this ignores the true variability in the reported data. When this is considered the effect size (and 95% CIs) is actually “5-6 ± 26 IQ points which is not statistically significantly different to zero IQ points,”

Remaining issues

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

So, to conclude, Mary Byrne is correct to say that the model derived by Bashash et al., (2017) predicts that an increase of “fluoride level in urine of 1 mg/L could result in a loss of 5-6 IQ points” – on average. But she is wrong to say this prediction is relevant to New Zealand, or anywhere else, because when we consider the data as a whole that loss is “5-6 ± 26 IQ points.”

I look forward to Mary’s response.

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Anti-fluoride group coordinator responds to my article

Image credit: Debate. The science of communication.

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

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

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

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

By Mary Byrne, National coordinator Fluoride Free New Zealand.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Where could you get a nerve agent in Salisbury?

Conspiracy theorists, especially those in the mainstream media and political spheres, seem to have no real imagination these days. Just look at how they have responded to news of the poisoning of Sergei Skripal, his daughter Yulia and police Sergeant Nick Bailey in Salisbury, UK, last week.

Isn’t it just too easy to claim “Putin did it” these days? Yes, Skripal is a Russian and former spy for the UK MI6 who ended up in the UK as part of a spy exchange. And yes, there is a compulsion for western media and politicians to demonise the Russian Federation and their president every chance they get. But isn’t that particular conspiracy theory rather thoughtless – the conspiracy theory you automatically go with when you haven’t the energy or skills to actually look for something in the way of evidence.

As we would say in New Zealand – a “Clayton’s conspiracy theory.” The conspiracy theory you use when you don’t have a conspiracy theory! (For the uninformed, this comes from an old advertisement for alcohol-free drinks).

Why can’t the news media, seeing they are only speculating at this stage anyway, look at little closer to home for the source of the nerve agent used in the poisonings?

Only a short distance from Salisbury (8.1 km if you are a crow or an 18 min drive is Porton Down. This is the site of the UK Ministry of Defence’s Defence Science and Technology Laboratory – known for over 100 years as one of the UK’s most secretive and controversial military research facilities. And well-known for their secretive work on chemical and biological weapons.

The map above shows how quickly one would get to Porton Down from Salisbury and back

Even closer (only a 15 min drive, or 6 km for crows) is the Defence Chemical, Biological, Radiological and Nuclear Centre (the Defence CBRN Centre or DCBRNC for short) at Winterbourne Gunner in Wiltshire. It is a tri-service site, with the Royal Air Force being the lead service. The centre is responsible for all training issues relating to chemical, biological, radiological and nuclear (CBRN) defence and warfare for the UK’s armed forces.

The map below shows how short the trip is to this facility from Salisbury.

Porton Down has barely been mentioned in the media reports of this poisoning – except more recently because experts from Porton Down are participating in the inquiry. But it seems to me rather fanciful that Russophobe conspiracy theorist Luke Harding should rave on about a weapons lab in Moscow that might not even exist as a possible source of the nerve agent and ignore this other source much, much, closer to Salisbury (see Russia’s Lab X: poison factory that helped silence Soviets’ critics).

Hopefully, the current inquiry will be open and come to a satisfactory conclusion (unlike the Litvinenko inquiry) and, given the murky world of spies and ex-spies, nothing would surprise me.

However, I do wish our mainstream media could surprise me once in a while by refusing to follow the obligatory narratives and perhaps do some speculating using real evidence.

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The first casualty . .

Independent reporter Vanessa Beeley raises questions about the White Helmets and their propaganda videos.

It’s an old truism – the first casualty in war is the truth. But this has become even truer over the years as psychological propaganda has become more sophisticated. And the mainstream news media is playing a more active role in hiding the truth and promoting lies to support wars.

Just look at the current political and media propaganda around the war in Syria, and particularly around the battle in east Ghouta. You would think the UN politicians and the people who run our media would have a bit more of a conscience. Yet, no. They are repeating the same stories and lies they fed to us during the battle in east Aleppo just over a year ago.

Remember all those hospitals and schools that were allegedly bombed by the Syrians and Russians. Talk of “barrel bombs,” chemical weapons and Assad’s war against his people. Claims that civilians would not leave the battle area because they were scared of reprisals from government forces and, anyway, it was a form of ethnic cleansing – transferring people away from their homes into areas they did not know.

Yet the reality was that when the terrorist groups were on the verge of defeat over 90,000 civilians did leave and came under government protection and aid. Today several hundred thousand former residents of Aleppo are returning to their homes as reconstruction proceeds.

Yes, as part of their surrender the “rebel”/terrorist armed groups and their families were relocated to Idlib province. That is simply a sane way of protecting civilians who had formerly been used as human shields by the terrorists – and shot by terrorist snipers when they intended to leave.

I can only hope that one day these “rebels”/terrorist will get their just deserts as Idlib is liberated. But sadly, some of these terrorists will have made their way to Afghanistan or Libya – or to Europe where they will wait for the opportunity to renew their battle, even by carrying out terrorist acts in their new countries.

Now it is Ghouta’s turn

Every night I watch Al Jazeera as it presents its substantial coverage of the battle for Ghouta. But all their news sources used are local (in Ghouta) “activists” and “independent” reporters. These sources are simply fighters and propagandists in the “rebel”/terrorist forces.

One of their propaganda arms is the “White Helmets.” They are a well-funded (by countries like the UK, Holland, and USA) civil defense and propaganda group for Al Qaeda. Yet they fool a lot of people.

Nevertheless, their video propaganda has a sameness about it which sticks out as propaganda – or at least professionally-managed reporting and sometimes as fake acting. See the video above for some analysis of this propaganda.

Reporters on Al Jazeera have been telling me that civilians refuse to use the humanitarian corridors to exit the area because the Syrian Army has snipers on the exits to kill any refugees. And, anyway, the people in Ghuota do not want to be forced to leave their homes. But, from other sources, I hear that the snipers are from the “rebel”/terrorist groups. These groups enforce a curfew during the hours the humanitarian corridor is open and civilians have been banned from leaving.  A humanitarian aid convoy that did manage to get into the area recently had to turn back because it was shelled by “rebel”/terrorist activists.

Two children have escaped

Yet there has been an escape – two young children who managed to get out, although the fate of their parents who were with them is not known. And the children reported that there were hundreds who were attempting the escape but were unsuccessful

But I didn’t learn this from Al Jazeera – and there is no excuse for that because videos of the escape and interviews with the children were available and screened by alternative media sources.

RT also screened these videos and provided some background to what is happening in Ghuota.

But people keep telling me I should never watch RT – it is just propaganda for the Kremlin. These people seem to keep insisting I wear blinkers or blinders to protect me from the truth. And that I should accept only media reports from “official” media like Al Jazeera.

Yes, the first casualty of war is the truth – we all accept that. Yet most of seem to fall victim the sophisticated propaganda being used to serve up these lies.

And worse, some people seem to be unthinkingly accepting demands from the establishment to cover our eyes and block our ears when it comes to information from war scenes. Even worse, these people attempt to demonise and attack anyone who refuses to go along with such self-imposed censorship.

I have been called one of “Putin’s useful idiots” for daring to mention RT. But perhaps the more relevant term when it comes to the Syrian war and the comments of politicians and mainstream media reporters is one of “Al Qaeda’s useful idiots.”

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Paul Connett’s misrepresentation of maternal F exposure study debunked

Title slide for Paul Connett’s presentation to parliament

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

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

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

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

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

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

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

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

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

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

This is what he says:

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

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

The small amount of variance explained

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

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

But he claims that this:

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

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

Notice his assumptions:

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

Those are huge assumptions. And they are wrong.

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

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

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

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

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

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

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

The size of the IQ effect

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

For example, Connett declares:

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

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

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

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

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

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

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

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

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

Comparing maternal urinary F levels to other countries

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

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

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

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


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

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

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

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

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February ’18 – NZ blogs sitemeter ranking

Image credit: LavaLux Web Studio

I notice a few regulars no longer allow public access to the site counters. This may happen accidentally when the blog format is altered. If your blog is unexpectedly missing please check this out. Send me the URL for your site meter and I can correct the information in the database.

Sitemeter is no longer working so the total number of NZ blogs in this list has been drastically reduced. I recommend anyone with Sitemeter consider transferring to one of the other meters. See  NZ Blog Rankings FAQ.

This list is composed automatically from the data in the various site meters used. If you feel the data in this list is wrong could you check to make sure the problem is not with your own site meter? I am of course happy to correct any mistakes that occur in the automatic transfer of data to this list but cannot be responsible for the site meters themselves. They do play up.

Every month I get queries from people wanting their own blog included. I encourage and am happy to respond to queries but have prepared a list of frequently asked questions (FAQs) people can check out. Have a look at NZ Blog Rankings FAQ. This is particularly helpful to those wondering how to set up sitemeters. Please note, the system is automatic and relies on blogs having sitemeters which allow public access to the stats.

Here are the rankings of New Zealand blogs with publicly available statistics for February 2018. Ranking is by visit numbers. I have listed the blogs in the table below, together with monthly visits and page view numbers. Meanwhile, I am still keen to hear of any other blogs with publicly available sitemeter or visitor stats that I have missed. Contact me if you know of any or wish help adding publicly available stats to your bog.

You can see data for previous months at Blog Ranks

Subscribe to NZ Blog Rankings Subscribe to NZ blog rankings by Email Find out how to get Subscription & email updates Continue reading

Anti-fluoride activist commits “Death by PowerPoint”

We have all sat through boring, and counterproductive, PowerPoint presentations. Boring because the presenter breaks all the rule relevant to the preparation of visual displays. And counterproductive because, in the end, the audience does not remember any of the information the presenter attempts to convey.

David JP Phillips gives some relevant advice on PowerPoint preparation in the video above and similar advice is available online.  All this advice is very helpful for anyone preparing a presentation – although constant reminders of the points and frequent practice or experience are needed to take it on board. The PowerPoint programme seems to tempt even the best presenter to make fundamental mistakes which can reduce the effectiveness of their visual material.

Learning from bad examples

Examples of bad PowerPoint presentations are ubiquitous – but I urge readers to critically consider this recent example. The PowerPoint presentation the anti-fluoride campaigner, Paul Connett, prepared for his recent presentation to a meeting in the NZ Parliament buildings. Fluoride Free NZ (FFNZ) has provided a link to Connett’s presentation – Prof Paul Connett Power Point Presentation to Parliament 22nd Feb 2018.

It has 155 slides for presentation with another 24 extra slides to be held in reserve if he had time. Just the sheer number of slides, let alone the extreme detail on individual slides, violates a basic presentation rule to start with.

Well, I say “prepared” but the recent Fluoride Free NZ newsletter describes it as “The Power Point presentation that Prof Connett showed” to the MPs meeting. I find that hard to believe as only three MPs turned up to the meeting. In such situations, a reasonable person gives up on a detailed presentation and resorts to having a chat with the people who did turn up.

An example of what not to do in a PowerPoint presentation – source  Prof Paul Connett Power Point Presentation to Parliament 22nd Feb 2018

I urge interested readers to download it and have a look. Critique it from the point of view of the advice given by David JP Phillips above. It really is a bad presentation and I don’t believe any objective person could have taken anything meaningful from it. Treat this as a learning exercise.

Mind you, these presentations are usually simply “singing to the choir” – presented to true believers. All indications are that the three MPs who attended that meeting can be described that way. Other MPs were probably well aware that Connett’s presentations given on his recent speaking tour had no relevance to their work – and probably most were aware of his bias and unreliability as a source of scientific information, anyway.

Second reading of fluoridation bill

Parliament will shortly undertake the second reading of the Health (Fluoridation of Drinking Water) Amendment Bill. It is currently 15th on the order paper.  This bill does not deal with the science of fluoridation – parliament wisely leaves that to the experts who can advise them when necessary. The bill simply concerns the procedure for decision-making – specifically suggesting transferring the decision from councils to District Health Boards. The Parliamentary Health Committee has already consulted widely on this – and FFNZ and Paul Connett have had every opportunity to present their views. In fact, Paul Connett and other opponents of fluoridation gerrymandered the system to get much longer presentation times than other submitters. I guess they have plenty of experience of making submissions and know all the tricks.


Here I am simply treating Paul Connett’s PowerPoint presentation as an example of how not to use PowerPoint. Later I will probably return to his presentation and deal with specific areas where he misrepresents the science.

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Paul Connett “updates” NZ MPs about fluoride?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Anti-fluoride activists misrepresent another thyroid study

Image credit: Hypothyroidism | Natural Approach To Low Thyroid Hormone

Anti-fluoride activists closely follow the publication of results from fluoride studies and react to new scientific papers in one of the following ways:

  1. Use it to claim community water fluoridation (CWF) is harmful – even if this requires misrepresentation or distortion of the studies findings (a recent example is the prenatal fluoride/child IQ study of Bashash et al., (2017)  heavily promoted and misrepresented by Paul Connett in his current New Zealand talks).
  2. Viciously attack the study if it finds CWF beneficial and reports no harmful effects (remember their reaction to the NZ IQ-Fluoridation study of Broadbent et al., 2014).
  3. Do their best to ignore the study if it can’t be misrepresented and the media is not reporting it.

Well, now we have a very new study from Iran reporting relationships between drinking water fluoride and thyroid problems and already we can see activists launching into reaction 1.

The paper is:

Kheradpisheh, Z., Mirzaei, M., Mahvi, A. H., Mokhtari, M., Azizi, R., Fallahzadeh, H., & Ehrampoush, M. H. (2018). Impact of Drinking Water Fluoride on Human Thyroid Hormones: A Case-Control Study. Scientific Reports, 8(1), 2674.

So what did this study find? The paper itself is a little difficult to read but here is what I got from it.

No effect of drinking water fluoride on hypothyroidism

The study investigated two groups (“cases” – which had hypothyroidism and “controls” – which did not have hypothyroidism) and two drinking water fluoride concentration ranges ( 0 – 0.29 mg/L and 0.3 – 0.5 mg/L). To quote the findings:

“The frequency distribution of hypothyroidism based on the different levels of fluoride in drinking water was not significant for the cases (P = 0.13) and controls (P = 0.21) in YGA.”


“At a concentration of below 0.5 mg/L, however, it [fluoride] is not an important factor for hypothyroidism in YGA.”

YGA is the “Yazd Greater Area . . . located in the Yazd province of Iran, which uses groundwater as the primary water source.”

So, no association found between hypothyroidism and drinking water fluoride. Yet, the Irish anti-fluoride guru, Declan Waugh, reported on Facebook

“the current study Published in Nature this past week, found that fluoride in drinking water, at levels below those present in tap water in Ireland, may contribute to thyroid impairment and a worsening of thyroid conditions in adults. In other words fluoride can contributed to sub-clinical and clinical hypothyroidism”

To avoid confusion, Waugh is referring to this study. Scientific Reports is a Nature journal.

So Waugh is citing a study which reported no statistically significant effect of fluoride concentration on the prevalence of hypothyroidism to claim “that fluoride in drinking water, at levels below those present in tap water in Ireland, may contribute to thyroid impairment and a worsening of thyroid conditions in adults!”

Incidentally, I do try to follow anti-fluoride activists on social media but did not see this myself as Declan Waugh blocks me. This was brought to my attention by a colleague who was probably more concerned about Waugh’s resorting to blaming homosexuality on fluoride – see the image of Waugh’s Facebook post. Citation dredging of the sort Waugh indulges in certainly makes one susceptible to these sort of claims – especially if they “confirm” a bias.

The study is already being used by groups like UK Against Fluoridation and Fluoride Free NZ who cite the paper as evidence of harm – but seem not to understand the paper and simply quote sections dealing with thyroid hormones and not the findings on the lack of effects on hypothyroidism prevalence.

Thyroid hormones

The study did report statistically significant differences in hormone levels.

I am not an endocrinologist so will not get into a discussion of what these changes might mean. Here I will simply present them and compare them with hormone levels considered normal.

The authors investigated the T4, T3 and TSH hormones.

No significant fluoride effects occurred with the T4 hormone.

A very small effect occurred for the T3 levels in the control group (no hypothyroidism present) – the authors claimed this was statistically significant but I find that hard to believe – see Figure.

The T3 hormone levels were within the normal range (yellow area) for both groups. It’s not surprising to see different levels in the hypothyroidism cases. But drinking water fluoride has no significant effect there (p=0.19) – and I am picking the claim of a statistically significant effect (p=0.026) on the control group is wrong.

The authors claimed significant differences of TSH hormone with fluoride concentration for both the control and hypothyroidism groups – see Figure.

The TSH levels for the control group was in the normal range (yellow area) and the difference (although statistically significant, p=0.001) was extremely small. The levels for the hypothyroidism cases were outside the normal range – probably as a result of hypothyroidism. Again, I wonder at the claimed statistically significant effect (p=0.003) of fluoride for the hypothyroidism cases.

Other risk-modifying factors

While hypothyroidism prevalence was not significantly related to fluoride concentration the study reported that it was related to gender, family history of thyroid disease, water consumption, exercise, diabetes, and hypertension.

The authors note that “patients with hypothyroidism . . .  have a higher consumption of drinking water.” So this association probably means increased water consumption is a result of hypothyroidism and not a cause of it.

Some misleading comments in  the paper

The authors seem to have an anti-fluoride bias, and I wonder at studies which demonstrate statistically significant relationship for a range of risk-modifying facts, but not for fluoride, yet still concentrate on possible fluoride effects. Particularly at such low fluoride concentrations.

For example, the authors say:

“we obtained an unadjusted OR of about 1.034 (CI 95%: 0.7–1.53) for fluoride in drinking water when its concentration was less than the standard (0.2–0.5 mg/L). This finding is consistent with the Peckham study in England, which reported OR = 1.5 (CI 95%: 1.16–2) for hypothyroidism, where the maximum fluoride concentration was more than 0.7 mg/L.”

That is just special pleading – trying to “save” a non-significant result. And special pleading to compare it with the Peckham study which has been roundly criticised for not considering the effects of iodine deficiency which is known to be a major contributor to hypothyroidism.

And another case of special pleading is this:

“TSH values are higher (in both cases and controls) with higher levels of water consumption. This is consistent with an association between increased fluoride intake (due to increased water consumption) and increased TSH.”

They have turned this water consumption on its head – now ignoring that it is caused by hypothyroidism (patients drink more water) and claiming the TSH changes are a result of increased fluoride intake. This is simply an attempt to overcome the lack of any statistically significant effect due to fluoride levels in drinking water by postulating there is really an effect because of increased water consumption by hypothyroidism patients.


I do not think this is a good paper. Decent peer review could have improved it – and hopefully removed the obvious bias and special pleading of the authors.
It cannot honestly be used to claim fluoridation causes hypothyroidism – as anti-fluoride campaigners will do. However, activists will dredge out quotes from this paper which will be used to give an impression of results actually not present in the paper (fluoridation causing hypothyroidism).

So a paper which actually doesn’t support anti-fluoride claims – but can easily be misrepresented to fool the uncritical reader.

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Fake news from the White Helmets returns

The so-called White Helmets” pretends to be a non-political aid organisation but in fact is a political construct.

In its on-the-ground activity, it acts as a disaster and relief civil defense organisation for Al Quaeda fighters in Syria. Its links with these terrorist groups were shown by their operations and bases connected with Al Nusra buildings in east Aleppo – and also by the fact it transferred out of Aleppo and into Idlib province together with the terrorist fighters when that city was liberated.

A genuine, neutral, civil defense organisation would have stayed in place.

But the White Helmets also plays an important role internationally in the propaganda campaign against Syria. It campaigned for a “no-flight” zone in Syria and continually promotes an anti-government message. It is often centrally involved in anti-Syria stories about the use of chemical weapons, the bombing of hospitals, etc. The videos they disseminate are often suspect – there have been several cases where they have been exposed at manufacturing false events.

I have written about the White Helmets previously – see these articles:

The above video is timely. With the current attempts by the Syrian Arab Army and its allies to liberate Idlib province and Gouta (near Damascus), the anti-Syria propaganda has again swung into action – and the White Helmets have again become more active in this propaganda.

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