Can we trust science?

Image credit: Museum collections as research data

Studies based simply on statistically significant relationships found by mining data from large databases are a big problem in the scientific literature. Problematic because data mining, or worse data dredging, easily produces relationships that are statistically significant but meaningless. And problematic because authors wishing to confirm their biases and promote their hypotheses conveniently forget the warning that correlation is not evidence for causation and go on to promote their relationships as proof of effects. Often they seem to be successful in convincing regulators and policymakers that their serious relationships should result in regulations. Then there are the activists who don’t need convincing but will promote willingly and tiresomely these studies if they confirm their agendas.

Even random data can provide statistically significant relationships

The graphs below show the fallacy of relying only on statistically significant relationships as proof of an effect. The show linear regression result for a number of data sets. One data set is taken from a published paper – the rest use random data provided by Jim Jones in his book Regression Analysis: An Intuitive Guide.

All these regressions look “respectable.” They have low p values (less than the conventional 0.05 limit) and the R-squared values indicated they “explain” a large fraction of the data – up to 49%. But the regressions are completely meaningless for at least 7 of the 8 data sets because the data were randomly generated and have no relevance to real physical measurements.

This should be a warning that correlations reported in scientific papers may be quite meaningless.

Can you guess which of the graphs is based on real data? It is actually the graph E – published by members of a North American group currently publishing data which they claim shows community water fluoridation reduces child IQ. This was from one of their first papers where they claimed childhood ADHD was linked to fluoridation (see Malin, A. J., & Till, C. 2015. Exposure to fluoridated water and attention deficit hyperactivity disorder prevalence among children and adolescents in the United States: an ecological association).

The group used this paper to obtain funding for subsequent research. They obviously promoted this paper as showing real effects – and so have the anti-fluoride activists around the world, including the Fluoride Action Network (FAN) and its director Paul Connett.

But the claims made for this paper, and its promotion, are scientifically flawed:

1. Correlation does not mean causation. Such relationships in larger datasets often occur by chance – hell they even occur with random data as the figure above shows.
2. Yes, the authors argue there is a biologically plausible mechanism to “explain” their association. But that is merely cherry-picking to confirm a bias and there are other biologically plausible mechanisms they did not consider which would say there should not be an effect. The unfortunate problem with these sorts of arguments is that they are used to justify their findings as “proof” of an effect. To violate the warning that correlation is not causation.
3. There is the problem of correcting for cofounders or other risk-modifying factors. While acknowledging the need for future studies considering other confounders, the authors considered their choice of socio-economic factors was sufficient and their peer reviewers limited their suggestion of other confounders to lead. However, when geographic factors were included in a later analysis of the data the reported relationship disappeared. 

Confounders often not properly considered

Smith & Ebrahim (2002) discuss this problem an article  – Data dredging, bias, or confounding. They can all get you into the BMJ and the Friday papers. The title itself indicates how the poor use of statistics and unwarranted promotion of statical analyses can be used to advance scientific careers and promote bad science in the public media.

These authors say:

“it is seldom recognised how poorly the standard statistical techniques “control” for confounding, given the limited range of confounders measured in many studies and the inevitable substantial degree of measurement error in assessing the potential confounders.”

This could be a problem even for studies where a range of confounders are included in the analyses. But Malin & Till (2015) considered the barest minimum of confounders and didn’t include ones which would be considered important to ADHD prevalence. In particular, they ignored geographic factors and these were shown to be important in another study using the same dataset. Huber et al (2015) reported a statistically significant relationship of ADHD prevalence with elevation. These relationships are shown in this figure

Of course, this is merely another statistically significant relationship – not proof of a real effect and no more justified than the one reported by Malin and Till (2015). But it does show an important confounder that Malin & Till should have included in their statistical analysis.

I did my own statistical analysis using the data set of Malin & Till (2015) and Huber et al (2015) and showed (Perrott 2018) that inclusion of geographic factors showed there was no statistically significant relationship of ADHD prevalence with fluoridation as suggest by Malin & Till (2015). Their study was flawed and it should never have been used to justify funding for future research on the effect of fluoridation. Nor should it have been used by activists promoting an anti-fluoridation agenda.

But, then again, derivation of a statistically significant relationship by Malin & Till (2o15) did get them published in the journal Environmental Health which, incidentally, has sympathetic reviewers (see Some fluoride-IQ researchers seem to be taking in each other’s laundry) and an anti-fluoridation Chief Editor – Phillipe Grandjean (see Special pleading by Philippe Grandjean on fluoride). It also enabled the promotion of their research via institutional press releases, newspaper article and the continual activity of anti-fluoridation activists. Perhaps some would argue this was a good career move!

Conclusion

OK, the faults of the Malin & Till (2015) study have been revealed – even though Perrott (2018) is studiously ignored by the anti-fluoride North American group which has continued to publish similar statistically significant relationships of measures of fluoride uptake and measures of ADH or IQ.

But there are many published papers – peer-reviewed papers – which suffer from the same faults and get similar levels of promotion. They are rarely subject to proper post-publication peer-review or scientific critique. But their authors get career advancement and scientific recognition out of their publication. And the relationships are promoted as evidence for real effects in the public media.

No wonder members of the public are so often confused by the contradictory reporting, the health scares of the week, they are exposed to.

No wonder many people feel they can’t trust science.

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May ’18 – NZ blogs sitemeter ranking

Image credit: Follow Teacher Blogs for Daily Inspiration & Classroom Tips

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.

Similarly, if your blog data in this list seems out of whack, please check your site meter. Usually, the problem is that for some reason your site meter is no longer working.

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 May 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

Anti-fluoridation activists buy scientific credibility using a predatory publisher

A group of well-known anti-fluoride activists have just published some new research. Well, this is what their social media publicity will tell us.

In fact, this is not new research. It is simply the republication of a shonky paper from two years ago as a  chapter in a book produced by a predatory open access publisher.

It is a clear example of anti-fluoride activists attempting to buy scientific credibility. This book chapter cost them GBP £1400!

The “new” paper, or book chapter, anti-fluoride people will be promoting is this:

Hirzy, J. W., Connett, P., Xiang, Q., Spittle, B., & Kennedy, D. (2018). Developmental Neurotoxicity of Fluoride: A Quantitative Risk Analysis Toward Establishing a Safe Dose for Children. In J. E. McDuffie (Ed.), Neurotoxins (pp. 115–131). Rijeka: InTech.

In fact, this is simply a slight rehash of the paper published 2 years ago:

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

Almost word for word. And the authors acknowledge this at the beginning of the chapter with an introductory statement:

” This work has, in slightly different format, form and content been published in the journal Fluoride, Vol. 49(4 Pt 1):379–400, December 2016.”

I guess that saves me the job of critiquing this new version – my analysis and critique of the original paper was posted as the article  Debunking a “classic” fluoride-IQ paper by leading anti-fluoride propagandists. I also discussed the issues in other articles (see Connett & Hirzy do a shonky risk assessment for fluoride, Anti-fluoride authors indulge in data manipulation and statistical porkies, and Anti-fluoridation campaigners often use statistical significance to confirm bias).

I have also submitted for publication a more formal critique of the original Hirzy et al., paper – see Does drinking water fluoride influence IQ? A critique of Hirzy et al. (2016)and  CRITIQUE OF A RISK ANALYSIS AIMED AT ESTABLISHING A SAFE DAILY DOSE OF FLUORIDE FOR CHILDREN.

Perhaps I will just repeat this qualification given by the authors in the first paper (and repeated in the book chapter), as it does call into question the whole campaign against community water fluoridation (CWF). They say:

“However, when comparing a fluoridated area of the USA to an unfluoridated area it would be hard to discern a mean IQ difference, because of the multiple sources of fluoride intake besides drinking water (Table 5). These sources greatly reduce the contrast in total fluoride intake between fluoridated and unfluoridated areas. A very high hurdle is thus created to gaining useful information in the USA, as it was in the New Zealand study [5], via a large, long-range longitudinal epidemiological study of fluoride and IQ.”

They are, in effect, accepting that no study of CWF has shown an IQ effect and argue that such studies will never show an  effect. Because, they argue, there is only a small difference in fluoride dietary intake between children in fluoridated and unfluoridated areas.

The fact that studies show no effect of fluoidation on IQ drives their need to “explain away” these results using dubious estimates of dietary intake. However they are essentially conceding there is no point campaigning against CWF. If they want to stick with their “explaining away” argument then, if anything, they should campaigning against other forms of dietary intake and leave CWF alone.

Scientific credibility

Anti-fluoridationists often argue that they have science on their side – and many of them seem to honestly believe it. Of course, when one is singing to the choir it is easy to delude oneself. The facts are that most claims made by anti-fluoride activists do not stand up to scientific scrutiny and when they cite scientific reports they are usually misrepresenting them.

I just wish these campaigners would sit down and actually read the papers they keep touting – very often they just do not say what is claimed for them.

On the other hand a small number of scientifically dubious papers do make their way into the scientific literature and these get used as “proof” by activists. Usually these are published in poor quality journals (like “Fluoride” where Hirzy et al., originally published their paper) and this is especially true when the authors are known anti-fluoride activists.

So, a combination of misrepresentation of the scientific literature and citation of poor quality papers get churned out again and again by campaigners to give scientific credibility to their arguments.

Shonky publishers

In my article Anti-fluoridation propagandists promoting shonky “review”, I discussed the use of shonky journals by anti-fluoride activists. These are usually open access journals which charge authors for publication and have very poor or non-existent peer review standards. I quoted one commenter as describing these journals as “bottom feeders,” but they, and their publishers, are often simply described as “predatory.”

Some “peer-reviewed” journals really are “bottom-feeders.”

Predatory because these publishers scam researchers and exploit young or naive scientists, often from third world countries, who are impressed by the ease of publication and apparent distinction. An ease which is lubricated by author payments and little or no proper peer review.

Prospective authors can search lists identifying such predatory publishers and journals. So I did my own search and was not surprised to find that the IntechOpen publishers of the Hirzy et al., (2018) book chapter are on such lists. However, even a search of the IntechOpen website and their information for authors showed the signs typical of such predatory publishers. This is what IntechOpen will give you for your money (GBP – see Open Access Publishing Fees):

• £1400 gets you a book chapter;
• £4000 will get you a compact monograph, and
• £10,000 will give you a long form monograph.

So, it looks like Bill Hirzy, Paul Connett, Quanyong Xiang, Bruce Spittle, and David Kennedy had a whip around (probably digging into the Fluoride Action Network funds) and produced £1400 to buy themselves some apparent “scientific credibility.”

I say apparent because more and more readers of scientific literature are becoming aware of the problem of poor quality journals and predatory open access publishers. Rather than providing scientific credibility, publication in such outlets may in fact leave a bad mark on a scientist’s reputation and credibility.

But I guess the politically motivated activists looking to confirm their biases will not care.

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

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

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

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

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

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

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

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

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

The email exchange

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

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

Pretty quick service. Remember this was a Sunday.

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

11 March, 2.11 pm

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

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

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

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

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

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

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Anti-fluoridation campaigners often use statistical significance to confirm bias

I was pleased to read this Nature article – Five ways to fix statistics – recently as it mirrors my concern at the way statistical analysis is sometimes used to justify or confirm a bias and not reveal a real causal relationship. Frankly these days I just get turned off by media reports of studies showing statistically significant relationships as evidence for or against the latest health or other fads.

As the Nature article says, statistical significance tests often amount “to uncertainty laundering:”

“Any study, no matter how poorly designed and conducted, can lead to statistical significance and thus a declaration of truth or falsity. NHST [null hypothesis significance testing] was supposed to protect researchers from over-interpreting noisy data. Now it has the opposite effect.”

No matter how good a relationship appears, or how significant the statistical analysis shows it to be, it is simply a relationship and may have no mechanistic or causal backing.  An example often used to illustrate this is the close relationship between the prevalence of autism and sales of organic produce.

Clearly statically significant but we don’t find those activists claiming autism is related to one thing or another ever citing this one. I am picking these activists may well have a bias towards organic produce.

Here are several examples I have discussed before which illustrates how “statistical significance” is sometimes used to confirm bias in fluoridation studies. I think these are very relevant as anti-fluoridation campaigners often cite statistical significance as if it is the final proof for their claims.

Ignoring relevant confounders

This is an easy trap for the biased researcher (and let’s face it, most of us are biased – it’s only human). Just ignore other confounders or risk-modifying factors that may be more important. Or ignore the fact that the risk-modifying factor one is interested in (in this case fluoride) may just be acting as a proxy for (and therefore is related to) something else which is more relevant.

This why all credible risk-modifying factors should be considered in correlation studies. They should be included in the statistical analyses.

It’s amazing how many researchers either ignore the possible risk-modifying factors besides their pet one – or pay lip-service to the problem by limiting their consideration to only a small range of such factors.

Examples of studies promoted by anti-fluoride campaigners where this is a problem include:

Peckham et al., (2015) hypothyroidism paper:

Peckham, S., Lowery, D., & Spencer, S. (2015). Are fluoride levels in drinking water associated with hypothyroidism prevalence in England? A large observational study of GP practice data and fluoride levels in drinking water. J Epidemiol Community Health, 1–6.

This has been widely condemned for a number of reasons – one of which is that iodine deficiency, a known factor in hypothyroidism, was not included in the statistical analysis.

(See Paper claiming water fluoridation linked to hypothyroidism slammed by experts and Anti-fluoride hypothyroidism paper slammed yet again).

The  Takahashi et al., (2001) cancer paper:

Takahashi, K., Akiniwa, K., & Narita, K. (2001). Regression Analysis of Cancer Rates and Water Fluoride in the USA based Incidence on IACR / IARC ( WHO ) Data ( 1978-1992 ). Journal of Epidemiology, 11(4), 170–179.

These authors reported an association between fluoridation and a range of cancers. Problem is, they did not consider any other risk-modifying factors. When some geographical parameters were included in the statistical analyses there were no statistically significant relationships of cancer with fluoridation.

(see Fluoridation and cancer).

The Malin & Till (2015) ADHD paper:

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

This reported an association of ADHD prevalence with the extent of fluoridation in the US. Anti-fluoride campaigners have cited this paper a lot because it is the only study indicating any effect of fluoridation on cognitive ability. All other studies they rely on were from areas of endemic fluorosis where the natural levels of fluoride are higher than that used in community water fluoridation.

Malin & Till (2015) considered only household income as a possible risk-modifying factor. No consideration was given to residential elevation which other researchers had around the same time reported as associated with ADHD prevalence.

I repeated their statistical analysis but included residential elevation and a range of other risk-modifying factors. This showed there was no statically signficant association of ADHD with fluoridation when other risk-modifying factors, particularly elevation, were included. My critique of Malin and Till (20215) is now published:

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

(See ADHD linked to elevation not fluoridation, ADHD link to fluoridation claim undermined again and Fluoridation not associated with ADHD – a myth put to rest).

Ignoring the lack of explanatory power

I think this is where the over-reliance on statistical significance, the p-value, can be really misleading. Researchers desperately wishing to confirm their bias will proudly claim  a statistically significant relationship, a p-value less than 0.05, etc., as if that is the final “proof.” These researchers will often hide the real meaning of their relationship by not making the actual data available or limiting their report of their statistical analysis to p-vlaues and, maybe, a mathematical relationship.

However, if the reported relationship actually explains only a small part of the observed variation in the data it may be meaningless. Concentration on such a relationship means that other more signficant risk-modifying factors which would explain more of the variation are ignored. Anyway, where a factor explains only a small part of the variation it is likely a more complete statistical analysis would show that its contribution was not actually statistically signficant.

Some examples:

The prenatal fluoride exposure and IQ study of Bashash et al (2017):

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.

These authors reported a statistically significant association of Child IQ with the prenatal fluoride exposure of their mothers. However, their figures showed a very wide scatter in the data indicating very little explanation of the variation in child IQ by the association with prenatal fluoride. (see below left). This must be why the Fluoride Action Network removed the data points from the figure when reproducing it for their promotion of the paper (see below right).

Bashash et al., (29017) did not give the complete statistical analysis of their data. However, I was able to digitally extract the data from their figure and my analysis showed that prenatal fluoride expose was only able to explain a little over 3% of the variation in child IQ. So, despite the statistical significance of their observed relationship prenatal fluoride exposure is unlikely to be a real factor in child IQ. In fact, concentration on this minor (even if statistically significant) factor will only inhibit the discovery of the real causes of IQ variation in these children.

Yes, anti-fluoride campaigners will protest that this study did consider some other possible risk-modifying factors. However the very low-level of explanation of the variation in the data indicates they did not consider enough.

(see Premature births a factor in cognitive deficits observed in areas of endemic fluorosis?,  Fluoride, pregnancy and the IQ of offspring and Maternal urinary fluoride/IQ study – an update).

The Xiang et al., (2003) water fluoride and IQ study:

Xiang, Q; Liang, Y; Chen, L; Wang, C; Chen, B; Chen, X; Zhouc, M. (2003). Effect of fluoride in drinking water on children’s intelligence. Fluoride, 36(2), 84–94.

Anti-fluoride campaigners rely a lot on this and other papers from this group.  Even though this research involved areas of endemic fluorosis it, in a sense, provides some of their best evidence because they reported a dose-dependent relationship of IQ to water F. Xiang et al., (2003) claimed a statistically signficant association of child IQ to fluoride water levels.  Other anti-fluoride campaigners, and some other researchers, have cited Xiang et al., (2003) to support such an association.

I don’t question these researchers found a significant association – but there is a problem. Nowhere do they give a statistical analysis or the data to support their claim! Very frustrating for critical readers (and we should all be critical readers).

They did, however, give some evidence from a statical analysis of the relationship of IQ with urinary fluoride. They did not give a complete statistical analysis but they included the data in a figure  (see below) – so I did my own statistical analysis of data digitally extracted from the figure.

The figure shows a high scatter of data points so this is another case of a statistically significant relationship explaining only a small part of the variability. My analysis indicates the relationship explains only about 3% of the variability in IQ value. Another case where researchers have concentrated on their own pet relationship and in the process not properly searched for more reasonable risk-modifying factors capable of explaining a larger proportion of the variation.

I have made a more detailed critique of Xiang et al.  (2015) and Hirzy et al., (2016) which relies on this data (see Does drinking water fluoride influence IQ? A critique of Hirzy et al. (2016)). A paper based on this has been submitted to a journal for publication and is currently undergoing peer review..

(see Anti-fluoride authors indulge in data manipulation and statistical porkies, Debunking a “classic” fluoride-IQ paper by leading anti-fluoride propagandists,  Connett fiddles the data on fluoride, Connett & Hirzy do a shonky risk assesment for fluoride and Connett misrepresents the fluoride and IQ data yet again).

Conclusion

This  briefly outlines the statistical problems of a number of papers anti-fluoride campaigners rely on. Two common problems are:

• Insufficient consideration of confounders or other risk-modifying factors – indicating a bias towards a “preferred” cause, and
• Reliance on a relationship that, although statistically significant, explains only a very small fraction of the observed variation – again indicating bias towards a “preferred” cause

I don’t for a minute suggest that only those researchers publishing “anti-fluoride” research are guilty of these errors. They are probably quite common. Authors will generally responsibly warn that “correlation does not prove causation” and suggest more work needs to be done including  consideration of a wider number of confounders or risk-modifying factors. However, bias is only human so researcher advocacy for their own findings is understandable. The published research may even be of general value if readers interpret it critically and intelligently.

However, in the political world such critical consideration is very rare. Activists will use published research in the way a drunk uses a lamppost – more for support than for illumination. This makes it important that the rest of us be more objective and critically assess the claims they are making. Part of this critical assessment must include an objective consideration of the published research that is being cited.

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Anti-fluoride “expert” finds the real reason oral health has improved – and it’s not fluoride

Anti-fluoride campaigners always promote people like Geoff Pain as “renowned” or “world experts.” They aren’t. Pain has no credible scientific publications on fluoride.

No, in fact, he claims lead is responsible for tooth decay and the improvement in oral health is a result of removing airborne lead contamination. And the “proof” is even in the title of his report – “Global Decline in Tooth Decay correlates with reduced Airborne Lead (Pb) but water Fluoridation prevents further progress“

Mind you, the word “correlate” appears only twice in the document – once in the title and once in the abstract. Nowhere else. Scientists usually restrict the use of words like this to results of proper statistical analyses – but he presents no evidence of a correlation anywhere in the document.

OK, we shouldn’t expect any better. This document is just another one of a series of documents, dressed up as scientific publications, supported by cobbled together citations which are often are irrelevant or don’t support the claims made. Produced by Geoff Pain, well-known Australian anti-fluoride activist, whose concept of scientific publication is to upload his unreviewed documents on to Researchgate. I have written about his citation trawling and false “publication” before in my article  An anti-fluoride trick: Impressing the naive with citations

But, perhaps he is on to something. Irrespective of fluoride (he has a hangup about that element) perhaps lead is somehow implicated in oral health problems. So let’s see what the document actually claims.

It has three aims:

1: Rejection of all evidence of the beneficial effects of fluoridation

He describes the evidence for fluoridation as “false” and “absurd.”

Of course, he doesn’t consider for a minute any of the many studies providing evidence of beneficial effects – he just relies on the naive use of selected World Health Organisation (WHO) data which the Fluoride Action Network is well-known for. I have written about this before (see, for example, Fluoridation: Connett’s naive use of WHO data debunked).

This simply argues that the fact that oral health has improved over time in both fluoridated and unfluoridated countries is “proof” that fluoridation has no effect.

Here is the graph he uses:

This figure is meaningless because of the huge influence of inter-country differences on these data, irrespective of fluoridation. That doesn’t require a scientific training to see. These differences introduce so much noise into the data that no conclusion is possible about the influence of fluoridation. Robyn Whyman pointed this out in his report for the National Fluoridation Information Service – “Does delayed tooth eruption negate the effect of water fluoridation?“:

“Studies that appropriately compare the effectiveness of water fluoridation do not compare poorly controlled inter-country population samples. They generally compare age, sex, and where possible ethnicity matched groups from similar areas. Inter-country comparisons of health status, including oral health status, are notoriously difficult to interpret for cause and effect, because there are so many environmental, social and contextual differences that need to be considered.”

The figure does not differentiate between fluoridated and unfluoridated areas within countries – a comparison that is more valid. When we look at the same WHO data for fluoridated and unfluoridated areas we can see the beneficial effect. For example, in the data from the Republic of Ireland:

2: Evidence for an effect of lead exposure on oral health

I can accept that – but certainly would not go as far as Pain’s claim that “lead exposure reduction as the major factor in tooth decay decline.” In fact, the articles he cites suggest that the association of  lead exposure with tooth decay is probably weak in most cases.

For example, he cites Gemmel et al., (2002) but ignores what that paper actually says:

“In summary, our findings are consistent with those of several other recent studies (e.g., Campbell et al. 2000; Moss et al. 1999) in suggesting a weak association between children’s lead exposure and caries in primary teeth. The association was region specific, however, suggesting that its magnitude depends on the local distributions of other, more important caries risk factors such as fluoride exposure, diet, and other aspects of environment. The most likely direct role for lead exposure in the development of dental caries, therefore, is as a modifier of host susceptibility. We cannot reject the hypothesis, however, that an elevated lead level is a surrogate or proxy index of some other factor that is itself directly cariogenic.”

Similarly, he cites Martin et al., (2007) but ignores what that paper actually concluded:

“We conclude that this study provides only weak evidence, if any, for an association of low-level lead exposure with dental caries.”

Mind you, he also cites Wiener et al., (2015) who reported:

“This study indicated a strong association of blood lead levels with increasing numbers of carious teeth in children aged 24–72 months.”

But still not evidence that lead is the major factor involved.

Pain ignores suggestions that results may suggest modification of the role of fluoride

I wonder if those who indulge in citation trawling ever actually read the papers they cite. Far from Pain’s citations being evidence of a lack of effect from fluoridation, in almost all cases they suggest the observed effects could be due to modification of the more important effect of fluoride on oral health.

For example, Martin et al., (2007) point out:

” Mechanisms which have been offered to explain the potential association include lead effects on salivary gland development and function (Watson et al., 1997; Bowen, 2001), effects on enamel formation (Lawson et al., 1971; Kato et al., 1977; Appleton, 1991; Watson et al., 1997), and an interference with fluoride uptake in saliva (Gerlach et al., 2002). “

Come on Geoff. Spend some time and actually read the articles you have trawled for your citations.

3: Fluoridation means increase lead concentration in tap water

Having rejected any beneficial role for fluoride and presented lead as the major influence on oral health Pain now puts it all together to “prove” that fluoridation actually enhances tooth decay by increasing dietary lead intake. Why? Because of:

“deliberate addition of Lead as a major contaminant of phosphate fertilizer industrial waste used in Fluoridation plus the exacerbation of Plumbosolvency by Fluoride”

The first point about lead contamination of fluoridating chemicals relies in a naive interpretation of the certificates of analysis required for these chemicals. Just because a very low concentration of lead is recorded in these certificates does not mean this causes an increase in dietary lead intake.

I showed in the article “Chemophobic scaremongering: Much ado about absolutely nothing“ that the fluoridating chemicals contribute less than 0.05% to the lead in tap water – already present from natural sources!

Pain’s reference to “exacerbation of Plumbosolvency” relies on a limited study which reported an association between blood lead levels in children and the treatment of tap water in the US. Of course, the release of lead from pipe fittings can be a problem irrespective of water treatment – which is why authorities recommend one should let the water run for a while first thing in the morning to get rid of such impurities. However, the studies Pain relies on seem to attribute plumbosolvency to specific chlorinating chemicals rather than fluoride.

One can make a simple check, however. In New Zealand authorities regularly make chemical analyses of their tap water available. These do not show increased lead concentrations after fluoridation.

Conclusion

So, again, Geoff Pain has indulged in citation trawling and confirmation bias to produce this report. The citations he uses do not support his claims.

Dietary intake of lead may be one of many factors influencing dental health – but his citations do not in any way support his assertion that it is the “major factor”. Nor do they support his claim that fluoridation does not have a beneficial effect on oral health.

In fact, it is Geoff Pain, not health authorities, who is making the “false” and “absurd” claims.

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New fluoride debate falters

Characters debate the “fluoride conspiracy” in Kubrick’s Dr Strangelove

What is it with these anti-fluoride campaigners – and particularly their leaders? They make a song and dance about having “science on their side.” They will heavily promote the latest research and papers if they can argue that they confirm their bias. And they will email politicians or make submissions to local bodies making scientific claims – often with citations and long lists of references.

But we simply can not get them to enter into a good faith scientific discussion of the sort I suggested in Do we need a new fluoride debate?

I thought this was going to happen. Bill Osmunson, the current Direct of the Fluoride Action Network (FAN), had agreed and even produced an initial article for posting. But he has now pulled out and asked me not to post his article. Apparently, my critique of a recent paper by him and his colleagues from FAN (see Flaw and porkie in anti-fluoride report claiming a flaw in Canadian study) was the straw that broke the camels back as far as he was concerned.

Talk about tiptoeing around a discussion partner. How can one have a discussion with someone this sensitive?

Excuses, excuses!

This is the explanation he gives for his withdrawal from the planned exchange:

“I have second thoughts about a discussion with you.  Do not publish my comments.*

After reading your comments in response to Neurath, it became obvious that you have no interest in discovering the truth or protecting the public.  Nor do you have reasonable judgment to evaluate research.

You do have good mechanical skills, but not judgment.

You correctly take weaker arguments and point out they are weak.  But you do not comment or appreciate the main more powerful issues.  Your comments make it sound like there is no value because some points have lower value.  Only a person who carefully rereads McLaren and Neurath, and then your comments understands some of your points are valid and you have missed others which are powerful.

In addition, you use derogatory, unprofessional mocking terms to attack the person instead of the issues.  I’m not interested in being your porky or sparky or pimp.

You are unprofessional and are not worth the time.”

• The “comments” Bill refers to are a 55-page pdf file he sent me as the first post in our exchange. We were discussing a shorter form more suitable for a blog post when he decided to back out.

Mind you, in a previous email he had acknowledged that his mates (presumably in FAN) were unhappy about him participating in this good-faith scientific exchange. He wrote:

“Several people have told me not to respond to you, because you are unprofessional with your statements and comments.  You attack the messenger instead of the message and you have such severe bias and faith in fluoride that you must have worked for the tobacco companies to learn your strident blind bias.  

OK, I gave you a try once before and found you to be violent with your personal attacks and lack of judgment.”

 Sounds like “excuses, excuses,” to me. Surely I am not such a horrible person? I asked Bill to identify anything in my exchange with Paul Connett (see The Fluoride Debate) where I had behaved in the way he charged. He couldn’t. And I challenge anyone else to identify such behaviour on my part in that exchange.

Bill Osmunson and his mates claim I behaved badly in this exchange with Paul Connett – but they refuse to give a single example

 I can only conclude that the people at FAN are unable to provide good scientific arguments to support their case. They may well produce documents with lists of citations and references with “sciency” sounding claims. But they will not allow their claims to undergo the sort of critique normal in the scientific community.

Still – I am willing to be proven wrong. if Bill feels that he doesn;t have the scientific background for this sort of exchange perhaps Chris Neurath, Harvey Limeback or one of the other authors from FAN of the article I critiqued in Flaw and porkie in anti-fluoride report claiming a flaw in Canadian study) could take his place.

The offer is open.

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

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

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

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

Timeline

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

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

The anti-fluoride critique was recently published in:

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

The response from the original authors was then published in:

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

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

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

And:

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

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

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

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

“whose policy is to promote fluoridation.”

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

What did the original study find?

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

What did the critique claim?

A number of the criticisms are debatable and relatively minor.

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

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

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

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

Data ignored?

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

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

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

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

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

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

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

Falsifying a “correction factor”

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

Looks bad, doesn’t it?

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

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

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

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

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

Conclusion

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

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

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

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Do we need a new fluoride debate?

I think we do. Something like the good faith scientific exchange I had with Paul Connett four years ago (see Connett & Perrott, 2014 – The Fluoride Debate).

After all, there have been a number of important scientific reports since then. They may have been thrashed out (and thrash is sometimes the operative word) in one of the “anti-fluoride” or “pro-fluoride” internet silos but there has yet to be a proper discussion.

I have been trying to get one going for a while. Paul Connett is no longer interested and everyone else on the “anti-fluoride” side seems unwilling. However, Bill Osmunson who recently replaced Paul Connett as director of the Fluoride Action Network has been contributing to the discussion on several of the posts here. He seems to be the obvious choice for a discussion partner and I  asked him if he is willing to participate in another scientific exchange of the sort I had with Connett.

So far he has not responded – but as he has made some relevant critiques of several recent scientific papers in these discussion contributions I think it is relevant to bring that discussion into the formal blog posts. Otherwise, some important points will just be lost because they are buried deep in the discussion threads.

Here I respond to criticisms Bill makes of two recent studies which looked for evidence of the influence of community water fluoridation (CWF) on IQ and cognitive deficits in general. I urge Bill Osmunson to respond to my points in a format which can be presented as a blog post here.

Community water fluoridation and IQ

The two studies were published after my exchange with Paul Connett and are:

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

And

Barberio, A. M., Quiñonez, C., Hosein, F. S., & McLaren, L. (2017). Fluoride exposure and reported learning disability diagnosis among Canadian children: Implications for community water fluoridation. Can J Public Health, 108(3), 229.

Broadbent et al., (2014)

This study used data from the Dunedin  Multidisciplinary Health and Development longitudinal study and found no difference in IQ of people in fluoridated and unfluoridated areas or any effect of fluoridated toothpaste or fluoride supplement use.

I hope I represent Bill correctly but his criticisms of this study are vague – I can’t help feeling he is succumbing to the general hostility anti-fluoride campaigners have had about this study.

Let’s deal with his last criticism:

” I have previously presented my reservations about the NZ study and Broadbent’s comparing fluoridation with fluoride supplements, which lacked power to evaluate IQ.”

It more or less encapsulates anti-fluoride criticisms of the study and does contain an element of validity in reference to the study’s “power.” However, Bill’s reference to “power” is far too vague. It needs to be quantified.

Is Bill claiming that there are declines in IQ caused by CWF but they are too small to be detected in a study like Broadbent et al., (2014)? Or was there something about that study which made it incapable of detecting a reasonable IQ decline? Or does it matter – after all someone who is ideologically committed to believing fluoride is bad for IQ can always fall back on this argument when experimental results don’t go their way. No study will realistically have the ability to detect an extremely small IQ change that they might argue for. And such a small change is more in the eye of the (biased) observer than a reality.

Fellow FAN members Hirzy et al., (2016) also argued that the “power” of the Broadbent et al.,  (2014) study was too low to detect their assumed change in IQ. They argued this case on the basis of total dietary intake of fluoride claiming that there was very little difference of total dietary intake between fluoridated and fluoridated areas.  Osmunson et al., (2016) made the same argument – appearing to give up completely on the contribution of CWF (as it “likely represents less than 50% of total fluoride intake”) and directing attention to total fluoride intake instead. However, their arguments are very subjective as they pull dietary data “out of a hat” and don’t deal with the real situation where the study occurred.

Osmunson mentioned the importance of fluoride supplements and fluoride toothpaste to fluoride intake but seemed to have missed the fact that Broadbent et al., (2014) had also included these as factors in their statistical analysis. Neither these factors nor CWF exhibited a statistically significant effect on IQ.

The apparent fallback position of Hirzy et al., (2016) and Osmunson et al., (2016) that the relatively small dietary F intake meant their assumed IQ differences were too small for the study to detect comes across as straw-clutching. Especially as oral health differences between fluoridated and unfluoridated areas were detectable See Evans et al., 1980 and Evans et al., 1984).

The “power” of a study

The “element of validity” I referred to in Bill’s complaint about the “power” of the experiment is one every practical researcher faces – especially when dealing with an existing programme rather than designing, from the ground up, a laboratory experiment. Numbers of participants, or samples, are always limited and researchers rarely have the luxury of the large number they would wish for to provide more “power.”

The “power” of a study is often represented by the  95% confidence interval (CI). This means that “if the same population is sampled on numerous occasions and interval estimates are made on each occasion, the resulting intervals would bracket the true  population parameter in approximately 95 % of the cases.” Usually, more sample numbers mean a smaller CI and therefore more confidence in the value of the result.

Broadbent et al (2014) reported a 95%CI of -3.22 to 3.20 IQ points for the effect of community water fluoridation with children of 7 -13 years. (The equivalent CIs for the effects of fluoride toothpaste and fluoride tablets were -1.03 to 2.43 and -0.38 to 3.49 respectively). The observed effects were not statistically different to zero. Their study used just 990 children. If more participants had been available the 95%CI could have been reduced to less than the range of 6.4 IQ points actually found for the effect of CWF.

In a very large Swedish study, Aggeborn & Öhman (2016) included between 20,000 and 80,000 participants and estimated a confidence interval of -0.23 to 0.89 IQ units when fluoride is increased by 1 mg/L. (They were able to consider a continuous measure of fluoride and not simply fluoridated or unfluoridated treatments). This study has far more “power” than that of Broadbent et al., (2014), and therefore a smaller CI value. But the conclusion was the same – fluoride at these concentrations had “a zero-effect on cognitive ability.”

Barberio et al., (2017)

This is a Canadian study with a large representative sample and individual estimates of fluoride exposure and reported learning disability diagnosis. Overall it concluded there was no “robust association between fluoride exposure and reported learning disability diagnosis.”

Bill Osmunson argues that this study “has limitations” and that the “conclusions overstate their data.”

I agree with Bill that diagnosis of learning disability based on a household questionnaire is not the same as a proper professional diagnosis, although presumably the question aimed at finding out if a professional diagnosis had been made – and what it was in some cases. The authors acknowledge that weakness but argue that more objective assessments are probably only feasible in small-scale studies.

Interestingly Bill and his fellow anti-fluoride campaigners did not raise this problem of reliance on parental answers to a questionnaire when they considered and argued strongly for, the Malin and Till (2015) ADHD study. (See  Perrott 2017 – Fluoridation and attention deficit hyperactivity disorder – a critique of Malin and Till (2015)) for more details of this study and its problems.

Of course, these are the real-world problems faced by researchers attempting to extract useful data from large-scale surveys. One of the reasons why readers should not consider single studies as definitive and should consider each one critically and sensibly.

However, I think Bill is straw-clutching when he quotes the authors:

“When Cycles 2 and 3 were combined, a small but statistically significant effect was observed such that children with higher urinary fluoride had higher odds of having a reported learning disability in the adjusted model (p = 0.03).” [Cycles 1 and 2 are two separate parts – 2009-20011 and 2012-2013 respectively – of the Canadian Health Measures Survey]

And then argues:

“Barberio could have concluded they found harm. Instead, they focused on data which did not show harm.”

Bill is aware that a statistically significant effect of fluoride exposure was observed in only a limited case – when data from two cycles were combined and the urinary fluoride data had not been corrected by using either creatine concentration or specific gravity. This correction is necessary as an attempt to overcome the shortcomings of single spot-samples of urine. As the authors point out “spot urine samples used to measure fluoride are vulnerable to fluctuations.” And :

“creatinine-adjusted urinary fluoride or specific gravity-adjusted urinary fluoride . . .  are thought to be more accurate because they help to correct for the effect of urinary dilution, which can vary between individuals and different points in time. Accordingly, these adjusted measures help to offset some of the limitations associated with spot urine samples. The finding that the effect was reduced to non-significance when creatinine-adjusted and specific gravity-adjusted urinary fluoride were used, suggests that the association between urinary fluoride and reported learning disability diagnosis may not be robust.”

So Bill would prefer that the authors had based their conclusions on uncorrected urinary fluoride data and not the more reliable corrected figures? And why? Because that would have confirmed his bias. That is an unfortunate personal foible – our biases often encourage us to go with unreliable conclusions and not allow them to be challenged by the more reliable data.

Conclusions

Here I have simply considered the Broadbent et al., (2014) and Barberio et al.,. (2017) papers because these are the ones Bill Osmunson has responded to. I urge him, to also consider the Aggeborn and Öhman (2016) paper.

I hope Bill Osmunson will respond to this post with his refutations of my points or further arguments about these and other papers. I hope also that he takes up my offer of space here for an in-depth exchange of the sort I had with Paul Connett four years ago.

References

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

Barberio, A. M., Quiñonez, C., Hosein, F. S., & McLaren, L. (2017). Fluoride exposure and reported learning disability diagnosis among Canadian children: Implications for community water fluoridation. Can J Public Health, 108(3), 229.

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

Evans, R. W., Beck, D. J., & Brown, R. H. (1980). Dental health of 5-year-old children: a report from the Dunedin Multidisciplinary Child Development Study. The New Zealand Dental Journal, 76(346), 179–86.

Evans, R. W., Beck, D. J., Brown, R. H., & Silva, P. A. (1984). Relationship between fluoridation and socioeconomic status on dental caries experience in 5-year-old New Zealand children. Community Dentistry and Oral Epidemiology, 12(1), 5–9.

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

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

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

Perrott, K. W. (20217). Fluoridation and attention deficit hyperactivity disorder – a critique of Malin and Till (2015)).  British Dental Journal, In press.

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Endemic fluorosis and its health effects

Much of the anti-fluoridation propaganda used by activists rely on studies done in areas of endemic fluorosis. Slide from a presentation by Q. Xiang to an anti-fluoride meeting organised by Paul Connett’s Fluoride Action Network in 2014.

 

The public debate in New Zealand might convince the casual reader that all the science related to fluoride revolves around tooth decay and IQ. But that is certainly not the case on a world scale.

The World Health Organisation gives guidelines for the concentration of fluoride in drinking water recommending it should be in the range 0.5 – 1.5 mg/L. OK, above 0.5 mg/L because of the positive effect it has on oral health, in reducing dental decay. That interests us in New Zealand because our drinking water is more likely to be deficient in fluoride.

But on the world scale, many people are far more interest in the higher limit – or at least in attempting to reduce their drinking water fluoride concentration to below this limit. This is because large areas of the world suffer from the health effects of endemic fluorosis due to the excessive dietary intake of fluoride and the high concentration in their drinking water.

There are significant health effects from endemic fluorosis – effects we don’t’ have here but are important to many countries. So there is plenty of research – both on the health effects and on reducing drinking water concentrations and dietary intake.

In fact, the anti-fluoride campaigners get all the scientific reports they use in “evidence” to oppose community water fluoridation from studies in countries where fluorosis is endemic. Not only is this misrepresenting the science. It is also unbalanced because scientific studies on IQ in areas of endemic fluorosis represent only a small proportion of such health-related studies.

To illustrate this I have done a number of searches on Google Scholar using the terms “endemic fluorosis” and one other term related to a health effect. Here is the resulting table.

“endemic fluorosis” and “?”	Hits in Google Scholar
Alone	8810
And “dental fluorosis”	3570
And “bone”	3570
And “skeletal fluorosis”	2910
And “cancer”	1690
And “death”	1180
And “birth”	1170
And “osteoporosis”	1130
And “body weight”	936
And “gastrointestinal”	808
And “Osteoclerosis	697
And “diabetes”	642
And “cardiovascular”	633
And “reproduction”	592
And “IQ”	480
And “cognitive”	331
And “heart disease”	327
And “hypothyroidism”	297
And “Renal failure”	292
And “obesity”	230
And “infertility”	216
And “non-skeletal fluorosis”	183
And “muscoskeletal”	178
And “birth weight”	135
And “birth defects”	86
And “premature birth”	29

40% of the hits related to “dental fluorosis” and another 40% to “bone” while 33% related to “skeletal “fluorosis.” Obviously, these are of big concern in areas of endemic fluorosis so receive a lot of research attention. In fact, the prevalence of these is used to define an area as endemic.

But only 5% of hits related to IQ – clearly of much less concern to researchers. Yet it seems to be all we hear about here and this illustrates how unbalanced most of the media reports we get here are.

To start with, these health effects do not occur in countries like New Zealand using community water fluoridation. They occur in regions where drinking water contains excessive fluoride and where the dietary intake of fluoride is excessive.

But the other fact is that IQ effects receive relatively little attention in health studies from those areas compared with the more obvious, and more crippling, effects like dental and skeletal fluorosis.

Mind you, that doesn’t stop activists making sporadic claims of all sorts of health effects from fluoridation and relying on studies from areas of endemic fluorosis. But the most frequent claims made by activists at the moment relate to IQ. Perhaps this is because it is harder to hide the fact that we don’t see cases fo skeletal fluorosis or severe dental fluorosis in New Zealand. IQ changes are not so obvious and this might make them a more useful tool for anti-fluoride campaigners to use in their scaremongering.

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