Category Archives: Health and Medicine

Fluoridation means money in the pocket

Local researchers recently presented data showing that the ordinary person, and not the taxation financed health system, is the main financial beneficiary of community water fluoridation.

Their research confirmed that community water fluoridation in New Zealand is highly cost-effective for all but the smallest communities. This study updates previous evaluations by including data for adults – previous studies were limited to children. It also corrected for under-estimation of averted dental restoration costs in a previous study.

The authors also make the point that an update is necessary because:

“Sound public health practice requires periodic re-evaluation of interventions’ benefits and costs.”

The results are reported in the paper:

Moore, D., Poynton, M., Broadbent, J. M., & Thomson, W. M. (2017). The costs and benefits of water fluoridation in NZ. BMC Oral Health, 17(1), 134.

Community size

As with previous studies, the results confirmed that fluoridation is not cost effective for very small communities because of the capital cost of fluoridation plants and the use of sodium fluoride instead of fluorosilicic acid as the fluoridating chemical in small plants. However:

“For ‘minor’ through to ‘large’ plants, there is a net cost saving. For a ‘large’ plant supplying 50,000 people, the cost offsets are over 20 times the cost of fluoridation. The break-even point appears to be reached by ‘minor’ plants supplying a population over 500.”

National net savings from universal fluoridation

The authours estimated the national costs and saving from averted ental costs over a 20 year period. If all New Zealand reticulated water supplies serving populations greater than 500 were fluoridated costs over 20 years would amount to$177 million while the cost offset due to averted dental treatment costs would be $1578 million.

The national 20-year net saving due to such universal community water fluoridation in NZ would amount to $1401 million.

That is a nine times pay-off!

Individuals save more than the state

I hadn’t thought of this before but the data enables separate estimates of savings to the state from universal CWF through reduced costs to the health budget, and to the individual citizen through their reduced costs for private dental treatment.

In fact, the major benefit is to the individual rather than the health budget.  National savings over 20 years for reduction of private dental care expenditure would be $1428 million – 10 times the savings to the national health budget.

Perhaps this helps people understand that they, personally, have something to gain fiancially from community water fluoridation

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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 fluoridationADHD 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 porkiesDebunking a “classic” fluoride-IQ paper by leading anti-fluoride propagandists,  Connett fiddles the data on fluorideConnett & 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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Meat substitutes – prospects and new ethical questions

Nigel Latta tells us about a plant-based meat substitute – chicken-free chicken – produced by  SunFed meats. This is an example and not meant as an endorsement of any specific product.

I am deeply ashamed of it now – but at the time it seemed like an experience I couldn’t afford to miss. It was so exotic – and I was travelling.

Twenty years ago I ate at a restaurant in Johannesburg, the Republic of South Africa,  which specialised in meat dishes – from game animals. It was a real feast. Stews of ostrich, zebra, hippo, giraffe and other animal meats. Not something us New Zealanders normally experience.

But I no longer eat animal meats – and haven’t for several years. My decision is based on ethical considerations. So you can understand my shame.

Some might call me a weirdo – but I do not think my ethical decision is really all that unusual. Vegetarianism, veganism and similar dietary approaches are relatively common these days. And I think there are many more of us who resist labels but wish to avoid animal meats for basically ethical reasons. Even if only reducing animal meat consumption to rare occasions.

However, in common with others who avoid eating animal meat, I am surprised that there are still so few choices for us. Restaurant menus only seem to give token recognition of our existence, if at all, and the dishes on offer are often uninspiring.

On the other hand, there does seem to be a renewed interest in meat substitutes. Not only for health reasons but also because of the growing appreciation of how animal-based agriculture is harming our environment. Even in little old New Zealand which usually insists it is “clean and green” but is also proud of its efficient and intensive animal-based agricultural industry.

I welcome that interest. These days I have no problem finding or producing tasty plant-based meat substitutes for myself but it has taken some research effort. Products on supermarket shelves are few and far between. However, if you believe some recent news reports the arrival of tasty meat substitutes is so imminent the established agricultural industry is starting to worry.  A recent report citing an agribusiness spokesperson, Ian Proudfoot, reckons:

New Zealand meat and dairy producers needed to identify what level of risk the products presented for their industry and plan accordingly.

The threat of vegetarian alternatives to meat products was looming as companies were beginning to create products that would genuinely appeal to consumers, Mr Proudfoot said.

For example, US company Impossible Foods has developed a plant-based food that is said to closely resemble the taste and smell of meat – and has attracted $US150 million in investment.

“This is definitely going to happen in the next five years and it could start to happen in the next two to three years.”

He said in the dairy sector, New Zealand would have multiple alternative milk products – such as almond and hemp milk – competing with it, all of which were designed to meet specific consumers’ desires.

The current alternative meat market was less of a threat because it was aimed at wealthy consumers. However, this would change as the new “alternative protein” companies were bought up by bigger players in the food industry, he said.

What about animal-based meat substitutes?

The company Sunfed Foods is producing plant-based meat substitutes. However, it’s founder Shama Lee says there are another two alternatives:

  1. Cultured meats – these are grown from starter cells taken from animals such as stem cells. This is the method Sergey Brin bankrolled to produce his rich-man’s hamburgers, and
  2. Bioengineered meat – where animal protein is grown from a bioengineered culture of yeast cells.

These alternatives may be a bit further down the line but could be in your supermarkets in 10 or 20ears.

I don’t doubt the possibilities – but I will believe it when I see it. I know for a fact that it is possible to produce very tasty plant-based meat alternatives but our supermarkets are hardly swamped with these products. In most cases, they still need to be home produced in New Zealand. So will cultured meat products get the supermarket shelf space – especially if competing with traditional meats?

Still, such products should solve the ethical dilemma many of us face. We would be able to eat “real” meat without worrying about how the animals had been treated and slaughtered.

Is there a new ethical dilemma?

OK, if I am still around when it happens I may be able to take part in a feast of stews like that in Johannesburg but using cultured meat instead of real animal meat. I could still get to taste the ostrich, hippo, zebra and giraffe stews without any feelings of guilt.

However,  will it stop there? We could go even more exotic.

Just think about it. We could also produce cultured meat using starter cells from humans! Imagine eating human meat knowing that nobody had been harmed in the preparation of the product!

Would this make cannibalism respectable? In fact, who could resist such artificial human meat – it would be so exotic.

And once more people got a taste for cultured human meat – will there be some adventurous people wanting to eat the “real” meat – uncultured human meat?

The mind boggles! One thing for sure – like all human advances there will be new ethical questions. And, no doubt, ideological groups and religions willing to use these ethical issues to promote guilt.

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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.

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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Maternal urinary fluoride/IQ study – an update

Model of a fetus in the womb. Photo credit: CP PHOTO/ Alliance Atlantis/ HO) 

The maternal urinary fluoride/IQ study  (Bashash et al., 2017) continues to get attention – but mainly from anti-fluoride organisations. The scientific community will evaluate the published report after giving it due consideration and there have already been criticisms. But anti-fluoride campaigners consider it the best thing since sliced bread. The Fluoride Action Network (FAN) describes it as “a cannon shot across the bow of the 80 year old practice of artificial fluoridation” and Fluoride Free NZ insist that it “must spell an end to fluoridation in New Zealand.”

We expect confirmation bias from the anti-fluoride organisations. But the misrepresentations in the propaganda from these organisations are of more concern because they are blatantly meant to scaremonger.

Misrepresentation by anti-fluoride organisations

These people have worked hard to stress the respectability of the authors of the Bashash et al., (2017) paper and claim the study is impeccable. They are not interested in a critical analysis of the data and the conclusions. And they are completely silent about the evidence from the study showing no association of children’s urinary fluoride levels and IQ – normally they are quick to criticise authors reporting such a lack of association.

But this time as well as their normal misrepresentations they have actually manipulated a figure from the paper. I wonder what copyright law would say about this.

I provided the relevant figures from the paper my earlier article (see   Fluoride, pregnancy and the IQ of offspring) and commented on the large amount of scatter in the data.  This scatter should be a warning to any sensible reader – so FAN simply overcomes that problem by deleting the data points in their presentation of the figure.

Here is the original Figure 2 and the FAN misrepresentation of it:

Notice 2 things:

  1. The original figure showed the data for GCI – general cognitive index. It is not IQ and not presented as IQ in the original paper. But it is a measure  of “verbal, perceptual performance, quantitative, memory, and motor abilities of preschool-aged children.” Perhaps a fine point and FAN may be excused for inserting the more popularly understood term IQ. Or perhaps they decided not to use the real figure for IQ (Figure 3A) because it implied no effect at normal urinary fluoride levels (see figure 3A in Fluoride, pregnancy and the IQ of offspring);
  2. FAN removed all the data points in their presentation of the figure. I am sure FAN would argue this was to “simplify” the figure. But in doing so they have removed what is the most important information in Figure 2 – the wide scatter of the data points. That scatter suggests that even though the reported association is “statistically significant” it explains very little of the observed variation and is therefore not important (and may not even be real).

Association of maternal urinary F with child IQ poor and probably misleading

In Fluoride, pregnancy and the IQ of offspring I estimated that “the reported relationships with maternal urinary fluoride could explain no more than a few percent of the variation in the data.” Purely an estimation because I did not have the data to analyse myself and the authors did not give the relevant statistical information.

I have since used a plot digitiser programme to extract the data for these figures and performed my own statistical analysis.

These are the results:

For Figure 2:

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

For Figure 3A:

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

So my estimate was pretty good. And my evaluation is valid:

“In this case, I would expect that other risk-modifying factors that explain the variation more completely could be found. And if these were included in the multiple regressions there may not be any observable relationship with urinary fluoride.”

Considering that this work was unable to explain about 97% of the variation in CGI and IQ I really question its publication. Certainly, scientific evaluations will conclude that this paper should not have any influence on policymakers.

It’s a pity that with all the data the authors had they did not seek out, or properly evaluate, other possible risk-modifying factors.

Other work by group showing no association ignored

Strangely, the Bashash et al., (2017) paper did not include relevant IQ information from the PhD thesis of one of their team Deena B. Thomas. This is her thesis citation:

Thomas, D. B. (2014). Fluoride exposure during pregnancy and its effects on childhood neurobehavior: a study among mother-child pairs from Mexico City, Mexico. PhD thesis, University of Michigan.

It can be downloaded from the full-text link.

The data in chapter 2 of this thesis – Urinary and Plasma Fluoride Levels During Pregnancy and Determinants of Exposure Among Pregnant Women from Mexico City, Mexico – was published. The citation is:

Thomas, D. B., Basu, N., Martinez-Mier, E. A., Sánchez, B. N., Zhang, Z., Liu, Y., … Téllez-Rojo, M. M. (2016). Urinary and plasma fluoride levels in pregnant women from Mexico City. Environmental Research, 150, 489–495.

Bashash et al., (2017) did reference this paper – after all, it dealt with the data they used for estimating fluoride exposure. But they did not reference the thesis itself – and two other chapters in that thesis are directly relevant to the relationship of fluoride exposure to child IQ.

Chapter 3 – Prenatal fluoride exposure and neurobehavior: a prospective study – is directly relevant except that where Bashash et al., (2017) reported data for the children when 4 years old and 6-12 years old Thomas reported data for child neurobehavioral outcomes at ages 1, 2 and 3.

She concluded:

“that maternal intake of fluoride during pregnancy does not have a strong impact on offspring cognitive development in the first three years of life.”

OK – perhaps the difference is purely due to age. But surely it is part of the picture and should at least been mention in the Bashash et al., (2017) discussion.

Chapter 4 – Concurrent Fluoride and Total WASI in 6-15 year old children from Mexico City, Mexico – is also directly relevant because Bashash et al., (2017) did include that data in their paper. They concluded that:

“there was not a clear, statistically significant association between contemporaneous children’s urinary fluoride (CUFsg) and IQ either unadjusted
or adjusting for MUFcr.”

This differs a little from the findings in Thomas’s thesis:

“In the overall population, urinary fluoride appears to have no significant impact on total WASI scores (β =1.32, p=0.33), but this association changes once the models are separated by male and female children. Male children showed a significantly positive trend (β=3.81, p=0.05), and females showing a negative trend that was not significant (β= -1.57, p=0.39).” [WASI score is a measure of IQ]

And she wrote:

“analysis suggests concurrent urinary fluoride exposure has a strong positive impact on cognitive development among males aged 6-15 years.”

She concludes:

“These results were surprising in that they show opposite trends to what has been reported in the literature so, more studies with similar reliable methodology, which account for plasma fluoride, diurnal variations in urinary fluoride and children’s SES, are needed. If these results are substantiated, different fluoride interventions may be needed for male children versus female
children.”

I would have thought these findings and conclusions were worthy of discussion by Bashash et al., (2017). It’s not as if the authors were unaware of their colleague’s findings.

Maybe internal politics are involved. but that does not justify the omission.

Conclusion

The anti-fluoride people, and particularly FAN, are misrepresenting the study and have manipulated a figure to hide information in an unethical way. The data presented in the Bashash et al., (2017) study shows maternal urinary fluoride can only explain 3 – 4 % of the variation in General Cognitive Index and IQ of the children. The inclusion of a more viable risk-modifying factor would probably remove even that small amount explanation.  Bashash et al., (2017) also neglected to discuss relevant information from a colleague which contradicted their conclusions.

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Fluoride, pregnancy and the IQ of offspring

Anti-fluoride campaigners don’t agree. Image credit:Dental Care Tips for Mom and Baby” presentation

What’s the story about this new IQ-fluoride study? The one that claims fluoride intake by pregnant women could endanger their children’s IQ?

Whatever the truth, it has certainly got the anti-fluoride activists going. Mary O’Brien Byrne, leader of the local anti-fluoride group is even suggesting people check if their mothers lived in fluoridated areas. And they are busy promoting the newspaper articles on this. For example Fluoride exposure in utero linked to lower IQ in kids, study saysChildren’s IQ could be lowered by mothers drinking tap water while pregnant, and Higher levels of fluoride in urine linked to lower IQ scores in children.

Best not rely on those media reports, though – you know how unreliable they can be. The original paper is available – this is the citation:

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.

And here is a link to the full text. Download it and see what sense you make of it. I warn you it is a difficult paper to read.  A lot of information is lacking and the information that is included is hard to find. The statistical analysis is incomplete.

A new twist on the tired old fluoride/IQ story

Basically, it is the old drinking water fluoride causes lowering of IQ story. This time it relates to a supposed association of fluoride intake by pregnant mothers with cognitive deficits in their children. Interesting, only one other similar study (involving fluoride exposure while pregnant) has been reported – in January this year, and also in Mexico. I wrote about that study of Valdez Jiménez et al., (2017), In utero exposure to fluoride and cognitive development delay in infants,  in the article Premature births a factor in cognitive deficits observed in areas of endemic fluorosis?

Briefly, the Valdez Jiménez et al., (2017) study was from Mexican areas of endemic fluorosis with very high fluoride concentrations in drinking water so the results are not applicable to areas where community water fluoridation is used. However, the high incidence of premature births, and low birthweights for the children, for mothers with high urinary fluoride levels does suggest that problems of birth in areas of endemic fluorosis could provide a biological mechanism to explain the IQ deficits. Rather than a direct chemical toxicity mechanism.

What about the Bashash, et al. (2017) paper?

Generally, the paper concludes that “higher prenatal fluoride exposure . . . .was associated with lower scores on tests of cognitive function in the offspring.”

So here are some concerns I have about the paper

1: An association is not evidence of, or proof for, causation. Yes, that is the normal and obvious qualification for such studies and authors tend to repeat it – even if they might still attempt to argue the case that it is evidence. A lot of confirmation bias goes on with these sort of correlational studies.

2: The information about the mothers is scant. My first question, given it was Mexico, was did they come from areas of endemic fluorosis? The women were recruited from three hospitals in Mexico city but this says nothing about their current or former residential areas. No information on drinking water fluoride is presented nor any biological assessment, such as dental fluorosis, given which could help estimate the role of endemic fluorosis.

3: Assessment of fluoride exposure relied completely on urine fluoride concentration measurements. With between one and three samples for each mother-child pair! (Of the total sampled there was only one sample for 217, two for 224 and three for 71 mothers). I believe that is completely inadequate for estimating exposure – especially as fluoride levels in urine vary markedly during the day and with diet. Besides the extremely low sample numbers,  the World Health Organisation has warned that while urinary fluoride can be useful for monitoring populations “Urinary fluoride excretion is not suitable for predicting fluoride intake for individuals.”  (see Contemporary biological markers of exposure to fluoride). They further warn that 24 hr collection is preferred to the spot sampling used in this study.

4: The statistical information presented is confusing – and insufficient to estimate how relevant the reported statistically significant associations are. I believe the best idea of the data can be gleaned from the following figures presented in the paper.

Figure 2 displays the data and association of maternal urinary fluoride (MUFcr) with a general cognitive index (CGI) for the 4 yr old offspring.

Figure 3A displays the data and association of maternal urinary fluoride (MUFcr) with IQ of the offspring at age 6 -12.

While linear regression analysis showed statistically significant associations of the CGI and IQ of offspring’s with maternal urinary fluoride levels the large scatter indicates these associations will explain only a small part of the variations observed. In such situations, reliance on p values can be misleading. As a reader, I would be more interested in the R2 values which indicate the amount of variation explained by the association.

I estimate the reported relationships with maternal urinary fluoride could explain no more than a few percent of the variation in the data. In this case, I would expect that other risk-modifying factors that explain the variation more completely could be found. And if these were included in the multiple regressions there may not be any observable relationship with urinary fluoride.

I discussed this issue more fully in my article Fluoridation not associated with ADHD – a myth put to rest which showed that a published relationship of ADHD with fluoridation extent disappeared completely when altitude was included as a risk-modifying factor. And that relationship showed less scatter of the data points than in the figures above.

5: The absence of any association of child IQ to child urine fluoride was also reported in this paper. This conflicts with other researchers working in areas of endemic fluorosis who have reported such associations. It could be that the urine fluoride measurements used in the present study were not suitable. But I am picking that the anti-fluoride campaigners will be very silent about that information, given the importance they give to other studies showing a relationship in their propaganda.

Conclusions

it is a very unsatisfying paper. I couldn’t determine if areas of endemic fluorosis were implicated – as they were for the Valdez Jiménez et al., (2017) study. Urinary fluoride is an inadequate measure of fluoride exposure – especially for individuals and spot samples – and its variability does not allow comparison with other studies and other regions. I couldn’t evaluate if the reported results were relevant to New Zealand which does not have any endemic fluorosis.

Finally, I believe aspects of the statistical analysis were inadequate. But on the positive side, I am pleased the authors did display the actual data in their figures. The information in those figures forced me to conclude that maternal urinary fluoride may not have the influence the authors suggest. If it does have an influence its contribution can only be minor and other more important risk-modifying factors will be involved.

Mind you – I am sure anti-fluoride campaigners will see it differently. They are currently heavily promoting the study and anti-fluoride guru Paul Connett sees it as the best thing since sliced bread. He has gone on record to say this means the end of community water fluoridation!

Update

I think the anti-fluoride people are aware of weaknesses in this study. The local Fluyodie Free NZ has put out a press release including a figure which they have doctored to remove the data points which show how little variation is explained. Compare their figure with the Fiugure 2 above.

Fluoride Free NZ doctors figure from paper to hide the scatter in data points showing how little of the variability the relationship explains

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