Tag Archives: urinary fluoride

Fluoridation and ADHD: A new round of statistical straw clutching

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

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

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

The paper is:

Bashash, M., Marchand, M., Hu, H., Till, C., Martinez-Mier, E. A., Sanchez, B. N., … Téllez-Rojo, M. M. (2018). Prenatal fluoride exposure and attention deficit hyperactivity disorder (ADHD) symptoms in children at 6–12 years of age in Mexico City. Environment International, 121(August), 658–666.

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

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

Bashash, et al., (2018)

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

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

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

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

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

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

Index

% Variance explained

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

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

The fact these relationships were so weak has two consequences:

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

Credible risk-modifying factors not considered

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

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

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

Could the reported weak relationship disappear?

Possibly. After all, it is very weak.

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

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

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

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

Conclusion

As the authors admit, this study:

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

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

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

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

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

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

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

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

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

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A conference paper on the maternal neonatal urinary fluoride/child IQ study has problems

Image credit: Do new mothers doing a Ph.D. get enough support?

The anti-fluoride movement has certainly mobilised over the neonatal maternal urinary fluoride study which reported an association with child IQ. They see it as the best thing since sliced bread and believe it should lead to the end of fluoridation worldwide.

They also seem to be putting all their eggs in this one basket and have started a campaign aimed at stopping pregnant women from drinking fluoridated water (See Warning to Pregnant Women: Do Not Drink Fluoridated Water).

So I was not surprised to see a newsletter this morning from the Fluoride Action Network reporting another output from this study – a conference paper (most likely a poster) presented at the  3rd Early Career Researchers Conference on Environmental Epidemiology. The meeting was in Freising, Germany, on 19-20 March 2018.

I had been aware of the poster for the last week so had expected FAN to gleefully jump on it and start promoting it in their campaigns.

Here is a link to the abstract:

Thomas, D., Sanchez, B., Peterson, K., Basu, N., Angeles Martinez-Mier, E., Mercado-Garcia, A., … Tellez-Rojo, M. M. (2018). Prenatal fluoride exposure and neurobehavior among children 1-3 years of age in Mexico. Occupational and Environmental Medicine, 75(Suppl 1), A10–A10.

It’s only an abstract and it may be some time before a formal paper is published, if at all. Posters do not get much in the way of peer review and often not followed by formal papers.  So I can’t say much about the poster at this stage as I never like to make an assessment of studies on the basis of abstracts alone.

But, in this case, I have Deena Thomas’s Ph.D. thesis which was the first place the work was reported. If you are interested you can access it from this link:

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

I will wait for a formal paper before properly critiquing the poster, but at the moment I find a big discrepancy between the Thesis conclusions and the conclusions presented in the poster abstract.

Thesis conclusions

In her work, Deena Thomas used the Mental Development Index (MDI) which is an appropriate way of determining neurobehavioral effects in young children.

She concluded in her thesis (page 37):

“Neither maternal urinary or plasma fluoride was associated with offspring MDI scores”

And (page 38):

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

And further (page 48):

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

So – no association found of child MDI score with maternal neonatal urinary F concentrations.

Poster conclusions

But the poster tells a different story.

The abstract concluded:

“Our findings add to our team’s recently published report on prenatal fluoride and cognition at ages 4 and 6–12 years by suggesting that higher in utero exposure to F has an adverse impact on offspring cognitive development that can be detected earlier, in the first three years of life.”

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

What the hell is going on?

The data

Obviously, I do not have access to the data and she does not provide it in her thesis. But from her descriptions of the data in her thesis and her poster perhaps we can draw some tentative conclusions.

The table below displays the data description, and a description of the best-fit line determined by statistical analysis, in her thesis and her poster.

Information on data Thomas Ph.D. Thesis Conference abstract
Number of mother/child pairs 431 401
Maternal Urinary F range (mg/L) 0.110 – 3.439 0.195 – 3.673
Mean maternal urinary F (mg/L) 0.896 0.835
Model β* -0.631 -2.40
Model p-value 0.391 – Not significant
95% CI for β -4.38 to -0.40

*β is the coefficient, or slope, of the best-fit line

Conclusions

Apparently at least 30 data pairs have been removed from her thesis data to produce the dataset used for her poster. Perhaps even some data pairs were added (the maximum urinary F value is higher in the smaller data set used for the poster).

This sort of change in the data selected for the statistical analysis could easily swing the conclusion from no effect to a statistically significant effect. So the reasons for the changes to the dataset are of special interest.

Paul Connett claims this poster “strengthens” the findings reported in the Bashash paper.  He adds:

“This finding adds strength to the rapidly accumulating evidence that a pregnant woman’s intake of fluoride similar to that from artificially fluoridated water can cause a large loss of IQ in the offspring.”

But this comes only by apparently removing the conflicting conclusions presented in Deela Thomas’s Ph.D. thesis. We are still left with the need to explain this conflict and why a significant section of the data was removed.

To be clear – I am not accusing Thomas et al. (2018) of fiddling the data to get the result they did. Just that, given the different conclusions in her thesis and the poster,  there is a responsibility to explain the changes made to the dataset.

From the limited information presented in the poster abstract, I would think the scatter in the data could be like that seen in the Bashash et al. (2017) paper. The coefficient of the best fit line (β) is relatively small and while the 95% CI indicates the fit is statistically significant its closeness to zero suggest that it is a close thing.

However, let’s look forward to getting better information on this particular study either through correspondence or formal publication of a research paper.

Other articles on the Mexican study

Fluoride, pregnancy and the IQ of offspring,
Maternal urinary fluoride/IQ study – an update,
Anti-fluoridation campaigners often use statistical significance to confirm bias,
Paul Connett “updates” NZ MPs about fluoride?
Paul Connett’s misrepresentation of maternal F exposure study debunked,
Mary Byrne’s criticism is misplaced and avoids the real issues

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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:

Bashash-fig2

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:

Bashash-figs3A

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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Anti-fluoridation campaigner, Stan Litras, misrepresents WHO

stan litras-300x225

Stan Litras, Principal Dentist at Great Teeth, Wellington, and anti-fluoride activist but uses fluoride in his treatments

Wellington anti-fluoride campaigner, Stan Litras, has penned an “open letter” about community water fluoridation (CWF) to the Associate Minister of Health, Peter Dunne. He titles his document  HEALTH RISKS TO NEW ZEALANDERS FROM FLUORIDEbut, as we would expect, it is full of distortions and outright misrepresentations. (I have discussed some of Stan’s previous misrepresentations of the science of CWF in my articles:

A blatant  misrepresentation of WHO recommendations

I will just concentrate here on Stan’s whopper about the World Health Organisation’s (WHO) recommendations on the  of monitoring total fluoride intake for populations considering and implementing CWF. It is central to the recommendations he makes to Mr Dunne.

WHO does recommend monitoring the fluoride ingestion by a population before and after implementation of programmes for supplementing fluoride intake (eg., CWF, fluoridated salt and fluoridated milk). This is to make sure that fluoride intake is neither too low for providing dental benefits or too high when problems of dental fluorosis can occur. However, this following claim of Stan’s is just untrue:

“The World Health Organization strongly recommends that where health authorities implement water fluoridation, they must monitor total fluoride ingestion at the individual level. v

WHO notes that community level analysis is inadequate for assuring safety of all individuals.”

Let’s see what WHO actually recommends. Stan “cites” the WHO document Basic Methods for Assessment of Renal Fluoride Excretion in Community Prevention Programmes for Oral Health,” to support these claims but he does not appear to have actually read the document.

Here is what the WHO document actually recommends:

“public health administrators should assess the total fluoride exposure of the population before introducing any additional fluoridation or supplementation programmes for caries prevention.”

It recognises that:

“Today, there are many sources of fluoride, and this needs to be taken into consideration when planning a community caries prevention programme using fluoride.”

And it concludes from the available research reviews that:

“at present, urine is the most useful biomarker of contemporary fluoride exposure.”

But notes its limitations – such as, the influence of diet (vegetables and meat influence the pH of urine and hence the degree of excretion of ingested fluoride through the urine), within-subject variation, lack of correlation between urinary fluoride excretion and fluoride intake and uncertainty about levels needed to give protection. It quotes the conclusion of Rugg-Gunn et al., (2011) in their book chapter Contemporary biological markers of exposure to fluoride:”

“While fluoride concentrations in plasma, saliva and urine have some ability to predict fluoride exposure, present data are insufficient to recommend utilizing fluoride concentrations in these body fluids as biomarkers of contemporary fluoride exposure for individuals. Daily fluoride excretion in urine can be considered a useful biomarker of contemporary fluoride exposure for groups of people, and normal values have been published.” [My emphasis]

And then goes on to warn:

“Urinary fluoride excretion is not suitable for predicting fluoride intake for individuals.” [WHO’s emphasis]

This is the exact opposite of Stan Litras’s claim. The monitoring must be done at a group level – with proper care to make sure of random selection of people to sample. This publication provides lower and upper margins of optimal fluoride intake and the average daily fluoride excretion recommended for fluoride levels to be optimal.

Just to be clear – the limitations due to diet are not caused by the fluoride content of the foods but their different effects on urine pH and hence the excretion of fluoride in the urine. Random selection of people to sample allows these dietary variations to be averaged out for the group.

In fact, the WHO publication describes the methods for “studies” aimed at monitoring a population or group – not for monitoring individuals. So it does not support Litras’s recommendation that our public health system regularly monitor the fluoride level in individuals. And Stan’s claim that WHO asserts community level analysis is inadequate is completely false. It is, in fact, the individual level analysis that is inadequate.

Using “monitoring” to fear-monger

“Monitoring the fluoride levels in individuals” is central to Stan’s advice to Mr Dunne. He is just fear-mongering as this is neither necessary nor meaningful for the normal person. The before and after monitoring of groups recommended by WHO is simply to check if fluoride ingestion is inadequate before the introduction of fluoride supplement schemes like CWF – and to make sure that, after the introduction of the scheme, fluoride ingestion levels fall within the optimum range.

There is absolutely no suggestion by WHO that normal individuals should be regularly monitored for fluoride levels as Stan is recommending. He want’s to see this because it would cause unwarranted concern in the population.

Most at-risk individuals

While the WHO document recommends “priority is given to children of the
younger ages because of their susceptibility to enamel fluorosis” it does recognise a value in monitoring some adults. For example:

“adults, exposed to fluoride in certain industries (for instance aluminium production, addition of fluoride to water, salt or milk, or exposed to drinking water with excessively high fluoride concentrations).”

These are not normal members of the population – but the increased risk of exposure resulting from their professions could warrant some sort of regular testing regime. I compare this to the monitoring of people working with ionising radiation sources like X-ray machines or handling radioactive isotopes. The wearing of radiation detection badges and regular blood testing is warranted for these people – where it is not for the ordinary person in the street who is exposed just to background radiation and the occasional X-ray.

I imagine, then, that regular individual monitoring could be advisable for water treatment staff handling fluoridating chemicals – and dental technicians and practitioners who handle fluoride containing dental formulations such as varnish and filling materials.

A question to Stan Litras

I know for a fact that Stan Litras uses fluoride-containing dental formulations in his practice. Has he organised for regular testing of himself and his staff for possible fluoride contamination? Is he recommending that any of his patients treated with such material receive regular fluoride testing?

If not – why not?

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