Beware of scientific paper abstracts – read the full text to avoid being fooled

Inaccuracies are very common in scientific paper abstracts. Image credit: Science in the Abstract: Don’t Judge a Study by its Cover

I have come to accept anti-fluoride campaigners will never stop cherry-picking research and findings to support their claims but it annoys me when scientists themselves cherry-pick their findings to support a preconceived belief. I guess it’s only human, but it does reinforce my belief that one should never rely on abstracts to understand a paper – one should read the full text. Abstracts are the very place authors will cherry-pick their findings to promote a preferred theory.

Hilda Bastian wrote “Ivan Oransky from Retraction Watch says it’s “journalistic malpractice” to report on a study after only reading an abstract or press release” (see Science in the Abstract: Don’t Judge a Study by its Cover): 

“To be fair, even though it’s a worry, every inaccuracy isn’t critical. But the spin is serious. It’s not just about language that exaggerates or massages results. It’s also about choosing the most exciting results, even when that’s misleading.

Spin in press releases and media coverage often reflects the spin in abstracts. And until more research is open access, that will be all that most people can get to read. In 17 studies of inconsistencies of all kinds in abstracts of biomedical medical research papers, the rate of major problems ranged from 5% to 45% (median 19%)!”

Here is a rather blatant example in recent findings on possible effects of fluoridation for formula-fed babies. The research findings were reported in two places. Firstly a conference paper:

Till, C., Green, R., Flora, R., Hornung, R., Martinez-Mier, E., Blazer, BFarmus, L., … Lanphear, B. (2019). Fluoride Exposure from Infant Formula and Child IQ in a Canadian Birth Cohort. Environmental Epidemiology, 3.

And secondly, a journal paper which provides a full text and the findings in full:

Till, C., Green, R., Flora, D., Hornung, R., Martinez-mier, E. A., Blazer, M., … Lanphear, B. (2020). Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environment International, 134(September 2019), 105315.

Let’s look at the actual findings and then consider how they were presented in the abstracts of these two reports.

The findings these reports rely on

This is the data taken from Till et al (2020) illustrating the differences in IQ measures for children (3 – 4 years old) living in fluoridated and nonfluoridated areas. Full-scale IQ (FSIQ) is the usual IQ measures and Verbal IQ (VIQ) and Performance IQ (PIQ) are indices resulting from subtests.

The only statistically significant differences are for VIQ (greater for children breastfed as babies living in fluoridated areas) and PIQ (lower for children formula fed as babies living in fluoridated areas)

The authors don’t comment on those results in either report but they also considered possible relationships between measures of fluoride exposure (water-F concentration and an estimate of F intake from formula). Here are the findings for these.

As we can see the relationship with FSIQ and VIQ are not statistically significant, but the ones with PIQ are. It’s a bit strange – and I do not have the understanding of IQ measurements to interpret the fact that while there were no relationships with the normal IQ measure, there were with the PIQ subtest. However, here is a statement from the reference used by Till et al (2020) in the Methods section (Wechsler, D., 2002. Wechsler Preschool and Primary Scale of Intelligence – Third Edition: Canadian. Pearson Clinical Assessment, Toronto, ON, Canada):

“Subtest and profile interpretation methods are not consistent with Standards for Educational and Psychological Testing (AERA, APA, NCME, 1999) and should not be used in clinical decision-making until psychometric support for them is provided. In the words of Weiner (1989), the ethical psychologist will “(a) know what their tests can do and (b) act accordingly” (p. 829).”

The conference abstract

Here is the relevant section from the conference abstract for Till et al (2019). Only FSIQ is discussed and there is no mention of VIQ or PIQ:

“An increase of 0.5 mg/L fluoride concentration (the difference between fluoridated and non-fluoridated region) corresponded to a drop of 4.4 FSIQ points (95% CI: -8.34, -0.46, p=.03) in the formula-fed group. In contrast, this relationship was not significant in the breastfed group (B=-1.34, 95% CI: -5.04, 2.38, p=.48). Controlling for prenatal fluoride exposure weakened the association between water fluoride concentration and FSIQ in the formula-fed group (B=-3.88, 95% CI = -8.12, 0.37, p=.07).
Conclusions: The results, which indicate that fluoride concentration in drinking water was associated with lower FSIQ in children who were formula-fed, underscore the need to reduce the use of fluoridated water to reconstitute formula during infancy.”

So concentration on FSIQ – and special pleading to make the relationship important (we “need to reduce the use of fluoridated water”) despite the fact it is not statistically significant.

OK, I acknowledge p<0.05 is arbitrary and we should not have hangups on that but one should also consider the scatter of the data and how that affects the strength (or in this case weakness) of the relationship. Here is the actual data as presented in Till et al (2020) – that, and the large confidence interval ( -8.12 to 0.37), warn us that any relationship, significant or not, is extremely weak.

[I discussed this in my article Anti-fluoride propagandists appear not to read the articles they promote and mentioned that although I was able to digitally extract about 90% of the data from this figure my statistical analysis was quite different to that of Till et al (2020).This is probably an inevitable result of the large scatter in data points and the very weak relationship – any change in the position of a few data points could have a big effect on the regression result.]

The paper abstract

Here is the relevant section from the full-text paper abstract for Till et al (2020). Now, there is no mention of FSIQ – only PIQ is mentioned:

“An increase of 0.5 mg/L in water fluoride concentration (approximately equaling the difference between fluoridated and non-fluoridated regions) corresponded to a 9.3- and 6.2-point decrement in Performance IQ among formula-fed (95% CI: −13.77, −4.76) and breast-fed children (95% CI: −10.45, −1.94). The association between water fluoride concentration and Performance IQ remained significant after controlling for fetal fluoride exposure among formula-fed (B=−7.93, 95% CI: −12.84, −3.01) and breastfed children (B=−6.30, 95% CI: −10.92, −1.68). A 0.5 mg increase in fluoride intake from infant formula corresponded to an 8.8-point decrement in Performance IQ (95% CI: −14.18, −3.34) and this association remained significant after controlling for fetal fluoride exposure (B=−7.62, 95% CI: −13.64, −1.60).

Conclusions: Exposure to increasing levels of fluoride in tap water was associated with diminished non-verbal intellectual abilities; the effect was more pronounced among formula-fed children.”

Changing the goalposts – but activists don’t care

Before the full-text journal paper was available activists promoted this work – completely ignoring the lack of statistical significance in the relationship – or at least relying completely on the significant relationship when unadjusted for other important factors.

I have said that activists usually don’t bother reading actual papers, sometimes not even abstracts. But we still have activists promoting this research and citing the relationships for PIQ – but still calling it IQ!

For example:


ChristineM@Christi45657364

All the more reason not to ADD F to tap water. Today the 63rd human study linking F with reduced IQ was published. Fluoride exposure from infant formula and child IQ in a Canadian birth cohort: https://www.sciencedirect.com/science/article/pii/S0160412019326145 

Fluoride exposure from infant formula and child IQ in a Canadian birth cohort

Infant consumption of formula reconstituted with fluoridated water can lead to excessive fluoride intake. We examined the association between fluoride…


And


ChristineM@Christi45657364

Example of recent Canadian studies: NIH-funded study: Fluoride exposure from infant formula and child IQ in a Canadian birth cohort https://ncbi.nlm.nih.gov/pubmed/31743803  found children fed infant formula mixed with fluoridated water (vs. unfluoridated) had significantly lower IQ’s.


So, this woman is heavily promoting a paper with misinformation as the story is not about IQ or FSIQ at all. The only significant relationships are with a subtest which we are warned against using anyway. (Mind you, this woman seems to alternate her prolific anti-fluoride tweets with prolific anti-vaccination tasks so we can see she is hardly worried about the truth of her claims).

Reader beware

I have always urged people not to rely on social media, or even mainstrem media, reports about new research but to actually read the scientific reports themselves. But this example makes clear that it is not enough to just read abstracts – a very easy lazy habit to fall back on as there is more work to obtaining the full text of papers.

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January ’20 – NZ blogs sitemeter ranking

Image Credit: Top 10 Blogging Mistakes To Avoid

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

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

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

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

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

Here are the rankings of New Zealand blogs with publicly available statistics for January 2020. Ranking is by visit numbers. I have listed the blogs in the table below, together with monthly visits and page view numbers. Meanwhile, I am still keen to hear of any other blogs with publicly available sitemeter or visitor stats that I have missed. Contact me if you know of any or wish help adding publicly available stats to your bog.

You can see data for previous months at Blog Ranks

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

Fluoridation and sex steroid hormones – or the mouse that roared

All the recent research anti-fluoride campaigners promote as “evidence” of harm from community water fluoridation amount to cherry-picking a very few statistically significant results from a large number of non-significant results. The whole exercise is a bit like the “Mouse that Roared.” Credit: The Mouse that Roared – TMTR Intro animation

Another one of those papers with weak or vague relationships with fluoride intake has just been released and is already being promoted by anti-fluoride activists. These activists probably don’t even read these papers but because they confirm their biases they will promote them anyway.

The evidence in this paper is very poor. A large number of sex steroid hormone measures were investigated. None were significantly related to fluoride in water and very few related to blood plasma F levels.

So this new paper is no better than those I reviewed in What are the recent fluoride-IQ studies really saying about community water fluoridation? (Incidentally, I have updated that article to include the recent paper I had discussed in Sleep disorders and fluoride: dredging data to confirm a bias and provided all the results from that study).

The new paper is:

Bai, R., Huang, Y., Wang, F., & Guo, J. (2020). Associations of fluoride exposure with sex steroid hormones among U.S. children and adolescents, NHANES 2013–2016. Environmental Pollution, 114003.

It uses data from a US database so is relevant to community water fluoridation (unlike most studies promoted by anti-fluoride campaigners which are from areas of endemic fluorosis). Basically, it looks for significant relationships of drinking water fluoride or blood plasma fluoride with three sex steroid hormones (testosterone, Estradiol and sex hormone-binding globulin -SHBG) in male children, male adolescents, female children and female adolescents. So a lot of measures and relationships from which to find significant ones.

The results they found are shown in the three figures below -which are figures 1, 2 and 3 from the paper. The methodology used appears quite confused. Instead of simply reporting regression results for the correlation of the hormone levels with water and plasma F they appear to have divided the fluoride data into tertiles. That is the set of one third lowest values, the set of middle third of the values and the set of one third highest values.

They then report differences between the mean hormone levels in the 2nd and first tertile and differences between the mean hormone levels in the third and first tertile. The p-values in the second to the last column indicates the statistical significance of these differences.

The last column reports a p-value for the “trend” – but this appears to be simply a correlation of the geometric mean hormone level against the median water-F or blood plasma-F for each tertile. That is only 3 sample pairs for each set considered. It is a mystery to me that they didn’t simply report linear regressions of all the values in the sample sets. Perhaps this is the only way they could find anything significant.

It would have been more helpful to present all the data graphically so readers could see how scattered it is. (The confidence intervals shown in the graphics below indicate a large amount of scatter).

There are very few statistically significant results – those shown in red. These were for male adolescents and the total sample where there was a decline in levels of testosterone and estradiol with increaser of blood plasma-F. The result foir the total sample probably reflects the male adolescent result as there was no significant difference between either the second or third tertile and the reference first tertile, or any significant decline, for any of the other groups (male children, female children and female adolescents). There were no significant effects with water-F for these hormones with any of the groups.

Ther only significant effects seen with  SHBG  was a decrease in the SHBG level for male adolescents when comparing the third tertile of water-F with the first tertile. And for female children a decrease in SHBG levels when comparing the values for the second tertile of blood plasma-F against the first tertile.

Conclusion

So all this is a bit like the mouse that roared. Despite claims in the conclusion that the public health applications of their finding “are substantial” I do not think there is anything here for public health experts to get concerned about.

My conclusions parallel those expressed for the cognitive studies in What are the recent fluoride-IQ studies really saying about community water fluoridation?.

This is the sort of picture one might expect from exploratory studies using several hormones for different population groups and several measures of fluoride exposure. While these results may be useful in suggesting possible hypotheses to check in future better-designed experiments they are not sufficiently coherent to inform social health policy.

My conclusions about the recent fluoride studies for levels relevant to community water fluoridation applies equally to this study:

“These recent studies do not provide sufficient evidence for revision of community water fluoridation policies because of possible effects on cognitive abilities. Anti-fluoride activists have only been able to use these studies in their scaremongering propaganda by cherry-picking results and ignoring the weakness of the relationships they cite.”

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What are the recent fluoride-IQ studies really saying about community water fluoridation?

Scaremongering graphic currently being promoted by Declan Waugh who is well known for misrepresenting the fluoride science

This graphic is typical of current anti-fluoride propaganda. It is scare-mongering, in that it is aimed at undermining community water fluoridation (CWF) which is accepted by health and scientific authorities as safe and effective. It relies on citations of recent research to give an impression of scientific credibility – but it misrepresents that research.

In fact, this research has produced confusing and contradictory results based on very weak relationships. Instead of the cherry-picking commonly indulged in by anti-vaccination and anti-fluoridation groups like this, all the findings in these studies must be considered. In this article, I have attempted to graphically present all these findings in one place. This makes clear how weak the evidence these activist groups rely on is and why it does not provide a basis for reviewing the current acceptance of CWF.

I have given below all the reported findings from the recent research (including the citations given by Declan Waugh in the above graphic). There is a lot here (I have not cherry-picked as the anti-fluoride activists do) so I present the findings graphically to provide a complete overview without the boring job of trying to understand  detailed text. My apologies for the length of this article.

NOTE: I recommend readers refer to the cited papers for more details on methodology and definitions of the cognitive measures and F-exposure measures.

Does fluoridation influence IQ?

The answer provided by these modern studies is clearly no. Remember, these studies use data from areas where CWF is used or where drinking water concentrations are similar. They are quite different from the studies (previously relied on by anti-fluoridation activists) from areas of endemic fluorosis where fluoride intake is much higher and where many health problems result.

All the comparisons from fluoridated and unfluoridated areas in these studies are presented in Figure 1 below. The bars represent the standard deviations for the data sets and the data points are the means. A * indicates differences are statistically significant.

Figure 1:  Comparison of IQ results in fluoridated and non0-fluoridated areas

The only statistically significant differences are for verbal IQ (VIQ) of 3-4 year-olds breastfed as babies (where the VIQ of children in fluoridated areas is higher) and for performance IQ (PIQ) of the same group (where the PIQ of children in fluoridated areas is lower). Till et al (2020) had to dig deep, use multiple measures of the cognitive score and subdivide the children into groups, to find an occasional difference. And these differences are contradictory.

I discussed the Till et al (2020) study which reported these occasional differences in Anti-fluoride propagandists appear not to read the articles they promote.

What about the relationships between IQ and measures of F intake?

Anti-fluoride propagandists ignore the data presented in Figure 1 above (and reported in the papers involved) and instead rely on cherry-picked relationships between measures of cognitive ability and various measures of fluoride exposure. Yes, some of these relationships, but only a small proportion, are statistically significant. But, importantly, none of these explain more than a few percents of the variation of the cognitive measure used.

Figure 2 below displays all the results from all the recent studies where linear regressions were used. The coefficient represents the size of the effect (eg., the change in IQ for every 1 mg/L increase of F exposure measure like drinking water F or maternal urinary F) and the bars represent the 95% confidence levels. The statistically significant (p<0.05) relationships are represented by red points while the green data points represent nonsignificant results.

Figure 2: Relationships of cognitive measures with exposure to fluoride obtained by linear regression analyses

Footnote: UF – concurrent urinary fluoride of the child. UFsg – UF adjusted using the specific gravity of urine. MUF – maternal prenatal urinary fluoride. MUFcr MUF – adjusted using urinary creatinine concentration. MUFsg – MUF adjusted using urine specific gravity. FSIQ – Full-Scale IQ. VIQ – Verbal IQ. PIQ – performance IQ. MDI – Mental development index.

Figure 3 below displays the results obtained by Barberio et al (2017) using logical regression of learning disabilities in children aged 3-12 years on urinary fluoride (UF), specific gravity adjusted urinary fluoride (UFsg), and creatinine adjusted urinary fluoride (UFcr). The data used was from two cycles of the Canadian Health Measures Survey (CHMS).

Findings for logical regression of ADHD and ADD on urinary fluoride are also included.

Figure 3: Relationships of cognitive measures with exposure to fluoride obtained by logical regression analyses

There are a lot of reported relationships in these two figures but only a few are statistically significant. Even these are contradictory – Thomas (2014) and Santa-Marina (2019) found positive coefficients while Bashash et al (2017), Thomas (2018), Green et al (2019) and Till et al (2020) reported some negative relationships. Barberio et al (2017) found a positive relationship for the data from combined CHMS cycles but this disappeared when UFsg or UFcr was used. Most of the reported relationships are not statistically significant.

Moving from nonsignificant to significant by adjusting urinary-F figures

This is illustrated by the evolution of the way the results are presented for the Thomas (2014) study which is related to the Bashash et al (2017) study. In this thesis and early conference reports (Thomas et al 2013 & Thomas et al 2014), She did not find any statistically significant relationships of child IQ with maternal urinary F (MUF) or maternal blood plasma F. But she did report a statistically significant relationship with MUFcr in her last conference paper (Thomas et al 2018).

So what happened?

There appears to be a change in the actual mother-child pairs used as indicated by the numbers and this sort of data selection can easily push a nonsignificant relationship into significance – especially when the relationship is so weak (see A conference paper on the maternal prenatal urinary fluoride/child IQ study has problems).

The other factor is that in the 2018 conference paper she has adjusted the MUF figures using creatinine concentration. Use of individual urinary fluoride measures, especially spot samples rather than a 24-hr collection, is a problem and is not a good measure of F exposure. Adjustment of urinary F using specific gravity or creatinine concentration is often used to improve the measure but this is problematic because creatinine concentration is influenced by a range of other factors.  The adjusted MUF figures may actually be acting as a proxy for one of these other factors. This is why Barr et al (2005) recommended that:

“ For multiple regression analysis of population groups, we recommend that the analyte concentration (unadjusted for creatinine) should be included in the analysis with urinary creatinine added as a separate independent variable. This approach allows the urinary analyte concentration to be appropriately adjusted for urinary creatinine and the statistical significance of other variables in the model to be independent of effects of creatinine concentration.”

This is not done by any of the authors of these recent papers where urinary fluoride was used.

Thomas (2014) also reported a positive relationship of concurrent child urinary F (UF) with a cognitive measure, but not for girls. This seems to have been ignored in later reports – and by Bashash et al (2017) which used the same data but only reported the non-significant result for all children.

Till et al (2020) found that only relationships with PIQ were statistically significant. It is not clear why this happened considering no significant relationships were found for FSIQ or VIQ. It’s interesting that Till et al (2019) initially did not report the PIQ results and instead relied on a significant relationship of FSIQ with water F in children formula-fed as babies. Maybe the PIQ measurement is considered unreliable in practice. This finding was also heavily promoted by ant-fluoride campaigners – despite the fact that adjustment for other factors made this relationship nonsignificant (see Anti-fluoride propagandists appear not to read the articles they promote).

Most anti-fluoride campaigners have stuck with the initial FSIQ relationship – although a few who may have read the paper are now cherry-picking the PIQ relationships and ignoring the others.

What about fluoride and ADHD?

Three of these recent studies used linear regression when considering ADHD – but those of Malin & Till (2015) (claimed to be the first study to suggest an effect of fluoridation on ADHD) and Perrott (2018) are important. Not because one of the studies is mine – but because they illustrate a basic problem with correlation studies.

Even when multiple regression is used to adjust for covariants or other possible risk-modifying factors the investigation may miss an important risk-modifying factor. Not only does correlation not prove causation – the “significant” relationships themselves may be false when important risk-modifying factors are not included in the multiple regressions.

This happened with the Malin & Till (2015) study which reported statistically significant relationships of the extent of fluoridation in US states with ADHD prevalence. However, when the mean state elevation was included in the multiple regression of exactly the same data by Perrott (2018) the relationship with fluoridation extent disappeared (this had a p-value of 0.269 whereas those for Malin & Till 2015 were <o.o5). See Figure 4 below.

Figure 4: The effect of including other important risk-modifying factors on reported significant relationships

Figure 5 below shows the data reported by Bashash et al (2018) for the linear regression of a range of ADHD symptoms against urinary fluoride (UFcr).

Figure 5: Relationships of ADHD symptoms with exposure to fluoride obtained by linear regression analyses

The relationships were statistically significant for only four of the ten symptoms considered. Those relationships were very weak, explaining only a few per cent of the variance in ADHD prevalence (see Fluoridation and ADHD: A new round of statistical straw clutching).

The logistical regression results reported by Riddell et al (2019) for ADHD diagnosis and SDQ subscale score Urinary fluoride (UFcr) are given in Figure 6 below.

Figure 6: Relationships of ADHD diagnoses  with exposure to fluoride obtained by logistical regression analyses

I discussed Riddell et al (2019) in my article ADHD and fluoride – wishful thinking supported by statistical manipulation?

This is another case where authors found unpromising results (no significant relationship for UFsg for example) and searched for other measures. It is also interesting that the significant relationships for water F and CWF status disappeared for younger children when age separation was used. The large confidence intervals in most cases indicate a large scatter in the data and very weak relationships.

I should also mention here the nonsignificant relationships reported by Barberio et al (2017) for ADHD and ADD (see Figure 3 above). These just underline how significant relationships are not common in these recent studies when looked at overall.

Update: Fluoride and sleep disturbances

Strictly, sleep disturbances don’t come under the classification of cognitive effects but a recent paper on fluoride and sleep disturbances is being promoted by anti-fluoride campaigners and should, therefore, be included here. For the sake of completeness.

I discussed the paper, Malin et al (2019), in my article Sleep disorders and fluoride: dredging data to confirm a bias. All the findings reported in that paper, and the supplementary files, are presented in Figure 7 below.

The authors report relationships of a range of sleep disorders against two measures of fluoride exposure – blood plasma-F and tap water-F. None of the relationships with blood plasma were significant (most had a p-value of 1.0). I discussed these in Sleep disorders and fluoride: dredging data to confirm a bias. and made the point that that bedtime and waketime were likely to be related to residence and the tap water F was simply acting as a proxy for regional location.

But again we see the use of a large number of measures for a “disorder’ and very few statistically significant relationships which are probably better explained by other factors than fluoride.

Conclusion

Considering all the findings together of the recent studies relevant to community water fluoridation and cognitive factors shows the results are weak, conflicting, and contradictory. This is probably not surprising considering the nature of the data (the studies were basically exploratory using existing databases – not designed experiments). Although adjustments were made for other possibly important factors this does not mean those really important ones (like the relationship of ADHD prevalence to elevation) were included. All the statistically significant relationships found were very weak – explaining a small proportion of the variance in the cognitive measure.

This is the sort of picture one might expect from exploratory studies using a large number of cognitive factors and measure of fluoride exposure. While these results may be useful in suggesting possible hypotheses to check in future better-designed experiments they are not sufficiently coherent to inform social health policy.

These recent studies do not provide sufficient evidence for revision of community water fluoridation policies because of possible effects on cognitive abilities. Anti-fluoride activists have only been able to use these studies in their scaremongering propaganda by cherry-picking results and ignoring the weakness of the relationships they cite.

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.

Barr, D. B., Wilder, L. C., Caudill, S. P., Gonzalez, A. J., Needham, L. L., & Pirkle, J. L. (2005). Urinary creatinine concentrations in the U.S. population: Implications for urinary biologic monitoring measurements. Environmental Health Perspectives, 113(2), 192–200.

Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., … Hernández-avila, M. (2017). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico. Enviromental Health Perspectives, 1, 1–12.

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.

Broadbent, J. M., Thomson, W. M., Ramrakha, S., Moffitt, T. E., Zeng, J., Page, L. A. F., & Poulton, R. (2015). Community water fluoridation and intelligence: Prospective study in New Zealand. American Journal of Public Health, 105(1), 72–76.

Green, R., Lanphear, B., Hornung, R., Flora, D., Martinez-Mier, E. A., Neufeld, R., … Till, C. (2019). Association Between Maternal Fluoride Exposure During Pregnancy and IQ Scores in Offspring in Canada. JAMA Pediatrics, 1–9.

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(1), 17.

Malin, A. J., Bose, S., Busgang, S. A., Gennings, C., Thorpy, M., Wright, R. O., … Arora, M. (2019). Fluoride exposure and sleep patterns among older adolescents in the United States : a cross-sectional study of NHANES 2015 – 2016. Environmental Health, 1–9. Retrieved from https://link.springer.com/article/10.1186/s12940-019-0546-7

Perrott, K. W. (2018). Fluoridation and attention deficit hyperactivity disorder a critique of Malin and Till (2015). British Dental Journal, 223(11), 819–822.

Riddell, J. K., Malin, A., Flora, D., McCague, H., & Till, C. (2019). Association of water fluoride and urinary fluoride concentrations with Attention Deficit Hyperactivity Disorder in Canadian Youth. Submitted to Environment International, 133(May), 105190.

Santa-Marina, L., Jimenez-Zabala, A., Molinuevo, A., Lopez-Espinosa, M., Villanueva, C., Riano, I., … Ibarluzea, J. (2019). Fluorinated water consumption in pregnancy and neuropsychological development of children at 14 months and 4 years of age. Environmental Epidemiology, 3.

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.

Thomas, D., Hu, H., Basu, N., Sanchez, B., Bellinger, D., Schnaas, L., … Tellez-Rojo, M. M. (2013). A prospective study of prenatal exposure to fluoride and neurobehavior : preliminary analyses. Environmental Health Perspectives.

Thomas, D., Hu, H., Basu, N., Martinez-Mier, E. A., Sanchez, B., Bellinger, D., … Tellez-Rojo, M. M. (2014). Urinary Fluoride in Pregnant Women and Prenatal Fluoride Exposure and Mental Development Index ( MDI ) in 1-3 Year Old Infants from Mexico City, Mexico. Environmental Health Perspectives, 1(Icc), 2–3.

Thomas, D., Sanchez, B., Peterson, K., Basu, N., Angeles Martinez-Mier, E., Mercado-Garcia, A., … Tellez-Rojo, M. M. (2018). OP V – 2 Prenatal fluoride exposure and neurobehavior among children 1–3 years of age in Mexico. Environmental Contaminants and Children’s Health, 75(Suppl 1), A10.1-A10.

Till, C., Green, R., Flora, R., Hornung, R., Martinez-Mier, E., Blazer, BFarmus, L., … Lanphear, B. (2019). Fluoride Exposure from Infant Formula and Child IQ in a Canadian Birth Cohort. Environmental Epidemiology, 3.

Till, C., Green, R., Flora, D., Hornung, R., Martinez-mier, E. A., Blazer, M., … Lanphear, B. (2020). Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environment International, 134 (September 2019), 105315.

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December ’19 – NZ blogs sitemeter ranking

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

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

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

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

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

Here are the rankings of New Zealand blogs with publicly available statistics for December 2019. Ranking is by visit numbers. I have listed the blogs in the table below, together with monthly visits and page view numbers. Meanwhile, I am still keen to hear of any other blogs with publicly available sitemeter or visitor stats that I have missed. Contact me if you know of any or wish help adding publicly available stats to your bog.

You can see data for previous months at Blog Ranks

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Fluoridation science and political advocacy – who is fooling who?

misinformation

It is a false balance to equate the advocacy of scientific and medical experts concerned with truth and child health to the advocacy of ideologically-motivated anti-fluoride and anti-vaccination activists known for their misrepresentation of science. Credit: World Congress for freedom of scientific research

I thank Dr Ghali for taking up my offer of a right of reply to my article Scientific integrity requires critical investigation – not blind acceptanceThis sort of discussion is important and I am pleased he took the time to read my article.

Unfortunately, he did not respond to my point about the need to critically examine research findings and claims. Or my point that he seemed to be attempting to “sweep aside” critical reviews which are inherently part of the scientific process. His characterisation of the letter sent by 30 academic and health experts to the US National Institute of Environmental Health Science (NIEHS) about the  Green et al (2019) study (see Experts complain to funding body about quality of fluoride-IQ research) was unjust and simply avoided the necessary discussion.

However, in his reply, he raises a new issue that is worth discussion. That of how scientists should respond to “advocacy positions.”

Equating political and scientific/health advocacy

He says:

“. . we tried in our presentations to shed some light on the controversy, and to show how advocacy positions have focused on attacking both the evidence on benefits of fluoride (e.g., the multi-pronged attacks on Lindsay McLaren’s study on CWF), and the more recent evidence on potential negative cognitive effects in developing brains.”

This characterisation falls into the trap of equating the advocacy of anti-fluoride activists, organisations like the Fluoride Action Network (FAN) and Fluoride Free NZ (FFNZ), who are well known for distorting and misrepresenting the science, with scientific and medical experts who are attempting to present a good faith expert scientific interpretation and critique of current research.

I believe this is a dangerous position because it comes across to policymakers as saying the scientists disagree with each other, that there is not a majority consensus,  and equates the standard of science presented by both sides. This impression is, of course, very much favoured by political activists because it is an easy way of discrediting scientific information, of avoiding the need to properly and objectively consider the information.

I saw this myself when the fluoridation issue was being considered by the local Hamilton City Council in 2013. Councillors were clearly not up to the job of considering the science (and why should they be) so reacted to any attempt to present scientific details by arguing that “scientists disagree with each other,” that there are “two sides to the science.” In the end, they even based their decision on things like the number of submissions as the deciding factor instead of on the science.

Incidentally, the voters in Hamilton did not let the council get away with such a sloppy disregard for the science and of their own previously expressed majority support for fluoridation. A new referendum was demanded and the result confirmed that of the previous referendum showing 70% support for community water fluoridation.

I cannot understand why Dr Ghali promotes this understanding – even to the extent of appearing to favour those who misrepresent the science above those who are attempting a good scientific critique. For example, he describes the anti-fluoride activist attacks on the science merely as “strong” and “rooted in positional anti-fluoride advocacy,” while he refers to “the unusually vigorous attacks on the fluoride cognition studies” and argues these are “seemingly rooted in the challenging findings of those studies. “

Interpreting normal scientific critique as an “attack”

Dr Ghali specifically mentions the fluoridation cessations study of McLaren et al (2016) as being strongly attacked. Part of that “strong attack” was a published critique of FAN members – Neurath et al (2017) – the sort of critique fully acceptable and expected in the scientific community. McLaren et al., (2017) in turn responded to that critique. Again a normal and necessary process in science. In fact, the opening sentence in this response was:

“Thank you for the opportunity to respond. We are pleased to see thoughtful debate in the peer‐reviewed literature and agree that careful consideration of study limitations can stimulate improvement.”

That is how such critiques should be dealt with – welcomed and responded to. That should have been the way to respond to the critique of the 30 scientific and medical experts who responded to the Green at al (2019) study in their letter (see Experts complain to funding body about quality of fluoride-IQ research).

Yet  Dr Ghali’s response to that letter was:

  • He described it as “The notion that you can just talk away 10 years of research.”
  • He leapt to an emotional defence of the authors of the Green study, saying: “I respect the doers of the research and the deliverers of the evidence and don’t think they should be shot for tough messages.”
  • He uses phrases like  “once published it can’t be unpublished” and refers to this critique as “sweeping aside because one disagrees.”
  • And in his response here (see Scientific integrity & fluoridation – Dr Ghali responds) he reverts to this emotional rejection of the normal scientific critique saying  he could not “pretend that the new studies do not even exist or that they are fatally flawed with irrelevant results.”

Ignoring the real political attacks on the science

But where is his emotional response to the way anti-fluoride activists have resorted to disgusting personal attacks on Lindsay McLaren for her work? That is surely unacceptable in any scientific discussion

An example of the personal attacks on Lindsay McLaren for her fluoridation cessation work. Source: Why the anti-fluoride haters are attacking a Calgary academic, calling her a ‘fraud’

Or to the way that these activists have misrepresented and distorted the findings of the Green et al (2019) study?

Image used in advertising campaigns of FAN and FFNZ which completely misrepresents the scientific findings.

This sort of scaremongering advertising has appeared quite widely in newspapers and public billboards in New Zealand and caused a lot of concern among health professionals and their patients.

Who is advocating for what?

The political position of the anti-fluoride activists is clear – they advocate to end fluoridation or prevent it where it is being considered. This advocacy comes from ideological positions as can be seen with their alliance with anti-vaccination activists in Health Liberty and their funding by the “natural”/alternative health industry (eg., Mercola.com and the NZ Health Trust and see Big business funding of anti-science propaganda on health).

But it is simply wrong to put the advocacy of scientific and medical experts as operating at the same level. This is made clear in the letter from the 30 experts (that Dr Ghali dislikes) which says in its summary:

“The aim of science is to gain a better understanding of our natural world and to build a shared knowledge base for the benefit of all. Every scientist is interested in the truth. If fluoride at common levels of maternal exposure does lead to lower IQ scores, we would certainly want to know. This is why transparency related to the Green article is crucial.”

To be clear – the scientific and medical experts are advocating for good science and the health of the public, especially children. That is what drives their legitimate demand for transparency in the science.

So, I think Dr Ghali is disingenuous to present a false balance between the arguments of scientific and medical experts and the ideologically-driven anti-fluoride activists. He is wrong to treat scientific and medical experts as just another “advocacy group” like FAN. And he is especially wrong to use this false balance to ignore or discredit normal scientific critique which is so essential to good science.

Dr Ghali falsely equates the advocacy of anti-fluoride activists as illustrated by this scaremongering billboard with the advocacy of medical and scientific experts who are concerned about child health and want to know the truth.

Dr Ghali’s characterisation of the new fluoride cognitive studies

I also find the way Dr Ghali’s presentation of both the recent cognitive studies and the expert discussion of them disturbing. he says:

“The new cognition studies (led, interestingly, by two Canadian public health research teams) and the ensuing NTP draft report from the US are now such that it would have been absurd for us to pretend that the new studies do not even exist or that they are fatally flawed with irrelevant results.”

Who the hell is pretending that these studies do not exist? How is a rational, good-faith scientific critique of these studies pretending they “do not even exist?”

As for the question of the possibility these studies “are fatally flawed with irrelevant results,” how can anyone ever decide that question if the scientific critique of the studies is not permitted – or thoughtlessly, even emotively, disregarded?

Even Dr Ghali admits these studies have limitations (although I am unaware of any discussion by him of those limitations). Surely an honest scientific discussion of the is work requires a discussion of these limitations – and that is exactly what the letter from the 30 experts did. It listed ten important limitations – yet Dr Ghali wishes to dismiss the letter. He has certainly shown no interest in considering the specific limitations of the study.

These limitations may well mean the results are irrelevant to the question of community water fluoridation. I have argued that in several articles. I think the conflicting and contradictory results from the different papers and different databases (ELEMENT in Mexico City, MIREC in Canada, INMA in Spain, and NHANES in the USA) do suggest the quality of the results mean they should not directly influence health policy. I have also raised the issue of naive presentation of statistical analysis, reliance only on p-values with no discussion of the small size of the effects as indicated by the inability of the relationships to explain more than a few per cent of the variance in cognitive factors. There is also the problem of using a large number of factors with the inevitable p-hacking – a problem which, I believe, is actually quite widespread in science and needs to be countered.

Dr Ghali appears to argue that these new studies are not fatally flawed despite acknowledging they have “limitations” and that the results of the studies are relevant to CWF. But how can he come to that conclusion without making an objective analysis of the study’s methodology, considering the weak nature of the relationships reported? He is certainly not performing a proper scientific review by simply taking the authors’ claims as fact.

Dr Ghali appears to argue that these new cognition studies be given a free pass – that they not be subjected to the normal scientific process of proper peer-review and critical analysis. He appears to be turning a blind eye to the way these studies have been misrepresented and their finding distorted in scaremongering advertising by anti-fluoride organisations. Does he not realise his attitude plays directly into the hands of the ideologically motivated anti-fluoride and anti-vaccination activists? Can he not draw an appropriate conclusion from the fact that his arguments are being promoted by ideologically motivated activists known for their misrepresentation and distortion of science?

Conclusions

If readers think I have been too harsh in my discussion here they should consider that Dr Ghali’s response did not in any way deal with the points I raised about the need for ongoing scientific discussion. In fact, he went further suggesting that I, or others,  may be pretending “that the new studies do not even exist or that they are fatally flawed with irrelevant results.”

That is patently not true as I have critiqued and discussed these studies in a number of articles here – there is no pretence in my position or the position of others who have participated in a principled discussion of the limitations and faults in this work.

I also did not appreciate Dr Ghali’s suggestion that we could “have a chat some time.” In my experience invitations to private chats as a substitute for participation in a good-faith open scientific discussion are simply a bureaucratic attempt to close down that discussion – or to silence a participant.

Another important factor is that while Dr Ghali attempts to discredit those who honestly critique these new cognitive studies from a scientific perspective he is apparently unwilling to criticise anti-fluoride activists who misrepresent the work and use that misrepresentation in scaremongering claims and advertising campaigns. I specifically asked Dr Ghali if he could point me to any video content where he was critical of the anti-fluoride campaigners – so that I could use it in this post as a balance to the video in my article Scientific integrity requires critical investigation – not blind acceptance where he strongly criticises those participating in a scientific critique. He did not respond which make me think he is unable to find anything where he has subjected anti-fluoride activists to the same emotive attack as he leveled at those critiquing the Green et al (2019) paper.

It is sad to see such partisanship in one who has had the responsibility of reviewing the research in this area.

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Scientific integrity & fluoridation – Dr Ghali responds

Video produced by Calgarians for Kid’s Health which is campaigning for the return of Community water fluoridation to Calgary, Canada. Dr Ghali’s presentation to recent Calgary City Council hearings on fluoridation has been promoted by anti-fluoridation activists.

In my recent article Scientific integrity requires critical investigation – not blind acceptance I expressed some concerns with arguments presented by Dr Ghali in his presentation to the Calgary City Council. The video accompanying the article is one that the Fluoride Action Network and Fluoride Free NZ are using in their campaign against community water fluoridation. A campaign which currently concentrates on misrepresentation of recent fluoride-IQ studies – and resorts to blatant scaremonger.

I offered Dr Ghali a right of reply to my article and he has sent me the following. As it arrived in an email form I have edited it slightly but not changed any of the arguments.


I appreciate your indicating in your email below that you sensed that the recent video posted by the Fluoride Action Network might be presenting just a portion of my comments, without the context of my full presentation (and the presentation of key public health colleagues) at the recent City of Calgary committee meeting on community water fluoridation.  That is indeed the case, and I would greatly appreciate your taking a look at the entire presentation if you have time to do so.  Also, the presentation should be viewed in relation to the full O’Brien Institute report on CWF (that I attach for your convenience).

The link to the full special council meeting is below.  Our O’Brien Institute presentations begin at approximately 17 minutes into the 9 hour meeting, and our main presentations last for 55 minutes followed by some Q&A.  We then reappear as a panel (that includes AHS public health leaders) at about 6h40m into the video.

https://pub-calgary.escribemeetings.com/Players/ISIStandAlonePlayer.aspx?ClientId=calgary&FileName=2019-10-28.mp4

At a high level, we tried in our presentations to shed some light on the controversy, and to show how advocacy positions have focused on attacking both the evidence on benefits of fluoride (e.g., the multi-pronged attacks on Lindsay McLaren’s study on CWF), and the more recent evidence on potential negative cognitive effects in developing brains.

I must say that this journey into the fluoride issue has been quite eye opening, as it exposes the challenge of making sense out of a complicated controversy (– which is, interestingly, the name of your organization…[in my email I had included my position as a scientific advisor for Making Sense of Fluoride]).  You will see in the opening part of my presentation to the City of Calgary that there is an interesting and extensive body of literature on the challenge of integrating science and advocacy (and balancing science vs. advocacy).   The matter of CWF is a particularly challenging one in that regard, as the strong attacks on, for example, the CWF cessation studies (including Lindsay McLaren’s), are rooted in positional anti-fluoride advocacy, just as the unusually vigourous attacks on the fluoride cognition studies are seemingly rooted in the challenging findings of those studies (– both MIREC and ELEMENT are, after all, both NIH-funded prospective cohort studies unlike any of the prior cognition studies, that despite some limitations are clearly also more notable studies than the cognition studies that preceded them).

The O’Brien Institute was tasked with providing Calgary City Council with a non-positional description of the existing studies and evidence.  The new cognition studies (led, interestingly, by two Canadian public health research teams) and the ensuing NTP draft report from the US are now such that it would have been absurd for us to pretend that the new studies do not even exist or that they are fatally flawed with irrelevant results.

Do watch the entirety of the City of Calgary CWF committee meeting, and let me know if you would like to have a chat some time.   And thank you again for your email.


I am still concerned about the way Dr Ghali presents this issue but he also raises an important point about advocacy which needs discussion. So I will be responding to this post with a blog article ion a few days.

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Sleep disorders and fluoride: dredging data to confirm a bias

Sleep disorders are common and have many causes. But anti-fluoride activists will now be blaming them on community fluoridation. Image credit: Sleep Disorders and Problems

There is a pattern to the recent research aimed at finding a link between fluoridation and cognitive deficits, ADHD prevalence or possible thyroid problems. These researchers are simply using large databases from recent health surveys (ELEMENT in Mexico City, MIREC in Canada, INMA in Spain, and NHANES in the USA). Connecting these up with available measurements of drinking water fluoride, their own measurements of urinary or blood plasma fluoride using stored samples from the surveys, or even their own unvalidated estimates of fluoride dietary intake, they then search for statically significant (p < 0.05) relationships.

This gives them a large amount of data to search for effects – and as the p-hacking tool in my recent article, Statistical manipulation to get publishable results, shows – they will, of course, find them. They might have to use different fluoride measure to get a statistically significant result – but they have several to choose from: drinking water F, community water fluoridation, urinary F for the individual or his/her mother, blood plasma F and their own subjective estimate of dietary F intake.

In my last article, Some fluoride-IQ researchers seem to be taking in each other’s laundry, I discussed the biased peer-review process used in a new paper from the research and commented:

“One might expect that the need to use an open-access journal like Environmental Health and to choose “in-house” peer-reviewers indicates that the quality of the paper might not be the best.”

I was correct – this is another poor quality paper on fluoride and health effects which make unwarranted claims – and which will be used by anti-fluoride activists in their campaign against community water fluoridation.

This is the paper citation:

Malin, A. J., Bose, S., Busgang, S. A., Gennings, C., Thorpy, M., Wright, R. O., … Arora, M. (2019). Fluoride exposure and sleep patterns among older adolescents in the United States : a cross-sectional study of NHANES 2015 – 2016. Environmental Health, 1–9.

Multiple parameters to dredge

The researchers had a list of parameters to work with. Sleep duration, sleep apnea symptoms, snoring, daytime sleepiness (subdivided into rarely, sometimes, often and almost always), trouble sleeping, bedtime and wake time. Ten sleep disorder measures. The authors searched for statistically significant relationships of these with two fluoride measures: household tap water fluoride and blood plasma fluoride.

See the problem here? If not have a look at Statistical manipulation to get publishable results, and have a go with the p-hacking tool.

Blood plasma fluoride

In a bit of special pleading involving subgroups divided by gender they report:

“Among males, higher plasma fluoride concentrations were associated with higher odds of reporting sleep apnea symptoms, although this did not reach the threshold for statistical significance (uncorrected p = 0.17).”

And added:

“Plasma fluoride concentrations were not significantly associated with any of the other sleep outcome measures examined herein”

So nothing here. Despite using ten different sleep disorder measures and looking at subgroups there were no statistically significant relationships with blood plasma F.

Water fluoride

The tap water fluoride concentrations were mostly below 0.7 mg/L with mean and median values of 0.35 and 0.29 mg/L. There was no differentiation between community water fluoridated and non-fluoridated areas, but water fluoridation covers a high proportion of US citizens.

The only statistically significant relations shown by regression analyses were for sleep apnea, snoring, bedtime and waketime. Two out of ten sleep disorder measures or four out of ten if one counts different bedtime and waketime as disorders.

Bedtime and wake time

The paper reports that:

“fluoride exposure may be associated with shifts in the sleep-wake cycle, as higher water fluoride concentrations were associated with later weekday bedtime and wake time, but not sleep duration. Specifically, for each 0.52 mg/L increase in adolescents’ water fluoride concentrations, they tended to report going to bed 24-min later and getting out of bed 26-min later. “

 

Why should a different bedtime or wake time be considered sleep disorders – especially as no change in sleep duration occurs?

I think they are indulging in special pleading by attempting to find a reason for this in calcification of the pineal gland. This idea rests on an old observation that calcified pineal glands taken from elderly cadavers are high in fluoride. This is easily explained by the fact that fluoride is attracted to active calcified tissue. Calcification is caused by old age, calcium and phosphorus – not by fluoride. Fluoride is adsorbed by calcified tissue after calcification.

They do acknowledge as a limitation of their work that:

“participants were older adolescents who may be prone to sleep disruptions for various reasons, including playing video games, studying, working at jobs or having social influences, for example.”

Well, yes. And these social influences, jobs, etc., will be more common for adolescents living in cities which are more likely to have community water fluoridation than in rural and small-town areas.

Why were such “sleep disturbances” even included in their study? And why indulge in such fanciful reasoning to “explain” the result.

Snoring

The authors report that:

“each 0.52 mg/L increase in household tap water fluoride concentration was associated with a 38% reduction in the likelihood of male adolescents reporting snoring.”

Maybe young men living in cities and having an active social life are less likely to admit to snoring than their counterparts in rural areas. But the authors again indulge in fanciful reasoning by speculating:

“that our findings may point to a role of fluoride exposure in disrupting this deep sleep stage, thereby reducing opportunities for snoring.”

Or, alternatively”

“another possibility is that the gains in oral health from consumption of fluoridated water may protect against tonsillar infections that can contribute to snoring .”

Perhaps surprising that they are discussing a possibility of beneficial effects of fluoridation but they concede that:

” Future studies are needed to explore potential mechanisms by which fluoride exposure may reduce self-reported snoring.”

Perhaps a more reasonable future study will find absolutely no effect of fluoridation on reported snoring if it includes more relevant factors in its multiple regressions. Remember how Malin & Till (2015) reported a significant positive relationship between fluoridation extent and ADHD prevalence in the USA – yet when more relevant factors where included in the multiple regression the relationship with fluoridation disappear (see Perrott 2018).

Sleep apnea

Only about 10% of the participants reported symptoms of sleep apnea at least once a week. Yet the paper report they found:

“that each 0.52 mg/L increase in household tap water fluoride concentration was associated with a 1.97 times higher likelihood of adolescents reporting having experienced symptoms suggestive of sleep apnea at least once per week.”

Well, there was a very large spread in the data with a confidence interval of 1.27 to 3.05.

On this basis they argue:

“This suggests that fluoride exposure at population-relevant levels may be a risk factor for sleep disturbances; however, additional studies are needed to explore this possibility, given the scarcity of data on this topic.”

Again, perhaps a more reasonable future study will find self-reported sleep apnea is related to living in a city or some other factor rather than fluoride. The results found in this study should not be used to argue that sleep apnea is caused by fluoridation. But, of course, that will not stop the anti-fluoridation activists from doing so.

Speculation without action is arrogant

I submitted a paper to a journal once where I speculated on mechanisms which could explain the associations I had found. One of the peer-reviewers pointed out that speculation was worthless in itself and that I should actually do some measurements to test the proposed mechanism before publication.

The reviewer was quite right – it was arrogant of me to think that my speculation had any scientific worth when it was not supported by data. I was simply resting on an assumed authority or credibility. But most proposed ideas in science turn out to be wrong. Speculation only has value when it is converted to a hypothesis and tested.

I did the experiment to test my speculated hypothesis, included it in my revised paper which was then published (and turned out to be a more valuable contribution). Perhaps this sleep disorder paper would have had more significance if one of the peer reviewers had made a similar comment and the authors had then set out to test some of their speculations. But fat chance of that happening when the peer-reviewers were selected from colleagues who already have a bias for finding similar effects of fluoride (see Some fluoride-IQ researchers seem to be taking in each other’s laundry).

The problem with this sleep disorder paper and other recent papers reporting relationships between fluoride and cognitive effects is that they are only reporting fishing expeditions. They simply report the results of searching through data sets containing a whole range of parameters to find statistically significant relationships. They put all their faith in the p-value so that the relationship appears important even when the effect size is small and explains a minuscule amount of the variability. In itself, a p-value can say absolutely nothing about the cause of an observed relationship or be used to claim an effect. That requires further work.

Nothing wrong with statistical fishing exhibitions like this. I also enjoy searching through data looking for relationships. But that is only the start. Identification of relationship can suggest research – experiments or survey aimed at identifying causes.

I don’t think there is any value in simply reporting the results of fishing expeditions without further research. Such papers only serve as an outlet for unwarranted and unsupported speculation – and as I say above that is arrogant. Why should anyone else take such speculation as evidence or identification of a cause?

Trouble is when one has a bias to confirm one can eagerly clutch at this sort of speculation and promote it as a real effect. When speculation like this is promoted by anti-vaccination or anti-fluoridation activists it can end up undermining effective social health policies – and that is bad.

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Some fluoride-IQ researchers seem to be taking in each other’s laundry

Image credit: Publish Peer Reviews. Illustration by David Parkins

Scientific peer-review is often touted as a guarantee of the quality of published research. But how good is peer-review? Does it guarantee poor science is weeded out? Or is it sometimes simply a bureaucratic manipulation aimed at endorsing a paper – despite its poor quality.

Any scientist with experience in publication and peer review knows that real-world peer-review is often poor. In fact, the whole process of peer review is being questioned these days because it doesn’t seem to work, is not taken seriously by many viewers who see it as an unpaid imposition on their time, and is open to manipulation by authors, journals and scientific cliques keen on promoting their own research and preventing publication of others.

I mentioned some of the problems from my own experience of scientific publication in Peer review – an emotional roller coaster and Peer review – the “tyranny” of the third reviewer and discussed the issue further in Sceptical humility and peer review in science. But I gave more specific examples of problems related to the peer review of papers that are often promoted by anti-fluoride campaigners in my articles Peer review, shonky journals and misrepresenting fluoride sciencePoor peer review – and its consequences, and  Poor peer-review – a case study

The last two articles discussed in detail the peer review of a paper reporting a relationship between fluoridation and ADHD prevalence in the US – Malin & Till (2015): Exposure to fluoridated water and attention deficit hyperactivity disorder prevalence among children and adolescents in the United States: an ecological association. This was later shown to be flawed as the relationship with fluoridation disappeared when other risk-modifying factors were included – see Perrott (2018): Fluoridation and attention deficit hyperactivity disorder a critique of Malin and Till (2015). But the poor, and biased peer-review of this paper may be a major reason for its publication despite its flaws.

The journal which published Malin & Till (2015), Environmental Health, makes the names of peer reviewers public and provides their reports. This is unusual – less than 3% of scientific journals do this despite the fact that about 60% of researchers favour open reports (see Publish Peer Reviews). Open access to the peer-review reports, in this case, provided a unique insight which enabled me to elucidate the relationships between the reviewers and authors, and the particular biases of the reviewers  (see Poor peer review – and its consequences, and  Poor peer-review – a case study).

Now the same journal has published a new paper – the first author is Ashley Malin of the Malin & Till (2015 paper) and one of the two peer-reviewers was Christine Till – the other author of the Martin & Till paper).

An incestuous peer-review by the journal?

This is the paper citation:

Malin, A. J., Bose, S., Busgang, S. A., Gennings, C., Thorpy, M., Wright, R. O., … Arora, M. (2019). Fluoride exposure and sleep patterns among older adolescents in the United States : a cross-sectional study of NHANES 2015 – 2016. Environmental Health, 1–9.

The reviewer’s comments and Ashley Marlin’s responses were made available by the journal (see the Open Peer Review Reports).

The second reviewer was Mara Tellez-Rojo. She is a co-author of several papers published from the prenatal maternal urinary F – Child IQ study in Mexico City, and along with Christine Till author of the Mexico city prenatal maternal urinary F – Child ADHD paper. The image below uses some links I found through published papers to illustrate the incestuous relationship between the main author of this paper and the two peer reviewers

Relationships between Malin and her peer reviewers as indicated by joint publications. Links to the papers listed from the top are: Malin & Till (2015) Thomas et al (2014)Bashash et al (2017), Marlin et al (2018), Malin et al (2018)Bashash et al (2018)Thomas et al (2018), and Riddell et al (2018)

These people are taking in each other’s laundry. In effect, this journal peer-review of this paper was only an “in-house” review – one you might expect from work colleagues. A good journal peer-review should involve outsiders – and should avoid including coworkers and cooperators in research programmes.

The journal

Environmental Health is an “Open Access” journal. Authors pay to be published (in this case about US$2500) – which is never a sign of good quality. Authors also appear to often choose their reviewers – or at least suggest them and leave the final choice to the editors.

The Chief Editor of this journal is Phillipe Grandjean who is known to have sympathies for the anti-fluoride movement – often being used as an authority for statements about new research the anti-fluoride movement promotes. He is the author of the paper Grandjean and Landrigen (2014) that anti-fluoride people love to use as evidence of fluoride neurotoxicity – but in fact, only references Chinese studies from endemic fluorosis areas.

More importantly, in my experience, he demonstrates bias in the way he manages the journal. He refused to allow the journal to even consider my critique of the Malin & Till (2015) ADHD paper which was published in his journal. I describe this refusal in my article Fluoridation not associated with ADHD – a myth put to rest

My paper was eventually published in another journal (Perrott 2018) – but this has made it very easy for Christine Till’s group to studiously ignore it in their publication discussions – despite being very well aware of it.

The quality of Malin et al (2019)

One might expect that the need to use an open-access journal like Environmental Health and to choose “in-house” peer-reviewers indicates that the quality of the paper might not be the best. I believe that is the case and will make my own critique of the paper in a post here soon.

Conclusions

For all its faults as an “open source” journal which enables publication for a fee and has a suspect peer-review process, Environmental Health does sometimes make the names of peer-reviewers, the content of their reviews and the responses of authors public. This has been very useful in the case of Malin & Till (2015) and Malin et al (2019) as it shows how authors and peer-reviewers are sometimes “in-house” reviewers who take in each other’s laundry.

I have been critical of the quality of the fluoride-IQ and fluoride-ADHD and similar papers coming from Christine Till’s group. The naive use of statistics (for example relying on p-values rather than providing a full statistical analysis), the lack of transparency for some of their methodology, the biased choice of citations meaning they ignore work which does not support their claims, their bias in the discussion of their results, and their promotion of their findings is concerning. Especially considering how they attempt to make their findings relevant to public health policy and their claims and statements are promoted and supported by the anti-fluoride movement.

Others are also concerned. Recently 30 academic and health experts wrote a letter to the funding body which had financed some of the work of Till’s group. The letter outlined ten important concerns and requested public release of the data for one of Till’s papers so that it could be independently analysed (see Experts complain to funding body about quality of fluoride-IQ research).

I  suspect that if the peer-reviewers of other papers from Christine Till’s group, and the content of there reviews were made public we could see a similar situation to that found for Malin & Till (2015) and Malin et al (2019).

Perhaps if more journals followed Environmental Health’s policy of transparency about peer-reviewers and their comments authors would be less likely to choose colleagues for peer review. This practice of taking in each other’s laundry is not good for science.

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Statistical manipulation to get publishable results


I love data. It’s amazing the sort of “discoveries” I can make given a data set and computer statistical package. It’s just so easy to search for relationships and test their statistical significance. Maybe relationships which we feel are justified by our experience – or even new ones we hadn’t thought of previously.

It’s a lot of fun. Here’s a tool readers can use to explore a data set involving information on US Political leadership and the US economy –Hack Your Way To Scientific Glory (The image above shows the tool but it’s only an image. WordPress won’t allow me to embed the site but you can access it by clicking on the image).

Try searching for relationships between political leadership and the economy. If you can find a relationship with a p-value < 0.05 you might feel the urge to publish your findings. After all, p-values < 0.05 seem to be the gold standard for scientific journal these days.

Statistical manipulation a big problem in published science

Problem is, by playing with this data you could producing statistically significant relationships that “show” both Republicans and Democrats hurt the economy, or that both are good for the economy. It’s simply a matter of choosing the appropriate factors to define political leadership and appropriate factors to measure the economic situation.

The process is called p-hacking or data dredging. Time spent playing with this tool should convince you that it is easy to confirm one’s own political biases about political leadership and political parties using statistical techniques. It should also convince you this is very bad science. But, unfortunately, it happens. Even respectable journals will publish papers reporting relationships obtained by p-hacking, provided a p-value of less than 0.05 can be shown.

The article Science Isn’t Broken: It’s just a hell of a lot harder than we give it credit for includes the p-hacking tool and discusses how widespread the problem is in the published scientific literature. It also describes the concern that statisticians and scientists have about this sort of publication.

The author, says:

“The variables in the data sets you used to test your hypothesis had 1,800 possible combinations. Of these, 1,078 yielded a publishable p-value, but that doesn’t mean they showed that which party was in office had a strong effect on the economy. Most of them didn’t.

The p-value reveals almost nothing about the strength of the evidence, yet a p-value of 0.05 has become the ticket to get into many journals. “The dominant method used [to evaluate evidence] is the p-value,” said Michael Evans, a statistician at the University of Toronto, “and the p-value is well known not to work very well.”

Statistical manipulation and p-hacking in fluoride studies

In my articles on the way scientific papers relating to fluoridation are misrepresented, I have often referred to the misleading use of p-values to argue that a study is very strong or a relationship important. Paul Connett, head of the Fluoridation Network (FAN), often uses that argument. (see for example  Connett fiddles the data on fluoride, Connett misrepresents the fluoride and IQ data yet again, and Anti-fluoridation campaigners often use statistical significance to confirm bias).

But I have noticed p-hacking and data dredging are real problems with some of the more recent studies of fluoride and IQ. Partly because these papers are being published by some reputable journals. Also because some reviewers and scientific readers seem completely unaware of the problem and therefore are uncritically taking some of the claimed findings at face value.

I have gone through some recent papers on this issue and pulled out the factors used to represent child cognitive abilities and to represent F exposure or intake. These are listed below for 7 papers and a thesis.

Study Cognitive factor F exposure
Malin & Till (2015) ADHD prevalence in US states Fluoridation extent in US states
Thomas (2014) WAS)
Bayley Infant Scales of Development-II (BSID-II)
MDI
MUF
Blood plasma F
Concurrent child urinary F
Bashesh et al., (2017) CGI
FSIQ
VIQ
MUFCr
Concurrent child urinary FSG
Bashesh et al., (2018) ADHD
CRS scores
3CPT scores
MUFCr
Thomas et al., (2018) MDI MUFCr
Green et al., (2019) FSIQ* boys
PIQ* boys
VIQ ns
Sex
MUFCr
Sex
Fluoridation
Estimated F intake by mother
Riddell et al., (2019) SDQ hyperactive/inattentive score
ADHD – parent-reported or questionnaire
MUFSG
Water F
Age
Till et al., (2020) FSIQ
PIQ
VIQ
MUF
Water F
Fluoridation
Santa-Marina et al (2019) perceptual-manipulative scale
verbal function,
perceptive-manipulative
general cognitive
MUF

Footnotes (see papers for full information):
MUF – Prenatal maternal urinary F
MUFCr – Prenatal maternal urinary F adjusted using creatinine concentration
MUFSG – Prenatal maternal urinary F adjusted using specific gravity
Concurrent child urinary FSG – child urinary F at the time of IQ assessment adjusted using specific gravity
CGI – general cognitive index
FSIQ – Full-Scale IQ
PIQ – Performance IQ
VIQ – Verbal IQ
MDI – Mental development index
WASI – Wechsler Abbreviate Scale of Intelligence

As you can see, just like the political leadership/economy example illustrated in the p-hacking tool above there is a range of both cognitive measurements and fluoride expose factors which can be cherry-picked to produce the “right” answer (or confirm one’s bias). Most of these studies can also select from up to three cohorts. So it’s not surprising that relationships can be found to support the argument that fluoride has a negative effect on child cognitive abilities. But we can also find statistically significant relationships to support the argument that fluoride has a positive effect on cognitive abilities. Or, alternatively, that fluoride has no effect at all on cognitive abilities.

Another warning sign is that the relationships that are cited (and which have p-values < 0.05) are all extremely weak and explain only a few per cent of the variance in the data. While the complete statistical analyses are not given in most of the papers (another big problem in published research) the figures show a very high scatter in the data and the quoted confidence intervals confirm this.

Even where p < 0.05 the data can be extremely scattered and the relationship so weak as to be meaningless. Figure 1 from Till et al., (2020)

Yet another warning sign is that when relationships are reported they are only true for different cognitive factors or different fluoride exposure factors. And again, they may only be true for one sex or for a limited age group.

Conclusion

Geoff Cumming wrote in A Primer on p Hacking that:

“Statisticians have a saying: if you torture the data enough, they will confess.”

We should always remember this when reading papers which rely on low p-values to support a relationship. I think this is a big problem in a lot of published science but it is certainly a problem with the fluoride-IQ research currently being published.

The real take-home message from this particular research is that all the reported relationships are extremely weak, the data has been “tortured,” and it is easy to select parameters to produce a relationship with a p-value < 0.05 to confirm a bias.

In fact, the results from these studies are contradictory, confusing and extremely weak. They may be useful to political activists who have biases to confirm or ideological agendas to promote. but they are not sufficient to influence public health policy.

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