One of the frustrations I have with the fluoridation issue is the refusal of anti-fluoride activists to engage on the science. They will pontificate, but they won’t engage in discussion.
On the surface, one would think there is a difference of opinion or interpretation of scientific issues and that could be resolved by discussion. Yet local anti-fluoride campaigners refuse to enter into discussion. Again and again, I have offered space here to local anti-fluoride campaigners so that they could respond to my articles and they have inevitably rejected the offer. They have also blocked me, and other people discussing the science, from commenting on any of their social media pages or web sites. Even when they, themselves, call for a debate they reject specific responses I have made accepting that call.
So I am left with the only alternative of responding to their claim with an article here – or on a friendly web or blog site. At least that gives me space to present my argument – I just wish I could get some intelligent responses enabling engagement on the issues.
The latest misrepresentation of the science is a claim by the Auckland Fluoride Free NZ Coordinator, Kane Titchener, that “recent research proves fluoridation [is] not needed.“
It repeats the same misrepresentation made by Wellington Anti-fluoride campaigner, Stan Litras, which I discussed in my article Anti-fluoridation cherry-pickers at it again. Kane has either ignored my article, chosen to ignore it or possibly not even understood it.
So here we go again.
“A New Zealand study published in Bio Medical Central Oral Health last month shows dental health improved the greatest extent for children in non-fluoridated areas. There is now no difference in dental decay rates between non-Maori children who live in fluoridated areas and non-Maori children who live in non-fluoridated areas, proving that fluoridation is not needed for children to obtain good dental health.”
Although he doesn’t cite the study (wonder why), his use of two figures from the study show he is writing about the paper:
Schluter, P. J., & Lee, M. (2016). Water fluoridation and ethnic inequities in dental caries profiles of New Zealand children aged 5 and 12–13 years: analysis of national cross-sectional registry databases for the decade 2004–2013. BMC Oral Health, 16(1), 21.
His claim relies on the comparison of data for “non-Māori” children in fluoridated and fluoridated areas. No – he doesn’t misrepresent the data – he just ignores the discussion by these authors of problems with simple interpretation of the data for non-Māori because of the fact it is not ethnically uniform. In particular, he ignores the qualifications they place on the data because of the inclusion in non-Māori of data for Pacifica who have poorer dental health than the rest of this group and live predominantly in fluoridated areas. This, in effect, distorts the data by overestimating the poor oral health for “non-Māori” in the fluoridated areas.
The apparent convergence
The data used in this study were taken from the Ministry of Health’s website. This divides the total population of children surveyed into the ethnic groups Māori, Pacific and “Other.” While the “other’ group will not be completely uniform (for example including Pakeha, Asian, other groups) it becomes far less uniform when combined with the Pacific group to form the non-Māori group.
So, Kane salivates over this figure from the paper especially the plots for non-Māori ethnicities in fluoridated (F) and non-fluoridated (NF) areas.
Yes, that convergence is clear and I can see why Kane is clinging to it – who can blame him. But he completely ignores the warning from the paper:
“It is likely that a substantial driver of this convergence was due to significant changes within the dynamic and heterogeneous non-Māori groups both within and between DHB regions. In effect, the ecological fallacy – a logical flaw whereby analyses of group data are used to draw conclusions about an individual – may be operating within the non-Māori group.”
When the Pacific data is removed (as is the case for the “other” group effectively made up from non-Māori and non-Pacifica) we get the plots below.
Nowhere near as useful for Kane’s confirmation bias and the message he wants to promote. OK – there is still some evidence of convergence from about 2007 on between fluoridated and unfluoridated children. But the graphs do show that community water fluoridation is still having a beneficial effect. And this apparent convergence could be explained by things like the introduction of “hub and spoke” dental clinics after 2004. One problem with this raw data is that children are allocated according to the fluoridation status of the school – rather than their residence. This will lead to incorrect allocation in some cases.
Some data for Pacifica
Just to underline the problems introduced by inclusion of Pacific in the non-Māori group of the study consider the data for Pacifica shown below.
The oral health of Pacifica is clearly poorer than that of the “other” group.
Also, Pacifica make up about 20% of the non-Māori fluoridated group. So they will influence the data for the non-Māori fluoridated group by reducing the % caries free and increasing the mean dmft.
So Kane, like Stan, is blatantly cherry-picking. He is misrepresenting the study – and its author – by ignoring (or covering up) the qualifications regarding the influence of inclusion of pacific in the non-Māori fluoridated group.
Now, I repeat the offer I have made in the past to give a right of reply to both Kane Titchener and Stan Litras. They are welcome to comment here and if they want more space I am happy to give space for separate articles for them in the way I did for the debate with Paul Connett. Now I can’t be fairer than that, can I?
So what about it Stan and Kane? What are your responses to my criticisms of the way you have cherry-picked and misrepresented this New Zealand paper?
NOTE: I have sent emails to both Kane and Stan asking them to respond and offering them right of reply.
UPDATE 1: Great minds and all that – Stan Litras sent out a press release today calling for a nation-wide debate on this issue (see FIND calls for a national debate on fluoridation). However, the seriousness of his request is rather compromised by his reply to my offer of a right of reply to the above article. He did respond to my email very quickly. This is what he wrote:
“Thanks for the offer, Ken, but I have not visited your blog site for a long time, as I object to the way you attempt to defame and discredit me.
You play the man and not the ball, which is not the mark of a reasonable person.
I hope to address that in due course as time permits, but for now I must leave you to indulge yourself without my company.”
So much for his wish for a “national debate” when he will not front up to a critique of his claims about the science.
UPDATE 2: Kane Titchener today also posted a press release today which was the text of the article I discuss in this post (see NZ research proves fluoridation not needed). He also responded quickly to my e-mail. The full text of his response was:
“Who is this?”
Rather strange – considering he often pesters me with emails.
So I guess both of them have turned down my offer.
Also there is no provision for transient population in the study, So a child could move from a fluoridated area to a non fluoridated area and adjust the data by being there with good teeth
I agree, Chris – it is a general problem with this sort of data and the authors discussed these and other problems.
I just though the role of Pacific was interesting because the data is very clear that they will have an influence on the fluoridated population of non-Māori.
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Many people registered as Maori do not have skin as dark as Pacifica people so will not have such a vitamin D shortage as them.
I politely suggest Ken there is little to learn from having a debate with people like yourself, who spend all their time in defending lies and myths rather than seeking the truth. It is a trait of cultists and zealots and their response when they are unable to be constructive is to engage in personal denigration. Sad people and a waste of time engaging with.
What a strange excuse, Trev. Your mates Stan and Kane misrepresented a NZ research paper. I have explained the details of that misrepresentation. I have also offered space for their right of reply where they can explain where they think I am mistaken.
They reject my offer – showing they have no confidence that they can find any flaws in my argument and that they would prefer to continue misrepresenting that research.
Yet you accuse me of defending lies and myths and engaging in personal denigration!
It seems that you think I am personally denigrating someone when I bring their lies and misrepresentation to public attention (while offering them a chance to respond).
You are actually denigrating me with these charges – and showing you cannot actually back them up because you don’t specify any lies or myths.
Yet I have specifically debunked the claims made by your mates. Claims which amount to lies because they have knowingly misrepresented a research paper.
Can you not see that your refusal or inability to actually engage with the points and evidence presented in my article show that in fact your are the one defending lies and myths – and denigrating me at the same time? 🙂
As far as I know there is no “science” around fluoridation, only epidemiological studies, which are not at all the same thing. The latter are of dubious value since there are other possible causes of improvements in dental health: ie good diet, improved diligence in dental care etc. Even if can be shown that fluoride has a prophylactic effect this does not demonstrate the necessity of fluoridating water supplies since nearly all toothpastes contain fluoride these days and, since toothpaste is not ingested, this seems a safer way providing a fluoride treatment. .
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Since you put the word in quotation marks, we have to assume that you use a different definition of science to the rest of the world.
For examples of the real-world science behind fluoridation, including the epidemiological science, Ken’s blog is a reasonable place to start.
I think mikesh meant experimental science where you do things to subjects.
The epidemiological study claiming fluoridation has does not cause IQ deficits, Broadbent, gives only sketchy information on which water supply its control group of about 100 were drinking from. It is not denied some come from Mosgiel whose water is from wells and can have 5mg/litre nitrate. At that level the thyroid may start to be affected which can affect development. I am not suggesting a very severe form of cretinism, but only a small IQ loss. The subjects in the fluoridated group did not have that level of nitrate in their water. IQ loss of fluoridated subects could be equal to the nitrated unfluoridated subjects. So the test is null.
The consensus of science is that fluoride, at the concentrations found in CWF, has no effect on IQ. Many, many investigations have demonstrated that result in the 70 years (3 generations) since the first community water fluoridation.
To overturn the scientific consensus is going to require extraordinary evidence. Your suggestion, based as it is on your personal thoughts about a single paper, has been taken on board, considered, found to be lacking that extraordinary evidence, and discarded.
Stuartg, could you then please explain Ken’s statement on Apr 8 a year ago: “After all, the only published study to compare IQ and community water fluoridation (CWF) is that of Broadbent et al., (2014) “
If you understood science and the scientific method, you wouldn’t have to ask others to explain things to you. (No, I’m not going to explain someone else’s writing to you – it’s up to you to read it both in context and with sufficient education to provide understanding)
If you are saying that the scientific consensus is wrong, then it’s up to you to provide the extraordinary evidence that proves it. Without evidence your thoughts and suggestions are not even hypotheses.
It’s been 70 years since CWF was first introduced. 3 generations.
Show us the masses of research that demonstrate any effect of CWF on IQ, either positive or negative, that has accumulated in that time.
Remember, it’s up to you to provide the evidence to support your thoughts and suggestions. Extraordinary claims require extraordinary evidence.
I gave a lot of football info and football requires sustained braun and brain at top levels.
Now here is some sort of “circumstantial” evidence.
NZHIS have a table of suicide risk in various countries, about 33 of them.
And I’ve got those countries’ average IQs from https://iq-research.org/en/page/average-iq-by-country. (NZ left out unfortunately)
I’ve done a Vassarstats rank correlation and got R = 0.53, with a two tailed p of 0.0014.
So if you think fluoridation nay be improving mental health by preventing tooth pain and helping appearance, the reduction in suicide may really only be a result of a dumbing down effect of fluoride and that dumber people suicide less. Though my quick calculation of NZ fluoridation vs suicide has a 2 tailed p value of only 0.64 so it is really meaningless if it says fluoridation explains about a 1% drop in suicide rate in NZ. Just keep all thought pathways open, please Ken, when you are claiming fluorosis is reducing IQ by affecting self image.
stuartg wrote: “If you understood science and the scientific method, you wouldn’t have to ask others to explain things to you.” I was just pointing out something rather obvious. Ken wrote that Broadbent is the only IQ- fluoridation study. A lot of the “consensus” engendered by the Royal Society therefore must be based on that Broadbent paper. And I challenge it. If Broadbent were confident he would be more forthcoming with the data on the water available to his control subjects, and not just say they came from outer Dunedin suburbs.
Thanks for supplying us with all your extraordinary evidence that shows the scientific consensus is wrong.
Err… my download of Ken’s blog seems to have missed it.
Where is your evidence that CWF has any influence on IQ? As I pointed out, three generations have had CWF, with millions of people drinking fluoridated water over those three generations. Plenty of time and enough numbers for even a tiny effect to be demonstrated.
If there was any effect of CWF on IQ there should be masses of evidence by now.
Show us that extraordinary evidence that supports your claim that the scientific consensus is wrong.
Braun? Eva liked Adolf, but there’s little evidence she enjoyed team sports.
70 years, millions of people, and all you have is “circumstantial” evidence?
Wow… That will really challenge the scientific consensus…
Stuartg, I conceded a high p value. Are you in with the sort of science that keeps quiet about the results?
Sorry about writing braun instead of brawn, brawn being sort of big-muscled for those who don’t know the expression brain or brawn.
Ideas do sometimes fly into different compartments. I think Stuartg thinks of “flight of ideas,” as some sort of illness. But I think it can be useful sort of lateral thinking.
When you asked for more evidence my ideas flew to if fluoridation reduces IQ then might it increase such things as suicide? But as I reported I found a possibility of a reduction in NZ. (I also did a latitude study and that is more and positively correlated.) Fluoride as I said shows a small negative correlation . So I reported it. May be nothing in it or the may be a few lives? Some scientists keep quiet about results.
In this case I decided to look up suicide and IQ, as I reported. I supposed it could mean that more dull people are suiciding and leaving a brighter country. Would need to look up actual IQs of victims.
Now anybody concerned about people might help me with my fluoridation stats I estimated in this table. How can the safety of fluordation really be measured epidemiolgically unles it is very well knowing the fluoridated consort, and that with good water.
Fluoridated? sui risk Vassarstats rank correlation
Northland 0 12.3664550345 R= -0.1097 T= -0.47
Waitemata 0 10.0904416337 P one-tailed 0.3219995
Auckland 1 9.5502498612 P two-tailed 0.643999
Counties Manukau 1 10.1479398459
Waikato 1 11.7693644543
Lakes 0 15.4324002266
Bay of Plenty 0 14.0351547209
Tairawhiti 1 16.3764868126
Hawke’s Bay 0.5 14.2184995605
Taranaki 1 13.5739966248
MidCentral 1 15.0741143958
Whanganui 0 14.8932124976
Capital & Coast 1 8.3818265512
Hutt Valley 0.5 11.4352652424
Wairarapa 1 15.4090863903
Nelson Marlborough 0 11.8606803981
West Coast 0 12.2339124052
Canterbury 0 12.4725544031
South Canterbury 0 17.5056268086
Southern 1 14.8426677221
sui risk from NZHIS
If we are serious about public health perhaps we can scan this sort of thing: “Results: There were 180 suicides amongst subjects with measured IQ. High IQ [measured in childhood] was associated with reduced suicide risk among men (OR per unit increase in age-adjusted model 0.90, 95% CI 0.83–0.99), while there was no statistical evidence of an association in women (OR 1.04, 95% CI 0.90–1.20). Among men with a history of psychosis, high IQ was associated with an increased risk of suicide.
Conclusion: Low childhood IQ at age 13 years is associated with an increased risk of suicide in men but not in women; however, amongst those with psychosis, low IQ appears to be protective.”
So that needs thought which is not just “either or.”
And that justifies the anti-fluoridationists misrepresentation of New Zealand research… How?
Or maybe provides that extraordinary evidence to prove the scientific consensus is wrong about fluoridation… How?
If you are serious about public health, soundhill, then follow the scientific evidence.
ALL of it, not just the fractions of a percent that you can cherry pick and mangle sufficiently so that you think they agree with your viewpoint on the world.
Brian – where are your ethics?
This article (and the next one) provide examples where the local FFNZ has blatantly lied. In this case, they completely misrepresented a recent NZ study. In the next one they completely misrepresented the latest data from the MoH on child oral health.
Ethically you should have been either condemning FFNZ – or debating the issue in an attempt to prove me wrong.
Instead, you attempt to divert attention away from these blatant6 examples of dishonesty by talking about vitamin D, football and suicide!
You are attempting to cover up this dishonesty.
Ken the red-green graph shows in 2004 some 14% difference bertween F & NF non-Maori non-Pacifica, dropping to 5% by 2007. Then after 2011 maybe when sun-safe is gaining momentum, a divergence again.
The blue-green graph show Pacifica teeth 50% apart from non-Maori non-Pacifica, though does not say which year.
Why just promote fluoridation and not see other messages for public health?
Brian – why not engage with the topic – the lies told by FFNZ – instead of attempting a diversion.
What is your opinion? Were the FFNZ people lying about this study and the MoH data?
Ken it seems the lie you point out is because it ignores a difference of 5%. It is something, I agree. Is your import to close that gap?
And you talk ethics, and that really was my entry point, because the argument may be implying identifying Maori and Pacifica as no-gooders, whereas I believe the colour of their skin may be making much difference through vitamin D problem.
If poverty is associated that may also be connected to skin colour – results of vitamin D deficiency, like hypertension and associated morbidity.
I haven’t got time at the moment, but take a look at USA where milk has been supplemented with vitamin D for many years. Dark skinned races may be more lactose intolerant and not show the difference as much as whites.
Lactose intolerant meaning milk may make them sick so they would miss that source of vitamin D.
Brian, my point is that FFNZ has been blatantly lying about the study and the MoH data – and that they dishonestly ignored the discussion of the problems with the non-Maori data in the study.
But it sees you agree with me. FFNZ is lying and should not be trusted.
Ken: “But it sees you agree with me. FFNZ is lying and should not be trusted”
Yes , whether intentionally or not, but if the current difference between fluoridated and non-fluoridated had not been so little I think they would have noticed, or they mightn’t have tried, if they had been trying.
Making out the effect as so great as to be a lie if you gloss over it seems to be another lie, to me.
Reprehensible – so now you accuse me of the lie, Brian. Pathetic.
It’s not a matter of not noticing a small difference. It’s a matter of purposely using a figure when the authors had pointed out the non-Maori data was compromised. FFNZ chose that figure, not because of a small difference, but because of a definite overlap. And in the process they completely ignored, covered up, the discussion warning about the heterogeneous ethnic nature of the data and the loading of the fluoridated group.
That was a definite lie – not a mistake. A mistaken person apologises and withdraws – they don’t go on repeating the lie.
You are incapable of acknowledging the nature of such liars because you indulge in it yourself.
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In your post at 8:33pm on 20 April you said “anybody…might help me with my…stats…in this table.”
Well, my first thoughts are that calculations made to ten decimal places hardly deserve to be called estimates! Calculations made to ten decimal places suggests that the person who made those calculations has no knowledge of error propagation or of significant digits.
The help I would afford is the advice to see a professional about statistics rather than making the assumption that you have the knowledge to make the appropriate calculations yourself. I would also repeat my previous advice to look up Dunning-Kruger.
Stuartg,(Sorry about all the dps. NZHIS did not give the rate and I got the spreadsheet to do it from their other figures.) So far as I know a the usual spreadsheets do not have a way of notating say 0.700, Can they be told how many signiicant figures are input so they spout out the appropriate number in the resutls? can
It is the fluoridation statistic I hoped for help with. I gave a 1 if a principal city or town in a DHB is listed as fluoridated in “Is my town fluoridated?” website. But the DHB covers more than the principal city or town. Knowing Napier and Hastings and associated areas make up about half fluoridated and half not so I gave Hawkes Bay DHB 0.5. Just wondered if someone could do better. The DHBs should I suppose be able to provide those stats since they soon may have to decide risk benefit analysis on fluoridation in their districts. Do you think the “consensus” regarding benefit is the 5% benefit figure for the non-Maori non-Pacifica population in the data Ken has introduced in this thread?
My advice stands: consult a professional, someone who knows what they are doing.
After all, that’s what researchers actually do.
Brian, setting the number of significant figures shown in a spreadsheet cell is a very basic feature in spreadsheets (check cell formatting). If you can’t even get that straight just imagine what other cock-ups you a setting up for yourself.
My advice, keep well away from any statistics package. You will only make yourself look foolish.
Ken and Stuartg
Northland 97 784380
Waitemata 271 2685710
Auckland 215 2251250
Counties Manukau 249 2453700
Waikato 214 1818280
Lakes 79 511910
Bay of Plenty 147 1047370
Tairawhiti 38 232040
Hawke’s Bay 110 773640
Taranaki 74 545160
MidCentral 126 835870
Whanganui 47 315580
Capital & Coast 122 1455530
Hutt Valley 82 717080
Wairarapa 31 201180
Nelson Marlborough 82 691360
West Coast 20 163480
Canterbury 313 2509510
South Canterbury 49 279910
Southern 225 1515900
They don’t give per 100,000 so I divided.
We need to use a bit of nous.
Don’t confuse significant figures and decimal places. Spreadsheets offer a setting for decimal places not significant figures to my knowledge.
West Coast 20 is 2 significant figures because it is a counting number but if it were a measurement on a continuous scale 20 would be only 1 significant figure.
Shouldn’t really have more significant figures in the result than in either of the numbers in the division. For some of those figures it is two and some 3. But that is a rough rule 1 significant figure 2 has a greater percentage error than 1 significant figure 9. Really you are supposed to add the percentage errors when multiply or dividing.
The DHBs would have varying percentage “errors” depending on their population.
What do I do with different percentage errors in a correlation? To be safe I could have kept the error at 5% the figure for West Coast, and also brought everything down to 2 significant figures. But it would have made no difference because it is a rank correlation I was doing which only looks at the relative size of the numbers. I don’t think it would be easy to find a package to do an ordinary Peasron correlation taking into account differing percent errors and adjusting the output p in accordance.
If I had set the number of decimal places in the spreadsheet to 1 before copying and pasting I suggest it would have meant more confidence about percent error than I was prepared to give for some of the figures and less for others, though you may have not realised that. Leaving in all the dps indicated I was not doing any faulty judgement. You may find quite a bit of that in error analysis in research papers.
Now let’s get back to the fluoridation proportions of the DHBs. Yes they are the professionals, it is their job to provide them. But will they bother? It would be nice to have more levels than my very rough 0 0.5 and 1.
Sorry my table should be headed no of sui, population. And watch out if you read that NZHIS material. When giving results for 5 years they add all the years’ populations, too. You may have noticed large figures in my table.
I didn’t bother looking, since it’s not formatted as a table in my browser. Even allowing for the lack of formatting, there’s nothing that could be identified as a header over each (potential) column.
In fact, including numbers greater than people in the province, or in the country, makes it instantly dismissible. (Is that Canterbury population = 2,509,510?)
sui = pigs? sui (generis) = unique individuals?
We find it (very) difficult to follow the terminology you are using in your flight of ideas.
“Don’t confuse significant figures and decimal places.”
You’re using ten decimal places, no-one else. How many of them are significant?
stuartg, sui abbreviation for suicide,
As I said beware because our NZ Health Information Service listed the populations that way adding 5 years.
,Can;t you figure out a table without it being tabulated?
“They don’t give per 100,000 so I divided.”
Divided what by what? Why? What was your reasoning for the division? Where is the independent justification for altering the original figures? Why didn’t the original figures demonstrate your reasoning without alteration?
The original author presented those figures as is. Nothing else was required.
You thought different and manipulated the figures, by your own admission.
Perhaps you had to mangle the figures until you thought that they agreed with your viewpoint?
“,Can;t you figure out a table without it being tabulated?” sic
Not really. One reason that tabulation was invented was to enhance data presentation by the author so that readers would find it easy to understand the author’s presentation of the data.
That reason obviously escaped your attention at intermediate school.
I would reverse the question – why are you unable to tabulate your data in order to make it understandable?
With the population figures you give, in your untabulated table, why does the New Zealand population exceed twenty million?
Yes Stuartg I haven’t seen it done before. Here is what they say: “Table A2: Estimated New Zealand resident population as at 30 June, by District Health Board of domicile, five-year age group and sex, 2008–2012 (aggregated)” and if you divide by 5 you get more understandable figures.
Brian, your discussion of this is inappropriate for a comments section of a blog – and your motive is simply an attempt at diversion from the purpose of the article.
How about you get your own blog where you will be able to format tables to your heart’s content and make all the arguments you want. If your ideas have any credibility people will come to comment on them.
This will also make you appear more genuine as you will no longer be accused of acting like a cuckoo and attempting to divert attention way from the specific arguments of articles in this blog.
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People who don’t know the current population of our country can’t expect to have any credibility when talking about incidence of illness in that (exaggerated, misrepresented) population.
If anti-fluoridationists misrepresent even the population of our country, then how can they expect us to believe anything else they say?
In the figures you use, why does the population of New Zealand exceed twenty million?
Using a New Zealand population that exceeds twenty million (compared with the real figure, easily accessible from census data) questions the veracity of every other part of your non-tabulated table.
I repeat my previous question, the one you neglected to answer: how does your comment justify anti-fluoridationists misrepresentation of New Zealand research?
You neglected to answer before. Here’s hoping…
The Watt St, Mosgiel, well has often been over 5 mg/l nitrate, and the Reid Ave over 4 mg/l. Blue Baby is not the only trouble with nitrate, There can be low birth weight which reduces IQ. In this just-published study it is a bit confusing as to when nitrate vs nitrate nitrogen is being measured. https://www.sciencedirect.com/…/pii/S001393511930218X
I suggest however it was unfair of Broadbent &c’s science not to comment on this nitrate burden that fluoridated areas of Dunedin were not being exposed to.
Sorry try again https://www.sciencedirect.com/science/article/pii/S001393511930218X
I see I am no longer soundhill1.
Brian, read the paper. Birth weight was one of the possible confounders included in the study.
Ken from the study: “On the basis of national nitrate occurrence data and relative risk ratios reported in the epidemiology literature, we calculated that annually, 2939 cases of very low birth weight, 1725 cases of very preterm birth, and 41 cases of neural tube defects could be related to nitrate exposure from drinking water. ” So are they all “confounders.”?
Ken, aren’t they saying?: Those conditions are related to nitrate in the water. Meaning more than just correlated. Then the IQ deficit of those resulting conditions has a calculable cost.
Brian, you, as I, were commenting on the Dunedin study. I simply pointed out that, contrary to your suggestion, birth weight was a factor included in the Dunedin study.
OK Broadbent: “Results. No clear differences in IQ because of ﬂuoride exposure were noted. These ﬁndings held after adjusting for potential confounding variables, including sex, socioeconomic status, breastfeeding, and birth weight (as well as educational attainment for adult IQ outcomes).”
So they determined in their study that no fluoride IQ effect appeared after controlling for birth weight..
But they had found: “.Associations of childhood SES (F=83.94; n=987; P<.001),breastfeeding(F=51.23; n=990;P<.001) and low birth weight (F=5.14; n=992; P=.024) with childhood IQ were statistically signiﬁcant."
It could be that nitrate and fluoridation are producing a bit different low birth weight results and by controlling for birth weight the IQ variation related to it is removed.
Brian, you can’t have it both ways. You initially said that the Dunedin study didn’t take birth weight into account. Now you are saying they shouldn’t have.
You are desperately trying to defend a hypothesis for which there is no evidence.
Ken: “Brian, you can’t have it both ways. You initially said that the Dunedin study didn’t take birth weight into account.”
Rather I said they didn’t take nitrate into account.
Nitrate lowers birth weight and if that effect on IQ is controlled out then the effect of nitrate on IQ will also disappear, won’t it?
So it is not a fair test of fluoridated water against normal low nitrogen water.
I mean the controlling seems to remove from the samples subjects susceptible to damage.
You said the effect of nitrate was via birthweight. That was considered as a confounder. You are simply searching for something to confirm your bias – but surely you are not that naive.
Considered as confounder, like young age might be considered a counfounder in the safety of pedestrians crossing the road. So control it out?
You don’t understand the meaning of control in this situation. It just means to check if something has an influence. I imagine pedestrian age has an influence – its should be a matter of recognising that.
In the Dunedin study, the analysis indicated that birth weight had an influence.
This is like comparing two pedestrian crossings. One has a barrier arm and the other only lights. I suspect less difference between the two if unattended children are not using them (controlled out). When controlling for low birth weight, no difference between the IQs in the fluoridated, non nitrate water supply and the non-fluoridated but nitrate heavy supply.
Broadbent study should have commented on the proportions of low birth weight in each sector.
You don’t understand, Brian. Nothing is “controlled out.” If anything,if developing a prediction give model fi6r IQ, fluoridation would be removed as a risk-modifying factor but things like birth weight, breast feeding etc. would be included.
Controlled out or mathematically held as if constant. Partialled out.
Partial correlation looks at the interrelations of several variables. If a
correlation between two variables is the same as the partial correlation
between the two when a third variable is partialled out in a partial
correlation then it is unlikely that the third variable is causal in any
relation between the two. (And other things can be found.)
I don’t think Broadbent et. al. have been clear about what actions their results were the outcomes of. Whether “controlling for,” that would be “partialling out” low birth weight made much difference. To me they seem as if they could be implying that without “partialling out” low birth weight, they had results they did not like.
You are away with the birds, Brian.
I suggest you take the job on your self. Until you do there is no point commenting here. There is absolutely no point lecturing the scientists about how to do their work if you can’t do it yourself. Put up or shut up.
The arrogance of ignorance.
Ken I won’t have access to the data.