BBC has a report that LC diet increase artery 'furring'

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BBC has a report that LC diet increase artery 'furring' Martin Barrett 01-26-2010
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Posted by Martin Barrett on January 26, 2010, 7:50 am


http://news.bbc.co.uk/1/hi/health/8218780.stm

Posted by Susan on January 26, 2010, 10:58 am


x-no-archive: yes

Michael Eades discusses saturated fat studies:

http://tinyurl.com/yklgays


As I’ve discussed before on these pages, meta-analyses are not my
favorite types of studies. I’ve attacked them when they’ve been used to
‘prove’ the low-fat diets are better, so I can’t very well embrace
meta-analyses when they present a conclusion I agree with. And I really
can’t embrace meta-analyses when they are compilations of observational
studies, which are themselves next to worthless.

For those who don’t know, meta-analyses are compilation studies in which
researchers comb the medical literature for papers on a particular
subject and then combine all the data from the individual studies
together into one large study. This combining is often done to bring
together a collection of studies, none of which contain data that has
reached statistical significance, to see if the aggregate of all the
data in the studies reaches statistical significance. I think these
types of meta-analyses are highly suspect, because they can lead to
conclusions not warranted by the actual data.


To give you an example of what I mean, let’s assume that we have a study
looking at a flipped coin. If a researcher flips a coin 10 times and
comes up with 6 heads and 4 tails, runs this through a program checking
for statistical significance, he/she will discover that the 6-4 ratio
isn’t a statistically-significant difference because of the low number
of overall flips (10). Now, let’s say that 50 researchers did the same
kinds of study and some found that their coins came up heads 6 times out
of 10 or 4 times out of 10, etc. If a researcher then wants to ‘prove’
that heads comes up more times than tails on a coin flip, he/she can
gather all the studies showing heads come up more times than tails, add
them together in a meta-analysis and come up with 25 studies, each with
10 flips, showing that heads came up 63 percent of the time. Now we’re
talking 250 flips and we would probably reach statistical significance.
We know that over the long run a flipped coin is going to come up
heads about 50 percent of the time and that the more the times it is
flipped the more likely the number of heads will close in on the 50
percent figure. But, the meta-analysis that selected the studies
showing the 63 percent heads is statistically significant because the
studies were cherry picked.

Researchers using meta-analyses set up selection criteria to pick which
studies will be included in their final product, which leaves the door
open for all kinds of mischief. For example, let’s say a researcher
wants to make the case that low-fat diets reduce cancer. He/she would
create a set of criteria, do a literature search for all the studies
that meet those criteria, then do a statistical analysis of all the
data. If the data demonstrate that low-fat diets are linked to lower
rates of cancer to a statistically significant degree, the researchers
submit their paper for publication. But let’s say that when the data is
crunched, it doesn’t show any such relationship? It’s easy to go
through all the studies and find which ones strongly show the opposite
of what the researchers want to show and then figure out how to change
the study-selection criteria in such a way as to keep those studies from
being selected, run the whole process again, and repeat until enough
studies are found to make the meta-analysis show the link between
low-fat diets and lower rates of cancer.

Sad to say, this is often how it is done. Which is why I don’t give a
lot of credence to meta-analyses.

But having said all this, I’m still happy to see a researcher with the
academic credentials of Ron Krauss coming out with a meta-analysis
showing no correlation between saturated fat intake and cardiovascular
disease risk. And getting it published in the AJCN, probably the
world’s most prestigious nutritional journal, no less. It’s called
putting your money where your mouth is. Many academics whom I’ve spoken
with admit that there is no correlation, but wouldn’t risk their
academic reputations doing a meta-analysis to ‘prove’ it.

I’ve had many people tell me that it’s really nice to finally see some
studies coming out vindicating saturated fats. Or at least not
attacking them.

I have to tell them that pro-saturated fat studies have been around for
years. Not just observational studies or meta-analyses, but real
controlled studies looking at death rates from heart disease as a
function of fat intake.

Let’s look at a couple.

Posted by Wildbilly on January 26, 2010, 11:56 am



> x-no-archive: yes
>
> Michael Eades discusses saturated fat studies:
>
> http://tinyurl.com/yklgays
>
>
> As I¹ve discussed before on these pages, meta-analyses are not my
> favorite types of studies. I¹ve attacked them when they¹ve been used to
> Œprove¹ the low-fat diets are better, so I can¹t very well embrace
> meta-analyses when they present a conclusion I agree with. And I really
> can¹t embrace meta-analyses when they are compilations of observational
> studies, which are themselves next to worthless.
>
> For those who don¹t know, meta-analyses are compilation studies in which
> researchers comb the medical literature for papers on a particular
> subject and then combine all the data from the individual studies
> together into one large study. This combining is often done to bring
> together a collection of studies, none of which contain data that has
> reached statistical significance, to see if the aggregate of all the
> data in the studies reaches statistical significance. I think these
> types of meta-analyses are highly suspect, because they can lead to
> conclusions not warranted by the actual data.
>
>
> To give you an example of what I mean, let¹s assume that we have a study
> looking at a flipped coin. If a researcher flips a coin 10 times and
> comes up with 6 heads and 4 tails, runs this through a program checking
> for statistical significance, he/she will discover that the 6-4 ratio
> isn¹t a statistically-significant difference because of the low number
> of overall flips (10). Now, let¹s say that 50 researchers did the same
> kinds of study and some found that their coins came up heads 6 times out
> of 10 or 4 times out of 10, etc. If a researcher then wants to Œprove¹
> that heads comes up more times than tails on a coin flip, he/she can
> gather all the studies showing heads come up more times than tails, add
> them together in a meta-analysis and come up with 25 studies, each with
> 10 flips, showing that heads came up 63 percent of the time. Now we¹re
> talking 250 flips and we would probably reach statistical significance.
> We know that over the long run a flipped coin is going to come up
> heads about 50 percent of the time and that the more the times it is
> flipped the more likely the number of heads will close in on the 50
> percent figure. But, the meta-analysis that selected the studies
> showing the 63 percent heads is statistically significant because the
> studies were cherry picked.
>
> Researchers using meta-analyses set up selection criteria to pick which
> studies will be included in their final product, which leaves the door
> open for all kinds of mischief. For example, let¹s say a researcher
> wants to make the case that low-fat diets reduce cancer. He/she would
> create a set of criteria, do a literature search for all the studies
> that meet those criteria, then do a statistical analysis of all the
> data. If the data demonstrate that low-fat diets are linked to lower
> rates of cancer to a statistically significant degree, the researchers
> submit their paper for publication. But let¹s say that when the data is
> crunched, it doesn¹t show any such relationship? It¹s easy to go
> through all the studies and find which ones strongly show the opposite
> of what the researchers want to show and then figure out how to change
> the study-selection criteria in such a way as to keep those studies from
> being selected, run the whole process again, and repeat until enough
> studies are found to make the meta-analysis show the link between
> low-fat diets and lower rates of cancer.
>
> Sad to say, this is often how it is done. Which is why I don¹t give a
> lot of credence to meta-analyses.
>
> But having said all this, I¹m still happy to see a researcher with the
> academic credentials of Ron Krauss coming out with a meta-analysis
> showing no correlation between saturated fat intake and cardiovascular
> disease risk. And getting it published in the AJCN, probably the
> world¹s most prestigious nutritional journal, no less. It¹s called
> putting your money where your mouth is. Many academics whom I¹ve spoken
> with admit that there is no correlation, but wouldn¹t risk their
> academic reputations doing a meta-analysis to Œprove¹ it.
>
> I¹ve had many people tell me that it¹s really nice to finally see some
> studies coming out vindicating saturated fats. Or at least not
> attacking them.
>
> I have to tell them that pro-saturated fat studies have been around for
> years. Not just observational studies or meta-analyses, but real
> controlled studies looking at death rates from heart disease as a
> function of fat intake.
>
> Let¹s look at a couple.

And then there is
http://www.biblelife.org/stefansson2.htm

Don't let the name of the web site weird you out.
--
"Fascism should more properly be called corporatism because it is the
merger of state and corporate power." - Benito Mussolini.

http://news.yahoo.com/s/ap/20100119/ap_on_re_mi_ea/ml_israel_arresting_activists
http://www.democracynow.org/2010/1/19/headlines

Posted by Hueyduck on January 26, 2010, 12:40 pm


Susan a écrit :

>
> As I’ve discussed before on these pages, meta-analyses are not my
> favorite types of studies.
(...)
-
Thanks for the detailed explanation, Susan.
Very instructive.

A bit frightening to see how manipulated numbers might be presented as
facts, but instructive.

Huey

Posted by Kaz Kylheku on January 26, 2010, 6:37 pm


> x-no-archive: yes
>
> Michael Eades discusses saturated fat studies:
>
> http://tinyurl.com/yklgays
>
>
> As I’ve discussed before on these pages, meta-analyses are not my
> favorite types of studies.

Who cares.

> I’ve attacked them when they’ve been used to
> ‘prove’ the low-fat diets are better, so I can’t very well embrace
> meta-analyses when they present a conclusion I agree with. And I really
> can’t embrace meta-analyses when they are compilations of observational
> studies, which are themselves next to worthless.

Meta analyses do have one thing: reproducible, verifiable results.

If you pick the same underlying data as a meta-analysis, and apply the same
transformation, you should be able to exactly reproduce the results of of that
analysis.

Whatever bias there is is apparent in the choice of underlying studies
and the methods used to massage the data.

Direct studies are less trustworthy because they the researcher's blundering,
bias or outright dishonesty can fudge the original data itself. To verify an
original study, you have to re-do the experiments; i.e. conduct a similar
study.

A meta-analysis is shielded from this fudging effect by averaging. It's more
reliable the same way that an index made up of several hundred stocks is a more
reliable market indicator than a single equity.

Even if their data is good, studies can massage it in order to present
biased conclusions that are not true. A meta-analysis can skip these
conclusions and just borrow the raw data.

Speaking of which, a meta-analysis has the advantage of larger data sets
sampled from more diverse populations, which reduces sampling bias.

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