
The relationship between telomere length and diet (2016) - discombobulate
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944490/?report=classic
======
mchannon
A lower T/S ratio is associated with advanced age (had to dig hard to find
that one- check out page 9 of this paper:
[https://www.rug.nl/research/genetics/students/internships/an...](https://www.rug.nl/research/genetics/students/internships/anastassiablanter_bsc_thesis.pdf)).
In other words, high T/S = good.

As far as statistical correlation, the p-value of 0.02 (lower, and further
away from 0.05, is better) is pretty strong.

Where this article fails to convince me to start waving red meat in the faces
of all the vegs I know is the limited sample size of a couple dozen people.
Maybe there's some protective factor in red meat, or maybe their small sample
size just overrepresented young carnivores and old vegetarians.

~~~
marze
This study should be replicated with n > 200.

~~~
relyks
Doesn't a sample size need to be at least 30 to be statistically significant?

~~~
naasking
P value is a measure of statistical significance. Sample size doesn't matter
as much as most believe, as long as your p value is really low.

~~~
hedora
P values can't save you if the number of diverse subpopulations in the general
population is larger than your sample size. Also, they break the two dozen
people into many groups, so they've implicitly tested many hypotheses.

Even if they did the stats right, there can be hidden causality at play with
samples this small. Maybe 100% of the people that don't eat red meat in their
sample grew up in poor households with poor nutrition, or maybe they all live
in the arts district, which is close to an industrial polluter.

Anyway, it looks like it is worth further study with larger samples, but I
don't think you can draw any actionable conclusions from the current study.

------
Mz
_Physical activity... was not related to telomere status._

Other studies say the opposite:

[https://www.ucsf.edu/news/2013/09/108886/lifestyle-
changes-m...](https://www.ucsf.edu/news/2013/09/108886/lifestyle-changes-may-
lengthen-telomeres-measure-cell-aging)

[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2581416/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2581416/)

[http://www.edinformatics.com/news/exercise_and_aging.htm](http://www.edinformatics.com/news/exercise_and_aging.htm)

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tomrod
Note: as an observational study, this is not the final word on the subject. A
p of 0.02 being the strongest evidence may also be the result of p-hacking.
More research is needed. Causal studies should be performed to confirm.

Further, the sample size is exceptionally low (n=28).

~~~
heisenbit
It is even worse, there were only 7 male participants. Imagine - of course
totally theoretical - that men eat more red meat then the study may attribute
the fact that men age faster to red meat.

~~~
astrange
That would make sense, for the same reason men's vitamins don't have iron in
them.

------
DangerousPie
I am extremely skeptical about the statistical analysis here.

It sounds like they tested nine food types, eight beverages and then even
tried out different types of comparisons for each food/beverage. And the best
p-value they observed was p=0.02:

"Among nine food types (cereal, fruits, vegetables, diary, red meat, poultry,
fish, sweets and salty snacks) and eight beverages (juices, coffee, tea,
mineral water, alcoholic- and sweetened carbonated beverages) only intake of
red meat was related to T/S ratio. Individuals with increased consumption of
red meat have had higher T/S ratio and the strongest significant differences
were observed between consumer groups: “never” and “1–2 daily” (p = 0.02)."

Nowhere in their methods do they mention adjusting for multiple testing. If we
do that using the standard Bonferroni approach, the p-value would have to be
multiplied by a factor of at least 17 x 2 to account for the number of options
that they tried. So the adjusted p-value would be 0.02 x 17 x 2 = 0.68 and
thus far from statistical significance.

In other words, this seems to be a real-life example of this:
[https://xkcd.com/882/](https://xkcd.com/882/)

Maybe I missed something, but if this is really the case then it's
embarrassing that this made it through peer review.

~~~
kerkeslager
I'm curious about multiple testing. Could you explain (our rather, link
something that does)?

~~~
veddox
Put simply: if you test a random event often enough, you're going to get lucky
eventually.

In statistics, the question everybody asks is whether or not a given result is
"significant". To answer this question, one calculates a p-value, which gives
you the probability that your data are purely random (i.e. not due to any
causal factor). By convention, if p < 0.05, one calls this result
"significant".

There are various tests to calculate this p-value, depending on the type of
data you have available. One of the most common types are t-tests, which are
used when you wish to compare two samples. (For example, you might want to
compare the number of butterfly species on mountain meadows with the number of
species in vineyards.) The t-test takes various factors into account,
including the mean and the variance of your datasets. This makes it a pretty
good tool for comparison, much better than looking merely at, say, the
arithmetic mean.

The problem is that occasionally, the t-test is going to give you a false
positive. That means you end up thinking that two things are causally linked
that in reality are completely independent. The probability of such a wrong
result rises with the number of tests you perform in a given study. That is
why such studies need to adjust for multiple testing. Often this is done with
the Bonferroni method, which basically means multiplying your p-value by a/n,
where a is your level of significance (0.05) and n is the number of tests you
perform.

Hope that made sense :-)

~~~
kerkeslager
The concept I was missing was that testing two different random variables at
the same time (do meat or vegetables affect telomere length in this group) has
the same probability of yielding a false positive for one of the variables as
testing the same variable twice (does meat affect telomere length in this
group, does meat affect telomere length in that group) has of yielding a false
positive for one of the tests.

------
dvcrn
Can someone rephrase the conclusion and results? I read through it multiple
times but can't figure out if a higher T/S ratio is a good thing or not.

~~~
scriptproof
They claim that eating more meat increase longevity, against popular belief.
But it is contradicted by what we can see: people that eat less meat like
those in blue zones have higher longevity in fact.

~~~
voidlogic
>against popular belief.

To be fair its amongst people who study diet, it is also common belief that a
ketogenic diet (which while can have lots of plant matter is often high in
meat) is almost as good for longevity as caloric restriction.. :)

------
JackFr
> Many factors can modify telomere length, among them are: nutrition and
> smoking habits, physical activities and socioeconomic status measured by
> education level.

That seems especially poorly worded.

~~~
veddox
I don't think the authors are native speakers, let's forgive them for that ;-)

------
Nomentatus
All speculative but... I've assumed since hearing about telomeres that they
were a failsafe against cancer; X cell divisions allowed, then apoptosis. If
so, maybe shorter telomeres are something you can afford if you have the
energy (etc) to engage in a lot of DNA maintenance.

------
veddox
This whole study strikes me as rather weak, I wouldn't give assign too much
importance to the results.

As mentioned below, the number of participants was rather low (though that is
not uncommon in the life sciences and medicine). Also, the statistics appear
to be sloppy, or at any rate not sufficiently documented to be verifiable.
Thirdly, they tried to investigate too many things at once ("diet, smoking
habit, physical activity and education"). And lastly, they base their whole
study on the supposed link between telomere length and human longevity - a
somewhat obsolete hypothesis.

------
pavement

      Study included 28 subjects (seven male and 
      21 female, age 18–65 years) completed the
      questionnaire and gave blood for testing 
      peripheral blood mononuclear cells telomere 
      length.
    

So, in other words anecdotal evidence, and an interesting sidebar, but really
just some notes about one type of tissue sample across 28 people.

If it were any other look at any other tissue sample, what would you say about
the sample size and the reliability of voluntary answers from subjects based
on memory?

------
uuuiiiiooooppp
Funny how a shitty study about how butter is good for you funded by the meat
and dairy industry is lavished with praise, but any study that says your bad
habits are bad for you is met with "oh I am unconvinced. Probably p-hacked.
Too small a sample size."

~~~
Mz
Actually, the thing I thought was funny is that some comments here interpret
the study as saying "red meat is bad for you" and others interpret the study
as saying "red meat is good for you." I actually couldn't quite figure out wtf
it was saying about red meat's impact on you. And given the conflicting
interpretations here, I feel like I am not the only one.

------
marvel_boy
Newbie here. So now to eat red meat was good? Really confused.

~~~
narrator
It's a low sample size, and observastional, but it points in that direction.
The effect is probably IGF-1 related as IGF-1 indirectly activates HTRT and
telomere lengthening
([http://www.sciencedirect.com/science/article/pii/S0047637409...](http://www.sciencedirect.com/science/article/pii/S004763740900147X)).

IGF-1 is also what the non-meat eating lobby use to connect red meat eating
with cancer. IGF causes cells to grow. Anything that causes cell growth, even
if it generally manifests as bigger muscles, stronger bones or longevity also
helps cancer cells grow and gets tagged as bad by association, even though
preventing cancer is more about having a strong immune system, early detection
and avoiding mutagenic chemical pollutants.

There is a huge pro-vegetarian bias is nutrition studies. That's because there
are a lot of people who want the world to switch to a vegetarian diet because
it is more ecologically sustainable or they are intensely devoted to animal
welfare and not necessarily because it is the most healthy.

~~~
georgewsinger
> There is a huge pro-vegetarian bias is nutrition studies. That's because
> there are a lot of people who want the world to switch to a vegetarian diet
> because it is more ecologically sustainable or they are intensely devoted to
> animal welfare and not necessarily because it is the most healthy.

This is the first time I've heard people charge nutrition studies are pro-
vegetarian. Usually I hear people claiming food industry pressure causes the
opposite bias.

------
eeZah7Ux
Honest, slightly OT question: what motivates researchers to perform and
publish studies with low N? Can it have a positive or negative impact on their
career?

~~~
JumpCrisscross
> _what motivates researchers to perform and publish studies with low N?_

Consider the systemic perspective. There are problems where we have no idea
what's going on. (The pool of possibilities is so big, relative to the budget,
that it's practically infinite.)

In these cases, lots of low-N studies _could_ be better than a few high-N
ones. It's a balance between the odds of your study giving a false result
against the odds of picking the wrong hypothesis.

~~~
wuschel
That - or the results are based on one of those low quality medical research
studies that is performed by medical students in order to get their MD in some
countries.

------
oliwarner
> Study included 28 subjects

Well beside the other process issues, 28 is a farcically small set to draw any
conclusions, even future hypotheses from.

Scale that to 2800 and we can talk.

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paulcole
Phew, I was worried this study of 28 people would make me reject the fad diet
I read about in a magazine.

