Comment by wisty
13 years ago
The other problem with blue zones is, they could just be a statistical blip. It's especially bad when you try to identify things like centurions, or spontaneous remission of cancer - things which are rare are the most prone to statistical blips.
I think you mean centenarians. Centurions were Roman foot soldiers.
Still, statistically unlikely ;)
Centurions were the petty officers of the legion. There was one for every manipel or about 80 legionaires.
To a certain extent they can be, however generally speaking the very tops of this set tend to have both good luck, good genes and good lifestyle. It's hard to get to right near the very top of lifespan without all three, and the population from which we select centrenarians is extremely large. Statistical blips (good luck or unmeasured factors) can be relevant, even highly relevant, but unless you're overlooking very important things it's extremely unlikely to rise to the top without favorable outcomes in other factors.
So maybe we observe things that are 95% of optimal instead of the best genes in the data set. Or maybe we observe diets that have 90% of the performance of optimal diets. We still learn a hell of a lot.
By optimal I mean best-performing in terms of life expectancy from among the total data set (people) not just among centrenarians.
Could you explain what you mean by "statistical blip"? It seems odd to say that, I mean, wouldn't it imply that there's interference from improper measuring, or interference from variables gone unnoticed, or interference from variables that are irrelevant? I'm probably reading it wrong, but it seems such a bizarre thing to say.
What I mean is, Poisson distributions don't look like normal distributions if lambda is low - there's a long tail.
There's about 500,000 centenarians (thanks bitwize for the spelling) in the world. That's about 0.01%. In a town of 10,000, that's an average (lambda) of 1. About 36% of such towns will have no centenarians, 36% will have one, 18% will have 2, 6% will have 3, 1.5% will have 4, and there's a long tail with 5 (0.3%), 6 (0.05%) or more.
It doesn't seem logical that most towns will have 0 or 1 centenarians, and some will have 5 or more, but it's just the way the numbers work.
If you pick a higher lambda (for example, the number of 50 year olds) it looks like a normal distribution. If some place has 2X the number of 50 year olds, there will be a good reason. If you pick a higher lambda (the number of people who survive incurable cancer) it looks even wackier, and it's very hard to draw conclusions.
What I'm saying is, it's hard to draw conclusions when you are looking at rare events, because there can be so much variation.
Thank you for that explanation. I believed you had said that studying what was different for centenarians - or similar biological anomalies - in a blue zone was quite possibly useless, but it seems that wasn't the case.
It could be a sample size effect. There are all these old people there, but how many? It may have nothing to do with the island, they may all have just been lucky and had a streak of heads in the coin flip game. This is especially likely since the researchers are looking all over the world for these small pockets of longevity.
Why don't you ever hear about these things in larger areas? Certainly different countries have very different lifestyles. What's different is that bigger regions have a smaller chance of a freak streak of long lived individuals as a proportion of the population (though as an absolute value, you'll probably find more).
I suspect "blue zones" will regress to the mean after these individuals in the study die, but you can never be sure. If they don't, maybe the islands do have an effect (or maybe they started to attract immigrant older people seeking longevity).