Curious why everyone is so focused on cardiac muscle tissue. Sarcopenia (age-related skeletal muscle tissue degeneration primarily affecting fast twitch fibers) plays a massive role in the decline of athletic performance.
Athletic performance in general, but not endurance exercise performance in particular, since the latter generally doesn’t require having a lot of large, powerful fast twitch fibers.
That said, it’s difficult to determine what is the chicken and what is the egg, since primary aging impacts all cells/tissues.
IOW, we lose cardiac myocytes at about the same rate at which we lose alpha motor neurons and skeletal muscle fibers*, so everything tends to fall in parallel. Indeed, if anything the effects of aging on the CV system are greater than the effects upon skeletal muscle, which is why “threshold” tends to move closer to VO2max with aging.
*Although atrophy of individual muscle fibers occurs, especially of type II, the primary mechanism accounting for the decline in muscle mass with aging is hypoplasia, i.e., a decrease in muscle fiber number. In this regard, skeletal muscle seems to be a “victim” of the effects of aging on the CNS, with a decrease in alpha motor neuron number preceding/leading to a (somewhat smaller) decline in muscle fiber number, with some “orphaned” muscle fibers being reinnervated by surviving alpha motor neurons, resulting in fewer, bigger motor units and fiber type grouping.
Is there a drop in the early 40s? Early mid-life crisis which manifests itself in hard training? I must admit that this was the age when I was able to get back to 5 W/kg and had successful races after taking the typical breaks for my children. I trained hard again and was still young enough to be competitive. I really noticed my age a few years later.
This really needs a box and whisker plot by age, as the uncertainty on that best fit will be greatest on the right hand side. Note the circles will just represent the average by age, and the range by age will be different. In the graphics, found in the link in the first post, most folks (maybe 99%) have given up by the age of 65. Its literally 200 skiers in total in the right hand tail, so the uncertainty on that is massive.
Something like a simple kernel regression will offer uncertainty bands, which will widen in proportion to
n**0.5, so if your age band say 50-55 contains 10k observations and your age band 70-75 contains 200 observations, then the uncertainty in the 70-75 will be something like 5-10x higher. And obviously thats just for the centre of the distribution. If you look at the tails in the 50-55, I bet there are some high times in there, but by the age of 70, the folks who had high times in the 50-55 bracket have all given up.
It looks like the guy who did the stats has a background in biostats, but he himself is in his 70’s and he is looking for assistance. A simple installation of
seaborn should do the trick, and it will work out of the box.
Its nevertheless intriguing that there appears to be a big change in the relationship. To really go to town on this, it would be possible to try something like the EM algorithm, to find parameters for two different distributions.
As I posted before, you will find this same relationship between age and many many different independent parameters (much more than I showed earlier). We all hit puberty around a certain age and (most of us) hit “senility” at a certain age
I noticed this and it reminded me of something I read about women in particular getting better around late 30s, early 40s because the demands of raising kids tend to lighten up. As someone who is 38, I appreciate this. I secretly hope the 20something on our team will get married around the time my kid can drive herself places and then I’ll finally be able to keep up with her. It’s a theory anyway.
I’m 68 in January, and I can’t keep up with most of the 15 yr olds in our cx training group.
But some of that is because of the decline in sprint ability, and the need to adapt my training and racing.
It does seem a bit odd that the performance drop goes from 1 minute/year to 5 minutes/year.
I don’t know whether the field of 85000 consisted of a similar spread of ability to ,say, the London Marathon, where you have the finishing times ranging from 2hrs 5 minutes to around 8 hours.
And assuming the over 65s in the ski race would be far fewer than the over 40 category.
So is this a big enough sample to get accurate figures?
What if the competitive level of most of these older guys was low, say like a pe rson who runs an 8 hour marathon?
And the entry numbers were low too? So there were possibly no elite athletes in that age group, compared to the over 40s where you might have 10% + elite athletes.
I don’t know, but I would guess that a 55k ski race would be likely to attract those with a high level of fitness in all categories (unlike the London Marathon).
I’m probably talking bull**** but that was my first thought.
But you’re both wrong.
I referenced IMDB, which is usually accurate. Apologies…
And parting words at the end, giving hope to all us average guys.
Joe and Rita had three children, the three smartest kids in the world. Vice President Frito took 8 wives and had a total of 32 kids. Thirty-two of the dumbest kids ever to walk the Earth. OK, so maybe Joe didn’t save mankind, but he got the ball rolling, and that’s pretty good for an average guy.
That kind of bias is likely in a lot of that kind of research. Would I sign up for an Iron Man? Unlikely. (I can’t swim) So if someone studied Iron Man competitors, they would start with a pretty small self selected population. Applying anything out of that study to the population in general would be ridiculous. When I took statistics I acquired a jaundiced view of anyone trying to use statistics to ‘prove’ something. You can elastically stretch statistics to fit almost any proposal. The prof went through tons of examples of how statistics can be loaded and used.
And I watched it again shortly after this thread diverged into the future history of humanity. I did catch a bunch of other issues with the movie, but to tell the truth, if they had a ‘Publix’ that was called ‘Pubics’, I would have completely lost it.
I hate the lyrics sites that claim to have ‘THE lyrics’, and I find errors. Usually IMDB is really pretty good with their dialogs though. Apologies…