The Peter Attia Drive - September 20, 2021


#176 - AMA #27: The importance of muscle mass, strength, and cardiorespiratory fitness for longevity


Episode Stats

Length

18 minutes

Words per Minute

166.42616

Word Count

3,114

Sentence Count

184


Summary

In episode 27 of the Ask Me Anything podcast, Dr. Bob Kaplan and I discuss all things related to the outputs of exercise and morbidity and mortality. Specifically, we go into great detail around the benefits one gets from a high degree of cardiorespiratory fitness, and the benefits that one will derive from a large amount of muscle mass and muscle strength. And conversely, what happens when you don't have those things? We also tease apart as best we can the relative contributions of each of those things.


Transcript

00:00:00.000 Hey everyone, welcome to a sneak peek, ask me anything or AMA episode of the drive podcast.
00:00:16.380 I'm your host, Peter Atiyah. At the end of this short episode, I'll explain how you can
00:00:20.460 access the AMA episodes in full, along with a ton of other membership benefits we've created,
00:00:25.440 or you can learn more now by going to peteratiyahmd.com forward slash subscribe. So without
00:00:31.800 further delay, here's today's sneak peek of the ask me anything episode.
00:00:39.200 Welcome to ask me anything episode number 27. I'm once again joined by Bob Kaplan. In today's
00:00:46.180 episode, we discuss all things related to basically the outputs of exercise and morbidity and mortality.
00:00:53.440 So specifically, we go into great detail around the benefits that one gets from a high degree of
00:01:02.580 cardiorespiratory fitness and the benefits that one will derive from a high amount of muscle mass and
00:01:08.840 muscle strength. And conversely, what happens when you don't have those things. We also tease apart
00:01:14.120 as best we can, the relative contributions of each of those things. So is it more about muscle mass?
00:01:20.420 Is it more about muscle strength? If you are optimizing to get the best health benefit in
00:01:27.380 the least amount of effort, not something I recommend, where do you get the most bang for
00:01:31.560 your buck? Is it strength? Is it cardiorespiratory fitness, et cetera? So anyway, this one is a really
00:01:37.840 fun episode. I would encourage you to watch this one. So obviously it is available as any podcast is
00:01:44.300 via audio, but this is one where I think the data being presented and we go through a lot of this
00:01:50.300 by showing the figures. It just makes a heck of a lot more sense if you can see what we're talking
00:01:54.680 about. So if you're a subscriber and you want to watch the full video, which I hope you do,
00:01:58.660 you can find it on the show notes page. If you're not a subscriber, you will watch a sneak peek of this
00:02:03.060 video on the YouTube page, but potentially this is the episode that gets you to subscribe. So without
00:02:07.520 further delay, I hope you enjoy AMA number 27. All right, Bob, we got a pretty fun AMA today here,
00:02:18.180 but before we do, I don't think I realized until looking at your background that the Boston Bruins
00:02:22.880 had a 30 year drought in which they did not win their division, 1940 to 1970.
00:02:29.800 Oh, I'm glad I missed that drought. Is that 1940, was that when there was fewer teams? I mean,
00:02:35.940 it'd be really embarrassing. That's embarrassing. Well, it's not as embarrassing as the Maple Leafs
00:02:42.040 who haven't won the Stanley Cup since I think 1967. Oh my goodness. If any team deserves a
00:02:48.280 Stanley Cup, it's Toronto. I enjoyed, I think I sent you a video of a guy talking about,
00:02:55.440 you know, that's bad enough, but was it a year ago or a couple of years ago? They lost to a
00:03:00.620 backup goaltender, it was a Zamboni driver. Yeah, right. At the ACC.
00:03:04.240 Yeah, that's a beautiful story though. Yeah. All right. So we've got a pretty fun topic,
00:03:10.260 an important topic on the docket today, which is effectively kind of scratching the exercise
00:03:16.960 itch as it pertains to longevity, but at a, probably a deeper level than folks who are used to. So
00:03:22.240 where should we start? I think we should start with, well, aerobic fitness or cardiorespiratory
00:03:28.080 fitness. Cause I think we've got a few of things that these questions have come in. I think a bunch
00:03:32.260 of questions related to this, which is studies that look at how much lean mass you have and
00:03:37.720 whether that is a predictor of longevity. And then there's also studies that talk about muscle
00:03:42.860 strength, not just muscle mass and whether that predicts longevity and whether one of those is
00:03:47.740 better than the other. But I think a good place to start is with cardiorespiratory fitness with
00:03:51.700 similar question, you know, is, does better lead to less mortality and does lower cardiorespiratory
00:03:57.440 fitness lead to higher mortality or is it at least associated? Okay. So let's start by kind of
00:04:03.100 explaining to folks the metrics that we're going to talk about through this. So the most common thing
00:04:08.900 I think we see in the literature is either METs, metabolic equivalents or VO2 max. And I think part of
00:04:14.800 that is it's quite objective. So if anybody's had a VO2 max test, they'll understand how objective and
00:04:20.920 unpleasant it is. I think we've talked about this before. So you are hooked up to an indirect
00:04:27.400 calorimeter. So it's a device that provides complete occlusion around your mouth and your nose.
00:04:33.480 Typically this device also sort of plugs your nose. So you're only breathing through your mouth.
00:04:38.360 And the important thing is that the device has two sensors on it. One sensor measures the
00:04:45.380 concentration of oxygen that is being expelled. And for the purpose of this discussion, that's the
00:04:52.340 more important of the sensors, but for what it's worth, the other one is also measuring the
00:04:56.420 concentration of carbon dioxide that's expelled. So because we know the concentration of oxygen and
00:05:04.120 CO2 on the way in by knowing what comes out and obviously oxygen will be lower, CO2 will be higher.
00:05:11.140 We know how much carbon dioxide was produced and how much oxygen was consumed. And knowing those two
00:05:18.720 things gives you a flow rate, a VO2 and a VCO2. Those two pieces of information alone tell you how much
00:05:28.640 energy you're utilizing via something called the Fick equation, if I'm not mistaken. So total energy
00:05:36.540 consumption is 3.94 times VO2 plus I think it's 1.11 times VCO2 at any point in time. So if you have
00:05:49.800 for this minute VO2 was this, VCO2 was that, you apply it to that equation and it will tell you
00:05:55.780 you were utilizing 10 kilocalories per minute, which would be, you know, 600 kilocalories per hour,
00:06:03.060 which is, you know, I do this sometimes when I'm doing my zone two, my zone two tends to be
00:06:10.760 about 780 kilocalories per hour. So interesting, but again, that's not how I test zone two. I'm
00:06:20.120 using lactate for zone two. But now what we're talking about is something different, which is
00:06:23.820 what is the maximum utilization of oxygen? So if you make somebody work harder and harder and harder,
00:06:31.360 so if they're on a bike and you keep adding wattage to the bike and they have to pedal against more and
00:06:36.140 more resistance, or if they're on a treadmill and you make them run faster and faster and up at higher
00:06:40.720 and higher incline, at some point they will reach a maximum, at which point they can no longer
00:06:48.720 utilize more oxygen. Now we're not going to go into the why right now, but I believe that Alex
00:06:55.160 Hutchinson and I covered that in some depth in our podcast, you may recall. And we talked about
00:07:00.000 some of the alveolar limitations, how much of that is being limited at the gas exchange surface
00:07:05.840 versus how much is being exchanged in the actual, pardon, how much of that is being limited in the
00:07:10.780 muscle. But regardless of which of those it is, and it's possible it's a combination or it's possible
00:07:17.000 that at low levels of fitness, it's more in the muscle and at high levels of fitness, it might be
00:07:22.540 more in the lung. But that number is the VO2 max. When you're doing the test, it's measured typically
00:07:31.680 in liters per minute, but then we normalize it by body weight. So we normalize it as liters per,
00:07:41.920 well, we do it actually as milliliters per kilogram per minute. So when you start to hear the numbers
00:07:47.220 that people kick around, the fittest of the fit are going to be North of 80, but what does that
00:07:53.420 mean? It means they're North of 80 milliliters of oxygen per kilogram per minute. And I think
00:08:00.400 actually Alex and I talked about that on the podcast, right? The highest ever recorded person
00:08:04.180 was probably about 96 or so. And any sort of elite athlete, elite cardiac type athlete, right? So
00:08:11.920 runner, cyclist, rower, those sorts of athletes, they're generally going to be above 70. So what does
00:08:18.980 that number tell us about mortality, right? I mean, I think that's a question. And I think we've got
00:08:23.640 some data to talk about that. So do you want to, you want to pull out one of these slides here?
00:08:28.120 All right.
00:08:29.420 Okay. So this took a group of people, do you recall how old they were?
00:08:34.740 About 53 on average.
00:08:36.220 Okay.
00:08:36.740 Mean age.
00:08:37.400 And it ran them through a VO2 max test and then it ranked them and low were people who scored,
00:08:44.040 I believe in the bottom 25th percentile. These are non equally weighted groups if my memory serves me
00:08:50.120 correctly. But I think that low were the people in the bottom 25th percentile. Check me on that. Below
00:08:58.140 average, I think was 25th to 50 percentile. And then 50 to 75th percentile was above average and high was
00:09:06.700 like 75th to maybe 95th. And elite was just that top 5 percent. I'm probably off by a little bit, but
00:09:14.560 directionally that's true. I just want to make sure people don't look at these and think that each of them
00:09:18.700 represents 20 percent of the population.
00:09:21.260 Yeah. I think that's directionally accurate. I'm looking at the third table one, their patient
00:09:25.620 demographics. It's interesting. So it's a total of 122,000 patients. And if you look at the low,
00:09:32.460 below average and above average and high, they're all about 30,000 participants in each one of those
00:09:39.540 groups. And then you've got the elite and there's a little over 3,500 versus the 30,000 that's split
00:09:46.820 amongst those other groups.
00:09:48.280 Got it. Yep. Okay. So that's about what we just said there. And we're looking at all cause mortality
00:09:53.960 here and you can see a pretty clear trend. The two things that stand out are there's kind of a
00:10:00.360 monotonic relationship between fitness and mortality. But the second thing that stands
00:10:04.520 out is by far the biggest gap is between the people in the bottom 25 percent, which are categorized as
00:10:13.700 low fitness and basically everyone above them. So if you go to the next figure, Bob, I think we get
00:10:20.380 to see this in a little bit more detail. I like this figure, frankly, more because it allows us to see
00:10:25.680 a bit more interesting stuff. So here we can see both for all patients. So lumping everyone in
00:10:32.860 together, male and female, if you have low fitness and then comparing it to everybody else, what's the
00:10:41.260 risk reduction? So if you go from low to below average to above average to high to elite, you can see
00:10:50.120 what is the hazard ratio. So it's interesting going from just being low to being below average is a
00:10:58.620 50 percent reduction in mortality over a decade if you're starting in your 50s. We're going to come back
00:11:05.660 to that, but that is so important. It is. It seems like a weird message to give to somebody that, you
00:11:10.480 know, I want you to be below average, but that is definitely a step up from low in terms of how they
00:11:15.920 categorize these. That's right. If you then go from low to above average, it's about a 60 percent
00:11:25.300 or 70 percent reduction in mortality. And it just continues monotonically to increase. Again,
00:11:32.820 the lowest improvement is going from high to elite. That doesn't buy you a whole heck of a lot.
00:11:40.460 It is still statistically significant. And that's to see that you have to look at figure C. Again,
00:11:48.660 this is going to be one of those podcasts where it's really going to be better to watch this over
00:11:52.480 video because, you know, the data just speak for themselves. And of course, the show notes are going
00:11:57.160 to include all of these. So make sure you're looking at this. But remember, the hazard ratio for
00:12:02.860 mortality is the reciprocal of the hazard ratio of risk reduction. So tables A and C are basically
00:12:11.560 showing you similar things in the group comparison. So again, when I said that going from high to elite
00:12:18.300 didn't have as much of a benefit, you can see it has the smallest hazard ratio of improvement in
00:12:24.740 benefit or the reduction going from high to elite. It's 29 percent. But notice that the confidence
00:12:31.220 interval does not cross one and therefore the P value is less than 0.05. Now, here's what's
00:12:37.300 interesting. What they've done, and you can see all of these listed, right? So if you compare someone
00:12:41.960 of low fitness to elite, it is a five fold difference in mortality over a decade, which is
00:12:49.020 pretty remarkable. And that's what they show you above. They give you context. They put this in the
00:12:55.420 context of other things that we commonly understand as being problematic for mortality.
00:13:00.720 Namely, smoking, coronary artery disease, type 2 diabetes, hypertension, and end-stage renal disease.
00:13:07.740 So look at these differences, right? And I believe, Bob, this is not just for someone who's
00:13:13.180 currently smoking. This is if you've ever smoked, right? Yes. I think it was previously used or used
00:13:18.680 tobacco. So they're really looking at the difference between never smokers. So you've never smoked in your
00:13:23.200 lifetime to if you've ever smoked. Okay. And that's a 41 percent increase in mortality over the decade.
00:13:29.300 Coronary artery disease, 29 percent. Diabetes, 40 percent. High blood pressure, 21 percent. And the
00:13:37.560 most of all of these things, end-stage renal disease, about 280 percent increase in mortality.
00:13:45.100 Now, we all understand what that means, but now when you compare that to the differences in these
00:13:50.800 fitness levels, it gives you, at least in my opinion, a greater appreciation for how much
00:13:56.060 improvement in mortality comes from improving your fitness. So if you look at the biggest driver
00:14:02.780 of mortality, which would be end-stage renal disease in this cohort, it's the same as going from
00:14:08.600 low cardiorespiratory fitness to above average cardiorespiratory fitness. So going from the bottom
00:14:14.100 25th percentile to being in the 50th to 75th percentile, which is a totally achievable feat,
00:14:20.440 as you'll see in a moment. Anything else you want to say about this, Bob, aside from the fact that it's
00:14:24.700 sort of stunning? It is. It's really striking. So one little pro tip or amateur tip is when Peter
00:14:32.160 was talking about the reciprocals, is that if you look at figure 2A and then you look at figure 2C,
00:14:39.000 and you look at the group comparisons, if you want to see that plotted point, for example,
00:14:43.520 on the right-hand side of figure 2A, elite versus low, you can look at figure 2C, where it says low
00:14:53.380 versus elite, and the hazard ratio is 5. The reciprocal is just take 1 divided by 5, and you
00:15:00.000 get 0.2. And then if you look at that, so then when you look at the chart, it makes sense. And then
00:15:05.860 high versus low, for example, it's 3.9 for hazard ratio, which is about 4. So 1 divided by 4 is about
00:15:11.620 0.25. That checks out. So just a little pro tip for the fans out there. That's helpful because these
00:15:18.800 graphs have a log linear axis. So it's not intuitive to look at these things. Going from low to below
00:15:26.040 average gives you half of the benefit, but you'll never get the remaining half ever, because that
00:15:32.040 would imply immortality, which obviously isn't happening. Okay. Now let's put some numbers to
00:15:38.180 this, because this is one of those things that we use a lot with our patients, because we want most of
00:15:44.620 our patients, we want all of them doing this, but not all of them are willing to do it. But we
00:15:48.720 certainly want everybody to have a VO2 max test so that we can kind of benchmark them on their way to
00:15:53.800 their centenarian Olympics. So let's actually see what these numbers look like. Thank you for listening
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