Exercise and Longevity

There’s a couple of recent studies out that look at the effects of exercise using telomere length as a surrogate for longevity. Our telomeres shorten as we age.

The first study is (Beate Ø Osthus, Ida & Sgura, Antonella & Berardinelli, Francesco & Alsnes, Ingvild & Brønstad, Eivind & Rehn, Tommy & Kristian Støbakk, Per & Hatle, Håvard & Wisløff, Ulrik & Nauman, Javaid. (2012). Telomere Length and Long-Term Endurance Exercise: Does Exercise Training Affect Biological Age? A Pilot Study. PloS one. 7. e52769. 10.1371/journal.pone.0052769). The study:

Older endurance trained athletes had longer telomere length compared with older people with medium activity levels (T/S ratio 1.12±0.1 vs. 0.92±0.2, p = 0.04). Telomere length of young endurance trained athletes was not different than young non-athletes (1.47±0.2 vs. 1.33±0.1, p = 0.12).

A second study looked at the effects of the specific mode of exercise (Christian M Werner, Anne Hecksteden, Arne Morsch, Joachim Zundler, Melissa Wegmann, Jürgen Kratzsch, Joachim Thiery, Mathias Hohl, Jörg Thomas Bittenbring, Frank Neumann, Michael Böhm, Tim Meyer, Ulrich Laufs; Differential effects of endurance, interval, and resistance training on telomerase activity and telomere length in a randomized, controlled study , European Heart Journal, ehy585).

The results were interesting.

This randomized, controlled, and prospective training study shows that specific training protocols lead to differential effects on cellular aging. Aerobic endurance and high-intensive interval training, but not resistance training, increases telomerase activity and telomere length in blood mononuclear cells.

This study was fairly impressively powered with 124 subjects.

One hundred and twenty-four healthy previously inactive individuals completed the 6 months study. Participants were randomized to three different interventions or the control condition (no change in lifestyle): aerobic endurance training (AET, continuous running), high-intensive IT (4 × 4 method), or RT (circle training on 8 devices), each intervention consisting of three 45 min training sessions per week.

The specific results were statistically significant.

Telomerase activity in blood mononuclear cells was up-regulated by two- to three-fold in both endurance exercise groups (AET, IT), but not with RT. In parallel, lymphocyte, granulocyte, and leucocyte TL increased in the endurance-trained groups but not in the RT group. Magnet-activated cell sorting with telomerase repeat-ampliflication protocol (MACS-TRAP) assays revealed that a single bout of endurance training—but not RT—acutely increased telomerase activity in CD14+ and in CD34+ leucocytes.

Things to note is that this is an older (~49 years on average), untrained group of people who were at healthy BMI (~24).

Mechanism

The mechanism is interesting.

Exercise Intensity and Blood Sugar

I’ve come to the conclusion that for me as a diabetic intense exercise (at high heart rates) is not good for my blood sugar control. Here’s a study of Type 1 Diabetics which shows the increase in blood sugar from intense exercise (Vinutha S, Paul F, Raymond D, et al. Effect of exercise intensity and blood glucose level on glucose requirements to maintain stable glycaemia during exercise in individuals with type 1 diabetes. Int J Pediatr Endocrinol. 2015;2015(Suppl 1):O39). The study looked at:

Nine young adults with T1D underwent euglycaemic clamps, whereby stable blood glucose levels between 4.5 to 6mmol/L were maintained during the study at basal insulin levels. Participants performed up to 40 minutes of exercise at four different exercise intensities (35%, 50%, 65% and 80% VO2peak) on four separate days following a randomised counterbalanced design. In a subsequent experiment, eight participants underwent either a euglycaemic or hyperglycaemic (9.5 – 10.5mmol/L) clamp at basal insulin levels, during which they performed 40 minutes of exercise at 50% VO2peak, on two separate days. In both studies, glucose infusion rates (GIR) to maintain stable glycaemia were measured during exercise, constant deuterated glucose was infused to determine glucose kinetics and blood samples were collected for the analysis of glucoregulatory hormones.

The result was:

The average GIR to maintain euglycaemia during exercise was 2.0±0.9, 4.0±1.5, and 4.1±1.7g/h (mean±SEM) at 35%, 50% and 65% VO2peak, respectively. These GIRs were all significantly greater than that at 80% VO2peak where no glucose was required (p<0.05). Exercise at 80% VO2peak was associated with a significant rise in catecholamine levels and endogenous glucose production (p<0.05). The average GIR to maintain stable glycaemia during exercise performed during the second experiment at 50% VO2peak was similar at euglycaemia (4.9±2.1g/h) and hyperglycaemia (5.5±2.5g/h; p>0.05).

 

MAF Plus 20

Peter Defty (of OFM fame) suggests that fat adapted athletes can increase their MAF number from 180 – age (with correction factors added/subtracted) to 200 – age (same correction factors) (Primal Endurance Podcast – #90: Peter Defty Talks Optimized Fat Metabolism).

His reasoning is that the heart rate is 10-15 beats per minute faster in fat adapted athletes (from the FASTER data). He reasoned that Maffetone came up with the number based on non-fat adapted athletes and that once fat adapted the number can be shifted up.

Tempting Idea, but…

I’ve had the same thoughts before and I’d really like to accept Defty’s ideas since I’m getting tired of mostly walking. I’d like to run more. But I’ve also had no injuries in the past few months. Recovery has been so easy that I’m finding myself doing two MAF efforts a day. I’d hate to jeopardize that.

I don’t think I’m getting much faster doing MAF, but I wonder if sticking with MAF and doing intervals would improve my speed. I do feel like I am improving my leg strength at MAF and they are not a limiting factor when I’m out for more than an hour.

The limiting part of MAF is that after 4 or 5 miles I can only run a few steps until I have to start walking again.

MAF is MAF

Of course, Maffetone’s approach is that MAF is MAF. And it’s 180 – age (with correction factors).  The program is fixed and doesn’t need to be changed. The athlete who is not yet fat adapted will burn more carbohydrates at MAF and the athlete who is fat adapted will burn more fat at MAF. This shift away from carbohydrate reliance to fat adaptation is the goal of MAF when done with the recommended lower carbohydrate diet.

20 Beat Shift – VO2 Data

To see what a 20 beat increase would do, take a look at my VO2max fat/carbohydrate oxidation curve. At my MAF (122 bpm) I am currently burning nearly all fat and very little carbohydrates.

Shifting up by 20 bpm from 122 to 142 just happens to be the 50-50 crossover point of calories from fat and carbohydrates. This will cause glycogen depletion which has good and bad aspects. My current view is that staying out of that range is the smartest idea since cycling glycogen doesn’t promote lower glycogen stores since the body responds by over saturating glycogen stores.

Shifting right by 20 bpm could have the advantage of causing a further shift of the curve to the right and increasing my fat oxidation at that same heart rate. If that is the effect then it would be positive since in the end I could have a higher VO2max and improved fitness.

Critique of MAF number

One difficultly of the Maffetone MAF number is that there’s no real explanation of the basis for the number. Maffetone himself says that the number can be adjusted based on actual metabolic tests but he never exactly explains how to adjust the number nor exactly what he based the number on other than observation of a lot of his clients/patients. The number fit the tests within a few beats but Maffetone never explains the derivation of the number in enough details to explain what lab test he used and what the correlation to the tests is. Maffetone has spent a lot of energy explaining what it isn’t (lactic threshold, VO2max, percent of max heart rate, etc) but not a lot explaining what it is. Without tying it to some external metric it’s hard to judge the value of the metric.

Is MAF at the cross-over point for a non-fat adapted athlete but the point of maximum fat burning in a fat adapted athlete? It is true from my data that 122 is the sweet spot. It is literally the peak of fat oxidation (the black theoretical curve fitted line) where no carbohydrates are being burned. Ten beats lower is still in the prime fat burning zone. For me, lower numbers are even ketone burning (evidenced by the RER of less than 0.7).

Rate of Perceived Exertion (RPE)

Mowing my lawn raises my heart rate beyond the MAF range and makes me sweat. MAF makes me sweat when it’s warm outside but it’s a pretty gentle pace. I could do exercises at 142 max and it would be fine. I know because I’ve mowed the lawn (and done CrossFit) at higher rates.

I don’t think I am going to change what I am doing at the moment but I will bear it in mind for the future. I did 5 sessions last week of 5Km or longer and I’d like to keep up the volume.

 

MAF Training And Metabolic Syndrome

There’s an interesting study which looked at two months of training at FATmax to see what the effects on Metabolic Syndrome (Dumortier M, Brandou F, Perez-Martin A, Fedou C, Mercier J, Brun JF. Low intensity endurance exercise targeted for lipid oxidation improves body composition and insulin sensitivity in patients with the metabolic syndrome. Diabetes Metab. 2003 Nov;29(5):509-18). The study showed good improvements from MAF level of training intensity.

The patients exhibited a significant reduction in body weight (- 2.6 +/- 0.7 kg; P=0.002), fat mass (- 1.55 +/- 0.5 kg; P=0.009), waist (- 3.53 +/- 1.3 cm; P<0.05) and hip (- 2.21 +/- 0.9 cm; P<0.05) circumferences, and improved the ability to oxidize lipids at exercise (crossover point: + 31.7 +/- 5.8 W; P<0.0001; LIPOX(max): + 23.5 +/- 5.6 W; P<0.0001; lipid oxidation: + 68.5 +/- 15.4 mg.min(-1); P=0.0001). No clear improvement in either lipid parameters or fibrinogen were observed.

There were significant improvements in the markers of Metabolic Syndrome.

The surrogates of insulin sensitivity evidenced a decrease in insulin resistance: HOMA%S (software): + 72.93 +/- 32.64; p<0.05; HOMA-IR (simplified formula): – 2.42 +/- 1.07; P<0.05; QUICKI: + 0.02 +/- 0.004; P<0.01; SI=40/I: + 3.28 +/- 1.5; P<0.05. Significant correlations were found between changes in body weight and HOMA-IR and between changes in LIPOX(max) and QUICKI.

Here’s a longer term study which shows positive results over a longer time period (Drapier E (2018) Long term (3 years) weight loss after low intensity endurance training targeted at the level of maximal muscular lipid oxidation. Integr Obesity Diabetes 4).

Average weight loss was -2.95 ± 0.37 kg after 3 months, -4.56 ± 0.68 kg after 1 year, -5.31 ± 1.26 kg at 2 years and -8.49 ± 2.39 kg at 3 years.

The beauty of this study was that it compared low intensity exercise to a low fat diet.

This study shows that this low intensity exercise training maintains its weight-reducing effect 3 years while diet is no longer efficient, and that this effect is initially related to muscular ability to oxidize lipids but that metabolic and behavioral adaptations have been further developed and contribute to a long lasting effect.

The results are powerful.

Here’s a third related study (J. O. Holloszy and E. F. Coyle. Adaptations of skeletal muscle to endurance exercise and their metabolic consequences. Journal of Applied Physiology 1984 56:4, 831-838).

The major metabolic consequences of the adaptations of muscle to endurance exercise are a slower utilization of muscle glycogen and blood glucose, a greater reliance on fat oxidation, and less lactate production during exercise of a given intensity.

These adaptations play an important role in the large increase in the ability to perform prolonged strenuous exercise that occurs in response to endurance exercise training.

From the results:

…Probably the most important of these is an increase in mitochondria with an increase in respiratory capacity. One consequence of the adaptations induced in muscle by endurance exercise is that the same work rate requires a smaller percentage of the muscles’ maximum respiratory capacity and therefore results in less disturbance in homeostasis.

A second consequence is increased utilization of fat, with a proportional decrease in carbohydrate utilization, during submaximal exercise.

 

Fat Burning – Running vs Cycling

In a previous post I took at look at the exercise intensity which produced the maximum fat oxidation rates (Maximal Fat Oxidation Rates in an Athletic Population). A study took a look at the fat oxidation rates which happen when exercise is performed at the FATmax rate with cycling and running.

There was a significant difference in the rate of fat oxidation between the two (Juul Achten, Michelle C Venables, Asker E Jeukendrup. Fat oxidation rates are higher during running compared with cycling over a wide range of intensities. Metabolism, Volume 52, Issue 6, June 2003, Pages 747-752.).

Maximal fat oxidation was 28% higher when walking [ed: did they mean running?] compared with cycling, but the intensity, which elicits maximal fat oxidation, is not different between these 2 exercise modes.

These are interesting results. Although both exercises were done at the same intensity level (as measured by heart rate) they resulted in different amounts of total fat oxidation.

This leads me to conclude that although cycling and running can be both done at the MAF heart rate they are not equal for fat oxidation rates.

What About Rowing?

It would be interesting to see what the fat oxidation rate at FATmax is for rowing (ROW) and other modes. Turns out there’s a study for that too. (Egan B, Ashley DT, Kennedy E, O’Connor PL, O’Gorman DJ. Higher rate of fat oxidation during rowing compared with cycling ergometer exercise across a range of exercise intensities. Scand J Med Sci Sports. 2016 Jun;26(6):630-7. The study found that:

…FATox is higher during ROW compared with CYC exercise across a range of exercise intensities matched for energy expenditure…

The details show:

Despite similar oxygen consumption, rates of fat oxidation (FATox ) were ∼45% higher during ROW compared with CYC (P < 0.05) across a range of power output increments.

The crossover point for substrate utilization occurred at a higher relative exercise intensity for ROW than CYC (57.8 ± 2.1 vs 42.1 ± 3.6%VO2peak , P < 0.05).

Putting the Pieces Together

  • Rowing is ~45% better than cycling.
  • Running is ~28% better than cycling.
  • Rowing should be ~17% better than running.

Mechanism to Explain Differences

The degree to which an exercise engages muscles determines the maximum fat oxidation. Rowing has more muscle involvement than running which has more muscle involvement than cycling.

 

 

 

FATmax Training Results

In principle, training at FATmax (Maximal Fat Oxidation Rates in an Athletic Population) should result in significant loss of body fat and the resulting improvement in body composition. However, it is something of a surprise just how few studies have been performed to determine the effectiveness of this type of training. A meta-analysis (A. J. Romain, et.al. Physical Activity Targeted at Maximal Lipid Oxidation: A Meta-Analysis. (J Nutr Metab. 2012; 2012: 285395.) took a look and only found 15 total studies of this subject which fit their criteria. These studies were relatively small but the results were encouraging.

This meta-analysis confirms the conclusions of the individual studies, that are very low intensity training targeted at the level of maximal fat oxidation significantly decreases body weight, fat mass, waist circumference and total cholesterol. On the average, the effects of this variety of training are thus well confirmed, and their average magnitude is more precisely described.

Study Limitations

Only 5 studies include a control (nonexercising) group. There were also no longer term studies.

Volume of Training

Interestingly, some studies demonstrated an important average weight loss (8 kg over two months) with a protocol based on 90 min/day exercise at the level of maximal lipid oxidation. This could suggest that large weekly volumes of exercise training may be much more efficient than those used usually (i.e, 3 × 45 min/week).

Loss of Visceral Fat

The study called out a reference paper (Ohkawara K, et.al. A dose-response relation between aerobic exercise and visceral fat reduction: systematic review of clinical trials. Int J Obes (Lond). 2007 Dec;31(12):1786-97. ) which indicated that there is a dose response between aerobic exercise and loss of visceral fat.

… at least 10 METs x h/w in aerobic exercise, such as brisk walking, light jogging or stationary ergometer usage, is required for visceral fat reduction, and that there is a dose-response relationship between aerobic exercise and visceral fat reduction in obese subjects without metabolic-related disorders.

 

Running Slow

I’ve taken my MAF training to a certain point where I am running a lot more than I was before but still not for very long. I’d like to be able to run the whole time – except perhaps on really steep hills like the Lincoln Brick hill.

I think the problem is that when I start running I am going too fast and my heart rate climbs too quickly. I need to work on running slower. I probably need to do this work on a track to avoid hills (I live in SW PA where it is very hilly nearly everywhere).

Here’s a video of the Niko Niko method which is very similar (Niko Niko uses a low intensity steady state training at a heart rate just below the bottom of the MAF range).

The key points in this video are:

  1. Be conscious about small steps and pitch. The woman in the video is taking steps where her shoes don’t go past the other shoe.
  2. Keep your back straight. Don’t lean forward into the run.
  3. Relax your shoulders. Your arms should move naturally.
  4. Breathe naturally.
  5. Slightly raise your chin and look far ahead of you.
  6. Be conscious about forefoot landing. Don’t land on your heels.
  7. Do not kick the ground.

There is a MAF video by Sherpa Herb along similar lines.

I am going to start working on this. I’ve been doing about three days a week with an hour or more each time so I feel like my consistency has held up.

Low Carb High Intensity Interval Training Performance

Here’s a new study that looked at the Low Carb diet and High Intensity Interval Training performance (Lukas Cipryan, Daniel J. Plews, Alessandro Ferretti, Phil B. Maffetone, and Paul B. Laursen. Effects of a 4-Week Very Low-Carbohydrate Diet on High-Intensity Interval Training Responses. J Sports Sci Med. 2018 Jun; 17(2): 259–268.).

The purpose of the study was to examine the effects of altering from habitual mixed Western-based (HD) to a very low-carbohydrate high-fat (VLCHF) diet over a 4-week timecourse on performance and physiological responses during high-intensity interval training (HIIT).

Eighteen moderately trained males (age 23.8 ± 2.1 years) consuming their HD (48 ± 13% carbohydrate, 17 ± 3% protein, 35 ± 9% fat) were assigned to 2 groups. One group was asked to remain on their HD, while the other was asked to switch to a non-standardized VLCHF diet (8 ± 3% carbohydrate, 29 ± 15% protein, 63 ± 13% fat) for 4 weeks.

Participants performed graded exercise tests (GXT) before and after the experiment, and an HIIT session (5x3min, work/rest 2:1, passive recovery, total time 34min) before, and after 2 and 4 weeks. Heart rate (HR), oxygen uptake (V̇O2), respiratory exchange ratio (RER), maximal fat oxidation rates (Fatmax) and blood lactate were measured. Total time to exhaustion (TTE) and maximal V̇O2 (V̇O2max) in the GXT increased in both groups, but between-group changes were trivial (ES ± 90% CI: -0.1 ± 0.3) and small (0.57 ± 0.5), respectively.

Between-group difference in Fatmax change (VLCHF: 0.8 ± 0.3 to 1.1 ± 0.2 g/min; HD: 0.7 ± 0.2 to 0.8 ± 0.2 g/min) was large (1.2±0.9), revealing greater increases in the VLCHF versus HD group. Between-group comparisons of mean changes in V̇O2 and HR during the HIIT sessions were trivial to small, whereas mean RER decreased more in the VLCHF group (-1.5 ± 0.1). Lactate changes between groups were unclear.

Adoption of a VLCHF diet over 4 weeks increased Fatmax and did not adversely affect TTE during the GXT or cardiorespiratory responses to HIIT compared with the HD.

I have a lot of respect for Phil Maffetone and Paul Larson. Both are long time advocates of Low Carb Athletics. Phil Maffetone coached Mark Allen to multiple wins at Kona Ironman (Mark Allen Interview: A look back at working with Phil Maffetone and what it means for today’s triathlete).

 

 

Nerding Out on Data

I like Strava for tracking my MAF runs but it doesn’t work well for me with my Polar Chest Heart Rate Strap (HR-7). So, I’ve switched to Polar Beat/Flow for the HR-7 strap since it’s easier to read the heart rate while running. I still use Strava along with Samsung Health. The watch sends data to Samsung Health and Samsung Health sends data to Strava. I still don’t like the result since the heart rate data gets blocky. Here’s an example:

So how did I get the data?

This is the fore-warned nerdy part. I’ve written a Python script. If you don’t know Python skip the rest of this post since I can’t support the code. If you care, the Python code is here on GitHub. Again, I can’t support the code. It uses libraries that are here.

After running the pyStravaParse code. I then open the CSV file (spreadsheet format) in LibreOffice (a Microsloth EXCEL clone). I can’t support your spreadsheet choice either.

The data looks like:

Time (secs) Lat Lon Elev Heart_Rate (bpm) HRmax (bpm) HRmin (bpm)
0 39.908913 -79.71205 323.7 93 122 112
2 39.908913 -79.71205 323.7 93 122 112

HRmax and HRmin are hard coded as string constants at the start of the code. They are based on your MAF number. They could be replaced by 180-age and 190-age.Data_Time is offset in seconds.

I then select the Time, Heart_Rate, HRmax and HRmin columns like this:

Select Insert, Chart.

Choose Chart Type – XY (Scatter) then Next.

For Data Range you should already be OK if you selected data above. The select Next.

For Data Series you should already be OK. Then select Next.

For Chart Elements enter your title, etc as below. After entering in the titles, select Finish.

You should get a result like this.

To edit the chart double click in the chart. Then right click on one of the numbers on the heart rate axis. You should then see.

Select Format Axis. Then enter your own heart rate range numbers. I selected Minimum of 80 and left the maximum at 140.

You should get something like this.

I also like to move the legend to the bottom and move the graph up a bit.

Not a bad result but it’s easy to see the blockyness of the data. The Polar strap does better. I don’t have data for that same run since I bought the Polar strap later but here’s a recent image.

Not bad!

 

NIKO NIKO Pace

There is another slow steady heart rate training called Niko Niko. Here’s a good page describing it (NIKO NIKO PACE – THE GENTLE PATH TO SUCCESS).

The formula for heart rate is different than the Maffetone MAF heart rate. Niki Niko uses:

138 minus half your age.

So for me at 58 that would be 138 – (58/2) = 109 bpm. That’s not too far below my MAF heart rate of 112-122. It it at an interesting point on myVO2max test results as well. A heart rate of 109 actually has a higher fat oxidation rate than the extrapolated curve (where the real world data veers from the idealized curve). It is certainly a good point for fat burning.

The MAF number has shifted my performance upwards in just the past three weeks. Here’s my splits from my MAF test three weeks ago compared with my MAF 5 mile this AM. I’ve had to go from walking to a little jogging and walking mixed together.

That’s a pretty good improvement – around a minute and a half.