I was training…

I was looking into training for a 5K race. A friend pointed me to a page which has a training plan (Hal Higdon 5-K Training: Novice).

This is an 8-week plan which starts with 1.5 mile runs three times a week and goes up by a 1/4 mile each week to the 5-K run.

If this is something you want to do this summer, now’s a good time to start. If you are running to lose weight, this might be helpful (Why Most Runners Don’t Lose Weight):

For the average runner, it takes about 30 minutes running at six miles per hour to burn about 300 calories. It takes that same runner just 30 seconds standing in her kitchen eating dark chocolate sea salt caramels to consume about 300 calories.

Possible Schedule

Sun Mon Tue Wed Thu Fri Sat
Activity Rest Run/
CrossFit Run/
Rest Run/

Plotting Your Run

Running on a track is relatively safe. You probably won’t get hit by a car on a track. But it’s also boring and unless you live next door to a track it takes some effort to travel there and back.

Instead you may be able to run in your own neighborhood. But how far do you need to go? Did you know that you can trace out roads near you using google maps and google maps will tell you the distance. Here’s how:

  • Open google maps
  • Go to the area you want and zoom to the general area
  • Select Satellite button (bottom left in browser)
  • Click right button on mouse
  • Select “Measure Distance”
  • Click left button on mouse for first and the rest of the points

Here’s an approx 1 mile loop near my house.

Here’s an approx 1.5 mile loop near my house.

Please watch out for cars!

Heart Rate Training (HRT) – Part 14

Part 1 of this series.

I convinced an athlete friend to do the Five Mile MAF baseline test. This is the same athlete friend who did the protein test with me (Blood Sugar Responses Compared).  He is a trained runner. Here are his MAF test results. He is 35 so his MAF HR is 145. He was able to keep an average heart rate of 144. His average pace at that heart rate was 7:58.

He currently eats a mixed diet but does Low Carb some portion of the time.


Heart Rate Training (HRT) – Part 13

Part 1 of this series.

Last month I was not following the Maffetone method. I was getting up in the morning and running as fast as I could. I captured the data from one run around my neighborhood. This is the map of the 1.4 mile loop I ran around my neighborhood.

Elevation Data

That run has a pretty decent uphill (and downhill is even steeper) which makes the heart rate challenge even more difficult.

My Heart Rate Data

During my run, I also recorded my heart rate data. My average heart rate was 157 bpm and my max heart rate was 173 bpm. The average includes the warm-up section at the start. The average after warm-up was more – somewhere around 162 bpm. This is my max heart rate from the 220 minus age method. At 173 bpm I was over the 220 minus age method value. Probably not a great thing to do.

How does this correlate to my VO2max numbers? What was I burning when I was running? My chart from the last post was:

HR RER %Fat %Carbs
120 0.70 99% 1%
125 0.74 88% 12%
130 0.77 77% 23%
135 0.80 66% 34%
140 0.84 55% 45%
145 0.87 44% 56%
150 0.90 33% 67%
155 0.94 21% 79%
160 0.97 10% 90%
165 1.00 0% 100%

This shows nearly all of my run was fueled from carbs and almost none of the run was fueled from fat.

What’s Wrong with Burning Carbs?

This level of heart rate is not sustainable for very long when on a Low Carb diet. Running burns about 100 calories a mile. That is a significant portion of the body’s store glycogen store. Additionally, the body is glucose sparing when on Low Carb so it resists the additional glucose that is in circulation.

My Pace

My pace wasn’t all that great either. The app shows the average pace of 9:38.

Since I was at my heart rate max without training my heart rate to be lower my performance gains would have been hard fought.

Why Heart Rate Train?

Heart rate training offers the opportunity to improve performance within the fat burning zone. The promise is that speed will increase at the same heart rate as cardiac health improves.


Heart Rate Training (HRT) – Part 12

Part 1 of this series.

Second MAF Test

I did a five mile walk on a track tonight. It was an attempt to get a better MAF baseline. Here is the Strava (with my Samsung phone).

Here is my heart rate from my Samsung Gear Sport watch.

I did a good job of keeping my heart rate in the 112-122 range. I would have liked it to be a bit higher and still in the range but I am pleased with the results. Here’s my splits graphically (from the phone).

The splits show a good drop starting at the third mile. This is as expected. Also, I didn’t do a legitimate warmup, I just started into walking so it took about a half mile for my heart rate to get to the range. Next time I do one of these I will do a warmup and then start recording data when at the correct heart rate.

Here’s the happy walker after the 1-1/2 hours were completed.

If the MAF method works for me and I put in the training effort I should see those split times decline. Also, I should be able to start slow running soon.


Heart Rate Training (HRT) – Part 10

Part 1 of this series.

Dr Noakes to the Rescue?

I think we are trying to fit big feet into small shoes by trying to make Low Carb fit into exercise modes which are by design not compatible with being fat fueled.

I have great respect for Dr Noakes, but in my opinion the following video illustrates how we are missing the point when it comes to athletic performance and Low Carbohydrate diets.

Dr Noakes (@20:00) makes a startling comment in the video (@20:04).

There must be an exercise duration for which fat adaptation is the preferred state for optimal performance and I don’t know if we have found it yet…

Dr Noakes is humble in this video and admits that his own studies which showed advantages may have been biased – that was helpful for those of us who bought the hype that we can perform any sport on LC and do it well.

However, this video completely misses the point in a weird sort of way. People do low carb and get great benefits but find it doesn’t mix well with their particular athletic modality. In fact, they may find it doesn’t mix well with any competitive athletic modality. And, all athletics is artificial in some sense so to conclude that it is a bad diet based on some artificial measurement is missing the mark. Low Carb has found a home with triathletes and ultra-marathon runners but those are fairly elite choices.

What Dr Noakes is missing is that the real issue isn’t one of duration. The issue is one of fuel source. Certainly intensity and duration are inversely related. Sprints are intense and short. Ultra-marathons are low intensity but very long in duration. Few people want to do an ultra marathon.

We low carb athletic proponents are fond of touting the advantages of fat adaptation. It is true that the low carb athlete is better at accessing fuel but only out of necessity since the body spares carbohydrate stores on the low carb diet. The body doesn’t want to spend carbs on exercise since those stores are limited. But if you push your intensity up high enough it will pull from carb stores and these are limited in both depth and speed that can be accessed on a low carb athlete. This necessarily reduces exercise intensity to levels that are not competitive.

This is why folks who do Crossfit or take up wrestling find that they need to supplement carbohydrates. They chose to alter their diet to fuel their exercise rather than picking an exercise mode which matches their diet. Personally, I view this as a fundamental mistake.

What is the Answer?

The right answer is to engage in athletic activities which utilize the fat as fuel and don’t rely on carbohydrates as fuel. When a person is completely fat fueled they have a very deep tank of storage for energy. The use of fat as fuel necessarily translates to a reduced intensity which is problematic on any medium duration sports.

What intensity level is this done at? Here’s where some data can illustrate the point. Ben Greenfield published his own VO2max testing and I’ve plotted his VO2max numbers vs his RER numbers. (Remember that RER is a measure of fuel mixture. An RER of 0.7 indicates that the person is 100% fat fueled and an RER of 1.0 indicates a person is 100% carbohydrate fueled. An RER of 0.85 would be 50-50 mix of fat/carbs.)

Ben’s data is pretty jumpy so the red line is a 3rd order polynomial which is fitted to the data (the R^2 was 0.85). It shows a dip (more fat burning) at around 35% of VO2max. The data also shows a fairly flat line across the entire range from 25% to 50%. The actual data showing the dip is:

This is a very specific point in time where Ben Greenfield’s data showed him burning 97% of his energy from fat – clearly the sweet spot for a person who is fat fueled since almost none of the energy he was using came from carbs. Ben never got an RER below 0.7 so this is the best he did during that time. Unfortunately, that point is a pretty low point level of intensity. Well, sorta. Ben’s VO2max is 61.1 and that point was at a VO2 rate of 27.2 so the point where Ben was being as fat fueled as he possibly could be was at 45% of his VO2max.

This correlates well with other published data:

This shows a peak fat oxidation rate at 65% of VO2max but the issue isn’t one of maximum fat oxidation since at 65% the fat is mixed with carbohydrate oxidation. That does produce the most efficient exercise but only in a non-fat fueled athlete. The attractiveness of the data is that it clearly shows a fairly wide curve. The whole graph is relatively flat from 50% to 75%. But what is different between these two points is the fuel source in the body.

Fine Tuning Fat Burning

The spot is the highest intensity which can be reached where 100% of energy comes from fat and 0% from carbohydrates. I don’t know if there’s a term for this but let’s call it the Maximum Glucose Sparing/Fat Burning the MGSFB point.

I happen to know my MGSFB from my VO2max data. Here, I’ve added a bulls eye at the MGSFB point. At this point my RER was 0.7 and rising.

[Note for people trying to lose fat: I have no interest  at all in fat burning at this point in time but the implications of the above should be obvious for those who are interested in fat burning. You can get the most bang for the buck in fat burning at a level which is much less than your max heart rate. If you are beating yourself up in the gym that may be good news.]

My MGSFB was at 65% of my VO2max and it was at a HR. This matches the point at the top of the curve shown of fat oxidation rates vs VO2max. In fact, that could well be the very definition of fat adapted – ie, the ability to most efficiently burn fat at the highest VO2max point.

This was at a HR of 117 bpm. This correlates well to the center of the Maffetone HR value of 112-122 bpm. In fact, it might suggest that I should drop my range to 107-117 max since that guarantees I stay in the fat burning range for the entire activity

So how do you figure this out for yourself?

Here’s the approach I essentially took to get to this number:

  • Get fat adapted by adopting a Very Low Carb diet (< 30g of carbohydrates)
  • Do this for the TBD (days/weeks/months) adaptation period
  • Get your VO2max tested
    • If your VO2max doesn’t show you with an RER of 0.7 for a large portion of the test time you are not yet fat adapted
  • Plot the curve or just look at the data and find the highest point where your RER is still 0.7 or less
    • The point at which it goes over 0.7 you are no longer burning fat exclusively
  • Find the corresponding heart rate
    • That is your max heart rate for exercising

A Cheaper/Easier/Faster/Close-Enough Way

Just use the MAF calculation. It’s close enough. I like it enough that I wrote an MAF calculator and put it on-line here.


Heart Rate Training (HRT) – Part 9

Part 1 of this series.

Does participation in strenuous physical exercise provide a shield against metabolic disorders? (Strenuous in this instance being defined as exercise at a heart rate above the MAF number).

The reason I ask is that one of the founders of Crossfit, Greg Glassman, says that Crossfit has the cure for metabolic syndrome (Chronic Disease: “We Have the Answer”). But what does the scientific data say about strenuous athletics and metabolic disorders?

Is blood sugar dysregulation primarily the result of lack of strenuous activity? Can diabetes be reverse by strenuous exercise?

Here’s a really interesting 2016 study on Blood Sugar levels in athletes (Felicity Thomas, BE(Hons), Chris G. Pretty, PhD, Thomas Desaive, PhD, and J. Geoffrey Chase, PhD. Blood Glucose Levels of Subelite Athletes During 6 Days of Free Living. J Diabetes Sci Technol. 2016 Oct; 10(6): 1335–1343). The study notes the mechanistic view that:

Physical training is known to improve insulin sensitivity, both immediately postexercise (up to 2 hrs) and through multiple adaptations in glucose transport and metabolism.

Therefore, it could be expected high BG would not be frequently seen in athletes and low BG would be of greater concern due to increased energy expenditure.

However, the data did not support that mechanistic view. As the study noted:

However, this hypothesis does not appear to be the case in the data we have collected.

Wow! Data that doesn’t match the theory? For this study they looked at…

Ten fit, healthy subelite athletes (resting HR <60 bpm) were recruited…

There wasn’t much in the study to indicate the normal intensity level of the activities except:

All subjects regularly trained > 6 hours per week in a range of endurance based sports, predominantly running and cycling.

However, the study did a fasted exercise – ramp test on day 2 – where the participants did 60 minutes of warmup and 30 minutes of exercise to exhaustion.

The researchers measured the subject’s blood sugars using continuous glucose monitors (and other parameters) and data was recorded for six days. They expected the athletes to be in good metabolic health but instead they found that:

4/10 athletes studied spent more than 70% of the total monitoring time above 6.0 mmol/L even with [sic: when] the 2-hour period after meals is excluded.

Fasting BG was also in the ADA defined prediabetes range for 3/10 athletes.

The conclusion of the study was:

Contrary to expectations high BG appears to be more of a concern for athletes then [sic: than] low BG even in those with the highest energy expenditure and consuming below the recommended carbohydrate intake.

This study warrants further investigation on the recommended diets and the BG of athletes to better determine the causes and impact of this hyperglycemia on overall athlete health.

Here is the most interesting paragraph:

However in contrast, strenuous exercise is known to increase circulating concentrations of catecholamines, such as adrenalin and noradrenaline, to near pathological levels, resulting in hyperglycemia and hyperinsulinemia post–intense exercise.

I wonder if all of this has a cause in the intensity of the activity? That seems to be an implicit part of the study which sought to look at:

asks what impact their increased insulin sensitivity, heightened energy expenditure and increased exposure to stress hormones have on their BG levels.

My n=1

I recently did my own measurements in relationship to strenuous activity (Ketones and Blood Sugar Responses to Exercise). This experiment showed my blood sugar rise from 92 to 129 and my ketones fall from 1.0 to 0.3 with 45 minutes of strenuous activity. That’s the highest blood sugar I have recorded in a long time. But that’s also the first time I measured my blood sugar in response to strenuous activity. I assume it always does the same thing.

I took my blood sugar after MAF heart rate activity and it didn’t rise much. In my view, a number of factors work against a diabetic Low Carb athlete:

  1. Strenuous exercise raises the RER out of the fat burning zone into the carbohydrate burning zone.
  2. In response to the high demand, the body mobilizes additional glucose from the body’s glycogen stores.
  3. Glycogen stores are seriously limited in a Low Carb athlete but still present.
  4. The ketogenic state creates a state of glycogen/glucose sparing in the muscles which resists taking up glucose.
  5. If the body didn’t resist taking up glucose the person would have no glucose since dietary sources are limited and it is metabolically costly to make glucose from other substrates (Fat and Protein).
  6. Diabetics have an attenuated first phase insulin response from their pancreas to glucose in the blood stream so they are unable to respond properly to the additional glucose that comes with strenuous exercise.

The only solution to these issues is either:

  1. Abandon Low Carb diets or increase carbs around exercise
  2. Suffer lower performance when performing strenuous activities
  3. Perform physical activities which are not glycogen dependent

This is where MAF fits the bill perfectly.

This is also where Crossfit fails miserably.


Heart Rate Training (HRT) – Part 7

Part 1 of this series.

My MAF Baseline – My Afternoon at the Track

I took a trip to the local track.

I walked a 5K in distance (3.1 miles).

I found it a little bit challenging to keep my heart rate at the MAF HR range of 112 – 122 but I did pretty good at it:

It took about 12 minutes walking to get to the baseline heart rate. This matches this article (Maffetone, Phil. Want Speed? Slow Down! MAF Website, April 30, 2015.):

The test should be done following an easy 12–15 minute warm up

At about 39 minutes into the walk I noticed that my HR went high (around 138 bpm) so I slowed down and my HR dropped pretty quickly back into the MAF HR range. I was shooting for 117 +/- 5 bpm.

My speed was very variable over this walk with speeds as low as 2 mph and as many as 5.5 mph. I wonder if that is an artifact of the GPS sampling. The watch app (Samsung Health) indicated that my average speed was 3.8 mph (3.15 miles in 49m 17s or 0.821 hours = 3.84 mph). If that was my average clearly my last 8 minutes was much slower.

Samsung Gear Sport Watch

Here’s a picture of the watch running the workout app in “walking” mode.

The watch shows that at 48:21 minutes into the walk my HR was 115 and my mile pace was at 17’49”. That is a decently fast walking pace. At no point did I run.

The orange color of the heart indicates that the watch is showing the HR in the appropriate range. It goes yellow if the HR goes too low and red if it goes too high. It seems like the MAF numbers are pretty close to the standard HR numbers that the watch uses. The watch also vibrates when the color change. It may vibrate differently but I’ve not noticed a difference.

Here’s the overall statistics from the app.

My average HR of 116 is right in the range for my MAF HR.

The only thing I probably could have done better would have been to run Strava on my cellphone at the same time and logged the speed in there. It might have been more accurate.

Calories Burned

The reality that a 49 minute brisk walk only burns 229 calories is pretty discouraging for anyone wanting to lose weight. That’s 0.065 lbs of fat. Doing this every day for a month would only result in a loss of 2 lbs of fat. That’s not a whole lot of weight to lose for that much effort.

The beauty of working out at this rate is that the loss is almost guaranteed to be all fat loss and no glycogen/carbohydrate loss.

Workout Frequency?

So far I haven’t seen how often this should be done. I don’t see a practical reason that it couldn’t be done every day. After watching some interviews with Phil Maffetone on YouTube I see that the regular program is prescribed. So I think I will go back to my 5K training program using this method. Unless I get a rower, that is.


Exercise Studies

This will be an accumulated list of exercise related studies.

Athletic performance on Low Carb

Exercise and Diabetes

Exercise Physiology (Mechanisms)

Exercise Supplementation


Splitting Low Carb Studies BLOG into Two Sites

The Low Carb Studies BLOG is being split into two sites. The original Low Carb Studies BLOG will concentrate on the Low Carb/Ketogenic diet. This site will focus on Athletics on the Ketogenic Diet.

It will take a while to move the content over but allow more focus on each subject individually.