Estimating glycogen usage from power meter data

I went down this path a few years ago and started looking at typical substrate utilization as a function of intensity curves. If you dig a bit you can come up with published data for glycogen vs. percentage of VO2 Max for instance. But it's very hard to tie that to percentage of power at a particular reference point (VO2 Max, MAP, etc.) and it varies between individuals and even for the same individual depending on training.

If you take the whole concept further through ideal refueling, glycogen resynthesis rates and RMR/BMI concepts it turns out not to matter very much.

Here's the problem, say you could accurately determine based on AP/NP or IF that you burned 1000 Calories of which 600 were from your stored muscle glycogen and blood/liver glucose. Naturally you'd want to replenish that glycogen and not much more if you're interested in weight loss but want to train on subsequent days. Trouble is you can't ingest 600 Calories of glucose and immediately resynthesize and store it as muscle glycogen. Even during the peak glycogen resynthesis phase immediately following exercise (the critical half hour) you can only resynthesize about half that amount of glycogen.

So you make a giant smoothie with the ideal (debabtable exactly what constitutes ideal btw) ratio of carbs to protein and try to get exactly 600 Calories of carbohydrate on board. Well half or more of that will be stored as fat since you've exceeded peak glycogen resynthesis rates.

Well it turns out that's not a big deal either. In the end your body requires energy even at rest and it still comes down to calories in vs calories out. So if your net caloric balance is negative you'll burn through those carbs you ingested that converted to fats. But you won't have replenished all the glycogen you burned on your ride.

Sure I guess you could come up with detailed schedules that attempted to restore just enough glycogen over your complete day and multiple meals and somehow estimate the glycogen burn rate during rest and daily activities to add to that burned during exercise. But then what, measure every meal, time it just right and hope your estimates of resting glycogen/glucose requirements are accurate?

In the end it makes sense to refuel with 200 to 300 Calories of healthy carbs combined with some protein (3:1, 4:1, 2:1 take your pick, the research isn't conclusive) immediately after exercise since that's about all you can process at once (and why the standard serving sizes for Endurox, Metabolol, Recoverite, etc. are all about the same). Follow it up with a healthy meal or another recovery drink 45 minutes to an hour later and eat a balanced diet including plenty of healthy carbs throughout the day.

And most of all, maintain an appropriate daily caloric balance to gain, lose or maintain weight. You don't have to exactly dial in the macronutrients to make sure you store just the right amount of glycogen. You do have to make sure you include plenty of healthy carbs across the day and the critical half hour refueling is key but it gets real hard to dial it in a lot more closely than that outside of a controlled lab environment.

-Dave

PS, There could be a relationship between TSS and glycogen consumed but it's certainly not a 1:1 relationship.

Take a rider with 300 watt FTP who rides a full hour FTP test to generate 100 TSS in an hour. That's 1080 kJ of energy consumed in an hour at relatively high intensity. Even taking a lowball swag at glycogen utilization being 75% at FTP (I'd guess much higher for most athletes) the rider would burn through more than 800 Calories of glycogen not 100 predicted by "glycogen = TSS"....

-Dave

perrygeo said:

Is there another estimate for the grams of muscle glycogen consumed on a given ride?

Glycogen doesn't belong to the "world" of feeding as much as it belongs to the "world" of training. Like Dave said, you can't eat Glycogen. By training, we increase our ability to store more. Key word here, is training. Good news though, is that you made your way in pinpointing such an important component to performance/fatigue. We do train in order to increase our potential to store it. And by training we deplete it.

I am no expert in training with Power (although I do own a pm). But as far as I can understand the concept (TSS/CTL/ATL etc), to me, CTL/ATL impersonates (among other things):
1- your potential for storing Glycogen (CTL which translate into greater work capacity) as well as
2- your current glycogen level (ATL, in a reverse relationship of course). That is, the higher ATL, the lower the Glycogen levels (or so I would expect).

My goal here isn't to oversimplify this wonderful concept by narrowing it down to just the Glycogen factor (there's more to it, Central and peripheral nervous system fatigue, muscle tissue damage rebuild etc). But I believe that this concept encapsulate the glycogen matter so well that there's no need to follow (in parallel) glycogen levels, even if it was indeed possible. Same thing with Lactate levels during workouts or any other factor that contributes to fatigue. This, I find, is yet an other occurrence of "Best predictor for performance, is performance itself" (A.Coggan)

So keep going with your quest to try to understand relations between nutrition and performance, follow Dave's advices, and trust PMC to monitor your Glyco levels.
- - - - -
here's little food for your thoughts: "Athletes can become nearly depleted of glycogen after one or two training sessions or by long, intense training sessions of 1hr or more (Houston 1978; Beltz et al. 1988). "Conclusive proof exists that successive days of intense training can almost completely deplete glycogen (Costill et al. 1988). Finally, Coggan wrote a huge paper on sugar (if I am not mistaken). I'd give this paper (which is fairly recent) a priority of you want to dig deeper into the topic.

daveryanwyoming said:

There could be a relationship between TSS and glycogen consumed

There is (with an R^2 of 0.75).

Pretty good fit considering the range of things involved.

So what does the best fit function look like? I'm thinking it has to also be a function of absolute FTP since that impacts kJ per hour at a given AP or NP.

-Dave

daveryanwyoming said:

Pretty good fit considering the range of things involved.

So what does the best fit function look like? I'm thinking it has to also be a function of absolute FTP since that impacts kJ per hour at a given AP or NP.

-Dave

I posted graphs of glycogen use vs. TSS, rate of glycogenolysis vs. IF, and and rate of glycogenolysis vs. blood lactate concentration to the wattage list earlier this year in threads titled "For your viewing pleasure" and "Two more plots":

Wattage | Google Groups

Wattage | Google Groups

Rather than attempt to reproduce them and the discussion that followed here, I'll just point you "that way!" (since I know you're on the wattage list).

Ahhh yeah, I remember at least one of those charts.

Thanks...

Guys, when you finished speaking Chinese, if you could dum your findings down for us, I'm sure I wouldn't be the only one to be interested in understanding 'em... 🙂

Well those are Andy's charts to describe and a fair amount has been hashed out on the Google Wattage Group: http://groups.google.com/group/wattage but you have to apply for the free membership to view the discussions.

But the one that intrigues me the most is the chart he's posted showing rate of glycogenolysis vs IF

Basically it shows a surprisingly good linear fit between rate of glycogenolysis in units of mmol/min/kg to (Intensity Factor)^2 which is the foundation of TSS.

The fitted line is described by:
rate of glycogenolysis = 2.6754(IF^2) - 0.9965
and its R^2 is 0.7862 showing a pretty good but not a perfect fit to the data (ideally, R^2 = 1)

But in english it means you can estimate rate of glycogen burn fairly well based on IF^2 and if you play around with units a bit can estimate glycogen burned from TSS. It also implies resting rate of glycogenolysis of negative 0.9965 mmol/min/kg if you take IF=0 which doesn't really make sense so I'd guess this model only applies for moderate to hard exercise.

But it's not as simple as Glycogen burned = TSS as the OP suggested and there's still the question of whether knowing the amount of glycogen burned on a ride with great accuracy is all that useful in terms of daily fueling strategies for the reasons listed above.

-Dave

Dave, thanks.

Was I right then in simply suggesting to OP to rely on performance management chart for this matter?

I mean, reason for this relatively good "fit" is probably because without it, the PMC wouldn't be doing that much of a good job would it?

(BTW, whenever I issue doubtful or wrong recommendations, please do advise. I don't bite ;-)

Quoted post said:

...Was I right then in simply suggesting to OP to rely on performance management chart for this matter?...

Well, the OP was asking how to estimate glycogen utilization for the purpose of refueling for weight management purposes. From that standpoint I wouldn't suggest basing refueling strategies on the PMC.

Trouble is CTL represents a weighted rolling average of roughly your last 3 to 4 months of daily training load and ATL represents roughly your last 3 to 4 weeks with the default time constants. So I wouldn't plan day to day caloric intake based on a 3 week or 3 month rolling average.

The PMC does a great job of modeling long term training load with CTL or in effect the long term average daily training load you've sucessfully adapted to. The sucessful adaptation is implied because it's hard to overtrain continuously for nearly 4 months so if you achieve a certain CTL then by definition you've been working at that average daily load for quite some time. It also does a good job of modeling short term or recent training load via ATL and predicting immediate fatigue vs. freshness by taking the difference between the two. But none of that is immediate enough to guide daily refueling strategies.

Actual energy in kj burned on the ride gets you much closer in terms of estimating immediate refueling needs. The graphs above imply that you could use TSS or IF to estimate the sugars that you burned but again in the end what really matters is total calories from a broad based and healthy diet and as long as that diet doesn't overly restrict carbs or protein there's not much value in trying to dial it in more accurately.

-Dave

Negative glycogenolysis at rest is not clearly wrong: at rest you are always resynthesizing glycogen at some non-zero rate, unless stores are 100% topped off.

I can understand zero glycogenolisis at rest, but negative? Would glycogen resynthesis actually represent itself as negative glycogenolisis?

'Guess it could but it hits me as strange that this data fit could predict both glycogen utilization and glycogen resynthesis based on the model's intercept as they're very different processes. Looks to me like a modeling artifact rather than part of a greater glycogen utilization-resynthesis model. But as I said above, I'm just eyeballing a couple of curves and that's what hit me, I don't claim to know the limits of those graphs or even the major points demonstrated by those curves.

-Dave

"Negative" glycolysis, glycogen resynthesis: they're the same process, putting glycogen back in the muscles. And yes, if you're at rest, and have a glycogen deficit, then the glycogen is getting put back at some non-zero rate. Or am I missing something?

Glycogenolysis or the catabolism of glycogen is an energy consumption phase, glycogen resynthesis or the restoring phase isn't just catabolism in reverse. It's an entirely seperate process that requires among other things a ready supply of blood glucose, is typically aided by insulin and is part of the magic during the critical half hour refueling after a workout but goes on at a slower rate throughout the day. Just the fact that glycogen resynthesis rates are known to change from the first half hour to hour after exercise to lower rates later in the day makes it hard to believe a linear data fit from exercise data accurately predicts that rate.

Like I said, all I've done is look at the charts, but they're just fitted scatter plots of data taken during moderate to hard exercise. I'd be amazed if that data linearly extrapolates down to rest and accurately describes how your body engages seperate processes to refuel. It would be like taking automotive fuel consumption data collected while driving, fitting a line and predicting rates of refueling at the gas pump.

At least that's how it hits me, but again I'm just thinking out loud and don't claim to know this stuff anywhere near this level of detail.

-Dave

daveryanwyoming said:

Actual energy in kj burned on the ride gets you much closer in terms of estimating immediate refueling needs. The graphs above imply that you could use TSS or IF to estimate the sugars that you burned but again in the end what really matters is total calories from a broad based and healthy diet and as long as that diet doesn't overly restrict carbs or protein there's not much value in trying to dial it in more accurately.

-Dave

Well it might not hold much value but seeing as how we can estimate it using available data from a power meter, it would not hurt to investigate it!

Let me give you an example of how it could be useful. Just assume for a moment that the normal sedentary person needs, say, 150 grams of carbs daily for their base metabolic activity. Anything significantly more increases insulin and causes weight gain, fat storage, insulin resistance, etc. But, as active cyclists, we need more. How much more? One could argue that we need 150 grams + x where x is the amount of carbs necessary to top off glycogen stores (x will therefore always be some amount greater than the glycogen consumed during a ride due to metabolic inefficiency).

So given these two rides, planning your diet to recover for a ride the next day:

Ride A: 2000 kj = 2000 cal = 250 g carbs + 111 g fat
Ride B: 2000 kj = 2000 cal = 40 g carbs + 204 g fat

Ride A would require doubling or tripling your carb intake over the next day. In addition to the recovery drink or two, this would mean planning carb-heavy dishes for several upcoming meals.

Ride B might only require a recovery drink and an extra helping of potatoes at dinner.

Now I know there are a lot of assumptions thrown in there (assumptions I'm in no way qualified to make 😉) but I'm just throwing this out there as an example of how info esimated from a power meter could be used to make dietary choices for riders on a semi-low carb or paleo type diet.

Well since I don't buy into many of the underpinnings of low carb or paleo diets I don't see much value in carb restricted diets. So basically you're losing me at the outset.

IME, there are a lot more endurance athletes that hinder their training and adaptation via short and long term glycogen depletion than those that run into insulin resistance or excessive fat storage by eating a relatively high carb diet coupled with regular training.

But from a purely academic standpoint I agree it's an interesting subject. I just don't think it's that valuable to endurance athletes but if you're a fan of carb restricted diets and are looking for minimum daily carb intake levels then I can see your interest.

Good luck and keep an eye out for bonking, chronic glycogen depletion and symptoms of overtraining. And remember your brain only feeds on glucose and in addition to the estimates of glycogen and blood glucose burned during exercise you'll also want to get good estimates of your daily non-cycling rate of glucose and glycogen burn. Dial those in perfectly, measure your meals with great accuracy, time your carb ingestion so you don't exceed your ability to store that as glucose and glycogen and you may be able to safely stay at low carb levels without leading to problems. But IMO it's playing with fire for little gain....

-Dave

daveryanwyoming said:

Well since I don't buy into many of the underpinnings of low carb or paleo diets I don't see much value in carb restricted diets. So basically you're losing me at the outset.

IME, there are a lot more endurance athletes that hinder their training and adaptation via short and long term glycogen depletion than those that run into insulin resistance or excessive fat storage by eating a relatively high carb diet coupled with regular training.

But from a purely academic standpoint I agree it's an interesting subject. I just don't think it's that valuable to endurance athletes but if you're a fan of carb restricted diets and are looking for minimum daily carb intake levels then I can see your interest.

Good luck and keep an eye out for bonking, chronic glycogen depletion and symptoms of overtraining. And remember your brain only feeds on glucose and in addition to the estimates of glycogen and blood glucose burned during exercise you'll also want to get good estimates of your daily non-cycling rate of glucose and glycogen burn. Dial those in perfectly, measure your meals with great accuracy, time your carb ingestion so you don't exceed your ability to store that as glucose and glycogen and you may be able to safely stay at low carb levels without leading to problems. But IMO it's playing with fire for little gain....

-Dave

Whether or not you personally subscribe to this diet is irrelevant to whether estimating glycogen usage from a power meter could be a useful dietary planning tool.

In terms of "playing with fire", the paleo/primal eating patterns has worked for many atheletes. Nothing too crazy, just lots of veggies, nuts, fruit, meat, fish and some root veggies, whole grains and sports drinks when carbs are needed. I've been on several podiums in the US Cup Cat 1 cross country race series this year, all following Friel's "Paleo Diet For Atheletes" book. So I find your scare tactics against such a diet to be somewhat baseless and amusing given the number of endurance atheletes that are successfull with it. But thats another topic for another forum.

perrygeo said:

Whether or not you personally subscribe to this diet is irrelevant to whether estimating glycogen usage from a power meter could be a useful dietary planning tool. ...

I do believe a PM is a useful dietary planning tool, total kj burned on a ride is very useful for planning my daily refueling. I just don't see a lot of added value in breaking calories burned down further. Attempting to single out the sugars burned only makes sense to me if I'm also trying to minimize carbs in my diet so yes, subscribing to a restricted carb dieting philosophy is relevent to this discussion. If you're not trying to restrict carbs and go with something like the common 70% carb recommendation for endurance athletes(see AIS link below) then there's not so much value in pinpointing the exact breakdown of the calories you burned during exercise.

Your approach of pinpointing sugars burned and using that to drive refueling strategies only makes sense if you believe you can accurately estimate glucose/glycgogen utilization for the rest of the day and also believe you can refuel in a way that translates all ingested carbs to stored glycogen or blood/liver glucose. Fail to do those two things and you're back to calories in minus calories out regardless of the macronutrient makeup so where's the value added?

Take an athlete with a daily BMR of 2000 Calories and they ride at an AP of 200 watts for 2 hours per day. That's roughly 1440 Calories per day on the bike of which some percentage comes from stored sugars, for the sake of discussion let's just say you have a method of determining that 1000 Calories came from stored sugars.

Well now you've got 1000 Calories worth of glycogen to replenish plus some percentage of that 2000 you burn just to make it through your day. How many of those come from sugar stores? Even if it's only 25% of the total that's still the difference between trying to replenish 1000 Calories of carbs per day and 1500, pretty big swing without a lot of tools to refine your estimate. IOW, the percentage of the day when we have PM data and tools like the IF chart posted above are a small percentage of our lives and to do what you suggest you'll want to account for more than just what happens on the bike.

As for the diets, sure folks have success with many approaches and many also find ways to modify diet templates to their own ends. See what the Australian Institute of Sport says about various diets. In particular note what they say about what athletes are actually doing in the context of the Zone diet. Sure it's not the paleo, but someone saying they follow a particular diet and what they actually do often differs.

Australian Institute of Sport :: Fact sheets

If you're going to make the argument that some high level athletes have had success perhaps even great success with a particular diet then you also have to acknowledge that far more athletes including very successful athletes have had success and even great success not following that diet. IOW, anectdotes of someone's success does not prove that the approach is superior, just different even if they have followed it to the letter which is hard to validate.

You may consider warning someone of bonking or chronic glycogen depletion a "scare tactic" but bonking happens all the time as does chronic depletion of glycogen levels and the poor training that results from it. As I said, manage it well enough and you can avoid those things but they happen all the time and if you intentionally restrict carbs you're increasing the odds of ending up there. Nope, not a given but again unless you buy into the "scare tactics" of insulin resistance and excessive fat storage that these diets promote then there's not much benefit for the added complexity and risk of fine tuning carb utilization estimates and refueling strategies.

Do whatever makes sense to you, but if you're asking for buy in or support for your approach you're not likely to find it here.

Still, interesting discussion even if I don't agree with the premise...

-Dave