As we have discussed at length in previous blogs, and in our courses, carbohydrates and fats provide the energy to fuel metabolism during prolonged, endurance exercise (3). The carbohydrate energy we have stored in our muscles and liver as glycogen is limited, and can become depleted to low concentrations during long-duration exercises like Ironman triathlon (1, 6). In contrast, our fat energy stores, whilst metabolised more slowly, are effectively limitless in the context of exercise. For example, given that 1 g of fat provides ~9.75 kcal of energy (4), it can be estimated that a lean 70-kg individual with 10% body fat has ~68,250 kcal of endogenous fat energy. Theoretically at least, this is enough energy to complete more than six full-distance Ironman triathlons (5).
Accordingly, exercise physiologists have conducted huge amounts of research into the factors that influence the rates at which we metabolise fats and carbohydrates during exercise. This research has been particularly useful for those seeking to manipulate substrate utilisation responses to specific training sessions. My PhD student Jeff Rothschild and I recently published a paper that sought to synthesise the vast existing literature on this topic, to identify the factors that are most determining substrate utilisation responses to exercise.
What we did
To do this, we extracted data from 433 studies reporting the respiratory exchange ratio (RER) during continuous cycling exercise. The RER is the ratio of an individual’s carbon dioxide production to oxygen consumption during exercise and is measured by indirect calorimetry or the collection of expired gases. As the burning of fat produces an RER of ~0.7, and the burning of carbohydrates produces an RER of ~1.0, we can make inferences about an individual’s substrate utilisation through the measurement of RER. For example, if an individual has an RER of 0.85 during exercise, this suggests they are fuelling their metabolism through a 50:50 mix of fat and carbohydrate; lower values suggest a greater contribution from fat, and higher values suggest a greater contribution from carbohydrates.
We ran correlations between RER and various factors previously linked to substrate utilisation responses to exercise; some easily modifiable, some easily measured, some neither. We then produced linear mixed-effect models to examine the contributions made by various factors to RER responses to exercise.
As I’m sure you can imagine, this work produced a lot of data. Below are the main findings of our initial correlational analyses:
Now I’ll briefly outline some of the main findings from our modelling:
So, as a practitioner or an athlete, what can we take away from all this analysis? Here are three key points:
1. If you are looking to maximise rates of fat oxidation during a training session, it seems more important to focus on daily fat and carbohydrate intake than how many carbohydrates you ingest during exercise, which had less influence.
2. Exercise duration has a very strong effect on RER; so, if you want to generate high rates of fat oxidation during a training session, make it long. As carbohydrate intake during exercise had a relatively modest influence on RER, it may be worth ingesting some carbohydrates during exercise, particularly in the latter stages of very long training sessions.
3. You can’t easily predict your RER response to exercise at an individual level, but we can be relatively confident that modifying these factors (diet and exercise duration in particular) will push it up or down.
And remember, as we like to say at SFuels, it's all about the "Right Fuel, Right Time". Taking in fat-based drinks (e.g. SFuels Train) in the first 90-120 min of endurance training, and then switching to a more carbohydrate-based drink (e.g. SFuels Race +) seems like the best option.
Last, if you want to play with the numbers, check out this app. It uses the same predictive models featured in this study. See what influences your substrate oxidation! It's a real geek-out ;).....
1. Bergström J, Hermansen L, Hultman E, Saltin B. Diet, muscle glycogen and physical performance. Acta Physiol Scand 71: 140–150, 1967.
2. Dandanell S, Meinlid-Lundby A, Andersen AB, Lang PF, Oberholzer L, Keiser S, Robach P, Larsen S, Rønnestad BR, Lundby C. Determinants of maximal whole‐body fat oxidation in elite cross‐country skiers : Role of skeletal muscle mitochondria. Scand J Med Sci Sport 28: 2494–2504, 2018. doi: 10.1111/sms.13298.
3. Hargreaves M, Spriet LL. Skeletal muscle energy metabolism during exercise. Nat Metab 2: 817–828, 2020. doi: 10.1038/s42255-020-0251-4.
4. Jeukendrup AE, Wallis GA. Measurement of substrate oxidation during exercise by means of gas exchange measurements. Int J Sports Med 26: S28–S37, 2005. doi: 10.1055/s-2004-830512.
5. Kimber NE, Ross JJ, Mason SL, Speedy DB. Energy balance during an Ironman triathlon in male and female triathletes. Int J Sport Nutr Exerc Metab 12: 47–62, 2002. doi: 10.1123/ijsnem.12.1.47.
6. Maunder E, Kilding AE, Plews DJ. Substrate metabolism during Ironman Triathlon: Different horses on the same courses. Sports Med 48: 2219–2226, 2018. doi: 10.1007/s40279-018-0938-9.
7. Maunder E, Plews DJ, Wallis GA, Brick MJ, Leigh WB, Chang WL, Stewart T, Watkins CM, Kilding AE. Peak fat oxidation is positively associated with vastus lateralis CD36 content, fed‑state exercise fat oxidation, and endurance performance in trained males. Eur J Appl Physiol in press: 1–10, 2021. doi: 10.1007/s00421-021-04820-3.
8. Nordby P, Saltin B, Helge JW. Whole-body fat oxidation determined by graded exercise and indirect calorimetry: A role for muscle oxidative capacity? Scand J Med Sci Sport 16: 209–214, 2006. doi: 10.1111/j.1600-0838.2005.00480.x.
9. Shaw DM, Merien F, Braakhuis A, Keaney L, Dulson DK. Adaptation to a ketogenic diet modulates adaptive and mucosal immune markers in trained male endurance athletes.
10. Stisen AB, Stougaard O, Langfort J, Helge JW, Sahlin K, Madsen K. Maximal fat oxidation rates in endurance trained and untrained women. Eur J Appl Physiol 98: 497–506, 2006. doi: 10.1007/s00421-006-0290-x.
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