HIIT vs. Steady-State for Fat Loss: Can EPOC Really Explain the Benefits of Intense Interval Training (HIIT, SIE, HIE)?

HIIT vs. Steady-State for Fat Loss: Can EPOC Really Explain the Benefits of Intense Interval Training (HIIT, SIE, HIE)?

EPOC fat loss fatty acid oxidation HIIT hit LISS; MCT MIT SIE steady state wingate workouts

HIIT has been touted to work its fat burning magic by increasing post-exercise oxygen consumption aka EPOC, a marker of the amount of fat you burn after your workouts. Eventually, however, only the total oxygen consumption and energy expenditure count and this is where the putative mechanism behind the fat loss effects of HIIT lacks scientific backup.

Higher excess postexercise oxygen consumption (EPOC) after high-intensity interval exercise (HIIT / HIE) and sprint interval exercise (SIE) has long been touted to explain the greater fat loss scientists observed in several studies which compared the fat loss effects effects classic "cardio" aka steady-state exercise (SSE) to interval training (HIIT / HIE).

To elucidate whether that's a reasonable and, more importantly, sufficient  (meaning: "Is the increased energy expenditure high enough to explain the fat loss, even if the steady state exercise consumes more energy and fat on total?") explanation for the previously mentioned advantages, researchers from the Healthy Lifestyles Research Center at the Arizona State University conducted a study to compare the EPOC response to the three most common forms of aerobic training: high intensity interval exercise (HIE), sprint interval exercise (SIE), and steady state exercise (SSE).

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Ten recreationally active males (age 24 ± 4 y) participated in this randomized crossover study. On separate days, subjects completed a resting control trial and three exercise conditions on a cycle ergometer:

• HIE (four 4-min intervals at 95% HRpeak, separated by three min of active recovery); and 
• SIE (six 30-s Wingate sprints, separated by four min of active recovery); and 
• SSE (30 min at 80% of peak heart rate (HRpeak)). 

Oxygen consumption (VO2) was measured continuously during and for 3 h after exercise to estimate the actual amount of excess energy / fat that was consumed in the three treatment conditions.

Figure 1: Oxygen consumption and respiratory exchange ratio (higher numbers = higher carbohydrate to fat oxidation ratio) during the first three hours after exercise (Tucker. 2016).

Unsurprisingly, VO2 was initially higher than resting control for all three treatments. The increased oxygen consumption, which is a marker of fatty acid oxidation, however, didn't last long: After only 1 h, it returned to pre-exercise levels.

There's room for "cardio": Even though it is not popular, these days, it would be wrong to assume that classic steady state training is always the inferior choice. For someone who's killing it in the gym regularly, the additional HIIT training may in fact be too much of a sympathetic stimulus. The "boring" classic "cardio" training, on the other hand, is predominantly parasympathetic, which is why walking on an incline treadmill may eventually be a better complement to your 4-5 resistance training sessions per week than HIIT cycling or sprinting.

It is thus not really surprising that both, the complete 3-h EPOC and the total net EE after exercise were not extremely different and that that 3-h EPOC and total net EE after exercise were higher (p=0.01) for SIE (22.0 ± 9.3 L; 110 ± 47 kcal) compared to SSE (12.8 ± 8.5 L; 64 ± 43 kcal).

Figure 2: The total O2 consumption (and thus fat oxidation) and energy expenditure during the workout and the 3h thereafter shows that steady state exercise burns more fat and energy than any of the two HIIT regimen (Tucker. 2016).

What goes against the idea of increased fat oxidation after workouts due to HIIT (i.e. SIE or HIE), however, is the scientists observation that the "total (exercise + postexercise) net O2 consumed and net EE were greater (p=0.03) for SSE (69.5 ± 18.4 L; 348 ± 92 kcal) than for SIE (54.2 ± 12.0 L; 271 ± 60 kcal)" (Tucker. 2016), while those for for HIE were not significantly different from SSE or SIE, so that Tucker et al. rightly conclude that "EPOC after SIE and HIE is unlikely to account for the greater fat loss per unit EE associated with SIE and HIE training reported in the literature" (Tucker. 2016).

Bottom line: As Tucker et al. rightly point out, simple math shows that the increased energy expenditure and O2 consumption during the steady state trial more than compensates the significant, but small increase in energy expenditure and fat oxidation after the workout.

Figure 3: Minute-by-minute energy expenditure during a sedentary day and a day beginning with a single bout of sprint interval training (SIT). Data are mean values (Sevits. 2016).

It is important to know that this does not negate the results of previous studies that found beneficial effects of HIIT on fat loss. What the study does do, however, is to refute the hypothesis that these benefits were a result of an increase in EPOC and thus overall larger total energy expenditure. This, on the other hand, doesn't mean that any effects after the EPOC window of 3h investigated in the study could be responsible for said benefits. As Tucker et al. highlight, "another previously confirmed benefit of intense exercise is that it can increase the resting energy expenditure (REE) [... 17-24 h after exercise ...] in part due to an increase in sympathetic tone " (Tucker. 2016).

In conjunction with increases in the ease of locomotion (16, 17) and increase nonexercise activity thermogenesis (NEAT) (14), these effects could well explain the benefits of HIIT. Studies to confirm that are yet not just lacking, as Tucker et al. highlight, the whole-room calorimeter study of Sevits et al. (32) even suggests that SIE does not elevate REE at 24 h postexercise (see Figure 3). More studies to get to the bottom of the fat loss benefits of HIIT protocols appear warranted | Comment.

References:

• Sevits, Kyle J., et al. "Total daily energy expenditure is increased following a single bout of sprint interval training." Physiological reports 1.5 (2013): e00131.
• Tucker, Wesley J., Siddhartha S. Angadi, and Glenn A. Gaesser. "Excess postexercise oxygen consumption after high-intensity and sprint interval exercise, and continuous steady-state exercise." The Journal of Strength & Conditioning Research (2016).

Carbohydrate Timing Boosts Training Effect: Cut Out Carbs After PM Glycogen Depleting HIT Workout ⇨ "Sleep Low" to Make Game-Changing Performance Gains in Only 3 Weeks

Carbohydrate Timing Boosts Training Effect: Cut Out Carbs After PM Glycogen Depleting HIT Workout ⇨ "Sleep Low" to Make Game-Changing Performance Gains in Only 3 Weeks

athletes carbohydrate timing CHO glycogen glycogen depletion high carbohydrate HIIT hit LISS LIT low carbohydrate performance triathlon

You are no triathlete or coach? That doesn't mean that this study isn't of interest for you. The figurative "extra wind" this training strategy can give you is relevant for almost every athlete.

In a recent study, scientists from the French National Institute of Sport investigated the effect of a chronic dietary periodization strategy in a group of twenty-one highly-trained male triathletes. Previous studies, in which "train-low" strategies, during which athletes are deliberately carbohydrate restricted over certain periods of their training cycle, have reported robust a up-regulation of selected markers of training adaptation (increased whole body fat oxidation, increased activities of oxidative enzymes) compared to training with normal glycogen stores and high CHO availability, however, the subjects experienced at best disappointing performance increases.

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Scientists have long speculated that the disconnect between the benefits "training low" offers on the level of cellular / mitochondrial adaptation, on the one hand, and the real-world performance increases, on the other hand, could be a consequence of the necessarily reduced high intensity training intensity during the low-carb phases (Yeo. 2008; Hulston. 2010). If we simply assume that this hypothesis is correct, the solution to the problem should be obvious: Train low when carbohydrates are not necessary and use them, whenever they promote maximal performance.

Marquet et al. implemented this principle in a way I tried to illustrated in Figure 1. More specifically, they tried to maximize the subjects' performance during PM high-intensity training (HIT) by providing copious amounts of carbohydrates before the session and restricted the carbohydrate intake to close to zero after this glycogen-depleting workout.To test the efficacy of this protocol, the scientists used a 2x3 week study design in which the first 3 weeks were used to standardize the volunteers training regimen (10-15 h·wk- 1 : 40% running, 35% cycling, 25% swimming), assess subjects' compliance to the study demands and ensure they all attained similar baseline fitness measures before study commencement.

Figure 1: Overview of important aspects of the dietary / supplemental aspects of the study.

During the decisive second 3-week phase, the subjects were instructed to follow identical diets (by prescribing exact menus, the scientists achieved a high degree of standardization) in combination with either the previously described "sleep low" carbohydrate intake strategy or their usual carbohydrate intake patterns. Unlike the diet / supplementation regimen, the training program the subjects followed was identical for all of them - it ...

Figure 2: Sample weekly protocol for training and CHO intake (g/kg) to achieve different CHO avail. around training (Marquet. 2016)

"consisted of six sessions over four consecutive days, including high intensity training (HIT) sessions in the afternoon and low intensity training (LIT) sessions the next morning. [...] LIT sessions consisted in 60 min cycling at 65% MAP (218.8 ± 20.4 W - 95% CI: 227.5 and 210.7), while HIT sessions consisted alternatively in 8 x 5 min cycling at 85% MAP (286 ± 26.7 W- 95% CI: 297.5 and 274.7) or 6x5 min running at their individual 10 km intensity with 1 min recovery between sets (37). [...] One LIT session per day was prescribed for the other days of the week for a total training volume of 10-15 h" (Marquet. 2016).

All subjects used their own training equipment to record their activity, the duration and intensity of exercise and heart rate. In conjunction with the volunteers' perceived exertion records, as well as VO2max tests, maximal and submaximal performance tests and the results of a simulation of the final leg of a triathlon race, the scientists got a pretty comprehensive set of data.

The effect of "training low" largely depends on the master regulator of mitochondrial adaptation PGC-1a. The latter is activated not just by the contraction induced calcium flux and exercise stress, but also by a lack of glycogen and increased levels of the (low) energy sensing protein AMPK.

How does "training low" work? By deliberately restricting the carbohydrate intake during certain phases of your training you will be able to train in a glyocogen-depleted state and thus with clearly suboptimal fuel availability. The lack of readily available glucose that can be derived from the glycogen stores in your muscle, whenever necessary, exerts profound effects on your overall resting fuel metabolism and patterns of fuel utilization during exercise and triggers acute regulatory processes underlying enzyme and gene expression, as well as cell signaling (signaling proteins, gene expression, transcription rate of several genes, enzymes activity) which regulate the adaptive response to exercise. The results are an increased capacity to oxidize fat, a reduced reliance on glucose as a preferred substrate, etc.

Data that tells us that the authors' hypothesis that they could get the benefits of training low while avoiding the negative sides by "sleeping low" was accurate:

• 

  Figure 3: Make no mistake about it! The total amount of CHO the subjects consumed was identical it was just timed differently. No difference existed for any of the other macronutrients, either (Marquet. 2016).

  There was a significant improvement in delta efficiency during submaximal cycling , i.e. the power output per calorie, a very important measure for endurance athletes, for the "sleep low" compared to the control group (CON: +1.4 ± 9.3 %, SL: +11 ± 15 %, P<0.05).
• A similarly pronounced, albeit due to inter-individual differences, which loom large in studies with relatively few participants, only borderline significant (P = 0.06) beneficial effect was observed during the supra-maximal cycling to exhaustion trial at 150% of peak aerobic power, where the control group saw improve-ments of only 1.63 ± 12.4 %, while the "sleep low" group improved by 12.5 ± 19.0 %.
• The "sleep low" protocol also triggered significantly higher (P < 0.05) improvements in 10k running performance, where the meager -0.10 ± 2.03 % increase in the control group was topped by a -2.9 ± 2.15 % performance increase in the "sleep low" group.

In the "sleep low" group, even the effects on the body composition were significantly more pronounced compared to the control group. To be precise, the subjects who "slept low" burned a whopping 8.7 ± 7.4 % body fat literally overnight, while the control group lost a likewise measurable, but significantly lower and overall non-significant -2.6 ± 7.4% of their body fat - don't be mislead by the size of the bars in Figure 4; the fat mass is on the right axis which starts at 8kg and ends at 10kg. So there was no significant inter-group difference at baseline. No significant inter-group differences were observed for the changes in lean and total mass, either.

Figure 4: Even if you're not training for performance, the improvements in body composition, or more specifically the significant reduction in body fat without sign. changes in lean or total mass, may be of interest for you | total and lean mass on the left axis, fat mass on the right axis; all values in kilograms; sign. changes in % above bars (Marquet. 2016).

Against that background, it is by no means an exaggeration to say that even in the short-term (and that's what I consider particularly impressive here) the "periodization of dietary CHO availability around selected training sessions" can promote "significant improvements" in several highly relevant performance marker of trained athletes" (Marquet. 2016).

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Drop the carbs pre-bed! No, that's not because carbohydrates in the evening would make you fat. As a SuppVersity reader you know that this is bogus (learn more). The reason why you should consider dropping carbs in the PM (or rather after intense workouts) is their "anti-adaptive" effect - an effect that occurs in response to their ability to replenish your glycogen-stores and thus shut down the "we need to adapt to use more fat" signal to your mitochondria...

Ok, that's not exactly the most scientific explanation (see red box for more), but it is one that highlights one of the most important and yet commonly overlooked principles of physiological adaptations: they occur in response to a need.

If you always provide more than enough carbohydrates, there's no need to increase your ability to use fat as a fuel. If, on the other hand, you (A) fuel yourself with carbs when your body really needs them (during HIT training) to perform at the crucial i + 1 level that will trigger an adaptive response at high intensities, and (B) cut yourself off of a readily available carbohydrate supply when you don't need them (during sleep and low intensity exercise) you maximize the adaptive response to both HIT and LIT (low intensity training) and boost your overall training results | Comment!

References:

• Hulston, Carl J., et al. "Training with low muscle glycogen enhances fat metabolism in well-trained cyclists." Medicine and science in sports and exercise 42 (2010): 2046-55.
• Marquet, et al. "Enhanced Endurance Performance by Periodization of CHO Intake: “Sleep Low” Strategy." Medicine & Science in Sports & Exercise (2015): Publish Ahead of Print.
• Yeo, Wee Kian, et al. "Skeletal muscle adaptation and performance responses to once a day versus twice every second day endurance training regimens." Journal of Applied Physiology 105.5 (2008): 1462-1470.