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.

Weight Loss, 'Metabolic Damage' and the Magic of Carbs? Human Study Probes Effects of Carbohydrate Content, GL & GI on Diet-Induced Suppression of Resting Metabolic Rate

Weight Loss, 'Metabolic Damage' and the Magic of Carbs? Human Study Probes Effects of Carbohydrate Content, GL & GI on Diet-Induced Suppression of Resting Metabolic Rate

dieting GI glycemic index glycemic load high carb high carbohydrate lose fat low carb low carbohydrate metabolic damage resting metablic rate RMR weight loss

Will slimming down from a 120 cm to a 60 cm waist always ruin your metabolic rate and set you up for weight regain or can high GI protect you from yoyoing?

Broscience tells us: "Carb up to preserve your resting metabolic rate." And in fact, there is some scientific evidence that suggests a link between high(er) carbohydrate intakes and increased thyroid function. The same amount of T3 will trigger a sign. higher stimulation of lipolysis and fat oxidation, for example, on high vs. low carb diets (Mariash. 1980). Low carb diets, on the other hand, lead to significant reductions of the active thyroid hormone and increases in the 'thyroid receptor inhibitor' rT3 - even in healthy individuals and if the energy intake is standardizes (Serog. 1982; Ullrich. 1985). So, is broscience right? Well, overfeeding studies show a similar increase in T3 in response to protein, fat and carbohydrates (Danforth Jr. 1979). So refeeds should work, irrespective of their carbohydrate content...

# Women appear to be particularly prone to # metabolic damage - more on # female fat loss:

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As you can see, it is hardly possible to confirm or reject the "carb up to prevent metabolic damage" (=prevent the diet induced over-proportional reduction in resting energy expenditure) hypothesis based on the existing evidence. A recent study by J. Philip Karl and colleagues who tried to determine "the effects of diets varying in carbohydrate and glycemic index (GI) on changes in body composition, resting metabolic rate (RMR), and metabolic adaptation during and after weight
loss" (Karl. 2015), however, may yet take us one step further towards rejecting or confirming this commonly heard of idea.

Figure 1: Overview of the key parameters of the study design and dietary composition (Karl. 2015).

In said study, Karl et al. randomly assigned adults with obesity (n = 91) to one of four diet groups for 17 weeks. As you can see in Figure 1, the diets all subjects were provided with differed in percentage energy from carbohydrate (55% or 70% | Figure 1, top-right) and GI (low or high, Figure 1, bottom-right) but were matched for protein, fiber, and energy. The study design itself comprised 5 phases:

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"Phase 1 was a 5-week weight maintenance phase in which weight maintenance energy needs were determined by adjusting provided energy intake to maintain stable weight. Mean Phase 1 energy intake was 12.2 MJ/day with 48% energy provided as carbohydrate, 16% as protein, and 36% as fat. Following Phase 1, participants were randomized by the study statistician to their Phase 2 dietary assignment using computer-generated randomization. The four diets differed in carbohydrate content (55%, ModCarb or 70%, HighCarb of total energy) and dietary GI (less than 60, LowGI or 80, HighGI), and were provided for 12 weeks at 67% of the weight maintenance energy intake determined in Phase 1. 

Participants were allowed to increase their energy intake during Phase 2 by requesting additional, randomization-appropriate foods from the metabolic kitchen if too hungry to be adherent. Phase 3 was a 5-week weight maintenance phase during which food was provided according to randomization. Energy intake during Phase 3 was prescribed to support weight maintenance at the new, lower body weight, and was predicted from body weight and energy intake measured at the end of Phase 2, with adjustment for self-reported physical activity. Phase 4 was a 12- month follow-up period during which participants selected and pre pared their own meals after being provided with instructions on fol lowing the diet to which they were randomized" (Karl. 2015)

To assess the effects of this sequence of induction (weight maintenance), and weight stabilization phases, the body weight, body composition, RMR, and metabolic adaptation (measured RMR vs. predicted resting metabolic rate = RMR) of the middle aged study participants (49-64 years) were measured before and after all phases of the study.

Figure 2: (A) Weight loss and (B) percentage of total weight loss attributable to fat mass and fat free mass while consuming provided-food diets differing in glycemic index (GI) and percent energy from carbohydrate (55%, ModCarb and 70%, HighCarb) for 17 weeks (n = 79). Values are mean 6 SEM. Weight loss analyzed by repeated measures ANCOVA, body composition by two-factor ANOVA. a,bMain effect of time; asignificant decrease from baseline (P < 0.001), bsignificant difference from Phase 2 end (P < 0.001). No diet effects (main effects or interactions) for any comparisons. GI, glycemic index; HighCarb, 70% energy from carbohydrate; ModCarb, 55% energy from carbohydrate (Karl. 2015).

Interestingly, the analysis of this data revealed no significant inter-group differences in terms of any of the relevant study outcomes. Yes, you read me right: This means that neither the GI, nor the GL, nor the carbohydrate content of the diet had statistically significant effects on weight loss, body composition, RMR, or the metabolic adaptation aka "metabolic damage" due to weight loss.

Figure 3: Measured resting metabolic rate as a function of predicted metabolic rate (Karl. 2015). Note: If there was no "metabolic damage", the solid line which represents the ideal body-weight dependent decline of energy expenditure and the dashed line which represents the actual ratio of the measured to the predicted RMR should be congruent.

While there were no inter-group differences and neither the amount or the type of carbohydrates had an effect on the reduction of the metabolic rate, there is still one interesting result you can see in the right graph in Figure 3. Said graph depicts the ratio of the measured to the predicted metabolic rate during the 5-week weight maintenance phase. If you look closely, you will realize that it suggests that having a high predicted RMR, i.e. being heavier, being taller and being more muscular, is associated with a non-significant decline of the non-predicted reduction of the energy expenditure (=metabolic damage) and thus a narrowing of the gap between the solid and dashed line.

"Solid and dashed? I don't get it!"

You're asking how I can support this hypothesis? Well, the dashed line that represents the true ratio of the actual to the predicted RMR approaches the theoretical one (the solid line) for higher RMR values. If this was more than a trend, it would suggest that two things: (a) Losing less weight and thus maintaining a higher predicted metabolic rate protects against metabolic damage (that would be useless). And (b) being tall and muscular and thus having a naturally high(er) predicted RMR can protect you from suffering metabolic damage when you lose weight.

Unfortunately, it's not possible to tell which (if any) of the two options is correct. If I had to make an educated guess, though, I would say it's a combination of both: The weight change of an average 5.5 kg did not wary too much and was withing 95% confidence intervals of [-7.1 kg, -4.6 kg]. In conjunction with individual physiological qualities of people with higher baseline RMRs, it could still explain the narrowing of the gap between predicted and true RMR after dieting.

Figure 4: Changes in body composition (absolute value in kg) after 20 weeks and after weight loss phase 2 (Karl. 2015).

Bottom line: As Karl et al. point out, "neither low-GI relative to high-GI diets nor moderate-carbohydrate relative to high-carbohydrate diets showed differences with respect to effects on changes in body composition or resting metabolism during weight loss when confounding dietary factors were tightly controlled in a study providing all food for 22 weeks" (Karl. 2015).

This does not just go against the mainstream assumption that low GI and/or low(er) carbohydrate diets facilitate weight loss, fat loss and weight maintenance (see data in Figure 4 for an overview of these parameters, it also contradicts the initially mentioned broscientific assumption that carbohydrates, in general, and high GI carbs, in particular, have a protective effect against the unexpected diet-induced reduction of basal energy expenditure many people know as "metabolic damage". If there's anything of which the study at hand suggests that it could protect you from such unexpectedly large decrease in RMR, it's not high GI carby, but rather an already high(er) baseline RMR (see Figure 3).

And what does that tell us? Right! Since a high predicted RMR is a function of (a) being male, (b) being tall, and (c) being muscular, all three attributes may protect you from diet-induced "metabolic damage" | Let me know your thoughts and comment on Facebook!

References:

• Danforth Jr, Elliot, et al. "Dietary-induced alterations in thyroid hormone metabolism during overnutrition." Journal of Clinical Investigation 64.5 (1979): 1336.
• Karl, J. Philip, et al. "Effects of carbohydrate quantity and glycemic index on resting metabolic rate and body composition during weight loss." Obesity 23.11 (2015): 2190-2198.
• Mariash, C. N., et al. "Synergism of thyroid hormone and high carbohydrate diet in the induction of lipogenic enzymes in the rat. Mechanisms and implications." Journal of Clinical Investigation 65.5 (1980): 1126.
• Serog, P., et al. "Effects of slimming and composition of diets on VO2 and thyroid hormones in healthy subjects." The American journal of clinical nutrition 35.1 (1982): 24-35.
• Ullrich, Irma H., Philip J. Peters, and M. J. Albrink. "Effect of low-carbohydrate diets high in either fat or protein on thyroid function, plasma insulin, glucose, and triglycerides in healthy young adults." Journal of the American College of Nutrition 4.4 (1985): 451-459.