|Mixed news about nutrition, exercise, and supplementation.|
In the absence of game-changing nutrition, exercise, and supplementation science I decided to post one of the recently rare installments of the good old “on short notice” column at the SuppVersity.
This installment of the “short news” features two plus one papers from the latest issue of “Medicine & Science in Sports & Exercise” and their, as of yet, unpublished “ahead of print” articles.
While we’ll start with a short discussion of the latest investigation into the accuracy (or rather usefulness) of your (old) Fitbit Charge 2.0, I suspect that most of you will be more interested in the “training low [carb/glycogen]” study which is the first to quantify the (to be expected) increase in protein/amino acid requirements in those who avoid carbs to maximize the mitochondrial response to exercise (see “Maximizing Training-Induced Cellular Adaptation: Training Low, Carb Cycling, Altitude & Hypoxia Training for Athletes” | check it out).
- Accurate… or not? Fitbit predicts VO2max at “an acceptable level of validity”: I’ve previously addressed the (in-)accuracy of fitness trackers. In the corresponding studies (learn more: “Activity Trackers, How Accurate are They?”), however, the focus was on energy expenditure. For today’s short news, I have picked a study in which scientists evaluated the accuracy of the Fitbit Charge 2’s ability to quantify (or rather qualify) your cardiorespiratory fitness.
Figure 1. For basic, rather qualitative fitness assessments, the 60s CRF is sufficiently accurate (Klepin 2019)
To this ends, researchers from California (Klepin 2019) tested N=65 healthy adults between the ages of 18 and 45 yrs (55% female, 45% male) using the “gold standard VO2max testing” and compared the result they got with their pro-equipment to the assessment of a Fitbit Charge 2 which had to be worn continuously for 1 wk during which the subjects were instructed to complete a qualifying outdoor run to derive the Fitbit CRF (units: mL/kg/min).
How did the test work? Basically, we’re talking about a maximal graded exercise test on the treadmill. After a 5-10 min warm-up at a self-selected pace, participants started running at 5 mph (8 km/h) with 0% incline for 3 min. Subsequently, the workload was increased by approximately 0.75 METs every minute. “This was achieved via an increase in speed (0.5 mph·min−1) for the first 2 min, and an increase in incline by 1.5% every minute thereafter,” the authors explain. When the subjects reported or showed signs of volitional fatigue, the treadmill was immediately slowed to 2.0 mph, and participants were encouraged to walk until completely recovered. The data from both pro-device and Fitbit was eventually analyzed in 15- and 60-s epochs – 60s, because the longer epochs supposedly have a lower susceptibility to overestimate subjects’ VO2max.
- The scientists’ Bland–Altman analyses revealed that Fitbit CRF had a positive bias of 1.59 mL/kg/min compared with laboratory data epoched at 15 s and 0.30 mL/kg/min compared with data epoched at 60 s (n = 60). That’s not too bad… and with a mean absolute percentage error of less than 10% for each comparison, using the Fitbit is unquestionably better than having no data.
Now, you may (rightly) argue that this is still pretty inaccurate, but let’s be honest: Who needs to know his exact VO2max? As an athlete you’re interested in making progress and the latter can be monitored pretty well by comparing how your Fitbit data changes over time.
Before you head over to Amazon to grab one of the meanwhile outdated fitness trackers, you should remember that the results were generated in young, healthy, and fit adults who are able to run. It’s thus not clear if the device is similarly accurate and the methods feasible for those who are in the direst need of improving their fitness: very unfit, potentially obese, and metabolically impaired people for whom even their ability to perform the VO2max test is questionable. Finally, it is also worth considering that we’re talking about one specific device. In that, it may be reasonable to assume that the quality of the fitness analysis didn’t deteriorate with ongoing R&D, but eventually one’d have to test each and every of the subsequent Fitbit generations for their accuracy, as well.
- Burning protein as Fuel: If you go low carb, you better eat that extra steak: A new study from the Faculty of Kinesiology and Physical Education at the University of Toronto claims “Low-Carbohydrate Training Increases Protein Requirements of Endurance Athletes” (Gillen 2019).
The authors base this statement on data from an experiment, in which Gillen et al. had N=8 endurance-trained males who regularly ran 56 ± 16 km·wk−1 undergo a study protocol that mirrored those of a previous acute “sleep-low” training protocol (Lane 2015).
As you can see in Figure 1, the participants completed two metabolic trials in a randomized crossover design, with each trial separated by a minimum of 5 d.
Figure 2. Overview of the study design. CHO periodization in LOW and HIGH before determination of postexercise protein requirements. 10 × 5 min run intervals at 10 km race pace, 1 min recovery; Run, 10 km run at ~80% HRmax.
“In each trial, participants performed an evening session of high-intensity interval training (HIIT) on day 1, followed by a moderate-intensity 10 km run on the morning of day 2. In the low-CHO availability trial (LOW), participants consumed the majority of their daily CHO intake before the evening HIIT session (7.8 g·kg−1), and subsequently withheld CHO postexercise and overnight (0.2 g·kg−1),” the authors elaborate.
In the high-CHO availability trial (HIGH), participants consumed less than half of their daily CHO intake before the evening HIIT session (3 g·kg−1), with the majority of CHO consumed postexercise (5 g·kg−1). In both trials, participants left the laboratory overnight before returning in the morning of day 2 to perform the 10-km run in either the fasted- (LOW) or CHO-fed (1.2 g CHO·kg−1; HIGH) state. Immediately after the 10-km run, participants received a postexercise meal (LOW: 1.8 g·kg−1; HIGH: 0.6 g·kg−1) to ensure groups were energy-matched before commencing the 8-h IAAO protocol (described below).
The foods were prepackaged and consumed in an order that would allow for the intended distinction between LOW (5.8 g CHO·kg−1, 0.85 g protein·kg−1 and ~0.80 g fat·kg−1) and HIGH (1 g CHO·kg−1, 0.68 g protein·kg−1 and ~0.52 g fat·kg−1) experiment. For more details on the timing, please refer to Figure 2.
- Likewise identical were the HIIT and MICT sessions the subjects underwent on the evening of day 1 (HIIT in form of 10 × 5 min run intervals at 10-km race pace, interspersed with 1 min of recovery) and on the morning of day 2 (MICT in form of 10-km run at ~80% HRmax using speeds that were predetermined during baseline testing).
And where does the protein come into play?
Easy… after the 10-km run and postexercise meal, the authors used the IAAO technique to assess differences in postexercise phenylalanine metabolism as an estimate for protein requirements. You may remember this from previous studies (see red box for an example).
|Figure *. You may remember that Arash Bandegan et al. (2017) recently calulated the protein requirements of male bodybuilders on non-training days using the same technology. Back in the day, the figure they came up with looked familiar: 1.7 – 2.2 g/kg, which is pretty much in line with various guidelines.|
Remember! The study results are athlete- and training-type specific! In other words, it would be foolish to assume that you or a client who’s doing a 1h full-body resistance training workout would see a similar, let alone the same increase in protein requirements as the “low” (=low glycogen = increased reliance on alternative fuel, including protein) training endurance athletes in the study at hand. A very long bout of fasted AM-cardio, on the other hand, comes much closer to the situation in the study and may, if done at an appropriate intensity and alongside a low(er) carb diet, increase your protein requirements to a similar extent.
- In that, each meal provided 1/12th of the participants’ total daily energy requirement and a protein intake of 0.93 g·kg−1 – with excess phenylalanine (the indicator amino acid; 30.5 mg·kg−1·d−1) and tyrosine (40 mg·kg−1·d−1) ensuring that the indicator amino acid was directed toward oxidation.
Put simply: When your body needs energy it will begin oxidizing amino acids to fuel its energy demands. With the tracer-aminos the scientists are able to quantify the amount of amino acids that are “burned” to fuel the workout in the absence of sufficiently stocked glycogen stores.
Figure 3. Postexercise net protein balance in LOW and HIGH after a 10-km run performed with low or high CHO availability. *Significantly different vs HIGH (P < 0.05 | Gillen 2019).
In the study at hand, the phenylalanine flux was not different between trials. The oxidation, on the other hand, was 11% higher in the LOW compared with HIGH trial (P = 0.03). Based on this observation, the authors calculate an increase in the subjects’ daily protein requirements of 0.12 g/kg, or for the avg. subject: 75kgx0.12g/kg = 9g of (preferably high EAA) protein.
Accordingly, we may assume that 9g of high EAA protein should compensate for the 12% reduction in net protein balance the researchers observed in the LOW vs. HIGH trial. What we don’t know, though, is how practically relevant this compensation would be in the long term. After all, we’re dealing with an N=9 subjects (only) acute response study, and not with the long-term investigation into effects on exercise performance and body composition we’d need to answer this important question.
As the authors point out, it is still logical to assume, “[g]iven the importance of dietary protein for postexercise remodeling of muscle proteins”, that their “findings may have important implications for optimizing recovery in athletes performing endurance sessions with low-CHO availability” (Gillen 2019). In this state, the exercise-induced amino acid losses that incur via the direct oxidation of AAs in muscle mitochondria and/or amino acids hepatic extraction of circulating AAs as a substrate for gluconeogenesis (the liver turns the aminos into sugar) has been shown to increase significantly. What exactly the effects of proper compensation are, will yet, as the authors themselves acknowledge, have to be elucidated in future research that “should consider the impact dietary protein intake (especially from whole foods) has on postexercise recovery, skeletal muscle adaptations, and performance outcomes with contemporary low-CHO availability training strategies” (Gillen 2019).
- Babcock, M. et al. “Salt Loading Blunts Central and Peripheral Postexercise Hypotension” Medicine & Science in Sports & Exercise: October 9, 2019. Published Ahead of Print.
- Bandegan, Arash, et al. “Indicator amino acid–derived estimate of dietary protein requirement for male bodybuilders on a nontraining day is several-fold greater than the current Recommended Dietary Allowance.” The journal of nutrition 147.5 (2017): 850-857.
- Gillen, JB. “Low-Carbohydrate Training Increases Protein Requirements of Endurance Athletes.” Medicine & Science in Sports & Exercise: November 2019 – Volume 51 – Issue 11 – p 2294–2301
- Klepin, K. et al. “Validity of Cardiorespiratory Fitness Measured with Fitbit Compared to V˙O2max.” Medicine & Science in Sports & Exercise: November 2019 – Volume 51 – Issue 11 – p 2251–2256.
- Lane, Stephen C., et al. “Effects of sleeping with reduced carbohydrate availability on acute training responses.” Journal of Applied Physiology 119.6 (2015): 643-655.