Each +30 Min/d of Physical Activity Reduce HbA1c by 11%, Protein + CHO Maintain Bone Mass, Overlooked Benefits of BFR, New Marker of Overtraining - Jan '17 Science Update

  This is what the Jan '17 Science Update has to offer? -11% HbA1c reduction per 30 minutes activity, new benefits of blood flow restricted tr., the bone protective effect of immediate post-workout whey plus carb ingestion, and a new overtraining gauge...

It's almost, February... almost and that's why today's SuppVersity article still qualifies as a January '17 research update. One that is based on the latest (ahead of print) papers from the peer-reviewed journal "Medicine & Science in Sports & Exercise" - papers about the large impact of short bouts of moderate-to-vigorous physical activity (MVPA) on the messed up glucose management of people with an increased T2DM risk, the bone-preserving effects of a mix of whey and dextrose and how this effect depends on timing, the belated and thus overlooked beneficial effects of blood flow restriction on muscular rapid force development and, last but not least, a potential new marker of overreaching and -training that could also explain the dichotomous role of IL-6 in the adaptive and maladaptive response to exercise.

Learn more about blood flow restriction at the SuppVersity

BFR for VO2 & Strength Gains

Using BFR in Periodization

BFR Precondi-tioning = Useless

Benefits of Cuffs After sets?!

No Extra-Gains W/ BFR vs. HIT

Hormonal Re-sponse to BFR

• Scientists find new marker of overreaching and potentially -training: You know that exercise will increase the levels of the allegedly "bad" cytokine IL-6. Now, as a SuppVersity reader, you will yet also know that this "cytokine" is, in fact, a "myokine" if it is released in response to muscle contractions and that it appears to figure in the hormetic response to exercise stress... or, in other words, without it, you're not going to get the adaptational response in form of strength and size gains you're training for. With that being said, studies also show that significantly elevated levels of IL-6 can also occur with overtraining and are - in this situation - a sign of dysfunctional adaptation.
  
  Recent research does now suggest that the "dichotomous nature of IL-6 signalling appears to be determined by the respective concentration of its receptors (both membrane-bound (IL-6R) and soluble (sIL-6R) forms)" (Cullen. 2017) - measuring these concentrations could thus provide important information about whether the circulating IL-6 is going to trigger a hormetic response or not. Accordingly, Cullen et al. conducted a study that investigated the response of sIL-6R to long-term training, and the relationship between sIL-6R, self-reported measures of wellbeing, and upper respiratory illness symptoms (URS) in highly-trained endurance athletes.
  

  

  Figure 1: Unlike cortisol, which has a long history as a suspected, but rarely useful overtraining gauge, sIL-6R doesn't have a circadian rhythm (see explanation in green box). This doesn't mean it's an accurate marker of overtraining, but it does mean that it is less complicated and more convenient to use, because with overtraining the circadian rhythm can be so messed up that simply measuring at the same time won't suffice to get comparable and thus useful results to gauge your training status.

  Their results are quite conclusive: Firstly, they confirmed that sIL-6R is responsive to prolonged periods of exercise training. And second- and more importantly, the subjects' sIL-6R levels varied according to the individual training volume and could be linked to common symptoms of overreaching such as high levels of stress, and/or depressed mood.
  
  This is obviously not enough to use sIL-6R as an overtraining gauge. With future studies that determine the level of sIL-6R in overreaching and overtraining athletes, it may thus be possible to distinguish between these states (and regular training) and to use this information to optimize athletes and gymrats workout routines. 
• Rapid Force Capacity (RFC) increases sign. with blood flow restriction, but study shows: Adaptation takes time: This observation Nielsen, et al. (2017) made in their recent study is an important one, because it implies that previous studies on the effects of blood flow restriction + low-intensity training may simply have missed the beneficial effects when they measured (just as Nielsen, et al. did it, too), the adaptational response only 5 days after having subjects participate in a series of standardized workouts.
  
  In the study at hand, this series constituted of twenty-three training sessions which were performed within 19 days. In all 10 male subjects (22.8+/-2.3 years) who performed four sets of knee extensor exercise (20%1RM) to concentric failure during concurrent BFR of the thigh (100mmHg), and the eight work-matched controls (21.9+/-3.0 years) who trained without BFR (CON), the scientists tested the maximal slow and fast knee joint velocity muscle strength and rapid force capacity (e.g. RTD) as well as evoked twitch contractile parameters before and after the study.
  

  

  Figure 2: Changes in rate of force development (left) and mean muscle fibre area (right | Nielsen. 2017).

  Now, that's nothing new. What was new, however, is that they tested before (Pre) and 5 and 12 days after training (Post5, Post12). In conjunction with the data from the biopsies, Nielsen et al. were thus able to detect the improved rate of torque development for the first time. The sign. difference in muscle fiber area (Figure 2, right), on the other hand, is - interesting as it may be - no news: after all, we're comparing light load with BFR to light load w/out BFR and not, as many other studies did, light load BFR to regular high load training, where time and again the regular training group saw the greater muscle increases.
• Each extra 30 minutes of daily moderate to vigorous physical activity improve HbA1c of subjects at increased T2DM risk by 11%: MVPA aka "moderate to vigorous physical activity" is the buzzword of the fitness tracker generation. Now, a three-year study confirms what the medals your fitness tracker software will award to you already suggested: each minute spend moving at moderate to vigorous intensity is an investment into your health and well-being.
  
  

  

  How Accurate Are Activity Trackers? EE Data From Omron, Fitbit, Jawbone & Other Devices Reveals 10% Error & More | read the full SV article

  The above is the result of a recent study that correlated longitudinal (three-year follow-up) activity tracker data with changes of the long-term glucose marker HbA1c in a sample of 489 men and women at high risk of developing type II diabetes, participants (mean age 64.2 +/- 7.3 years, BMI 31.7 +/- 5.1, 63.4% male). And it's a result based on which the authors, Mathew McCarthy, and colleagues, rightly conclude that "[i]ncreases in MVPA and body weight were associated with a reduction and increase in HbA1c respectively, particularly in those with dysglycemia" (McCarthy. 2017).
• Immediate Protein + CHO post-workout nutrition protect your bone from the bone resorption in the hours after exhaustive running: Next to its important result, there are two things which make a recent study by Rebecca Townsend et al. particularly interesting. Firstly: The subjects were young, healthy men, not post-menopausal women as in so many other bone health studies; and second- and not less importantly, the study tested both the efficacy of a mix of 1.5g/kg dextrose + 0.5g/kg whey as a means to reduce bone resorption (=calcium leeching) markers and the effects of timing.
  

  

  Figure 3: Overview of the study design, note that active treatment or PLA were administered at three different time points with two servings of placebo ensuring that the subjects could not differentiate between the immediate supplementation, the 2h-post and 4h-post supplementation trial (Townsend. 2017).

  And guess what. The study, in the course of which the dextrose + whey drinks were administered either before or after a placebo drink immediately or 2h after the run (see Figure 3) did not just confirm that the nutrient mix can ameliorate and shorten the exercise-induced (75% VO2Max run to exhaustion) increase in the bone resorption markers β-CTX and P1NP, it also found that this effect is time-dependent with the administration of the dextrose + whey mix right after the workout having more beneficial effects than taking it 2h post. With the immediate consumption reducing the levels below pre-exercise levels (-22% to -61%) within 1h, while it remained elevated with the placebo drink and/or in the DF group in which the supplement was consumed 2h after the workout. Now all that could well be a mere time-shift in the bone anabolic response. The scientists' observation that "[t]he overall β-CTX response was significantly lower in the IF trial than the DF trial (P=0.019, d=0.37) and the PLA trial (P≤0.001, d=0.84)" (Townsend. 2017) does however clearly suggest a definite benefit of immediate (IF) vs. postponed (DF and PLA) nutrient consumption after exhaustive workouts.
  
  In this context, however, it is important to realize that that, eventually, i.e. 3-4h after the run, the level of β-CTX decreased to similar below pre-test levels in all groups. Practically speaking this means that the net effect of a single session of exhaustive exercise on the young men's bone was almost certainly positive, irrespective of whether and when they ingested the supplement.

What's the take away of the studies in this Science Update: For me personally, the most important lesson comes from the MVPA study by McCarthy et al. (2017). A mere 30 minutes of "exercise" (even fast walking would qualify) is after all an easily manageable workload of that will contribute to statistically and, more importantly, clinically significant improvements in blood glucose management.

Drop the weights, grab the shake! Timing matters for advanced trainees.

Sort of surprising was the time-dependence of the beneficial effects of a dextrose + whey mix on bone resorption after exhaustive running in young male subjects. As I hinted at in the discussion of the study, however, we got to be careful not to mistake a timeshift in the response for an actual improvement.

Imho, future (best longitudinal studies) should investigate the net effect on bone mass to avoid a similar confusion as we've had them for protein supplements of which the majority of studies refutes that their ingestion in the immediate vicinity of the workout would improve your gains.

Last but not least, there's Nielsen's BFR study, which doesn't just prove another hitherto overlooked benefit of blood flow restricted low-intensity training, but also constitutes a lesson in study design, which reminds us that the timing of a retest will often determine if you find an effect or not. Apropos timing, while the latter may matter less for sIL-6R data than it does for cortisol, there's still a lot of research necessary to confirm the validity of this new marker of overreaching and -training and develop reliable tests for athletes and gymrats | Comment on Facebook!

References:

• Cullen, Tom; Thomas, Andrew W.; Webb, Richard; Phillips, Thom; Hughes, Michael G. "sIL-6R Is Related to Weekly Training Mileage and Psychological Well-being in Athletes." Medicine & Science in Sports & Exercise: Post Acceptance: January 24, 2017.
• McCarthy, Matthew; Edwardson, Charlotte L; Davies, Melanie J; Henson, Joseph; Gray, Laura; Khunti, Kamlesh; Yates, Thomas. "Change in Sedentary Time, Physical Activity, Bodyweight, and Hba1c in High-Risk Adults." Medicine & Science in Sports & Exercise: Post Acceptance: January 24, 2017.
• Nielsen, Jakob Lindberg; Frandsen, Ulrik; Prokhorova, Tatyana; Bech, Rune Dueholm; Nygaard, Tobias; Suetta, Charlotte; Aagaard, Per. "Delayed Effect of Blood-Flow-Restricted Resistance Training on Rapid Force Capacity." Medicine & Science in Sports & Exercise: Post Acceptance: January 23, 2017. 
• Townsend, Rebecca; Elliott-Sale, Kirsty J.; Currell, Kevin; Tang, Jonathan; Fraser, William D.; Sale, Craig. "The Effect of Postexercise Carbohydrate and Protein Ingestion on Bone Metabolism." Medicine & Science in Sports & Exercise: Post Acceptance: January 24, 2017.

How Accurate Are Activity Trackers? EE Data From Omron, Fitbit, Jawbone & Other Devices Reveals 10% Error & More

Even though the study doesn't provide a straight-forward answer to the question "Which is the best activity tracker?", it is still revealing.

I hope you don't rely on the data from your activity tracker as a basis to decide how much you can, should or may eat on a daily basis. Why? Well, the first and most important result of a recent study from the Human Performance Laboratory at the Ball State University is that "consumer-based PA [physical activity] monitors should be used cautiously for estimating EE [energy expenditure]" (Nelson. 2016) - and this goes for the data from all the devices that were tested by Nelson et al.: The BodyMedia FIT and the NikeFuel armband, the DirectLife monitor, the Omron HJ-720IT, the Fitbit One, the Fitbit Zip, the Fitbit Flex, the Jawbone UP24, the Basis B1 Band Monitor and the ActiGraph.

Don't tell me you use an activity tracker, but don't periodize your training!

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In view of the fact that tracking your energy expenditure is only one of the functions activity trackers are supposed to fulfill and considering the fact that you probably use them only to see if you have gotten more or less active (I do at least hope that you don't use them to guide your appetite ;-), it is still worth to take a look at the detailed results of this recent study.

As you will have guessed, the study was designed to "examine the validity of EE estimates from a variety of consumer-based, physical activity monitors under free-living conditions" (Nelson. 2016). To this ends, sixty (26.4 ± 5.7 yr) healthy men (n = 30) and women (n = 30) wore eight different types of activity monitors simultaneously while completing a 69-min protocol.

If you work out to be able to allow yourself to eat, you know you have a serious problem | learn why!

"The monitors included the BodyMedia FIT armband worn on the left arm, the DirectLife monitor around the neck, the Fitbit One, the Fitbit Zip, and the ActiGraph worn on the belt, as well as the Jawbone Up and Basis B1 Band monitor on the wrist.

The validity of the EE estimates from each monitor was evaluated relative to criterion values concurrently obtained from a portable metabolic system (i.e., Oxycon Mobile) [which is obviously in itself not 100% exact]. Differences from criterion measures were expressed as a mean absolute percent error and were evaluated using 95% equivalence testing" (Nelson. 2016).

A brief glance at Figure 2 reveals that the accuracy was surprisingly similar among the devices. To be more precise, the mean absolute percent error values (computed as the average absolute value of the group-level errors) were 9.3%, 10.1%, 10.4%, 12.2%, 12.6%, 12.8%, 13.0%, and 23.5% for the BodyMedia FIT, Fitbit Zip, Fitbit One, Jawbone Up, ActiGraph, DirectLife, NikeFuel Band, and Basis B1 Band, respectively (unfortunately, not all data appears to be fully reported in the manuscript version of the study I had access to, so don't ask me about missing data, please ;-).

What did the test protocol look like? Subjects took part in a structured activity protocol consisting of 11 activities (three sedentary, four household, and four ambulatory/exercise) chosen by researchers from a list of 21 activities ranging from lying around on the couch to treadmill jogging. Activities were counterbalanced so that sex and age categories had approximately equal participation in the activities. All subjects began by lying quietly on a bed for 10 min. All other activities were performed for 5 min each, in order of generally increasing intensity. All activities were performed at a self-selected intensity by the subject. Subjects chosen to perform the jogging activity had the option of participating in a brisk walk if unable to jog for 5 min.

As the scientists point out, of all tested devices, only "[t]he results from the equivalence testing showed that the estimates from the BodyMedia FIT, Fitbit Zip, and NikeFuel Band (90% confidence interval = 341.1-359.4) were within the 10% equivalence zone around the indirect calorimetry estimate. If you still insist on trying to match your energy intake "exactly" to your energy expenditure, you should plan for a 10% + X% difference from your actual energetic demands - after all, even the indirect calorimetry that was used as a yardstick to judge the accuracy of the devices is not 100% accurate.

Figure 1: Mean absolute percent error when estimating energy expenditure for selected devices (Nelson. 2016).

In that, it is also worth mentioning that the accuracy of the devices was activity and device dependent. The Fitbit One, for example, produces the least error for stair climbing. For the Jawbone UP24, however, the "activity" for which it predicts your energy expenditure best is sitting around.

Accordingly, you could argue that you'd have to wear a certain device for a certain activity, e.g. (a) the Fitbit One, when sitting around (13%), working in the household (27%), taking the stairs (11%), jogging (22%) or cycling (43%) [note: on absolute terms, the error of the Fitbit for being sedentary is still lower than with the device from Jawbone], and (b) the Jawbone UP24, when you're simply walking around... but let's be honest: Since even that wouldn't be 100% accurate, it would be dumb to buy multiple fitness / activity trackers, wouldn't it?

Figure 2: With the exception of data from cycling and housework, the step count data (this graph) is sign. more accurate than the EE data in Figure 1 | If you want to learn more about what activity trackers are good / not good for and what you can / should make of the results of the study at hand, listen to me discuss this study on Monday's installment Super HumanRadio | click here to download the complete podcast that also includes discussions of the links NSAIDs and satellite cells and BPC-157 for muscle and tendon repair!

With an error of 10% you will always lose or gain weight involuntarily: The idea that a tiny technical device on your arm or belt could exactly tell you how much energy you need is in itself hilarious. And that's not just because the study at hand shows that even the best devices are on average +/-10% off (remember: that's +/-10% off another rough estimate that's never 100% exact). If you were dumb enough to match your diet blindly to the data your activity tracker provides, you would thus never achieve reliable results.

With that being said, our body is no biological machine that works according to a set of several (complex) equations. Therefore, the whole idea of a "quantified self" - as awesome as it may seem for the average control freak - must be seen as a tool to hold yourself accountable; a qualitative or semi-quantitative tool in the sense of "oh, I have been roughly 20% less active this week than last week, maybe I should..."

If the previously described rationale is behind the way you use the data from your activity tracker, congratulations! If not, I have to warn you: The margin between "quantifying yourself" and suffering from obsessive-compulsive disorder (OCD) and/or using the devices to fuel your exercise addiction is narrower than you may think | Do you agree, disagree? Let's discuss. Leave a comment on Facebook!

References

• Nelson, Benjamin N; et al. "Validity of Consumer-Based Physical Activity Monitors for Specific Activity Types ED." Med Sci Sports Exerc (2016): Ahead of print.

Gender Dependent Effects of TV Consumption on Body Fat Percentage of Canadian Teens

A longitudinal study (57 months) published by the American Journal of Epidemiology on July 8, 2010 found that although there is a negative effect of increased TV-consumption on boys (12–13y), no such correlation exists for the girls:

"Relative to that of steady-low screen-time trajectory group boys, percent body fat was 2.9 (95% confidence interval: 0.7, 5.0) and 2.4 (95% confidence interval: 0.5, 4.2) percentage units higher on average among "increasers" and "steady-high" trajectory group boys, respectively. There was no evidence that screen time has an effect on percent body fat in girls overall, although physical activity modified the association between screen time and percent body fat in both sexes."

Despite these findings, the scientists conclusion,

"Efforts to prevent obesity in youth should emphasize reducing screen time,"

unquestionably holds true, even if it is your daughter who is sitting in front of her TV-screen 24/7 ;-)