Where do Your Strength Gains Come From? Muscle Activity > Hypertrophy > Initial Strength - 3/5 Candidates Matter

Find out what's taking you from PR to PR, is it an increase in muscle size or activation on how important is how strong you already are?

Have you ever asked yourselves why you've been adding 20lbs of weight to your squat and your legs still don't look any bigger? If you're a man you're probably not happy about that. I am not sure if the insights into Balshaw et al.'s recent study provide into the mechanism behind the resistance-training-induced strength gains will help you will make you happy/-ier, but certainly smarter ;-)

The British scientists got to the bottom of your gains by assessing the individual and combined contribution of the adaptations in neural (agonist quadriceps EMG, antagonist hamstring EMG) and morphological (quadriceps muscle volume and θp, the fascicle pennation angle) variables.

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Based on the data from their 12-week study in twenty-eight healthy young men, who had not completed lower body RT for >18 months and were not involved in systematic physical training, the scientists were able to calculate the individual contribution of the previously named variables and the trainees' baseline strength on the effect of the following workout:

"After a brief warm-up of submaximum contractions of both legs, participants completed four sets of ten unilat eral isometric knee extensor contractions of each leg; with sets alternating between dominant and non-dominant legs. Each set took 60 s with 2 min between successive sets on the same leg" (Balshaw 2017). 

To differentiate potential interference with explosive vs. sustained contractions, the participants were further randomized to two groups:

• the explosive contraction group completed short, explosive contractions with participants instructed to perform each contraction “as fast and hard as possible” up to ≥80% MVT for ~1 s, and then relax for 5 s between repetitions.
• the sustained contraction group completed prolonged contractions at 75% MVT, with 2-s rest between contractions. 

For both groups, the scientists provided a computer monitor that displayed the rate of torque development (10-ms time epoch) and a target torque trace 2 s before every contraction, in the explosive and sustained contraction group, respectively.

Without a follow-up study in trained individuals, we have to speculate to which extent increases in muscle activity, hypertrophy, and the pre-training strength explain the variability of strength gains in trained individuals. The above is my estimate - just an educated guess.

What does the study tell us about better-trained individuals? If we compare the results of the study at hand to related study, it may be possible to make predictions about the driving forces of muscle growth in better-trained individuals, eventually, though, the study would have to be repeated with a different subject group to tell for sure.

As Balshaw et al. point out, their results are in line with other EMG studies assessing the effect of training on the lower extremities. What is interesting, however, is that they conflict with a study by Erskine et al. (2014) who found only a marginal correlation between improved activity patterns and strength gains for the biceps a muscle with an already high level of activation even in untrained individuals.

This result is important for our prediction because it suggests that a higher baseline activation level will reduce the contribution of improvements in agonist neural drive to the strength gains. This, in turn, obviously suggests that, in trained individuals who have already undergone significant improvements in neural drive, muscle activity will contribute significantly less to the strength gains than it does in untrained individuals. An equivalent to Figure 3 for well-trained athletes may thus look as I have sketched it in the figure on the left-hand side: Hypertrophy could make the largest, while improved muscle activation, only a marginal contribution to strength gains - but keep in mind: that's just an educated guess that is based on the assumption that the relative contribution of hypertrophy will increase as the relative contribution of improvements in muscle activation patterns will decrease over time (Note: Whether the three variables will then still explain 60% of the variation appears questionable, though; thus the 10% reduction in total predictive power in the figure above).

Each subject performed the above isometric knee extensor RT thrice a week (3/week). Before and after isometric maximum voluntary torque (MVT) as well as the neural drive to the agonist (QEMGMVT) and antagonist (HEMGANTAG) were assessed simultaneously. In addition, QUADSVOL was determined with MRI and QUADSθp with B-mode ultrasound.

Figure 1: Relationships of percentage change (∆) in knee extension may. voluntary torque (MVT) and ∆ quadriceps muscle volume (QUADSVOL; r = 0.461, P = 0.014), b ∆ quadriceps muscle fascicle pennation angle (QUADSθp; r = −0.207, P = 0.291), after 12 wks of resistance training. Solid and dashed lines indicate the trend of the relationship between variables and 95% confidence intervals, respectively. Black triangles denote sustained-contraction resistance training participants (n = 15); white circles denote explosive-contraction resistance training participants (n = 13 | Balshaw 2017)

I have to say that the way the scientists plotted the data is a bit odd - with the strength gains being the actual outcome variable of interest, I would expect it to be placed on the vertical, not the horizontal axis... but anyway. Figures 1-2 tell you that...

• hypertrophy contributes quasi-linearly to the gains (Figure 1 A) - I would estimate the reciprocal of the slope of the linear regression line to be ~2.5, meaning for each 1 % increase in muscle volume there was a 2.5% increase in maximal voluntary torque;
• agonist activity changes contribute quasi-linearly to the gains (Figure 2 A) - I would estimate the reciprocal of the slope of the linear regression line to be "only" ~0.8, meaning for each 1% increase in muscle activity there was a 0.8% increase in maximal voluntary torque;
• pre-training strength negatively predicts the strength gains (Figure 2 C) - What may sound odd, initially, is actually only logical. The stronger you are at baseline, the lower your strength gains are going to be. For this relationship, I would estimate the slope of the linear regression analysis to be approx. -1.5, which means that for each extra Newton-metre (nM) of pre-training maximal voluntary torque, the increase in response to training will be reduced by 1.5%;
• pennation angle and antagonist activity changes do not contribute clearly to the strength gains (Figure 1 B, Figure 2 B) - you know that because there was no clear correlation between the corresponding variables in the regression analysis the scientists did

So, there's clear evidence that size gains (hypertrophy), muscular activation (EMG) and, of course, the baseline strength determine the strength gains in resistance training rookies.

Figure 2: The relationships between the percentage change (∆) in knee extension maximum voluntary torque (MVT) and: (A) ∆ quadriceps EMG at knee extension MVT (QEMGMVT; r = 0.576, P = 0.001); (B) ∆ antagonist hamstrings EMG during knee extension MVT (HEMGANTAG; r = 0.298, P = 0.123) and (C) pre-training knee extension MVT (r = −0.429, P = 0.023), after 12 weeks of resistance training (Balshaw 2017).

The pennation angle, and antagonist activity (here the hamstring) on the other hand appear to contribute only marginally to the increase in strength gains the previously untrained subjects saw over the course of the 12-week study.

Figure 3: The scientists' multiple regression analysis reveals the strength of the contribution of each variable the scientists assessed in their study (Balshaw 2017).

So, what's the most important contributor? That's difficult to tell. With the individual correlations being relatively weak, one cannot rely on the previously calculated slopes. Those give you an idea of what the real-world contribution would be if there was a perfect correlation between the individual variables.

To answer the above question, we will thus have to turn to the subsequent multiple regression analysis of which the scientists highlight that it "found for the first time that these three variables simultaneously contributed to the total explained variance in strength" (Balshaw 2017).

Even if you take the  size gains (hypertrophy), muscular activation (EMG) and, of course, the baseline strength them into account, these variables explain only 60% of the total variance in strength gains - with the individual contributions (see Figure 3) being agonist neural drive, aka the muscle activation (EMG) explaining 30.6%, the size gains 18.7% and the pre-training strength 10.6% of the strength gains the rookies made over the course of the 12-week study... which leads me to an inevitable question: What about experienced strength trainees? I knew you'd be asking that and have addressed this question in the red box above Figure 1, so read it before you ask about the implications for trained individuals on Facebook!

References:

• Balshaw, Thomas G., et al. "Changes in agonist neural drive, hypertrophy and pre-training strength all contribute to the individual strength gains after resistance training." European Journal of Applied Physiology (2017): 1-10.
• Erskine, Robert M., Gareth Fletcher, and Jonathan P. Folland. "The contribution of muscle hypertrophy to strength changes following resistance training." European journal of applied physiology 114.6 (2014): 1239-1249.

Role of Muscle and CNS in Diet-Induced Decline of Exercise-Induced Energy Expenditure | Caffeine & Nicotine May Help!

While "calories count" when it comes to losing body fat, the notion that you would always burn the same amount of energy with a given workout - irrespective of your energy intake - is completely bogus and only one of the reasons why meticulous calorie counting won't work. 

Let's address it right away: Yes, the paper Tariq I. Almundarij et al. published in the peer-reviewed journal "Physiological Reports" (Almundarij 2017) deals with a rodent experiment, but with the goal of the study being to identify the fundamental mechanisms behind, not the extent of metabolic adaptation to calorically reduced energy intakes, this does not disqualify its results as irrelevant for humans - on the contrary (and trust me, I'd prefer a human or at least a pig study, too).

With that being said, let's take a look at what the scientists did to "investigate the role of MC4R in the modulation of muscle work efficiency, and test the hypothesis that energy restriction alters economy of activity through decreasing the response to central activation of MC4R" (Almudarij 2017).

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For their study, the scientists used male Sprague-Dawley rats (total N = 48) which were selected to measure adaptive thermogenesis in a baseline population - not because Martin et al. (2010) have mad ethe argument that these animals are potentially metabolically morbid, anyway, but rather because they are metabolically morbid. Just as metabolically morbid as human beings for whom the ever-increasing obesity rates indicate that we are similarly susceptible to diet-induced obesity and the associated detrimental health effects.

These rats were subjected to 3 weeks of 50% calorie restriction (CR). Over the course of this - in rodent years - intermediate time period, the scientists assessed their lab animals resting and nonresting energy expenditure (EE) and calculated the total, as well as the activity-associated EE, muscle thermogenesis, and sympathetic outflow.

Figure 1: Three weeks of 50% calorie restriction (CR) significantly suppressed both resting and nonresting EE, including physical activity-related EE, i.e. the energy you spend while working out (Almundarij 2017).

You can see the results of this basic measurement in Figure 1: The prolonged food restriction resulted in a 42% reduction in daily energy expenditure, a 40% decrease in resting energy expenditure, and a 48% decline in nonresting energy expenditure.

Dieting is when you leave only 360kcal not 600kcal in the gym, despite doing the same workout

What is particularly interesting, yet often forgotten when we talk about dieting (especially within the fitness community), is the fact that the energy that you will burn during exercise will also decrease significantly (see Figure 1G). One of the implications of the study at hand we cannot ignore is that the reduced physical activity energy expenditure stems from "the dampening of both the amount and energetic cost of activity" (Almundarij 2017) - and the latter, i.e. the reduced energy expenditure in response to a standardized exercise regimen amounts to a 30-40% decrease in EE that would degrade the 600kcal you believe to be burning on the treadmill to a meager 360-420 kcal/session!

Figure 2: Fat & lean mass and the rel. (%) difference in body comp. w/ ad-libitum vs. restricted diet (Almundarij 2017).

This 180-240kcal difference, alone, could easily explain why you see people complaining all over the internet that "[they] don't lose weight, even though [they're] doing everything right, not missing any of their daily workouts and not cheating on [their] diets" (modeled on the often-heard complaint of dieters worldwide).

Illustration of the allegedly over-simplified example calculation to show the significance of the fasting-induced reduction in AIEE for meal timing and fat loss as observed in Garaulet 2013.

Never forget the importance of reductions in activity-induced energy expenditure: You may remember an older study that has recently resurfaced on Facebook from previous SuppVersity articles about fasting: The study, "Timing of food intake predicts weight loss effectiveness" (Garaulet. 2013), indicates that having your major meals in the AM when dieting favors fat loss even if the total energy intake is identical. Knowing how significant the reduction in activity-induced energy expenditure (AIEE) in man is (%-age wise its contribution to the metabolic downregulation is much higher in man vs. rodent), the results of the study at hand may easily explain why CICO (=the C-alories I-n vs. C-alories O-out hypothesis) failed in Garaulet's study.

Let's illustrate that with a simple example (see Figure to the left). Let's assume the reduction in AIEE is indeed 40%. Let's further assume that you'd "burn" ~1000kcal from working out and walking in your waking phase before the PM meal and only 150kcal after the PM meal when eating an energetically balanced. According to Cooker, that would put your effective AIEE while dieting to 600kcal + 150kcal when you eat in the PM, but 1000kcal + 90kcal if you eat the meal in the AM. Obviously, this oversimplified example assumes that the metabolism would not slow down over the day (which will be the case). Eventually, the difference will thus certainly be smaller (maybe 15% instead of the 31% in my example). That does not mean, though, that it could not still be statistically and practically significant (note: it is unlikely that a relevant reduction would be observed for intermittent fasting in the absence of a significant caloric deficit).

In this context, it is also important to emphasize that these decreases in EE were significant even when the reductions in body weight and lean mass were taken into account. In other words, it is not the often-cited loss of lean mass (alone) which mediates the reduction in basal and exercise-induced energy expenditure. This alone, however, is nothing we didn't observe in previous human studies, already. What's truly new, however, is that the study at provides extended mechanistic insight into the origin of these unwanted reductions in energy expenditure. In fact, the study at hand ...

is the first report of reduced muscle NETO [norepinephrine turnover], indicating lower SNS drive to skeletal muscle after 3 weeks of food restriction (Fig. 2), an effect not seen during short-term energy restriction (Dulloo et al. 1988)" (Almundarij 2017).

With the importance of skeletal muscle to both resting and activity EE, (Zurlo et al. 1990; Gallagher et al. 1998), "this low SNS drive" could, as the authors further point out significantly "contribute to both the resting and nonresting aspects of adaptive thermogenesis" (Almundarij 2017).

Figure 3: The MC4R induced increase in energy expenditure in the study at hand is probably not coincidentally of a similar magnitude as the effects of nicotine (Almundarij 2017).

Nicotine targets the mechanism even more directly than caffeine: Even though the safety of nicotine as a fat loss adjuvant is, as previously discussed in detail, debatable, I think it's worth mentioning that Mineur et al. have shown 6 years ago that nicotine's effect on food intake are mediated by an activation of POMC neurons, neurons that will then activate the very melanocortin 4 receptors of which the study at hand shows that their medical activation can - albeit only partly - restore the reduced energy expenditure in dieting rats (as you can see in Figure 3, the MC4R agonist will, just as it has been shown for nicotine in humans, also increase the energy expenditure in non-dieting rats.

The latter, i.e. the ability of the muscle mass to react to central nervous system stimuli, however, is not lost while you're dieting. It is - and that's a primary result of the study at hand - rather centrally (in the brain) deactivated. Otherwise, the muscles wouldn't have reacted to either the central MC4R agonist nor any form of physical activity with an increase in thermogenesis. This result is of paramount importance, because it does, as the authors point out, ...

"[...] provide potential avenues to counter adaptive thermogenesis and [thus to] promote continued weight loss and weight maintenance through targeting physical activity EE and skeletal muscle thermogenesis (Almundarij 2017).

Now the bad news is that the melanocortin 4 receptor agonists Almundarij et al. used in their study are not (yet?) ready to be used in human beings. Other tools to increase the decreased norepinephrine turnover in skeletal muscle, however, are available and you'll all be familiar with their names: caffeine or ephedrine (and to a lesser extent green tea extract).

Figure 4: Effects of caffeine (CAF) and ephedrine (EPH) alone or in combination (C+E) on epinephrine levels during exercise. 12 recreational runners (10 males and 2 females; 6 regular coffee drinkers and 6 irregular or non-caffeine users) ingested placebo (PL), CAF 4 mg/kg, EPH 0.8 mg/kg or C+E (CAF 4 mg/kg and EPH 0.8 mg/kg). After 90 minutes of rest they performed a 10km run while wearing a helmet and backpack weighing 11kg; the intensity of this effort was >90% of VO2peak; * p < 0.05 vs PL; † p < 0.05 vs EPH; ‡ p < 0.05 vs CAF; § p < 0.05 vs C+E (Magkos 2004)

As Magkos et al. pointed out in their 2004 paper in Sports Medicine, "[b]oth drugs may enhance norepinephrine turnover, but each one alone only modestly". This supposition is supported by both previous human data (Berkowitz 1970), as well as data presented in the researchers own paper which shows that the benefit of combining the two is mostly due to the prolongation and potentiation of caffeine's effect by ephedrine (or vice versa; cf. Dulloo 1992).

Figure 5: There is a link for nicotine and there may even be a link of caffeine to the melanocortin 4 receptor - one that's mediated by the POMC neurons.

Unfortunately, corresponding data on caffeine's muscle-specific norepinephrine turnover is (and I openly admit that) not yet available. That's mostly because research has not really zoned in on the autonomic modulation of muscle compared to adipose tissue; and where it did, this was not about the effect of caffeine and co., but the upstream effects of melanocortin receptor activity (Gavini 2014), which would yet be a downstream target of the caffeine, if Laurent et al. are right and "caffeine ingestion promotes corticotropin-releasing factor release from the hypothalamus [...], which, in turn, increases POMC release" and - guess what - downstream melanocortin 4 receptor activity.

In a different context this relationship has already been established (Bhorkar 2014), whether and to which extent caffeine stimulates the melanocortin 4 receptors (MC4R), however, is - at least as far as I know - not known. Anyway... when all is said and done, there's still no doubt that caffeine, even when it's used alone, will still have a significant enough effect on the sympathetic nervous system (SNS) to promote weight loss and weight maintenance in multiple diet studies (Dulloo 1989; Westerterp‐Plantenga 2005) - and let's be honest: many people won't even care if that involves an increase in MC4R activity or not ;-)

If your diet of choice is a ketogenic diet, caffeine will not just help you to compensate the reduction in exercise-induced energy expenditure and thus "restore the calories" you leave in the gym. A recent study shows that it will also help you to get and stay in ketosis - and that's even when you've been cheating on carbs | learn more.

So what's the implication for human beings? Even though a reduction in thermogenesis at rest contributes less to the reduction in energy expenditure during periods of restricted dietary intake in humans compared to rodents. The effect of on non-resting EE and thus regular activity- and exercise-induced EE is proportionally even higher - and increases the more weight you lose (Leibel  1995).

Now, this effect reflects in a reduced central activation of hypothalamic melanocortin receptors, which could be countered by medical intervention only theoretically. After all, corresponding drugs as they have been used for experimental purposes on the rodents in the study at hand are still in the early experimental phase - that they do work without short-term side-effects has yet been demonstrated in obese individuals by Chen et al. (2015) who observed a 111 kcal/24 h increase in REE.

For the average gymrat, these drugs will yet probably never be available legally. Against that background you can count yourselves lucky that Almundarij et al.'s results also point to another, already available and (if used sensibly) perfectly safe class of drugs. central nervous stimulants like the ubiquitous caffeine. These agents have a proven record of being able to promote diet-induced fat loss by increasing/restoring SNS-induced thermogenesis (Dulloo 1988 & 1989) - especially when used in conjunction with exercise so that they can partly compensate the diet-induced reduction in sympathetic tone and thus restore the significantly reduced energy expenditure during workouts to near-normal levels.

It is often belittled, but even in non-dieting humans, the increase in energy expenditure following the consumption of caffeine is significant (Astrup 1990).

In conjunction with caffeine's ability to shift the fuel oxidation from glucose to fatty acids and its likewise central nervous system-mediated lipolytic (=fat releasing) effect on fat cells, it is thus still the most widely available and best-researched diet aid - an aid that doesn't make dieting obsolete, but one that will partly compensate the negative effect of prolonged energy restriction on basal and exercise-induced thermogenesis. Ah, ... and let's not forget that nicotine is a viable yet, as previously discussed, less harmless OTC alternative of which we know already that it acts via the same downstream signaling cascade as a melanocortin receptor agonist (Mineur 2011) | Comment!

References:

• Almundarij, Tariq I., Chaitanya K. Gavini, and Colleen M. Novak. "Suppressed sympathetic outflow to skeletal muscle, muscle thermogenesis, and activity energy expenditure with calorie restriction." Physiological Reports 5.4 (2017): e13171.
• Astrup, A., et al. "Caffeine: a double-blind, placebo-controlled study of its thermogenic, metabolic, and cardiovascular effects in healthy volunteers." The American journal of clinical nutrition 51.5 (1990): 759-767.
• Berkowitz, Barry A., James H. Tarver, and Sydney Spector. "Release of norepinephrine in the central nervous system by theophylline and caffeine." European journal of pharmacology 10.1 (1970): 64-71.
• Bhorkar, Amita A., et al. "Involvement of the central melanocortin system in the effects of caffeine on anxiety-like behavior in mice." Life sciences 95.2 (2014): 72-80.
• Bracco, David, et al. "Effects of caffeine on energy metabolism, heart rate, and methylxanthine metabolism in lean and obese women." American Journal of Physiology-Endocrinology and Metabolism 269.4 (1995): E671-E678.
• Chen, Kong Y., et al. "RM-493, a melanocortin-4 receptor (MC4R) agonist, increases resting energy expenditure in obese individuals." The Journal of Clinical Endocrinology & Metabolism 100.4 (2015): 1639-1645.
• Dulloo, A. G. "Stimulation of thermogenesis in the treatment of obesity: A rational approach." Journal of obesity and weight regulation (USA) (1988).
• Dulloo, A. G., et al. "Normal caffeine consumption: influence on thermogenesis and daily energy expenditure in lean and postobese human volunteers." The American journal of clinical nutrition 49.1 (1989): 44-50.
• Gavini, Chaitanya K., et al. "Leanness and heightened nonresting energy expenditure: role of skeletal muscle activity thermogenesis." American Journal of Physiology-Endocrinology and Metabolism 306.6 (2014): E635-E647.
• Garaulet, Marta, et al. "Timing of food intake predicts weight loss effectiveness." International journal of obesity 37.4 (2013): 604-611.
• Laurent, Didier, et al. "Effects of caffeine on muscle glycogen utilization and the neuroendocrine axis during exercise 1." The Journal of Clinical Endocrinology & Metabolism 85.6 (2000): 2170-2175.
• Leibel, Rudolph L., Michael Rosenbaum, and Jules Hirsch. "Changes in energy expenditure resulting from altered body weight." New England Journal of Medicine 332.10 (1995): 621-628.
• Magkos, Faidon, and Stavros A. Kavouras. "Caffeine and ephedrine." Sports Medicine 34.13 (2004): 871-889.
• Mineur, Y. S., Abizaid, A., Rao, Y., Salas, R., DiLeone, R. J., Gündisch, D., ... & Picciotto, M. R. (2011). Nicotine decreases food intake through activation of POMC neurons. Science, 332(6035), 1330-1332.
• Mountjoy, Kathleen G. "Functions for pro-opiomelanocortin-derived peptides in obesity and diabetes." Biochemical Journal 428.3 (2010): 305-324.
• Westerterp‐Plantenga, Margriet S., Manuela PGM Lejeune, and Eva MR Kovacs. "Body weight loss and weight maintenance in relation to habitual caffeine intake and green tea supplementation." Obesity 13.7 (2005): 1195-1204.

'Training on Cycle': Hitting the Weights Frequently (5x/WK), Alone, Very Unlikely to Trigger the 'Female Athlete Triad'

The squat was not part of the training regimen in the study at hand - that's bad because it would certainly have made the workout more intense and might thus have affected the results.

If you don't remember what it was, I suggest you (re-)read the classic 'SuppVersity Athlete Triad'-Series (read it)... and if you don't have the time to devour those classics, here's the gist: While it is often accompanied by eating disorders, the athlete triad can also arise in periods of either low energy availability or high training loads. Next to an ongoing decline of physical (and eventually also cognitive performance), the main features of the female athlete triad are amenorrhoea / oligomenorrhoea (no, or a disturbed menstrual cycle, respectively), and - in the long(er) run, i.e. after months and years - an often highly significant decrease in bone mineral density (osteoporosis and osteopenia).

As et al. point out in their latest paper, the female athlete triad "has shown to be related to both training intensity and duration" (Wikström-Frisén. 2016). It is thus a threat for endurance athletes, strength athletes and gymrats alike; and a very similar effect can be observed in men when they're overtraining - even though, their fertility is not threatened as easily.

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"Intensive exercise-associated disorders, such as the female athletic triad, generally originate from hypothalamic dysfunction failing to initiate a normal hypothalamic-pituitary-ovarian function. This is leading to a decrease in pituitary secretion of luteinizing hormone (LH), and follicle-stimulating hormone (FSH), which in turn limits ovarian stimulation and estradiol production" (Wikström-Frisén. 2016).
In spite of everything we know, evidence pertaining to the effects of increased resistance training load on the athlete triad is scarce. The aim of the scientists from the  Umeå University in Sweden was thus to investigate potential exercise-related negative consequences on components in the female athlete triad following high-frequency leg resistance training.

So far, so good. What is new, or at least almost new, in this 2nd paper by Lisbeth Wikström-Frisén et al. addressing the issue of what I previously called tongue in cheek "training on cycle" (read my 2015 article of mine) is that the subjects' training regimen were periodized according to different parts of the menstrual/OC cycle. Practically speaking, the participants, all of whom had regular menstrual cycles (at pre-test 27.9 ± 1.9 days), or were taking oral contraceptives (OC cycles of 28 days), and had previous experience of leg press and leg curl resistance training, were randomized into either one of two periodized training groups or a control group:

• one training group were allocated to high-frequency training (5 times per week) during the first two weeks of the menstrual/OC cycle (group 1), and 
• the other training group to high-frequency training during the last two weeks of the menstrual cycles (group 2), 
• the controls trained at a low frequency (3 times per week) during the whole cycle. 

During training, all participants performed leg resistance training according to current recommendations in order to achieve strength gains. The completed number of leg training sessions were logged and was equivalent in the three groups (group 1 = 41 ± 4.0, group 2 = 41 ± 4.8, control group = 42 ± 4.4).

Figure 2: While the relative changes (pre- vs. post-test) clearly indicate that training intensely in the latter phase of the menstrual cycle appears to have the most favorable effect on the women's hormonal profiles, none of the visible inter-group difference reached statistical significance - probably because of the rather small(ish) study size (N = 59 in three groups of 19, 19, and 21 subjects, respectively) as well as large inter-individual variation (Wikström-Frisén 2016).

At post-test, the participants reported how they perceived their leg training program during the four consecutive menstrual/OC cycles. Their perceptions were categorized on a three-graded scale; 1 = positive, 2 = neither positive nor negative, 3 = negative. The analysis revealed "a significant difference in regards to how the training was experienced, χ2(2) = 11.552, p = 0.003" with a significantly more positive perception of the leg training in the "on-cycle" group #1.

Figure 2: For those of you who are interested only in the takeaway messages, here are the implications of this (Study 2 / 2016) and the previous paper by Wikström-Frisén et al. (Study 1 / 2015) in a comprehensive form.

Now, the way you feel about your workouts is unquestionably important. The objectively measured hormonal response in Figure 1, however, is unquestionably a more objective measure of the training load or overload ... unfortunately, the lack of statistical inter-group differences (in spite of visible differences in the relative changes of the hormonal marker), doesn't allow for any definite conclusions on what's "best" hormone-wise (it's not even clear how to define "best" in this context, by the way). Nevertheless, the study does provide an important new insight, a result Wikström-Frisén et al. summarize as follows:

Women Have a Hard(er) Time Losing Body Fat W/ Exercise 'cause it Increases Their Appetite More Than Men's, Right? | Find out!

"The results are in contrast to endurance training where negative exercise-related consequences are common when increasing the training load (Warren 2001). 

Thus, we observed no evidence that the high frequency periodized menstrual/OC cycle based resistance training resulted in exercise-related negative consequences which could contribute to a suppression of LH, FSH, and further decrease of the estradiol production (Meczekalski 2000)" (Wikström-Frisén 2016).

This conclusion is corroborated by the lack of changes in body composition and/or bone mineral density, but should still be taken with a large quantity of healthy skepticism.

Figure 3: Relative changes in lean mass (DXA data), measures power and strength (torque) in 59 trained women in response two weeks of frequent leg-training in the first or second two weeks of their estrous cycle (Wikström-Frisén. 2015).

After all, the long-term results of the 5-days-a-week approach to leg training cannot be accurately predicted based on these findings from a 4x28-day study and the higher motivation and previously detected performance increments (see Figure 3, from Wikström-Frisén 2015; learn more in my previous article about this study from 2015) speak in favor of a (maybe non-hormonal) advantage of training more intense in the first two weeks.

Read my analysis of the previous paper on this matter | learn more

So, how do I train, now? While the paper and hand suggests that it does not matter when you plan to increase the volume, a previously discussed study by the same researchers found that leg resistance training performed during the first two weeks of the menstrual/OC cycle will additionally improve physical performance in women (Wikström-Frisén 2015), the authors recommend to periodize accordingly: if you want to increase the training frequency, do it in the first two weeks of your menstrual cycle, ladies - your performance and, as the study at hand shows - your training experience will benefit! Comment on Facebook!

References:

• Meczekalski, Blazej, et al. "Hypothalamic amenorrhea with normal body weight: ACTH, allopregnanolone and cortisol responses to corticotropin-releasing hormone test." European journal of endocrinology 142.3 (2000): 280-285.
• Warren, M. P., and N. E. Perlroth. "The effects of intense exercise on the female reproductive system." Journal of Endocrinology 170.1 (2001): 3-11.
• Wikström-Frisén, Lisbeth, Carl Johan Boraxbekk, and Karin Henriksson-Larsén. "Effects on power, strength and lean body mass of menstrual/oral contraceptive cycle based resistance training." Journal of Sports Medicine and Physical Fitness (2015).
• Wikström-Frisén, Lisbeth, Carl J. Boraxbekk, and Karin Henriksson-Larsén. "Increasing training load without risking the female athlete triad: menstrual cycle based periodized training may be an answer?." The Journal of sports medicine and physical fitness (2016).

Monthly 5-Day 'Fast' Supposedly Helps Healthy Humans to Keep Aging, Cancer, Diabetes & Heart Disease in Check

Even on the five fasting days per month your plate doesn't have to be completely empty. Real foods, however, weren't served in this trial.

An international consortium of scientists has recently published an intriguing study about the effects of a "fasting-mimicking diet" on markers/risk factors for aging, diabetes, cancer, and cardiovascular disease (Wei 2017). The study builds on the ever-increasing evidence that calorie restriction or changes in dietary composition can enhance healthy aging.

Now, as effective and healthy as it may be, fasting is not exactly what the average pre-diabetic (of whom the study at hand shows that he would benefit most) wants to do and/or what he or she can adhere to in the long run.

Learn more about fasting at the SuppVersity

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To test whether it may not even be necessary to fast for weeks and months, Min Wei et al. conducted a randomized clinical trial with 100 generally healthy participants. With a cross-over after 50% of the study period of three months, the study ensured that all subjects were fed the fasting-mimicking diet (FMD) group for 3 months. Aside from being low in calories and protein -

• day 1: ~4600 kJ = 1100kcal | 11% protein, 46% fat, and 43% carbohydrate 
• day 2-5: ~3000 kJ = 717kcal | 9% protein, 44% fat, and 47% carbohydrate

- the diet that was consumed for 5 consecutive days per months for three months (with a lower kcal-deficit on day 1 vs. 2-5 that's supposed to make it easier to get into the fast), each, was plant-based diet, and designed to attain fasting-like effects on the serum levels of IGF-1, IGFBP-1, glucose, and ketone bodies.

Figure 1: Overview of the study design (left) and post hoc comparisons for changes in risk factors for age-related diseases and conditions by baseline subgroups (right | Wei 2017).

To compensate for the lack of macro and micronutrients the scientists used ready-made food products from USC and L-Nutra (www.prolonfmd.com): vegetable-based soups, energy bars, energy drinks, chip snacks, tea, and a supplement providing high levels (25% of the RDA per serving for most ingredients) of minerals, vitamins, and essential fatty acids were on the subjects' daily menu.

Figure 2: Overview of changes in several markers of metabolic and overall health (Wei 2017).

As you can see in the table on the right-hand side of Figure 1 and the series of graphs in Figure 2, fasting for only 5 out 30 days of a months and a total of 15 days in 3 months yielded quite impressive effects in all (Figure 2) and even greater effects in those subjects with lower metabolic health (see Figure 1, right) - a statistical significance between the improvements in those with the worst and best risk factors in Figure 2 was yet observed only for glucose and IGF-1.

The parameters improved, but you may still not live longer or stay healthier! It's not the lack of improvements in plasma lipids an it's neither the relatively small effect size of many changes. It is the mere fact that the glucose, insulin, IGF1 and triglyceride levels of the average Westerner will still skyrocket acutely on the 25 days of the months on which they don't fast. And that's really bad news, because many of the unassessed markers like the postprandial glucose and lipid levels are highly significant predictors of heart disease (Lefebvre 1998; Hanefeld 1999; O’Keefe 2007) or cancer (Michaud 2002; Prescott 2014; Larsson 2016) - to reduce the level of fasted / non-postprandi-ally measured markers of disease risk is thus clearly not enough to predict the true reduction of disease risk.

Bottom line: Overall, it is thus prudent to say that the three FMD cycles every subject underwent triggered significant reductions in body weight, trunk, and total body fat; lowered blood pressure and decreased insulin-like growth factor 1 (IGF-1) without serious side effects.

What looks like an easy way out does yet also have it shortcomings: (a) the subjects' blood lipids did not improve (neither total, nor LDL, or HDL cholesterol and their ratios); (b) the treatment may have been free of health-relevant side-effects, side-effects that will have many people fall off the wagon, however, existed, nevertheless (e.g. fatigue, weakness or headache see additional figure); (c) with no effect on peak values of glucose, insulin, IGF-1 etc. on the non-fasting days, it's far from being obvious that the treatment will have any of the hoped for long-term effect.

Especially (c) is something you should remember: before the scientists produce the long-term evidence that confirms that 5 days every month are enough to let you live longer, reduce your cancer, CVD and diabetes risk, I still recommend to change your lifestyle on 365 days of the year - that's the tried and proven method to live long(er) and healthy(-ier) | Comment!

References:

• Hanefeld, M., et al. "Postprandial plasma glucose is an independent risk factor for increased carotid intima-media thickness in non-diabetic individuals." Atherosclerosis 144.1 (1999): 229-235.
• Larsson, Susanna C., Edward L. Giovannucci, and Alicja Wolk. "Prospective Study of Glycemic Load, Glycemic Index, and Carbohydrate Intake in Relation to Risk of Biliary Tract Cancer." The American journal of gastroenterology (2016).
• Lefebvre, P. J., and A. J. Scheen. "The postprandial state and risk of cardiovascular disease." Diabetic Medicine 15.S4 (1998).
• Michaud, Dominique S., et al. "Dietary sugar, glycemic load, and pancreatic cancer risk in a prospective study." Journal of the National Cancer Institute 94.17 (2002): 1293-1300.
• O’Keefe, James H., and David SH Bell. "Postprandial hyperglycemia/hyperlipidemia (postprandial dysmetabolism) is a cardiovascular risk factor." The American journal of cardiology 100.5 (2007): 899-904.
• Prescott, Jennifer, et al. "Dietary insulin index and insulin load in relation to endometrial cancer risk in the Nurses' Health Study." Cancer Epidemiology and Prevention Biomarkers (2014): cebp-0157.

Training Volume, Intensity, and Your Libido - How Bad is It? Who Read the Study Knows: It's not Just About Cardio ... !

Both, the male and female libido are at risk by overtraining. So don't continue your daily 1h stairmaster sessions, ladies!

You may have seen this study elsewhere on Facebook before... and I have to apologize that I am late to the party, but it disappeared in the "to write about" pile on my virtual desktop and resurfaced only today when I didn't find another recent study worth writing about.

Enough of the excuses, though. After all, the SuppVersity is the place to get all the study details - including an assessment of its practical relevance and a brief glimpse at relevant related research. What? No, I bet you didn't get that in one of the reposts to the abstract on PubMed, did you? Or did you understand what a low, medium or high "total intensity" was when you read those copy and paste jobs? It's not simply the VO2max. If you thought so, you probably misunderstood the study.

Overly frequent use of intensity techniques will also put you at higher risk of libido loss:

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Now, without further delay, let's take a look at what the study actually did. To study the associations between aspects of endurance exercise training and the sexual libido in healthy men using a cross-sectional online survey was conducted. Since this is the first study of its kind, a new online survey questionnaire had to be developed. As the scientists explain, ...

"[t]he questionnaire was based upon pre-existing validated questionnaires and use to assess elements of physical characteristics, exercise traininghabits and libido of participants (n=1077). Three evidence-based categories were created for the primary outcome of total libido score and low, normal, and high response categories set. The high and normal categories were combined to form a high/normal score group and the low category formed a low score group" (Hackney 2017). 

The fact that it "was based on pre-existing validated questionnaires", namely the ADAM, the SDI-2 and the AMS questionnaire for the libido-, and the IPAQ and the Baecke questionnaire for the physical activity, i  quite important. Even though this gives it an air of authority, we have to keep in mind that questionnaires can be pretty misleading (de Yébenes Prous 2009; Rosen 2004) and eventually the one at hand is non-validated - regardless of the excellent Cronbach's alpha of 0.70 to 0.96 (Tavakol 2011) and thus a high internal consistency of the individual constituents.

Table 1: The physical and exercise training characteristics of the participants (Hackney 2017).

If we assume that there were no built-in problems with the questionnaire, and appreciate that the scientists recruitment via sports clubs, national sports organizations, university athletic departments, and sporting magazines was decently successful (N = 1077 participants filled out the questionnaires | see Table 1 for participant data | mind the age groups: 1: < 18 years = not included in analysis; 2: 18-25; 3: 26-40; 4: 41-55; 5: ≥ 56), I guess we can live pretty well with the correlations the scientists calculated between their three evidence-based categories: duration, intensity of the workouts, age and total libido score (all featuring low, normal, and high response category sets).

Update on the significance of the results for women:On Facebook, Lillian rightly asked how I could claim that women would have to avoid hours of medium-to-high intensity cardio based on a study in men. Here's a brief reminder of what I've discussed in other articles about overtraining and the (female) athlete triad. There's very good evidence that - unlike resistance training - high(er) intensity long-duration "cardio" messes with the female reproductive system and female libido (Boyden 1983; Warren 1992 & 2001). Later this week I will discuss a recent study showing that this is not the case for frequent intense resistance training, though.

The fact that all participants were men, by the way, reduces the significance of the absolute results (i.e. the hours of exercise per week and the so-called "total intensity", but the general trend(s) should be similar for women). Unlike men, however, women will yet not just lose their libido (early phase), but also notice concurrent irregularities in their menstrual cycle (later phase | see red box above).

Table 2: Part of the dataset the scientists generated - I will dissect and discuss the relevant parts below (Hackney 2017).

A problem that we cannot ignore, though, is that the high and normal categories were combined to form a high/normal score group, while the low category formed a low score group before the odds ratios (OR = how likely is it that...) - to identify what "promotes" your libido is thus not possible. What we can tell, is what will keep you in either the normal or the high libido zone and that's:

• low "chronic duration" (1-16h per week; 4-fold more likely) and medium "chronic duration" (20-40h per week; 2.5-fold more likely) compared to high "chronic duration" training (50 – 100h per week for years)
• training at low "total intensity" (0-1100 VO2max x hours per week; 6.9-fold more likely) and medium intensities (1140-2480 VO2max x hours per week; 2.8-fold more likely) compared to subjects with a high "total intensity (2500-1000 VO2max x hours per week).

So what do you make of the results? Well, the total intensity was a computed variable representative of a number of training sessions at a low, moderate, hard intensity times the hours of each per week using the well-known VO2 cutoffs of low ≤35% of VO2max, moderate ~50% of VO2max, and high ≥70% of VO2max. 

Figure 1: Odds ratio of having a normal or high libido with low and medium duration, intensity, and age (Hackney 2017).

This is an important insight, after all, it goes against the notion that "steady state cardio [even walking on the treadmill as a cool-down] is generally bad" that many people who shared this post online evoked (deliberately or not) - a HIIT session of only 10 minutes at 95% of VO2max would, after all, generate a higher "total intensity" than a steady state session of walking at 30% of your VO2max on the treadmill if both had been done five times a week in the past five years which was the median value. 

Figure 2: Intensity and duration for different types of training done five times per week for five years plotted alongside the calculated "total intensity" values and information about the risk of libido loss (Hackney 2017).

In general, however, there's no debating, the highest "total intensity" levels are probably going to be generated by the typical "fat burning workouts" I have been criticizing for years, i.e. the 45-90 minutes on the treadmill at ~70% of your VO2max, in the alleged "fat burning zone". An even higher value would be observed for the Crossfit addict doing 5x60 min workouts powering the weights up and down at 80% of his/her VO2max per week (see Figure 2 for a comparison of the different exercise modes and the corresponding "calculated intensity").

Much easier to understand than the total intensity is the "chronic duration". Being computed as the arithmetic product of the time you spend in the gym or elsewhere doing any sports it is a simple proxy of your total training volume irrespective of the form and intensity of your training that - and this is important - does not involve the number of years you've been following this approach already (for me that is a questionable methodological choice the scientists made with the previously discussed "total intensity"). The unmistakable message here is: the more you work out on a weekly basis (or the less you recover per workout hour?), the higher your risk will be.

Could something as simple as a saliva test tell you if you or your clients are overtraining? I mean, common sense would dictate that cortisol, free T and IL-6 should tell us something. Learn more in my 2016 article "Overtrained or in the Zone? Tests & Analyses of Samples of Athletes' Saliva Shall Help Determine Objective Criteria" | more

So, you better limit your weekly sports activity to 16h total!? True, that's the message the non-exercise and non-intensity specific "chronic duration" data sends. If you train more than 50hrs per week your risk of suffering from a low libido is maximal. On the other hand, people who train only 20-40h per week and 1-16h per week are 4x and 2.5x more likely to have either normal or even high libido ratings on the subjective tests that were used in the test at hand.

The "total intensity" data, on the other hand, is hard to interpret. It mixes training volume, intensity, and number of the years of sticking to this madness. So, don't remember the actual figures, but rather the following interpretation: the higher your intensity, the lower your training frequency, training time and the time you stick to this intensity withing your year-long periodization regimen should be.

Practically speaking this means: Yes, you can CrossFit or do the classic 1h cardio regimen five days a week for some time, but you should know that after months and years this is going to crush your libido, while 5x20 minutes walking or doing 5x10 minute of HIIT at 95% of your VO2max are not that likely to induce the same libido reduction | Comment!

References:

• Boyden, Thomas W., et al. "Sex steroids and endurance running in women." Fertility and sterility 39.5 (1983): 629-632.
• de Yébenes Prous, M. Jesús García, Francisco Rodríguez Salvanés, and Loreto Carmona Ortells. "Validation of questionnaires." Reumatología Clínica (English Edition) 5.4 (2009): 171-177.
• Hackney, Anthony C., et al. "Endurance Exercise Training and Male Sexual Libido." Medicine and science in sports and exercise (2017).
• Rosen, Raymond C., et al. "Male Sexual Health Questionnaire (MSHQ): scale development and psychometric validation." Urology 64.4 (2004): 777-782.
• Tavakol, Mohsen, and Reg Dennick. "Making sense of Cronbach's alpha." International journal of medical education 2 (2011): 53.
• Warren, MICHELLE P. "Clinical review 40: Amenorrhea in endurance runners." The Journal of Clinical Endocrinology & Metabolism 75.6 (1992): 1393-1397.
• Warren, M. P., and N. E. Perlroth. "The effects of intense exercise on the female reproductive system." Journal of Endocrinology 170.1 (2001): 3-11.