Abstract
Despite the vast public policy efforts to promote the consumption of healthy foods and the public’s growing concern with weight management, the proportion of overweight individuals continues to increase. An important factor contributing to this obesity trend is the misguided belief about the relationship between a meal’s healthiness and its impact on weight gain, whereby people erroneously believe that eating healthy foods in addition to unhealthy ones can decrease a meal’s calorie count. This research documents this misperception, showing that it is stronger among individuals most concerned with managing their weight—a striking result given that these individuals are more motivated to monitor their calorie intake. This finding has important public policy implications, suggesting that in addition to encouraging the adoption of a healthier lifestyle among overweight individuals, promoting the consumption of healthy foods might end up facilitating calorie overconsumption, leading to weight gain rather than weight loss.

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Background

In introducing today’s paper, I am reminded of an old joke/quip to the effect that “All that separates man from the animals is our ability to rationalize.”   I’d add “And accessorize” but that’s neither here nor there.  But the reality is that humans are able to do a wide variety of mental gymnastics in how they approach life.  Effectively, we appear to be slave to what psychologists call cognitive biases, ways in which we think about the present, past, future or ourselves that often lead us to make some fascinatingly bad choices.  This is a topic that many recent books has discussed in a variety of contexts.

And while I don’t know if I can say that it occurs to a greater degree in terms of eating and health behaviors, there is no doubt that people often engage in some exceedingly interesting mental gymnastics when it comes to those topics.  Some of this is conscious but much of it can be chalked up to either unconscious behaviors, misunderstandings (or a lack of information/education) or mishearing/misinterpreting the message.   And these types of things, as much as anything else, often derail many people’s attempts to eat healthy, lose weight or simply avoid weight gain.

In the realm of exercise for example, many people grossly overestimate the actual caloric expenditure from activity, as I discussed in Normal Weight Men and Women Overestimate Energy Expenditure – Research Review, and this leads them to either expect far more of an impact on weight loss than is realistic or to eat more calories than they actually need based on the assumption that they burned it off during activity.

In the arena of eating, this issue can show up in a myriad ways.  A classic example of a misunderstanding/garbling of the message occurred back in the 80′s during the low-fat eating craze.   While it’s hard to say where the blame lies, the general public sort of got the message that so long as they kept fat intake low, nothing else really mattered.  Caloric intake and portions went out the window. 

Food companies capitalized on this by rushing plenty of energy dense, high-calorie (but low-fat) foods to market and it all went wrong.  Studies routinely found that people ate more food when it was labelled ‘low-fat’ compared to one that was labelled as being higher in fat.  Either consciously or unconsciously, they gave themselves permission to eat more of it.  And often ended up consuming more calories than they would have otherwise.

Another example deals with artificial sweeteners where you often see a pattern where artificial sweetener (or diet soda) intake is associated with weight gain (or a lack of weight loss).  And while there is some speculation that artificial sweeteners do some odd things in the brain in terms of driving appetite, it’s probably more related to people rationalizing that they can eat more of something else because they are getting less calories by choosing diet soda or using artificial sweeteners.   That is, they figure that since they are ‘saving so many calories’ by making one choice, they end up compensating (or more than compensating) by choosing something unhealthy.  Call this the skim milk and chocolate cake or Diet Coke and cheeseburger approach to eating. 

I’d note before continuing that this much of the above rationalizing tends to be more for people who are only paying somewhat ‘superficial’ attention to ‘eating well’ (or some other fairly abstract goal).  That is, the type of thing I’m going to talk about doesn’t generally occur among folks who are diet obsessed and track macros or calories or what have you.  Rather it’s for folks who, while they may say that they are concerned with their diet or body weight or body fat, are focusing on the wrong things (a topic I addressed in more detail in Fundamental Principles vs. Minor Details).

Finally type of behavior seems to occur more prevalently in people who tend to divide foods into ‘good’ and ‘bad’ categories (a category that many popular diets and dietary approaches tend to promote).  ‘Good’ foods become equated with healthy and, altogether too often, can be eaten without consequence (i.e. weight gain).  Researchers call this the ‘health halo’ by which supposed ‘healthy foods’ have a halo of invincibility around them  In the same vein ‘bad’ foods are equated with being unhealthy and this categories are not only absolute but cause us to do some of those strange mental gymnastics when it comes to how we approach our food intake.

You can find examples of this all over the place where people assume that ‘healthy/good’ foods can be eaten in uncontrolled amounts whereas the tiniest amount of ‘unhealthy/bad foods’ mean that the diet has failed, the dieter is immoral and weak, and health will simply be destroyed (this is seen at the greatest extreme in a psychological condition called orthorexia whereby people see food as a moral choice judging not only themselves but others by the foods that they choose to eat).  You can see some good examples of this in the comments section of Straight Talk About High-Fructose Corn Syrup: What it is and What it Ain’t. – Research Review. 

Which basically segues into today’s paper which examines a behavior pattern that is often seen whereby folks tend to get fixated (or perhaps ‘blinded’ is a better word) by the concept of ‘healthy’ foods and end up missing the forest for the trees when it comes to their food and caloric intake.   There is also evidence that people who are (or at least state that they are) more ‘weight conscious’ are even more prone to make these kinds of mis-estimations which was a secondary aim of the study.

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The Paper

The study recruited 934 people, of whom the majority (74.2%) were female aged anywhere from under 20 to over 50.  Subjects were then shown 4 meals which either consisted of ‘unhealthy’ foods or those same unhealthy foods coupled with a healthy option.  The four meals, with the healthy addition shown in parentheses, were a hamburger (three celery sticks), bacon and cheese waffle sandwich (small organic apple), chili with beef (small salad without dressing) and meatball pepperoni cheesesteak (celery/carrot side dish).   So, for example, subjects were either shown a bacon and cheese waffle sandwich (which sounds amazing in so many ways) either by itself or side by side with a small organic apple.

Half the subjects were shown the unhealthy choice alone and the other half were shown the combination of the unhealthy choice with it’s healthy add-on and they were asked to estimate the caloric value of the meals.  I’d mention that this design is problematic because it’s not comparing how a given individual might rank each of the two meals; rather it’s comparing the average estimate of the caloric value of the different meals between people.  All subjects were also asked to rate how concerned they were with managing their weight on a scale of 1-5 (with 5 being extremely concerned).

The study generated a total of 2750 total observations of the different meals and, on average, subjects estimated that the unhealthy meal alone contained 691 calories.  Now, logically it’s obvious that a food consisting of an unhealthy item PLUS a healthy item would have to have more calories than the unhealthy item alone.   Clearly two foods can’t have less calories than either food alone.

Yet, on average, subjects estimated the unhealthy plus healthy choice as having only 648 calories.  I’d mention that as a third part of the study, a separate group was asked if they believed that the healthy foods contained negative calories and this was not the case.  So it doesn’t appear to have been the case where subjects figured that the healthy addition was literally ‘reducing’ the caloric value of the food by containing negative calories.  Rather, the ‘health halo’ effect caused people to systematically underestimate the caloric value of the combination of an unhealthy and healthy food.

But it gets even odder.  When the estimates were ranked by how folks reported their concern with managing their weight, the values changed even more.  The most ‘weight conscious’ subjects estimated the unhealthy meal as containing 711 calories while the combination of the unhealthy and healthy choice was only 615 calories. In contrast, the non-weight conscious individuals estimates were only 684 for the unhealthy choice versus 658 for the combination and there was a direct relationship between how weight conscious the subjects were and their mis-estimate of the different meals.

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My Comments

I really don’t have a ton to add to the above, the paper goes into lot of discussion that I’ll spare you here since it’s a lot of detailed examination of the possible underlying mechanisms behind these types of odd cognitive biases.   One point that was made was that while one might expect more motivated/involved people to have less problems with these types of conceptual biases, this research found the opposite.  To whit:

The negative calorie bias is more pronounced for more involved/motivated individuals. Thus when evaluating vice/virtue combinations, greater motivation does not necessarily result in greater accuracy but instead can lead to more biased judgments.

I would add that I think really has more to do with what I mentioned in the background above, the issue isn’t with dietary motivation per se but rather with how people often conceptualize the process.  By focusing on things like good/bad foods, clean vs. unclean eating, meal frequency exclusively or organic vs. non, people lose sight of the issue of portions and calories which are what really matter when it comes down to it. They rely on estimates which are oh so often off.  And which appear to be colored heavily by the cognitive biases that many humans are so prone towards.

Make no mistake, certain types of eating patterns often automatically get people to reduce their intake, often by the outright removal of a so-called ‘bad’ food.  What is defined as good or bad depends on the diet in question and certainly these types of good/bad approaches to dieting can work in at least the short-term (and sometimes longer than that).  The problem is when people start focusing on the goodness/badness of the foods they are eating to the exclusion of everything else.  That’s when it often goes wrong; this is not helped by many dietary approaches telling folks that calories/portions don’t count and that focusing only on the aforementioned ‘good/healthy’ foods is all that matters.

In this vein, the paper’s author notes that:

In particular, the negative calorie illusion has been shown to be less pronounced when individuals pay attention to the quantity of the combined items, instead of focusing solely on the healthy/unhealthy aspects of the items.

In a related vein, the author points out that:

Another public issue raised by this research concerns the viability of promoting the very notion of stereotyping foods into vices and virtues.  Despite it’s intuitive appeal as a decision heuristic to simplify choice, vice/virtue categorizations focuses consumers’ attention only on one aspect of the meal [my note: whether the food is a 'vice' or a 'virtue'] and ignores other important aspects such as its overall quantity.

And I really think that that’s the big take home message of this rather odd paper: people often get so fixated and focused on the wrong things that they end up hamstringing their own attempts to reach their goals.  Because while it’s all well and good to focus on healthy/unhealthy, good/bad, clean/unclean or whatever, at the end of the day quantities always count.  When people lose sight of that and focus on the wrong aspects exclusively, they often end up hurting their own progress.  This paper just points out one way that this happens. 

I’ll finish by pointing interested readers to a book by the paper’s author titled  The Dieter’s Paradox: Why Dieting Makes Us Fat that addresses not only this research but a great deal of other research looking at similar issues.  How humans tend to categorize foods into good and bad and how it can lead them to make a lot of really weird assumptions about what they are actually eating.  It was a pretty fascinating read and shows how many different ways we can end up screwing our own progress by relying on our (often incorrect) intuition, primarily by focusing on the wrong factors that are relevant to what we are eating.

The optimal volume of resistance exercise to prescribe for trained individuals is unclear. The purpose of this study was to randomly assign resistance trained individuals to 6-weeks of squat exercise, prescribed at 80% of a 1 repetition-maximum (1-RM), using either one, four, or eight sets of repetitions to failure performed twice per week. Participants then performed the same peaking program for 4-weeks. Squat 1-RM, quadriceps muscle activation, and contractile rate of force development (RFD) were measured before, during, and after the training program. 32 resistance-trained male participants completed the 10-week program. Squat 1-RM was significantly increased for all groups after 6 and 10-weeks of training (P < 0.05). The 8-set group was significantly stronger than the 1-set group after 3-weeks of training (7.9% difference, P < 0.05), and remained stronger after 6 and 10-weeks of training (P < 0.05). Peak muscle activation did not change during the study. Early (30, 50 ms) and peak RFD was significantly decreased for all groups after 6 and 10-weeks of training (P < 0.05). Peak isometric force output did not change for any group. The results of this study support resistance exercise prescription in excess of 4-sets (i.e. 8-sets) for faster and greater strength gains as compared to 1-set training. Common neuromuscular changes are attributed to high intensity squats (80% 1-RM) combined with a repetition to failure prescription. This prescription may not be useful for sports application owing to decreased early and peak RFD. Individual responsiveness to 1-set of training should be evaluated in the first 3-weeks of training.

Background

There has been a literally decades old argument going on regarding the optimal volume of strength training (and here I’m primarily focusing on the argument about doing a single set vs. multiple sets) for various goals including strength, hypertrophy and the training of athletes. 

Claims that “One set is just as good as three” or what have you are often made based on a variety of arguments.  Most of those I’m not going to address here since I want to focus primarily on the research into the topic.  I’m also going to be focusing only on the issue of strength since muscular size gains are sort of a different issue.

In general the proponents of single set training are also advocates of training to failure, that is taking each set to the point of momentary muscular failure (where no more repetitions can be performed). I’d mention only in passing that there can actually be different definitions of failure here.  In contrast, those advocating multiple sets often (but not always) work at something less than the point of failure.  Again, not universal but common as it can be difficult to perform lots of sets to the point of actual failure.

I’d also note empirically that almost all successful athletes, strength/power or other have used multiple sets in training which at least lends some empirical weight to the idea that multiple sets are better.  One oft brought up exception is football where there are examples of winning teams that use a single set to failure approach winning championships (an equal if not larger number of teams use multiple set programs). The problem being that football is a very complex sport ruled as much by skill, tactics and strategy as what the athlete does in the weight room. 

A good team will usually beat a strong team although a good and strong team may beat either (or may lose because something tactically or strategically happened on the field).  Football players also have the additional factor of being so beaten up (especially in season) that they can’t do more than a single set of machine training; they are just too wrecked to do more.  In any case, using football success or failure to ‘prove’ the relative merits of one style of training versus another just sort of misses the point in a lot of ways: the strength training program is at most one part of a very complex sport and win/loss ratios don’t prove anything.

So what does the research on the topic say?  Part of the confusion is that it is actually fairly mixed which makes it possible to draw different conclusions depending on how you look at the issue.  Certainly some data does seem to show that a single set is ‘as effective’ as three although there is also research showing multiple sets to be superior.   A lot of this has to do with the difficulty in designing decent training programs, often far more than just the variable of number of sets is changing and this makes interpretation difficult.   

For example, several of the studies ostensibly comparing different numbers of sets were also looking at periodized training models (so not only did one group do multiple sets, they also use a variety of rep ranges) and as often as not it’s 1 repetition maximum (1 RM) that is being tested.  If the periodization group worked into low repetitions (as they usually do) but the single set group did not, that automatically biases the results towards the multiple set/periodized group.  Simply because a 1 RM requires practice and the group performing lower repetitions gets it.  But you can’t conclude much about the volume of training per se from such a study.

In a related vein, some of the studies, for example, will have the single set group train on machines (as many of the ‘one set to failure’ groups advocate machine training) while the multiple set group will train on compound free weight exercises.  Subjects are then often tested on the free weight movements that only the multiple set group performed; specificity alone would predict superior results but the study design is a bit biased towards the free weight group.

Perhaps the biggest issue is the training status of the subjects.  As a generality, most of the research showing that one set is as good as three is done in beginners but plenty of other research shows that beginners pretty much make the same gains almost no matter what they do (a topic I discuss in detail in the Beginning Weight Training series).   And extrapolating from studies done on beginners to trained athletes clearly misses the point due to changes in what is required to stimulate further gains in trained versus untrained individuals.

As a final issue, many trained athletes perform far more than three sets of a given exercise (or at least more than three sets for a given muscle group) and it’s possible that studies comparing one to three sets of training simply aren’t looking at volumes that are different enough to see a real difference in gains.    A study examining far greater differences in number of sets (while hopefully avoiding some of the issues I mentioned above) might help to determine if more sets are or are not better from the standpoint of strength gains.

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The Paper

To address the above issue, the study recruited 43 males who had been performing resistance training at least twice weekly for the past two years (experience was 6.6 +- 1 year) with a minimum back squat of at least 130% of body weight; subjects were excluded if they were listed as taking any performance enhancers.  So these were not total beginners.

The training program was divided into 12 total weeks.  The first two weeks were a break-in/washout period that simple served to standardize their training and eliminate any residual effects from their previous training; back squats were not performed during this two week period. A basic three way split (chest/biceps, back/triceps, legs) routine was performed during this period.

The next 6 weeks were the primary training period and subjects were assigned to either a one, four or eight set squat program and the back squat was the only lower body exercise performed.  During this period, a two way split was used with chest/shoulders and arms trained on one day and legs and back trained on the other.  The volume of all exercises except the squat was identical between groups.

For the squat training, the intensity was set at 80% of 1 their starting 1 RM and all sets were taken to the point of volitional muscular failure.  For the multiple set groups, three minutes were taken between sets and all groups performed the same warm-up (10 body weight squats, 10 reps at 50% 1RM, then singles at 60% and 70% of 1RM) prior to the work sets.  Basically the only variable between all three groups was the number of sets of squats performed and each group ended up having 11 total subjects.

Following the main training block, all participants performed an identical 4 week ‘peaking’ program consisting of low repetition, high-load exercises combined with ballistic exercises.  Squats were performed at 3X4RM for all groups during this period.

The subjects were tested on a variety of things including squat 1RM (which was tested in a fairly standard way with depth taken to a measured knee angle of 90 degrees).  As well, to examine neuromuscular factors in strength, knee extension rate of force development (RFD, effectively how quickly a muscle can generate force) along with maximal isometric quadriceps strength, a variety of EMG measured was also made.  Finally, body fat and body composition was measured via skinfold.  All tests were performed after the washout period, at 3 and 6 weeks and again after the 4 week peaking block.  One thing that is not described is how weights were or were not progressed throughout the study which is an odd ommission.

Finally, to examine individual response, the researchers grouped the results for each squat group into high responders (defined as making >20% strength gains), medium responders (10-19% gains) and low responders (less than 10% gains).  Ill come back to this but each squat volume group had it’s share of high responders (3 in the 1 set group, 5 in the 4 set group and 5 in the 8 set group) as well as low responders (6 in the 1 set group, 5 in the 4 set group and 2 in the 8 set group).

I’ve presented the reults below in terms of average changes in squat strength (in kilograms) among groups.

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* indicates a difference from the post-washout period.  the letter ‘a’ indicates a difference from the single set group.

Note that only the eight set group showed further strength gains after the peaking program.   I think it’s interesting that the eight set group made better gains despite starting out with higher absolute numbers.  Usually it’s the opposite with the group that is less well trained that shows the best results.

In terms of body composition, all three gropus showed minor changes, primarily a small loss of body fat but there was no difference beteween groups.  The 8 set group also saw a significant increase in total body weight possibly suggesting an increase in muscle mass.  In terms of the neuromuscular adaptations measured there were no changes in quadriceps force output or activation although all groups showed a drop in rate of force development.

As I mentioned, one observation was that there were high, medium and low responders in all three groups with average increases in squat strength of 29.4±2.2% for high responders, 14.3±0.9% for medium responders and 2.6±2.0% for low responders.  11 of the 13 total low responders were from the one and four set groups although the design of the study makes it impossible to know if these subjects would have responded differently with more sets.

As well, it’s impossible to know if the 10 high responders in the four and eight set group would have gotten the same results off of one set.  That is, it’s possible that these subjects would have been low and high responders regardless of training volume.  It’s also impossible to know if the three high responders in the one set group would have gotten different results on the higher volume training programs.  The researchers do state:

Nonetheless, that the numbers are so clearly skewed to associate high volumes with responsiveness lends some weight to the argument that regardless of categorical variables, high training volumes are preferred to develop strength.

Of some interest, the researchers point out that the 8 set group was the only group to achieve significant strength gains (compared to the 1-set group) by the three week mark; they conclude that for short-term strength improvement, clearly a higher volume approach is indicated. 

Looking at the neuromuscular adaptations, the researchers suggest that the lack of improvement in force output or activation suggests that trained individuals can already recruit maximal numbers of muscle fibers. They also note that this type of training did decrease explosiveness (as evidenced by decreased RFD), most likely due to the high-intensity nature of the training along with each set being taken to failure.  It’s also possible that testing neuromuscular variables with an isolated leg extension doesn’t show possible neuromuscular adaptations during the squat itself.

A final point made by the researchers is that previous studies of one versus three sets may have been limited in that the training volumes were just too similar, they suggest that subsequent research on training volume use at least four sets for the multi-set group in order to give a more realistic comparison (and potentially show differential results).

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My Comments

I don’t have a tremendous amount to add to the above.  The study, which was far more well controlled than most previously on this topic (in that only a single variable, the number of sets of back squats done), showed that, on average the higher volumes generated higher strength gains.

Certainly there was some individual response (and clearly a single set to failure does generate significant strength gains in at least *some* subjects) but, in the aggregate, more people made better gains with the higher  volumes.  And this was especially true over the shorter periods of time (i.e. only the 8 set group had made significant strength gains by week 3). 

That final point has some clear relevance for athletes in a situation where they may have a limited time per year to make strength gains (usually in the early part of the season) before other training becomes too important for them to be constantly wrecking themselves in the weight room.  An athlete with only 8 weeks to improve strength might be best served by a high volume program to get the maximal results in the shortest period of time before reducing weight room work to lower or maintenance levels.  Even short blocks of ‘top up’ training might be best served by higher volumes for the same reason.

Of course this brings up a potential negative of higher volumes: the time and energy commitment.  Athletes often have a lot on their plate in terms of training and spending endless hours in the weight room (if their sport isn’t already based in the weight room like powerlifting or Olympic lifting) may not be a good use of time depending on how their weight room work impacts on other work.  

An athlete for whom strength is a secondary characteristic (see The Sports, Training and Adaptation Continuums) and for whom lots of weight room work impairs their actual sports training wouldn’t be best served by spending tons of time in the weight room regardless of the potential gains.  Clearly for an athlete for whom maximal strength is absolutely required in their sport, putting in the extra volume would appear to be indicated.  Typically those athletes don’t have as many capacities to develop, mind you, giving them more time to invest in the weight room.

This also brings me to my final point and that is the reality of the time requirements of the high-volume training.  Consider that the eight set group was spending 30 minutes squatting twice per week compared to about 5 minutes for the single set group.    And that’s just for that one exercise.  By the time you add in other exercises at higher volumes, you’re see a large increase in overall training time.  For any given trainee depending on their goals, etc. it may or may not be worth spending that much extra time training for the difference in gains.

That is, a missed point in a lot of the single versus multiple set arguments tends to ignore the time commitment (along with the goals, etc.) of the trainee.  For someone with very limited time and modest training goals (i.e. general trainee looking for basic strength, health, etc.) a low volume of training may give them all the gains that they want or need.  Even if a higher volume would generate greater strength gains, there is always a huge point of diminishing returns in this: you end up spending 4-5 times as long in the gym for far less than 4-5 times the gains.  Whether that time investment is worthwhile simply depends on the situation.

Finally I’d note that the presence of high, medium and low responders in all three groups (again noting more high responders in the higher volume groups and more low responders in the single set groups) does lend at least some weight to the idea of individual response although it’s impossible to know if any of the subjects would have gotten different results on the different programs. But clearly some people get excellent results from low volumes (while others get nothing) and vice versa. 

Many coaches and trainers tend to engage in some projection, often assuming that what works for them will de facto work for anyone that they train.  It may be that some of the one set to failure proponents are the high responders from that type of training, but that doesn’t mean that everyone will be.  And, again, vice versa.  Just because one person gets the most results out of lots of volume doesn’t mean that everyone else will.  

Addressing this within the context of the current study, the researchers state “We recommend that responsiveness to single-set training be evaluated in the early stages (<3-weeks) of a training program, with progression to higher volumes of training in those who are not responsive to lower training volumes.”  Basically, if low volumes are working for someone, that’s great; if not, change it.

The idea that dietary supplements can improve athletic performance is popular among athletes. The use of antioxidant supplements is widespread among endurance athletes because of evidence that free radicals contribute to muscle fatigue during prolonged exercise. Furthermore, interest in vitamin D supplementation is increasing in response to studies indicating that vitamin D deficiency exists in athletic populations. This review explores the rationale for supplementation with both antioxidants and vitamin D and discusses the evidence to support and deny the benefits of these dietary supplements. The issue of whether athletes should use antioxidant supplements remains highly controversial. Nonetheless, at present there is limited scientific evidence to recommend antioxidant supplements to athletes or other physically active individuals. Therefore, athletes should consult with their health care professional and/or nutritionist when considering antioxidant supplementation. The issue of whether athletes should supplement with vitamin D is also controversial. While arguments for and against vitamin D supplementation exist, additional research is required to determine whether vitamin D supplementation is beneficial to athletes. Nevertheless, based upon the growing evidence that many athletic populations are vitamin D deficient or insufficient, it is recommended that athletes monitor their serum vitamin D concentration and consult with their health care professional and/or nutritionist to determine if they would derive health benefits from vitamin D supplementation.

Background

Supplements for athletic performance have been a part of the landscape for decades and athletes are always looking for an edge in terms of either promoting adaptations to training, recovery, or outright performance.    And while many in the field tend to think of me as anti-supplement, this really sort of misses my issue with supplements.  Because I’m not anti-supplement; rather I’m simply anti-bs. 

I’m also anti-anything that takes focus away from the factors that actually do matter, namely things like training, diet, lifestyle, etc.  And the sad fact is that all too many athletes try to use supplements in place of proper training, attention to their diet, etc.  It goes to something I discussed ad nauseum in the thankfully finished Why the US Sucks at Olympic Lifting series, quick fixes are more appealing than things that take work.  And popping a pill is easier than working your nuts off in the gym or watching your diet.

And the reality is that most claims made for most supplements are about 99% bs and 1% “Well, maybe”.   Of course, that never stops athletes, who fall prey to the logic of “IF this is the next big thing, I don’t want to miss out on it.”  Of course, supplement industries pander to that very thought process; that’s how they make shocking amounts of money off of desperate athletes.

I’ve been in this field for over 2 decades and in that time I’ve seen thousands of products come and go, always with the same hype and exciting ad copy claiming that they are the solution for the woes of athletes, only to disappear months later to be replaced by the newest crop of crap.  Because over that 20 years, I can count the number of products that even came close to living up on maybe two hands.  That gives supplements about a 99.9% failure rate; in my mind it’s absurd to hold any opinion about anything new except to assume it’s crap until proven otherwise.  But I’m sort of getting off track here and really only want to focus on two specific supplements since they relate to today’s paper. 

Because for about three decades, one ‘class’ of supplements that has been popular (and very often recommended) is that of anti-oxidants.  In short, these are compounds that help to scavenge or ‘deal with’ what are called reactive oxygen species (ROS) in the body. These are produced under various conditions (including exercise) and one early theory of aging and bodily damage was that the production of ROS was part of the overall breaking down of the body.  With the logical solution being to simply take these nutrients in doses ranging from reasonable to ‘Oh my god, you want me to take how much?’ levels.  I can fondly remember Colgan and his laundry list of high-dose anti-oxidants in Optimum Sports Nutrition (an excellent book so long as you ignore every word about supplements) for example.

More recently, there has been great interest in Vitamin D status, both from a general health standpoint (Vitamin D deficiency is literally being considered a current vitamin deficiency epidemic and there is actually a staggering amount of data that this is the case) and from an athletic standpoint (and data going back to the 1920′s actually suggested this very early on).  Vitamin D does about a million and one things in the body but one thing it is strongly related to is muscular function and performance; I even mentioned explicitly in the Why the US Sucks at Olympic Lifting that one advantage that Kenyan runners may have is the ability to train outdoors year round (the same holds for Jamaican sprinters) and this may maintain better Vitamin D status compared to athletes who live in harsher environments.

Which is all just a lead up to today’s paper, a relatively short review on both anti-oxidant and Vitamin D (and calcium) supplementation for athletes, looking at the role that they play in the body and arguments both for and against the use of either by athletes.

The Paper

The paper starts by looking at the role of antioxidants in the body.  As I mentioned above, ROS are produced in the body under a variety of conditions including exercise and there is at least some evidence that ROS may cause fatigue during exercise when they are produced in large quantities; this is along with potentially causing overall bodily damage through oxidative stress (also caused by things like pollution and smoking for example) and muscle damage.

And this provided the idea that providing supplemental anti-oxidants (which include but are not limited to compounds such as Vitamin A, Vitamin C, Vitamin E, beta-carotone and a host of others; the list of potential anti-oxidant compound seems to grow daily).  However, with the exception of N-Acetyl Cysteine, which appears to reduce fatigue during some types of submaximal exercise (and it’s thought that this occurs by reducing ROS fatigue in breathing muscles, believe it or not), most studies supplementing anti-oxidants have not found any impact on performance.

Even the studies on anti-oxidant supplementation on muscle damage and oxidative damage are pretty mixed, probably reflecting differences in the type, amount and intensity of exercise along with the specific anti-oxidants and doses that were supplemented.  Basically, outside of NAC and submaximal endurance performance, the data is far from conclusive.

Moving to arguments for anti-oxidant supplementation, the paper examines three potential reasons that athletes might consider anti-oxidant supplementation.  First is the known increase in ROS production during activity, coupled with the general principle that the compounds are pretty much non-toxic even at relatively high levels. This is sort of a ‘It probably won’t hurt and might help’ kind of argument.  Kind of weak.

A second argument has to do with the role of excessive ROS on muscle fatigue but, as I noted above, with the exception of NAC, most supplementation studies have shown no performance benefit of anti-oxidants so this argument pretty much fails.  The final argument that they address is the idea that many athletes have poor or insufficient diets (note that most anti-oxidants in the diet come from fruits and vegetables) and that an athlete who’s diet is poor may need supplementation.  Which is equally weak for a number of reasons I won’t go into just yet.

In terms of arguments against anti-oxidants, the paper examines a number of arguments against supplementation. First they point out that while exercise certainly does increase ROS production it’s very transient (and this does distinguish it from the pollution or smoking examples which may be generating more chronic levels).  As well, the body already has an in-built system to deal with ROS production; quite in fact it increases it’s activity with training. 

That is, by exposing the body to ROS in moderate amounts, it adapts by being better able to handle further ROS production (some have even theorized that high-dose antioxidant supplementation might be harmful down the road by limiting the body’s upregulation of it’s inbuilt system).

In a related vein, there is considerable evidence and this has been accumulating for a while that the production of ROS is part of the overall adaptation to training (and the data here is more geared towards endurance athletes than strength/power athletes).  That is, the production of ROS, like inflammation and a whole host of other things that occur with training appear to be part of the overall training stimulus; blocking this with high-dose supplementation could conceivably limit the adaptations to training.

Finally is the simple fact that studies are routinely showing that individual anti-0xidant supplementation (as opposed to diets high in natural anti-oxidants; that is diets including lots of fruits and vegetables) either have no real benefit to health or may actually be harmful and increase mortality in the long-term.    The authors conclude that outside of ensuring a mixed, energy sufficient diet (which should provide adequate ‘natural’ anti-oxidants) that there is no reason for athletes to supplement with individual high-dose anti-oxidants.  I’ll come back to this when I wrap-up below.

Moving on the authors next address Vitamin D along with calcium (since it’s a bit tough to separate the two).  Vitamin D is a bit odd among the vitamins for a number of reasons, not the least of which that it can actually be produced by the body specifically in response to sun exposure.  The authors overview the metabolism of Vitamin D but I won’t repeat that here, go Wikipedia it if you must know.

Vitamin D is critical in the body for a number of reasons, not the least of which is bone health; in this vein, adequate Vitamin D status is required for optimal calcium absorption in the body.  As well, Vitamin D regulates genes all over the body, controls inflammation and immune system function; a great deal of research has focused on low Vitamin D status and colon cancer.   Of more relevance to athletes is that Vitamin D status is tied to muscular function and Vitamin D is involved in the expression of a number of genes involved in muscular function and performance; all issues relevant to athletes.

There’s actual a considerable history of evidence on the issue of Vitamin D and performance although it’s only recently that researchers have realized that Vitamin D might be playing a role.  Let me explain: back in the early part of the 20th century, it was observed that athletes often made less progress during the winter months in terms of strength or performance and that exposure to ultraviolet light improved trainability and strength gains.  We now clearly know that UVB exposure would have had one effect of increasing Vitamin D synthesis in the body and as discussed in Athletic Performance and Vitamin D, this may have been the mechanism at work.

Of more relevance, recent research is finding that almost everyone is Vitamin D deficient, all over the world. This is due to a number of factors including things like overuse of sunscreen, working indoors, poor diet, etc.  Both calcium and Vitamin D come from the diet (and many foods are fortified with both) but, as I mentioned, Vitamin D is an oddity among the vitamins in that it can be produced by the body, specifically in response to direct sun exposure.

Moving to Vitamin D status, the authors point out that determination of optimal level of Vitamin D in the body is still a bit of a controversial area.  It’s generally considered that Vitamin D levels below 50 nmol/L (or 20 ng/mL) is a sign of deficiency while levels below 80 nmol/L (32 ng/mL) is insufficient.  What level is optimal is harder to determine but a concentration of 100-250 nmol/l (or 40-100 ng/ML) is thought to be ideal.

It’s worth mentioning that while there is less work on the Vitamin D status of athletes, what work exists suggests that many athletes show Vitamin D insufficiency or outright deficiency levels; depending on the study and the definition used this may be as high as 90% of the athletes tested.  This is especially true for athletes involved in indoor sports, or who train in areas with a harsh winter that limits sun exposure (while Vitamin D levels go up during summer training, they are only maintained for perhaps a month or so without supplementation or sun exposure.  Interestingly, even athletes in sunny areas, such as Qatar may be at risk for deficiency, probably due to athletes preferring to train after sundown since it’s about a billion degrees during the day.  It’s only athletes who live in temperate year round sunny climates that are likely to not be at risk for Vitamin D deficiency.

And from that standpoint alone, supplementation is probably warranted for athletes who train indoors or who live in cold weather areas where sun exposure for a great part of the year simply isn’t available (note that the use of a tanning bed would be another option so long as the duration are moderate).

Mind you, the direct data on Vitamin D and athletic performance isn’t major except for what I talked about above, a handful of studies have examined it and there does appear to be a positive correlation between Vitamin D status and things like strength and muscle force, along with decreased risk of stress fracture (important for athletes in high-impact activities).  Mind you, claims such as “The higher the Vitamin D status the better your performance” are absolutely not supported by current research; it’s likely that it’s more an issue of correcting a highly likely deficiency or insufficiency.

In terms of arguments against supplementation, the main one is the overall lack of data indicating a performance boost; mind you that keeping an athlete healthy in general terms (and Vitamin D contributes to immune system function and bone health) is just as critical here.  An injured or sick athlete isn’t training nor performing and the realities of Vitamin D deficiency should be addressed regardless of whether or not it improves performance.

The other argument against has to do with toxicity, as a fat soluble vitamin, it is possible to take too much Vitamin D.  It does take pretty stupid levels but athletes often fall into a ‘more is better’ trap.  But this is more to do with ensuring that athletes don’t do stupid things and take 5X the recommended dose than the supplement itself.  I’d note that roughly 30 minutes of direct sun exposure pretty much maxes out Vitamin D synthesis (at roughly 10,000 IU’s) in the body and this might be taken as a rough realistic maximum daily intake level.  Others have set more conservative maximum intake levels of 4000 IU’s/day; at the current time it’s not really known what level of supplementation is toxic or problematic.

Finally the authors note that there is individual difference in the absorption and utilization of Vitamin D and this could conceivably impact on how a given athlete responds to supplementation (a great deal of research suggested a problem with Vitamin D levels in obesity but that’s a different research review).  The authors recommend that, while there is little evidence that Vitamin D supplementation will improve performance (outside of correcting a deficiency), athletes should monitor their Vitamin D levels and supplement as needed.  Again I’ll give my recommendations below.

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My Comments

For the most part what I wrote above doesn’t really differ to any signicant degree from what I wrote in the articles Supplements Part 1 and Supplements Part 2.  In terms of anti-oxidant supplementation, I’m really not a fan under most circumstances.  Not only do they not appear to have much if any benefit, especially taken in isolated form in high-doses, they may actually be detrimental to training adaptations.  Using them during a primary training phase could slow adaptations.  In contrast, athletes in heavy competition might consider supplementation; some studies do show decreased muscle soreness and damage and taking them during a heavy competition schedule might be worthwhile simply to keep the athlete in one piece.  That’s in addition to NAC having a potential ergogenic benefit before certain types of endurance performance.

In terms of Vitamin D, outside of those athletes who can train consistently in the sun, I think supplementation is probably mandatory.  Few athletes live in climates where outdoor sun exposure is available year round and the simple fact is that even if optimal levels occur during summer training, they only maintain about a month or so after the stimulus of regular sun exposure is removed. 

Athletes who’s sports keep them indoors, or who live in areas with actual winter (where training is done indoors by choice or there is simply limited sun exposure) will find Vitamin D levels falling rapidly, potentially compromising immune system function, bone health and even trainability.  Supplementation (or going to the tanning bed a few times per week for reasonable amounts of time, perhaps 30 minutes 2-3X/week) will serve to maintain optimal Vitamin D status during those time periods.

And while it would be ideal for athletes to get regular blood work to determine levels along with their response to supplementation it’s not cheap work to do and has to be done at least twice.  For athletes that can get it done, I’d mention that it takes, on average, 100 IU of Vitamin D to raise levels by 1 ng/mL.  So an athlete with a Vitamin D level of 30 ng/mL who wants to get to 50 ng/mL would need 2000 IU’s per day.

As I noted above, 30 minutes of direct sun exposure generates 10,000 IU’s of Vitamin D and that appears to be the maximum the body will synthesize.  A daily intake of half that should be more than safe and is in keeping with other maximum daily recommendations of 4000 IU/day.  And outside of extreme deficiencies, that level should cover most folks (that is if we assume levels drop to an insufficient 20-30 ng/mL during the winter, 5000 IU/day would be expected to raise that to 70-80 ng/mL right in the middle of the optimal range).

I’d note in closing that, as a fat soluble vitamin, Vitamin D should be taken with a fat containing meal for optimal absorption, Vitamin D is also a supplement that can be taken only weekly (i.e. 35,000 IU’s all at once or what they’d get from 5000 IU’s per day for a week) for athletes who are bad about taking pills.

One of the proposed causes of obesity and metabolic syndrome is the excessive intake of products containing added sugars, in particular, fructose. Although the ability of excessive intake of fructose to induce metabolic syndrome is mounting, to date, no study has addressed whether a diet specifically lowering fructose but not total carbohydrates can reduce features of metabolic syndrome. A total of 131 patients were randomized to compare the short-term effects of 2 energy-restricted diets-a low-fructose diet vs a moderate natural fructose diet-on weight loss and metabolic syndrome parameters. Patients were randomized to receive 1500, 1800, or 2000 cal diets according to sex, age, and height. Because natural fructose might be differently absorbed compared with fructose from added sugars, we randomized obese subjects to either a low-fructose diet (<20 g/d) or a moderate-fructose diet with natural fruit supplements (50-70 g/d) and compared the effects of both diets on the primary outcome of weight loss in a 6-week follow-up period. Blood pressure, lipid profile, serum glucose, insulin resistance, uric acid, soluble intercellular adhesion molecule-1, and quality of life scores were included as secondary outcomes. One hundred two (78%) of the 131 participants were women, mean age was 38.8 ± 8.8 years, and the mean body mass index was 32.4 ± 4.5 kg/m(2). Each intervention diet was associated with significant weight loss compared with baseline. Weight loss was higher in the moderate natural fructose group (4.19 ± 0.30 kg) than the low-fructose group (2.83 ± 0.29 kg) (P = .0016). Compared with baseline, each intervention diet was associated with significant improvement in secondary outcomes. Reduction of energy and added fructose intake may represent an important therapeutic target to reduce the frequency of obesity and diabetes. For weight loss achievement, an energy-restricted moderate natural fructose diet was superior to a low-fructose diet.

Background

Every since John Parillo said that fruit makes you fat over 30 years ago, fruit has held an odd place in the world of dieting.  It’s quite common to see contest dieters talking about ‘dropping out fruit’ and removing fruit from the diet is not an uncommon recommendation when someone stalls on their diet.

More recently, the rabid furor and hype over refined fructose (and especially High-fructose corn syrup or HFCS) has only added to this.  If reports I’m seeing are right, the consumption of fructose and/or HFCS will make you fat, drive up blood pressure and make your muscles fall off.  HFCS is responsible for the problems with the economy (when Obama isn’t being blamed), the war in Iraq and just general human meanness and unhappiness.  Ok, I may be exaggerating slightly but it’s only slightly.

I addressed the issue of HFCS in Straight Talk About High-Fructose Corn Syrup: What it is and What it Ain’t. – Research Review, an article that drew quite the share of comments (inane and otherwise) and I’d point readers towards that article for a more detailed look at what I’m going tot talk about next.

Make no mistake, studies have clearly shown that excessive fructose intake (and this is usually due to an excessive HFCS intake and that is typically due to the consumption of non-diet soda) cause problems. But often the studies are, well, let’s just call them silly.  They almost always revolve around the chronic intake of simply non-physiological intakes of whatever is being studied (sometimes pure fructose, sometimes HFCS).

In one that people like to cite at me, rats (rarely a good model for humans) were fed a 60% fructose diet for 6 straight months and this induced leptin resistance.   I was actually going to do a research review on it (mainly to point out everything wrong with it) but couldn’t be bothered.  The short version is that a 60% fructose diet isn’t even possible in humans.  Humans don’t do well with large amounts of pure fructose intake as it causes stomach upset.

And if you’re going to argue that most fructose in the diet comes from HFCS (which is about half fructose), that means that the equivalent 60% fructose diet in a human would consist of 120% of the diet being from HFCS.   Except that that is impossible.

I’d mention, humorously, that the rats didn’t actually gain weight during the 6 months of fructose overfeeding; rather,  it was during the high-fat part of the study that the weight gain occurred.  But the anti-HFCS crusaders (who are often pro-fat) missed that point since they seem to only read abstracts on this stuff.  Not that it applies in either case because it’s freaking rats and the diet was completely impossible for a human to achieve in the first place.

In another study, humans were given 200 grams of pure fructose to see what happened.  I don’t recall the details but the results were negative.  First and foremost, that’s 800 calories of pure fructose which is just a ton.  Second, again going by the fact that HFCS is only about 1/2 fructose (the other half is glucose) that would be the equivalent of someone eating 400 grams of HFCS. 1600 calories per day just from HFCS.

That’s about 16 standard sized non-diet sodas per day (or one super duper mega insane Big Gulp).  Now, I’m not saying that’s healthy, I’m not disagreeing that that is a problem.  But have you ever seen someone drinking that much soda who didn’t have the rest of their diet look like absolute shit?   Usually the ones refilling the 128oz cup with coke are eating a ton of other junk food.   My point being that the HFCS may not be the only thing causing issues here.  Yet folks are fixated on HFCS as the source of all evil.

Which isn’t to say that smaller amounts of fructose don’t or can’t cause issues.  I wrote an article over 10 years ago looking at this issue and it was clear that beyond a certain level (about 50 grams of pure fructose per day) there was the potential for issues.  At the time, the big endpoint had to do with blood triglycerides.  Fructose is metabolized almost exclusively in the liver (quite in fact almost zero incoming fructose will ever reach the bloodstream in humans) and this is a rate limited process.  Above a certain point, fructose starts being converted to fat in the liver.

It’s worth mentioning that some studies have also found that, because it doesn’t raise insulin, fructose consumption doesn’t blunt fat oxidation after you eat it.  So while eating a ton of fructose at once (which is abnormal) can cause fat production in the liver, the body burns more fat.  Almost as if it all sort of cancels out.

But the above invariably was looking at either absurd levels of pure fructose or HFCS.  What about fruit?  To a degree, fruit has become sort of guilty by association.  One of the sugars in fruit is fructose and the hysteria over HFCS (again coming primarily from non-diet soda and refined foods) and the fructose content has caused people to lose their minds.

Basically, people have written off anything containing HFCS or fructose IN ANY AMOUNT.  If either are on the label, that food is ‘evil’. Evil I tell you.  Even consider eating it and your muscles will fall off and you’ll explode with fat.  You’ll start beating your pets and probably become a serial killer and end up with your story on Law and Order: SVU.  Fructose is serious stuff if Internet message boards are to be believed.

But it’s key to realize that fruit doesn’t even contain that much fructose in the first place, about 7% by weight.  So a 100 gram piece of fruit (a medium sized apple or banana for reference) might contain about 7 grams of fructose in addition to the other calories.  Even if you use a 50 grams per day cutoff, that’s 7 medium pieces of fruit.  Not impossible but that’s a lot of fruit.

A second issue is that fruit, as opposed to pure fructose or HFCS, contains other stuff, micronutrients, anti-oxidants, flavonols and everything else that might, just might, impact on how it’s metabolized in the body.  You can’t automatically throw out the fruit with the dishwater (yes, I’m mixing my metaphors) because studies of purified fructose/HFCS using insane amounts have found problems.

Finally is an issue that the dynamics of how nutrients are handled while dieting (that is, in a hypocaloric state) are often vastly different than when someone is weight stable or gaining weight.      So yeah, it’s pretty clear that large amounts of fructose/HFCS are a big issue for the average person who is inactive, gaining weight and for whom the entirety of their diet is pretty much crap.  But that doesn’t mean that fruit as part of an overall hypocaloric weight/fat loss diet is automatically the same problem.  And that, finally brings us to today’s paper.

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The Paper

The researchers set out to address two questions.  The first was whether a calorie restricted diet that specifically restricts fructose would improve markers of the metabolic syndrome.  They also hypothesized that a diet high in natural fructose (From fruit) would be superior to one where fruits were limited.

Towards this end, 131 patients were recruited of which 107 finished the study, all were obese (average body fat 40%) and nearly 80% of the subjects were women.  After determining basal caloric requirements, subjects were placed on meal plans of 1500, 1800 or 2000 calories.  The diet itself consisted of 55% carbs, 15% protein and 30% fat and the main difference between the two groups was the fructose content.  One group was limited to less than 10 grams of fructose per day, the other was allowed 50-70 grams of fructose per day coming almost exclusively from fruits.

Food was not provided for the subjects (arguably the biggest limitation of the study); rather they were given meal plans and had to record their food intake at least once weekly (food reports can be notoriously inaccurate and I’ll come back to this).  Adherence to the diet was defined as at least 80% attendance for scheduled clinic visits.

A variety of things were measured including weight and waist measurement along with body fat percentage.  A Tanita BIA scale was used and I’d note (as I discuss in Measuring Body Composition: Part 1 and Measuring Body Composition: Part 2) BIA is not a perfect method as it can be drastically impacted by changes in hydration state.  A vast number of metabolic variables including blood glucose, blood pressure, insulin, creatinine, uric acid cholesterol, triglycerides and others were also measured.  A measure of quality of life was also made in both groups.

The study lasted 6 weeks and these were the results.

In terms of changes in the measured health parameters there were no significant differences between groups in terms of anything.  The fructose group showed a slightly better drop in blood glucose (no surprise there) and the low-fructose group showed a slightly better drop in blood pressure; neither of these reached statistical significance.

I’d comment here that this isn’t uncommon: in a dieting situation, most things change/improve as a function of the weight/fat loss and diet composition tends not to matter.  This is a point lost on many who look at dieting situations (such as a recent study where a high fat intake caused no problems when weight was being lost) and extrapolate it to situations where someone is weight stable or gaining weight.    Basically, weight/fat loss tends to trump just about everything else but that doesn’t meant that the same results will be seen if the person is gaining weight.

But what about the weight/fat loss?  The two groups’ weight losses were 4.19+-0.30 kg and 2.83 +-0.29kg after six weeks.  And perhaps to the surprise of many, the high-fructose group was the one that lost the greater amount of weight.  Body Fat percentage also dropped 2.09+-6.32% in the low-fructose group compared to 2.89+-6.33% in the high-fructose group but this wasn’t statistically significant. The BMI drop was also higher in the high-fructose group but the change in waist to hip ratio was not.

I’d note that there was massive overlap in total weight loss and I’ve reproduced the actual results below.

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Weight Loss for High vs. Low Fructose Diets

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Like I said, a huge amount of overlap even if the weight drop was larger in the high-fructose group.  There was an improvement in quality of life in both groups with no difference between them.

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My Comments

Ok, so what does this paper say?  I think the first point I’d make is that this current idea that carbs make you fat or prevent weight/fat loss is clearly incorrect.  I wish someone would send this paper to Gary Taubes to help him try to remove his head from his ass.  Both groups lost a significant amount of weight and fat and did it eating 55% carbohydrate.

And clearly, at least in the population tested (obese subjects, mostly women), fructose in the form of fruit caused no problems.  At worst, the high-fructose diet was no worse than the low-fructose diet (in terms of all health parameters measured).

And, at least looking at weight loss, it may have been slightly superior.   The researchers had no real explanation for the differential given that the caloric intakes were supposed to be identical.    They suggest that perhaps the higher intake of anti-oxidants, etc. from the fruit might have played a role.  They also point out that the low-fructose diet had a higher glycemic load (since natural fruits had to be replaced by higher glycemic index carbs, I doubt this given the Glycaemic Index Effects on Fuel Partitioning in Humans – Research Review.

Rather, I suspect that the difference in weight loss is just a weird artifact of the study especially given that there was no significant difference in changes in body fat percentage or waist/hip ratio.  While higher insulin doesn’t really impact on fuel utilization, it does impact on water retention, causing the kidney to resorb water.  Lowering insulin (as would occur in the fructose group) might have caused greater water loss.

There is also the issue of the diet not being perfectly controlled since only meal plans were given.  Fructose tends to blunt hunger in many people (this occurs through a vagally mediated mechanism in the liver which sends a fullness signal); perhaps the high-fructose group ate a bit less.  Again, this isn’t really supported by the lack of body fat or waist/hip ratio changes.

Regardless, clearly the idea that the data on massive intakes of either fructose or HFCS doesn’t seem to apply to fructose coming from fruit.  At least not in the population tested.  As I mentioned above, the fruit group did at least as well on all measured markers and was slightly superior in terms of weight loss.  The idea that fruit needs to be eliminated because it contains fructose would seem to be flawed, at least in this group.

Of course, readers of this site are wondering if this applies to leaner individuals and this study can’t answer that question. I’d note that for every anecdotal report of someone removing fruit and getting lean, there are just as many (and many coaches) who keep fruit in the diet and their guys get plenty lean.  One is Borge Fagerli (aka Blade) who has found, in many clients, that the re-addition of fruit to the diet helps people get lean.  But that’s not research, just his observation.

Objective: To test whether physiological satiation as measured by the gut peptide ghrelin may vary depending on the mindset in which one approaches consumption of food. Methods: On 2 separate occasions, participants (n = 46) consumed a 380-calorie milkshake under the pretense that it was either a 620-calorie “indulgent” shake or a 140-calorie “sensible” shake. Ghrelin was measured via intravenous blood samples at 3 time points: baseline (20 min), anticipatory (60 min), and postconsumption (90 min). During the first interval (between 20 and 60 min) participants were asked to view and rate the (misleading) label of the shake. During the second interval (between 60 and 90 min) participants were asked to drink and rate the milkshake. Results: The mindset of indulgence produced a dramatically steeper decline in ghrelin after consuming the shake, whereas the mindset of sensibility produced a relatively flat ghrelin response. Participants’ satiety was consistent with what they believed they were consuming rather than the actual nutritional value of what they consumed. Conclusions: The effect of food consumption on ghrelin may be psychologically mediated, and mindset meaningfully affects physiological responses to food. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

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Background

Ok, in addition to having possibly the coolest title of any paper I’ve reviewed on the site, this is also one of the weirdest papers I’ve looked at.  But I’ve seen it getting a lot of press and, of course, have to put in my own two cents, if for no other reason than I suspect many people will take the findings far out of context.  First, some necessary background; this will probably take more space than discussing the actual paper itself.

In recent years, the number of factors in the body controlling hunger has multiplied by leaps and bounds.  Leptin was discovered in 1994 or so and since then numerous other compounds have been identified that play some role in hunger, appetite, body weight regulation or even body composition.  One of those is ghrelin, which I also talked about in more detail in the Bodyweight Regulation Series.

In brief, ghrelin is a compound released from the gut in response to a whole host of physiological factors.  Among other things, ghrelin binds to a receptor in the brain and stimulates growth hormone release (useless trivia for the day: ghrelin was a compound where the brain receptor was discovered before the hormone itself was discovered; it was actually the presence of the receptor that drove researchers to go look for what was supposed to bind to it).

More relevant to today’s article, increases in ghrelin stimulate hunger (and alter fuel utilization and calorie partitioning, at least in animal models) and acute injections of ghrelin reliably increase hunger.  As well, ghrelin antagonists reliably blunt hunger.  Please note that ghrelin is one of those hormones where, in a sense, high levels are ‘bad’ and low levels are ‘good’, at least from the standpoint of things like hunger and appetite.  As is to be expected, as leptin levels fall on a diet, ghrelin typically goes up.

One of the oddities of ghrelin was that levels appeared to change in anticipation of meal time.  That is, through some mechanism (that so far as I could tell was never determined), ghrelin levels would go up just prior to normal meal times.  So if you habitually ate lunch at 12pm, ghrelin would go up right before then, lowering blood sugar and making you hungry.   Scientists call this entrainment and ghrelin levels would entrain to normal meal times through some mechanism or another.

Tangentially, this probably explains why changing meal frequency is at least initially difficult: ghrelin levels are changing in accord with your normal meal times and get out of synch with the new one.  So if you’re trying to increase meal frequency, you initially find that you’re simply not hungry when you’re supposed to eat.

And if you’re trying to decrease meal frequency, for a few days at least, you’re ravenous at the times you used to normally eat, at least initially.  However, over a few days time, ghrelin entrains to the new meal frequency and you stop being hungry when you used to eat, only getting hungry when you’re habitually eating.

Most of the early studies on ghrelin looked at how food intake, calorie intake and macronutrient intake and such were impacting on ghrelin levels.  Carbs seemed to have a greater impact than fat, protein was unclear (at least the last time I looked at the research); mind you ghrelin is not the only hormone of relevance.  I look at a bunch of the others in Bodyweight Regulation Wrap-Up: Other Hormones.

The total caloric value of the meal seemed to play a determining role; more calories dropped ghrelin more than fewer calories.   I seem to recall one odd study where sham feeding (I think they gave them noncaloric fiber or something) reduced ghrelin which is the first indication that something weird was going on: how could thinking you were eating something lower ghrelin?  Ok, that’s the first half of the background on this paper.

The bottom line is that the above is all good and well and interesting and relevant.  And would be the final word in all of this if humans were nothing more than a gut and a nervous system. That is, if we just responded in a lovely deterministic way to changes in hormones, this would all be a lot simpler.  Sadly, that’s not the case.

Big brained humans have this thing called self-awareness, sometimes we even use it for our own benefits.  We can think, reason, etc. and this impacts on many things including hunger, appetite, food choices, etc.  So while most animals will pretty much eat when hungry and not when full, it’s not nearly so clear cut in the case of humans.

Humans will eat out of boredom, depression, because they are at a party.  Most eat more on the weekends and there is a reliable relationship between the number of people at a meal and how much people eat: more people and folks eat more food.  My point is that you can’t just look at the physiology of what’s going on and ignore the psychology or other aspects.

A simple example is that of anorexia, or even dieting in a more general sense: in the case of full blown anorexia there is a situation where despite presumably massive drive to eat, the individual consciously chooses not to do so (I’d note here a brand new study, that I am still trying to get ahold of where researchers are suggesting a metabolic ‘brokenness’ contributing to anorexia and driving the psychology; I suspect it’s a complex loop where one is driving the other).

Even dieters, in the face of hunger, make conscious choices whether or not to ‘obey’ the signals being sent by hormones.  Basically, humans do not represent some deterministic system where you just look at the hormones and go ‘This is what’s going to happen’.  And if that didn’t complicate things enough, it’s clear that people differ in their psychological approach to things like eating.

Researchers often talk about things like restrained and unrestrained eaters, rigid versus flexible dieters (a topic I looked at in my own A Guide to Flexible Dieting), disinhibited eaters and others and there are clearly different psychologies when it comes to how people approach eating, food restriction, overeating.

And it won’t be surprising to find that all of the above psychological  (along with physiological) stuff differs to at least some degree for lean versus obese individuals.  We already know that there can be an insensitivity to leptin in the brains of the obese (whether this is a cause or effect of obesity is still up to debate) and there is evidence of differing sensitivity to other hormones such as ghrelin, GLP-1, PPY and the rest of the mix.

Basically, human hunger and appetite and real-world food intake is very complicated and something the strangest things impact on food intake in a way that you might not necessarily predict ahead of time (i.e. who would have thought that having more people present at a meal would lead to higher food intakes).  One of those is related to belief or how people can often rationalize certain food choices because of the situation or what else they are eating.

Here’s a classic example that will finally segue into today’s paper: back during the low-fat craze someone did a study more or less along the following lines.  Folks were given a food (I think it was frozen yogurt) and then ‘told’ that it was either low-fat or full/high-fat yogurt.  Note that the yogurt was identical in both cases, they were simply told that they were being given different types.  Subjects who thought they were eating the low-fat yogurt ate more.  Presumably they rationalized that since it had less calories/fat, they could eat more of it and this, among many other factors, has been held up as one reason that the whole low-fat movement failed.

You might also look at this as the Oreo/skim milk or double cheeseburger/diet coke effect whereby people rationalize eating something crappy because they are ‘balancing’ it out with something healthy or whatever.  This is often given as a reason that things like diet sodas fail to impact on bodyweight; some people simply justify eating more of the other stuff because they aren’t getting calories from the diet soda.  Yes, there’s more to it than that but this introduction is already way too long.

My point is this: human appetite and hunger is clearly an interaction between physiology and psychology, not that you can ever really separate the two (as I discussed in Dieting Psychology vs. Physiology before I lost the plot of what I was trying to talk about).  Because physiology impacts on psychological function.  And, as today’s study shows, psychological function impacts on the physiology of eating behavior. Ok, on to the paper.

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The Paper

46 participants, between the ages of 18-35, within a normal to overweight BMI were recruited to take part in two separate sessions for the study.  Of those 46 people, 65% of the subjects were women, 56% were white, 12% African American, 11% Asian American, 10% Hispanic/Latino and 11% other.  Subjects were told that the Yale nutritional center was working on two different milkshake with differing nutrient contents that they would sample and that the goal of the study was to evaluate whether or not the shakes tasted different and to examine the body’s reaction to the different shakes.

Basically, they were lied to; the milkshakes were identical in composition, but were presented with two different labels, which I’ve shown below.

Decadence You Deserve

Guilt Free Satisfaction

So the indulgent shake was presented as a high fat, high calorie shake and the sensible shake was touted as being low fat and low calorie.  Again, the shakes were actually identical in terms of their nutrient and caloric content, all that differed was the labelling.   Each day lasted 2.5 hours divided into two time intervals.  In the first interval, after 20 minute rest period, blood was drawn at 60 and 90 minutes and the subjects were asked to rate the label of the shake in terms of hunger ratings.

In the second interval, subjects drank the shake within 10 minutes and were asked again to rate hunger along with taste (including smell and taste along with enjoyment and healthiness).  If you’re wondering how hunger is rated, it’s done subjectively through something called a Visual Analog Scale (VAS), a little graphic doodad that ranks things from 0-100; it’s subjective as hell but used commonly.

Measurements of ghrelin were made from the blood draws and subjects also filled out a questionnaire to determine their degree of dietary restraint and this was used to see if there was any effect of dietary restraint on the other variables measured.

So what about the results.  Not shockingly, subjects rated the sensible shake as 7 times healthier than the indulgent shake and the degree of restraint had no impact on this.  Basically, they firmly believed that the sensible shake was healthier.  No differences were seen in the ratings of tastiness between shake conditions.

Ok, let’s look at ghrelin first since this seems to be where most of the Internet punditry is focusing.  The indulgent group showed a much higher rise in ghrelin prior to consumption of the shake followed by an equally significant drop after consumption.  In contrast, the sensible shake situation found a fairly flat ghrelin change: there was a small increase with little change downwards.  I’ve shown the actual changes in ghrelin in the graph below and you can see the clear difference in ghrelin response pattern for the two conditions.

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Changes in Ghrelin

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Looking solely at this physiological response, the researchers state:

When drinking the shake in an indulgent mindset, participants’ levels of ghrelin reflected a moderate level of physiological craving followed by a significant level of physiological satiety…when drinking the shake in a sensible mindset, suggesting that, despite consuming the same nutrient contents, they were not physiologically satisfied.

So good intersting stuff, mindset affects physiology and the folks who thought they were indulging had a significantly different ghrelin response, suggesting of differences in both craving and satiety, than those who thought they were eating the sensible shake.  Clearly how you approach your diet meals or whatever can impact your physiology and all you have to do is adjust your mindset to sail along in your diet.  Right?

But, now, you’re wondering, what’s the catch in all of this because we all know I wouldn’t be discussing this paper if there wasn’t something more going on?  Be patient, I know this is long but bear with me.

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My Comments

Today’s paper is certainly interesting, if nothing else it indicates that an individual’s mindset going into eating something can affect at least one marker of physiology, in this case ghrelin.  Specifically, the ghrelin response to the shake intake was based on the person’s expectancies of the shake rather than it’s actual caloric content.  And that’s what the researchers talked about in the abstract: how mindset affected this one singular physiological response.

That’s most of what I’ve seen people focusing on in their commentary about this study on the Internets (one title was “It’s All About the Hormones”).  It’s also why I spent so much time in the introduction trying to point out that humans aren’t just physiological automatons responding to changing hormones in this fashion.  Because it’s not just about the hormones in humans.  There’s way more going on.

Before moving on the researchers point out something that most seem intent on ignoring: this was a single meal study.  As the researchers state:

Although the effects of such psychologically mediated differences in subsequent consumption or long-term alterations in weight were not measured in this particular study, future research on the impact of this phenomenon on metabolic maintenance is warranted.

I don’t disagree and in the real-world the above matters since what is seen acutely often doesn’t translate at all to the long-term; you often see compensation at the next meal or the next day or whatever and it all balances out in the wash.  Simply, few conclusions can be drawn from this one study in terms of food intake across a day, a week, a month.

Don’t misread me: I’m not saying it won’t or couldn’t have an impact.  It might or it might not.  But it might also all balance out given that there are other systems regulating things as well.  There is also the fact that, as I discussed in Homeostatic and Non-Homeostatic Pathways Involved in the Control of Food Intake and Energy Balance the physiological systems present in humans can clearly and easily be overwhelmed by non-physiological factors (such as how many people you are eating with).

Looking at their results, the researchers get into a whole speculative discussion about how some of the mindset of dieter’s about their food might be contributing negatively to overall results.  For example, based on data that increased ghrelin tends to drive hunger and lower metabolic rate (at least in animal models), they speculate that:

The relatively flat ghrelin profiles in response to consuming the shake in a sensible mindset may be placing participants in a psychologically challenging state marked by increased appetite and decreased metabolism.

Two problems with this.  One they didn’t measure metabolic rate and speculating from what is mostly animal data is a mistake. But that’s not the bigger issue here, it’s time to focus on their claim of increased appetite (or perhaps less blunting of hunger).

Did you notice something missing in my discussion of the study above?  Like how I mentioned that they measured hunger using a Visual Analog Scale early on but then didn’t say anything more about it?  It’s because I was saving it for now. In a single throwaway sentence hidden at the end of the results section that nobody who has just read the abstract will actually see, the researchers state what I think is the truly important finding that everyone seems to be ignoring:

For the measure of hunger, these analyses produces no significant main or interaction effects as a function of shake, time or restrained eating.

Translated into English that means this: despite the changes in ghrelin as a physiological marker of craving and satiety there was no difference in hunger between the indulgent and sensible condition and dietary restraint had no impact on this.   So the differential ghrelin  response, while interesting, didn’t amount to anything in the real-world in terms of actual hunger ratings differences between the two mindsets.  Please read that sentence again until it sinks in.

Hell, the researchers didn’t even bother to provide the VAS hunger data for the different conditions anywhere in the paper.  They just went through this whole involved discussion on ghrelin and everything else and then, as an afterthought mentioned “Oh yeah, there was no difference in actual hunger.”  And they didn’t mention it in the abstract.

So while the physiological response they measured is nifty as hell and certainly worthy of more research, the simple fact is that it didn’t amount to any real world difference in actual hunger.   Which is important because people are already taking this paper completely out of context, going from the hormonal response (which was different based on mindset) and extrapolating that to differences in hunger (which was not different based on mindset).

A question might be why there was no difference in hunger and the best the researchers could do was to say:

This study did not find any significant differences with respect to subjective hunger regardless of mindset after participants consumed the milkshake.  This result may have been a function of the measuring timing (hunger levels were assessed 10 min prior to ghrelin changes as opposed to simultaneously or subsequently), or the manner in which hunger was measured (visual analog scale).

Basically they are crapping on their own measurement methodology to try to dismiss their non-result.   Don’t get me wrong, maybe they would have seen a difference in hunger had they measured things differently.  At least they used the word ‘may’ above.

I’d note that the VAS is used extensively to measure hunger and has been for years now; so far as I know, it’s pretty accurate and able to discriminate different levels of hunger.  So saying ‘The measurement method we choose might have sucked’ is kind of weak given that VAS is a commonly used measure.  And, of course there are other potential reasons that their nifty physiological response didn’t generate a real world change in hunger.

Maybe those small changes in ghrelin were irrelevant to overall hunger drive (the graph looks pretty impressive but the absolute difference in ghrelin wasn’t huge).  Maybe that kind of small change just isn’t enough to have an impact.  Maybe you need to factor in the myriad other hormones such as leptin, GLP-1, PPY and the rest when you look at this; there are too many overlapping systems here to just focus on a small difference in ghrelin response and then extrapolate to the entire system. Or maybe it was something else going on. We don’t really know until more research is done and speculating is kind of pointless at the end of the day.

What we do know is this: psychological mindset impacted on the response of a singular hormone that is important in terms of hunger drive and satiety.  But despite a measured physiological change in that hormone that differed between groups, there was no difference in real world hunger based on psychological mindset.  The hormonal response simply didn’t amount to anything in the real world.

And that last paragraph above is really my main point, and yes I took a long time to get to it.  Everywhere I’m seeing folks prattle about ‘thinking themselves thin’ hoping that thinking that what they are eating is more indulgent than it is while dieting will lower ghrelin and make them be less hungry.  But that’s absolutely not what the paper found as there was no difference in actual hunger ratings based on mindset.

As well, I think you could just as easily parse this paper to suggest that the indulgent group would be more likely to overconsume calories due to the early increase in ghrelin.  That is, if increasing ghrelin drives hunger, who’s to say that folks won’t eat more of a food if they put themself in an indulgent mindset? Especially if they aren’t in the artificial situation where regardless of hormonal response, they are being given a fixed calorie shake to drink.

Mind you, the study didn’t find this either since, beating the dead horse, hunger ratings didn’t differ at any time point for either group.  But it would be just as accurate an interpretation of the physiological response as assuming that the drop in ghrelin will decrease hunger (which it didn’t).

So here we have a fascinating paper, clearly things are more complex than we even thought up until this point, and this study shows that psychological mindset can impact on at least one measure of the physiology of hunger regulation (the mechanism wasn’t even guessed at).  Hopefully more work on this will determine not only if there is an impact but what the mechanism of it all is.

But at the end of the day, it didn’t amount to any actual change in real world hunger which is what matters.  More research is needed but drawing unwarranted conclusions from this paper is a mistake even if that’s what the Internet is doing right now.  So the physiological response while interesting as all hell simply had no real-world impact on actual hunger.  That’s the bottom line.

INTRODUCTION: The magnitude and duration of the elevation in resting energy expenditure following vigorous exercise have not been measured in a metabolic chamber. This study investigated the effects of inserting a 45-min vigorous cycling bout into the daily schedule versus a controlled resting day on 24-h energy expenditure in a metabolic chamber.
METHODS: Ten male subjects (ages 22 to 33 yrs) completed two separate 24-h chamber visits (one rest and one exercise day) and energy balance was maintained for each visit condition. On the exercise day, subjects completed 45-min of cycling at 57% Wattsmax (mean±SD, 72.8±5.8% VO2max) starting at 11:00 am. Activities of daily living were tightly controlled to ensure uniformity on both rest and exercise days. The area under the energy expenditure curve for exercise and rest days was calculated using the trapezoid rule in the EXPAND procedure in the Statistical Analysis Systems (SAS) and then contrasted.
RESULTS: The 45-min exercise bout resulted in a net energy expenditure of 519±60.9 kcal (P<0.001). For 14-h post-exercise, energy expenditure was increased 190±71.4 kcal compared to the rest day (P±0.001).
CONCLUSION: In young male subjects, vigorous exercise for 45-min resulted in a significant elevation in post-exercise energy expenditure that persisted for 14-h. The 190 kcals expended post-exercise above resting levels, represented an additional 37% to the net energy expended during the 45-min cycling bout. The magnitude and duration of increased energy expenditure following a 45-min bout of vigorous exercise may have implications for weight loss and management.

Background
In recent years there has been a focus on the calorie burn that occurs after training, referred to in science terms as EPOC (Excess Post-exercise Oxygen Consumption).  A variety of different types of training (usually revolving around brief duration, high-intensity methods such as interval training or circuits) have been proposed with the major effect of such activity being in the EPOC that is created.

Now, EPOC used to be thought to be related to something called the ‘oxygen debt’, essentially the difference in how much oxygen the body needed to sustain activity and how much was available.  We now know that it’s related to a host of other processes but these aren’t really that relevant practically.   What is relevant from a fat/weight loss point of view is how large the EPOC is and whether or not it contributes meaningfully to the overall caloric expenditure of an individual.

In a previous research review with the imposing title of Effects of Exercise Intensity and Duration on the Excess Post-Exercise Oxygen Consumption I examined a monster review on the topic.  In brief, looking at the data in aggregate, the study concluded that intensity was more important than duration in terms of the EPOC created.

And while the relative EPOC was higher for high-intensity activities (that is the percentage increase), the absolute level of EPOC was still pretty irrelevant  (maybe 30-50 calories).  The researchers concluded that the primary impact of exercise was still through the calories burned during the activity itself: the absolute EPOC was fairly irrelevant to the total whether an individual did long-duration low-intensity activity or short-duration high-intensity activity. Their conclusion based on review of the data was:

The manipulation of energy balance for these individuals should not be concerned with generating large EPOCs but focused on both the energy expended during the actual exercise and the design of programmes that enhance compliance.

The compliance issue is actually quite relevant given that the intensities used in the interval studies are generally exceedingly high and unlikely to be performed consistently by most people, especially beginning and/or overweight exercises (for more on this topic, please read Training the Obese Beginner series).  An added issue that I have talked about variously on the site is that many people looking for fat loss train daily; trying to perform high-intensity activity too frequently is a recipe for disaster. Read the previous review for the details, or the series on Steady State vs. Interval Training that it was a part of if you’re particularly bored.

However, several people have asked me about a recent study that seems to contradict the above conclusions, as it found that the EPOC following what was terms ‘vigorous’ activity was significant and it’s that paper I want to look at today.

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The Study

The study recruited 10 male subjects, aged 23-33 years who were capable of bicycling for 45 minutes continuously. Body composition was measured via DEXA and the subjects all underwent VO2 max testing using a fairly standard protocol.   The subjects performed two ‘exercise’ sessions.  In the first they sat quietly in a metabolic chamber (which was measuring the actual energy expenditure); in the second they performed actual exercise.

Basically, the ‘sitting quietly’ was the control condition, the researchers had to see how many calories the subjects burned at rest and in the following hours so that they could determine the difference in caloric expenditure and EPOC following the actual workout.

The exercise bout consisted of 45 minutes of cycling at 57% maximum wattage (so if a subjects Vo2 max wattage occurred at 300watts, they cycled at 171 watts), this put them at roughly 70% of their VO2 max; the duration was chosen to represent a midpoint for some rather standard recommendations for activity.  There was actually a short (4 minute) warm-up before the main set along with a short cool-down but I’m not going to bother detailing it.

Food intake was controlled (this can be a huge confound to a lot of these studies as eating raises metabolic rate and a lot of early exercise and metabolic rate studies confused the increase from eating with an increase from the exercise session); it is important to note that food intake was increased on the exercise day to maintain energy balance  That is, the subjects were not in a caloric deficit during the period following the training session.  The subjects stayed in the metabolic chamber following the exercise session and this is how the caloric expenditure following the exercise bout was determined.

For the exercise bout itself, the session burned a total of 519 +- 60 calories so about 11 calories per minute for the 45 minute exercise session.  This is consistent with it being a vigorous intensity.  And over the next 14 hours (including 3 hours of sleep), the subjects burned an additional 144+-50 calories with the majority of this occuring in the first 9 hours after training.

This EPOC represented a whopping 37% of the actual exercise bout energy expenditure, far higher than what was reported (usually 15% or less) in the LaForgia review I linked to above. And the total impact of the exercise bout was an energy expenditure of ~750 calories above and beyond the resting condition.  The researchers conclude

“The 24-h net energy expenditure difference between exercise and rest days was 750 kcal, a meaningful quantity over time if two or three such exercise bouts are inserted into the weekly schedule and energy intake is controlled.”

Fair enough.  And obviously a workout burning 750 cal/session (including the workout and EPOC) is meaningful.

My Comments

I think the first issue worth addressing is why this particular study found such a difference compared to previous studies, such as the ones reviewed in the LaForgia review I linked above.  Certainly there could be methodological differences; for example this study used a metabolic chamber to get an accurate measure of caloric expenditure, other studies using a different method (such as Douglas bags, think big balloon looking things that folks breathe in for later analysis) might be getting different measurements.

Another has to do with the fact that the subjects were deliberately kept in energy balance, and fed an additional 660 calories to offset the energy expenditure of the exercise bout.  The researchers state:

The increased energy intake balanced against energy expenditure (energy flux) has been shown in several studies to contribute to the elevated 24-h energy expenditure on exercise days or in trained individuals.

Of course this is a problem with applying this study to a dieting/fat loss situation where, by definition, you can’t be in energy balance (since you have to create a deficit by not replacing the exercise induced energy expenditure with more food).  This study needs to be re-done under conditions where energy intake isn’t increased to see if the same big increase in EPOC is seen under dieting conditions (as that would have actual application to fat loss).

The final reason that contributed is likely this: the workout tested in this study was  HARD.  As I noted above, subjects pedalled at a workrate equal to 57% of their max wattage output.  This corresponded to 70% of VO2 max which corresponds to roughly 85% of maximum heart rate.  Quite in fact, the heart rate measured during the activity was 163 +-16 beats per minute.  This would be equivalent to the Sweet Spot training that I discussed the Methods of Endurance Training series.  I’ll come back to this.

Without going into the details of what determines the EPOC, the researchers state fairly simply that:

The magnitude of post-exercise energy expenditure is greatest when the body experiences significant physiologic stress during prolonged and high intensity exercise.

Basically, through whatever specific mechanisms (and a host have been implicated), the ‘afterburn’ effect is maximized when you massively disrupt homeostasis in the body.  And this tends to occur most significantly for workouts that are a combination of high-intensity AND high-volume (i.e. long-duration).

Earlier studies tended to either look at EPOC following longer duration lower-intensity work or short-duration high-intensity work (such as interval training).   And the simple fact is that neither tend to cause the greatest homeostatic changes to the body: the longer duration stuff is too easy and the high-intensity stuff is too short.  In contrast, this workout had the subjects working pretty damn near their maximal steady state level (for most this falls around 170-180 beats per minute).  Anybody who has done this type of training can attest to the fact that it’s work.

Conceptually this is no different than what I discussed in the Reps Per Set for Optimal Growth where an intensity of 80-85% of maximum tends to put you in the range where you get both a high stimulus intensity coupled with a high-volume.  Higher intensities limit volume (both per set and per workout) and lower intensities don’t tend to have the stress associated with it even if you do more total volume.  Somewhere in the middle you get that maximal response where you combine high-intensity AND a high-volume.

In that vein, having done all three types of workout (long-durations at piss easy intensities, interval work of varying durations, long sessions at sweet spot), by far and away the sweet spot training is the hardest. Long duration/low intensity stuff is mainly just dull.  It’s not hard, just boring (and your butt gets sore on the bike).  The high-intensity stuff certainly hurts but the work bouts are too short for you to really suffer; the workout is over before it gets too awful.

In contrast, working for extended periods near your maximal output level is just uncomfortable as hell and the duration makes it pretty gruelling as the minutes tick slowly by.  This is even more true on a bike where the stress tends to be localized to the legs (running at this pace is a bit easier since the stress is ‘spread out’ a bit more.

That’s what this study did.  Most folks can go about an hour at their maximum steady state; this study was 45 minutes at maybe 90% of that intensity.  It’s a tough workout, most can’t do it that frequently and this would be more true if they are dieting and/or including weight training as well.  So while these study results are certainly interesting, and it’s clear that EPOC can be significant at least under the conditions tested (essentially energy balance and a hard/long workout), I find it questionable how relevant this is to real-world dieting situations where calories are lowered and/or weight training is being done.

Background

A long-held belief that has floated around the world of strength and hypertrophy training is that training legs (for a variety of reasons including hormonal) has a positive effect on either strength or size.  Many, many systems of training are based around that (including Dan John’s Mass Made Simple which I recently reviewed and others).

Previously I examined a paper that looked at this in a confusingly titled Casein Hydrolysate and Anabolic Hormones and Growth – Research Review (this was  a brief period when I was looking at two papers at once, it’s the second paper I reviewed) which, in a somewhat confusing study design found no impact of raising ‘ostensibly anabolic hormones’ (translation: testosterone and growth hormone) on size gains.

They concluded that the small hormonal pulses caused by leg training did not in fact affect growth in the arms.  I talked in some detail about a bunch of other issues related to the topic and I’d refer readers to that review rather than write it all again here.

However, a single paper (I’d note that the same group had done a second paper with identical results) isn’t the case closed answer to things; that’s not how science works.  And when another paper comes along with opposite conclusions, you have to look at all the data to see what’s going on.

Which is a, for me anyhow, fairly short introduction to today’s paper which, as you might imagine, looked at the same topic with (at least somewhat) different results.

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The Paper

Eleven untrained male subjects were recruited, aged 20-34 years, none had performed any strength training in the previous 6 months.  Two subjects did not complete the study which means that only 9 did.  The study lasted a total of 11 weeks and weight training was carried out 4 days/week with the biceps being trained at every workout.

However, each arm was only trained twice/week.  For one of the arms, the biceps exercises were performed after the subjects had performed heavy leg training.  For the other arm, arms only was trained.  Subjects were informed to ‘keep the arms relaxed’ during the leg training although I doubt this happened; folks always hold on for dear life on heavy leg machine work.

This design confused some people (check the comments section) in the previous research review and I want to explain it.  Basically the study was allowing each subject to be his own control.  That is, for all 9 individuals who finished the study, each one trained one arm after heavy leg training and the other arm without heavy leg training. This way any differences in arm size or strength gains could be attributed to the performance (or not) of the leg training rather than just to being differences between individuals.

That is, say we took two people and had one of them train arms after legs and the only one train just arms.  Let’s say that the first guy made better gains. We wouldn’t be able to say if it was due to the leg training per se, or if it was just because he had better gains (maybe the first guy would have made better gains no matter what he did).  The study design used, having each subject be their own control avoids this confound.

The researchers measured both strength gains (for biceps and arms) with 1 repetition maximum (1RM) biceps curl, leg strength was measured as 1 repetition maximum leg press.  Peak power was also measured for the biceps at 30 and 60% of 1RM.  Muscle size changes were measured using magnetic resonance tomography to determine changes in muscle cross sectional area and 9 images were taken with the final 4 being used to determine changes in muscle size (this will make more sense in a second…maybe).

Hormone levels were measured to ensure that changes in testosterone and growth hormone had actually occurred during the leg training which consisted of leg press, leg extension and leg curl. The arm training consisted of warm-ups followed by 2 sets each of biceps curl, hammer curl and reverse curl. The training was marginally periodized and started with 3 sets of 10RM and 8RM with 60-90 seconds rest in weeks 1-5 and was adjusted to 8RM and 6RM for weeks 6-10.   This note will seem out of place but the subjects were told to ‘relax the arms while performing the leg exercises’.

In terms of strength, the leg press strength went up 23%.  For the arm trained alone, the strength gains was from 39.2 to 44.7kg over 11 weeks; for legs plus arms the gain was from 37.5 to 45.3 kg so the relative improvement was greater.  It’s worth mentioning that the legs plus arms ‘arm’ started out weaker meaning they had more room to improve.  But note that the end result was only 1kg difference in maximum strength; sure it’s 20% gain vs. 15% gain but the absolute amount and the end difference is still pretty irrelevant.  Peak power increased in both the arms only and legs+arms group with no difference between them.

But what about size?  Recall from above that the researchers took a bunch of sequential photos of the arm and then looked at the final 4 to look at size differences.  And here’s where it gets confusing.  The researchers found that the size gains for arms only vs. leg+arms were identical for the first 2 measured slices but that the legs+arms group had larger gains in the last two (furthest away) slices.  I know, this doesn’t make any sense, here’s the chart.

That's so weird....

What you can see is that for Section 6 and 7, both groups made identical gains.  For sections 8 and 9 the legs+arm arm made gains and the arms only group did not.  And the results of all of this is colored by the error bars which are almost as large as the difference between groups.  I have no clue about sections 1-5 which were not reported on.

The researchers state that “ANOVA analyses revealed that both groups increased the CSA of the two proximal sections, while only L+A increased the elbow flexors’ CSA at the two middle sections, where the CSA of th elbow flexors was largest.”  Essentially, the belly of the biceps is where the difference was seen.

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My Comments

Ok, so now we have two disagreeing papers, what’s going on?    In the study described in Casein Hydrolysate and Anabolic Hormones and Growth – Research Review, training legs with arms had no impact on size gains.  In this study, there was a difference although an odd one (only part of the arm showed a differential growth) with a very very slight difference gain in strength although this is confounded by the legs+arm group ‘arm’ starting weaker.  Sure they made better relative gains but they also had more room to improve.  And although the legs+arm ‘arm’ ended up a bit stronger, the difference was a stunning 1kg (2.2 lbs) stronger.  Yippee.

First, how do we explain the discrepancy between studies?  I mean other than just dismissing whichever study you don’t agree with.

The researchers suggest that the main difference in results is in the timing of the exercises.  In the first study on the topic, the leg training was done AFTER the arm training while in this paper the leg training was done BEFORE the arm training and perhaps anabolic hormones need to be increased prior to the arm training to have an impact.  This would require further study.  Basically they’d need to repeat the study and have one group do legs + arms with legs first and the other legs+arms with leg training second to see if timing was the difference.

Regarding the rather odd regional difference in growth, the researchers simply state “..the finding of no statistical significant increase in CSA at the part of the elbow flexors with the largest CSA in A was not expected and the reasons remain unknown.”  Science speak for “I dunno.”

Here’s my actual random-assed guess.  Recall from above how subjects were told to ‘keep the arms relaxed’ during the leg training.  Have you ever seen anybody actually do it on heavy leg machine training?  Me neither.  Invariably they hold on to the machine handles with a death grip and I am willing to semi-seriously argue that the legs+arms group got a better direct arm training stimulus from the isometric work.  Please note the phrase ‘semi-seriously’ and don’t get all freaked in the comments on this one.

So what’s the conclusion of all of this?  Honestly, I’m not sure.  The difference in strength gains was minimal and I can’t make any more sense of the size gains, especially the weird differential size gains seen in different ‘parts’ of the biceps, than the researchers did.  Small group size, measurement error, just variability in all of this.  I’m sure at least one person will argue that ‘If they’d squatted like real men, there would have been a difference’ in the comments section.

Maybe a longer study would show more pronounced results.   There’s just no way to tell.   Frankly, given the exceedingly small differences in anything measured I find it hard to use this study to support the long-held idea that training legs has a systemic anabolic effect.

It is interesting to note that the subjects reported generalized fatigue during the arm training following the heavy leg work and this is a practical consideration that people tend to miss I think.  If the goal is increased upper body strength or size, training heavy legs first often takes so much out of the person that the upper body training is compromised.  Sometimes severely.

Anybody who has done the classic 20-rep squat routine can attest this, you’re usually cooked after the squat set which means compromised upper body work.  And if you want to use this study as support for the impact of leg training, you can’t say “Just train legs last” because timing may matter.

As usually I think it comes down to priorities; if your goal is optimal upper body training, tiring yourself out first with heavy leg training would seem to have as many cons as pros.  Even if the hormonal effect is improving overall gains, the impact (at least based on this study’s results) would appear to be tiny at best.

And I realize that I’m finishing up this research review without much of a conclusion.  But this paper has been making the rounds to ‘prove’ the old idea of training legs to improve upper body growth.  Certainly it adds to the body of literature (we now have two studies showing no impact of leg training on arm growth and one study showing a small effect with the difference appearing to be when legs were trained).  But too many guys have gotten huge upper bodies (go to any weight room) without ever training legs for the argument that leg training is required to make much sense.

AIM: The limited potential of exercise to induce weight loss could be partly due to the overestimation of the energy cost of exercise. The objectives of this study were twofold: 1) to investigate whether men and women are able to accurately estimate exercise energy expenditure (EE); and 2) to determine whether they have the ability to accurately compensate for the EE of exercise during a buffet-type meal.
METHODS: Sixteen (8 men, 8 women) moderately active (VO2 peak=45.4±7.7 mL.kg-1.min-1), normal weight (BMI=22.8±3.3 kg/m2) individuals, aged 20-35 years, were studied. They were blinded to two randomly assigned experimental conditions: a 200 and a 300 kcal (measured by indirect calorimetry) exercise sessions that were performed on a treadmill at the same intensity (50% of VO2 peak). At the end of each exercise session individuals were asked to estimate EE of the exercise sessions and to then eat the caloric equivalent of their estimated exercise EE from a buffet-type meal.
RESULTS: Estimated EE was higher than measured EE for both the 200 kcal (825.0±1061.8 vs. 200.1±0.7 kcal, P<0.05) and 300 kcal (896.9±952.4 vs. 300.2±0.7 kcal, P<0.05) sessions. Further, post-exercise energy intake was higher than measured EE for the 200 kcal (556.8±204.4 vs. 200.1±0.7 kcal, P<0.001) and the 300 kcal (607.2±166.5 vs. 300.2±0.7 kcal, P<0.001) sessions. Although post-exercise energy intake was lower than estimated EE, no significant differences were noted.
CONCLUSION: These results suggest that normal weight individuals overestimate EE during exercise by 3-4 folds. Further, when asked to precisely compensate for exercise EE with food intake, the resulting energy intake is still 2 to 3 folds greater than the measured EE of exercise.

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Background

Several years ago, a friend of mine (who now is of the two folks who runs Grassiron personal training here in Austin, look them up if you’re in town and want coaching) related a story of a phone conversation she’d had.  A girl had called and wanted to know how much exercise it would take to burn off a bag of M&M’s (calorie count about 270 calories).  When my friend told her the realities of it, the person asking the question apparently got annoyed and then outright angry about it.  Basically, she didn’t want to hear the reality of just how much activity it would take to burn off an exceedingly small amount of candy.

In a related vein, and this is something I’ve discussed in other articles on the site, it’s not uncommon in the least for people to drastically sabotage their own fat loss efforts by drastically overestimating the caloric expenditure from activity.   Folks will do an hour aerobics class (which really amounts to about 45-50 minutes by the time you factor in set ups and stuff) and say things like “I must have burned at least 1000 calories, I deserve a hamburger and milkshake.”  Or things of that nature.

Basically, along with many other reasons that exercise tends to have a fairly small impact on weight and fat loss (see Exercise and Weight/Fat Loss Part 1 and Exercise and Weight/Fat Loss Part 2 for a more thorough discussion), a gross over-estimation of the actual caloric expenditure from activity is one of them.

But while numerous studies have documented the degree to which folks tend to under-estimate their own food intake (a value ranging from 30-50% depending on the study and the group studied), no studies have actually examined the degree to which people overestimate the caloric expenditure from exercise. Which brings me to today’s study.

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The Paper

The study I want to review today actually wanted to examine two different, but related (and important) aspects of the issue I brought up above.  The first was the degree to which people over-estimated the actual caloric expenditure of exercise.  The second was the degree to which those same people compensated for the exercise bout in terms of how many calories they ate at a buffet type meal after the exercise bout.   They also wanted to see if there were any differences in macronutrient preference following exercise or between genders in terms of response.  Some psychological parameters were also measured but since no interaction with the actual results were found, I won’t detail them.

Towards that end, the study recruited 17 subjects (of which 16 completed the study; half were men and half were women) aged 20-35 who were ‘normal’ weight.  Body fat percentage ranged from 10% (the lowest male) to 42% (the highest female) who had only been moderately active (defined as no more than three hours exercise per week) and were weight stable for the past 6 months.

Subjects were tested for VO2 max (really VO2 peak, a distinction I won’t bother explaining here) and then put through two different exercise bouts at 50% of VO2 peak or about 65% max heart rate; this was done after they were all given a standardized breakfast meal.

The two different exercise bouts were measured (via indirect calorimetry) to burn either 200 or 300 calories and the women were tested a month apart to standardize for menstrual cycle (which can vastly impact on appetite as discussed in Impact of the Menstrual Cycle on Determinants of Energy Intake – Research Review.  The exercise bouts took on average, 28 minutes for the 200 calorie exercise bout and 44 minutes for the 300 calorie exercise bout.  So this was pretty moderate intensity exercise.

The exercise was done walking and the subjects were prevented from knowing how long they had walked (no clocks or watches could be seen) or having any way of knowing how many calories they had burned. Following each exercise session, subjects were asked to estimate how many calories they had burned, an hour later (after a shower) they were asked to consume food from a buffet type meal corresponding to their estimated exercise energy expenditure.  The chart below shows the results.

So the chart is showing the actual energy expenditure on the far left (200 calories on to the top, 300 calories on the bottom) along with the average estimated energy expenditures (825 calories on top, 896 calories on bottom) along with the actual energy intakes at the buffet meal (556 calories on top, 607 calories on bottom).  Basically, people overestimated the caloric expenditure of activity by about 4 fold while eating about 3 fold more than they burned.  But this actually doesn’t tell the whole story on the estimated energy expenditure since it’s only reporting the average overestimation.  Check this out.

For the 200 calorie exercise bout, the estimated energy expenditures, that is what subjects thought they burned ranged from 120 to 4000 calories.  No, that’s not a typo.  4000 calories. For the 300 calorie exercise bout, the range was 150 to 3000 calories.  Again, not a typo.  3000 calories.  Let that sink in, for exceedingly moderate amounts of activity, 30-45 minutes of brisk walking some of the study subjects thought they burned 3000-4000 calories.

I’d note that the researchers found no difference in macronutrient preference for the 200 vs. 300 calorie bout (no big shock there) and there was no difference between genders in terms of the response.  I’d also note that, in the discussion, the researchers discussed some of the limitations of the study.  First and foremost it was done on ‘normal’ weight individuals; whether or not it applies automatically to the obese is therefore unknown though I’d be surprised if it didn’t.

As well, whether or not a similar effect would be seen for high intensity activity is also currently unknown.   It actually wouldn’t surprise me if the effect weren’t actually larger for people performing high-intensity activity.  Contrary to what people believe, things like interval training actually do not burn that many more calories than moderate intensity activity because the caloric expenditure of the rest intervals brings the total way down. As well, interval sessions are usually far shorter; often interval sessions burn fewer calories.  But I’m not getting into the details of this here, read the Steady State vs. Interval Training series for more details.

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My Comments

In the simplest terms, this study had two major conclusions one of which we already knew about.   The first, and the ‘novel’ (at least in scientific terms) finding is that the average person probably sucks as much as estimating the actual caloric expenditure from activity as they do at estimating their actual energy intake from food.

You can see this all the time on Internet forums, people throwing out values for an hour of exercise that are simply fantasies.  They simply don’t realize that moderate activity burns maybe 5-10 cal/min (higher if you’re VERY VERY fit) so if you get 600 calories per hour you’re doing well.   Again, if you’re very well trained you can get higher values than this but well trained people aren’t usually the population we’re talking about when we’re looking at major weight and fat loss.

A secondary finding of this paper is that people still suck at estimating their actual food intake.  That is, even with their guesstimate at their actual energy expenditure, they still didn’t get close to it with their food intake at the buffet.  Recall that the subjects were instructed to consume food to balance out their guessed energy expenditure.  And they were still several hundred calories off.

Perhaps more importantly, the amount of food eaten after the activity was threefold what was actually burned during the activity itself.  As I mentioned in the background section above, this is common; people come out of fairly moderate amounts of activity thinking they’ve ‘earned’ a zillion calories and more than offset what they burned during activity.

At least one interesting thing to come out of this study was the absolutely massive variation between subjects in their estimated energy expenditure (remember it ranged from 150-200 at the low end to 3000-4000 calorie at the high end) and the researchers write:

The important inter-individual variation of estimated exercise EE likely results from the fact that some individuals have little knowledge with regards to the real energy cost of exercise and the energy value of food intake.  It would be tempting to speculate that the degree of over-estimation of the energy cost of exercise may relate to a poor exercise-induced weight loss response in some individuals.

That is, perhaps the people who get the least out of exercise in terms of weight/fat loss are the ones who drastically overestimate how many calories have been burned.  This requires further testing although it would be eminently logical.

I should finish by saying that this paper shouldn’t be taken as more ‘evidence’ that ‘exercise doesn’t work’ (though I have no doubt that some will use it as such).  Rather, people need to be educated and informed about how many calories exercise can realistically burn.  And the realities are that, except for highly trained athletes, the value is much lower than most think, hope or expect.  And certainly far less than the average person estimates it to be.

Background

It seems like I haven’t done a research review in forever, probably because I haven’t done a research review in forever.  But since I’m holding off on my little surprise until next week, this seemed as good a time as any.  Today’s paper is also something that is rather important in the overall scheme for folks seeking weight/fat loss.

Now, in the Training the Obese Beginner series, one comment that I made was that most studies have not found a massive impact on exercise in terms of increasing weight or fat loss and I outlined some of the reasons that was the case (mostly focusing on the generally low calorie burn).

That, of course raises the question

But even there, there are often some confusing things that occur in studies of exercise and weight loss, situations where the deficit created by exercise and the measured weight/fat loss aren’t the same.  That is, even where the exercise should have generated X fat loss but doesn’t.  A long-standing question has been why this is the case and there are a number of reasons for it.

One of them, of course, has to do with adjustments to the out side of The Energy Balance Equation that can occur when you perturb things; sometimes people are less active during the day due to fatigue or what have you from exercise.  This works to offset the apparent deficit.

Of course, there are other potential reasons not the least of which is an increase in food intake that occurs with exercise.  That is, while exercise can impact on the energy out side of the equation, it can also potentially impact on the energy in (food) side of the equation; the problem is figuring out which way exercise is going to impact things.

What I didn’t really address in the Training the Obese Beginner series is that, for some people, adding exercise works stunningly to generate fat loss.  That is, while the average response is often poor, averages tend to mask individual responses.  Some people do great but others do not.  Raising the question of what the individual differences between folks are.  One of those is how exercise impacts on appetite and hunger.

Until I write another overwritten series on the topic, simply realize that there can be a hugely variable response in whether or not someone gets appetite suppression (through physiological or psychological means) from exercise or an actual increase in activity.  Clearly, in the case where calories are not being controlled, if exercise causes someone to increase their food intake (for either psychological or physiological reasons), the predicted weight/fat loss will not occur.

And that brings us to today’s paper.

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The Paper

The paper wanted to address the question of why the obese don’t lose more weight in response to exercising by looking at how changes in the reward value of food changed with exercise; the basic assumption being that folks who showed a larger increase in the reward value of food would be more likely to overeat foods following exercise.

In looking at this, forty sedentary overweight and obese individuals (13 males, 27 females) with an average BMI of 31.03 and age of 39.3 years were recruited from a larger 12-week exercise study. The researchers examined the acute impact of exercise on the reward value of food before and following a 12-week supervised exercise program.

To assess food reward, the subjects were shown 20 pictures of foods varying in taste and macronutrient properties which were categorized according to sensory domain (sweet or non-sweet) and fat/carbohydrate content (high/low). Subjects rated the subjective reward value using a visual scale based on liking, wanting and preference.

I won’t detail this because it’s boring and uninteresting.  Results were tallied for each of the four food categories (high-fat/non-sweet, low-fat/non-sweet, high-fat/sweet, low-fat/sweet) to see if there were differences in changes in reward for different types of foods.  The foods were rated immediately before and after a single exercise bout (to see if exercise impacted on reward value) and both initially and 12-weeks later (to see if there were any long term changes).

Subjects were subjected to a 12 week exercise program where they burned 500 cal/session 5 days per week for a total of 30,000 calories over the total study length.  Weight loss was assessed and subjects were divided into responders based on their actual weight loss.

Only 34 of the original 40 subjects finished the study and of those there were 20 responders (6 of whom were males) and 14 non-responders (7 of whom were males) and the individual variability in net energy balance (based on measured weight loss) was massive (see graphic below).

Variability in Energy Balance

Subjects below the zero line were those that lost the expected amount of fat or more (based on estimations of the energy values of body fat and muscle) and were termed responders; those who are above the zero line lost less weight/fat than predicted and were termed non-responders.  The average responder lost nearly 5kg (10+ lbs) over 12 weeks, the non-responders a mere 1 kg (2.2 lbs).

And, as expected, there was a clear correlation between the actual changes in fat mass and the changes in reward value of foods.  The non-responders fairly consistently demonstrated a different response in terms of reward value for foods following activity with the largest impact being seen for (drum roll please) high fat and sweet foods.  In contrast, the responders showed either no significant response or a slight decrease in the reward value of the different categories of foods.

I’d note that after 12 weeks, even in the non-responders there was a difference by week 12, while they still showed a greater response in terms of reward value following activity compared to the non-responders, the effect was blunted compared to at the beginning of the study.  Something had changed in the physiology of the non-responders; it wasn’t eliminated mind you but the effect was blunted.

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My Comments

Clearly the results of this study (which I’d note fit into a previous data set showing that exercise tends to either have a neutral or increasing effect on food reward; it rarely has a negative effect) indicate one potential reason that exercise is either ineffective for weight/fat loss or, if not ineffective, shows such variable responses.

Clearly some people add activity to their regimen and lose fat/weight just as expected; others are frustrated.  And while there are other reasons that might cause this to occur, clearly an increase in food intake (and especially high-fat/sweet foods) would be a real problem.  Of course, this is only a real issue under conditions where calories/food intake isn’t being controlled.  Which is the condition that a lot of exercise studies are tested under.

Of some interest is that the impact of exercise on food reward is blunted after 12-weeks although it doesn’t appear to go away completely in the non-responders.  I actually mentioned in the Training the Obese Beginner series that I had often seen an increase in hunger in the first few weeks of exercise but that often switched itself as adaptations started to occur.  Clearly something may go on with long-term activity in terms of reprogramming some aspect of physiology.

If anything else, I think this study points out, yet again, that exercise is no magic pill for fat loss.  Clearly for some people, those who don’t find an increase in their hunger and liking for high-fat/sweet foods, exercise can work wonderfully even in the absence of explicit calorie control.  Since they don’t increase their food intake from high calorie/high-fat/sweet foods, they don’t get into trouble.   But for others, those who get an increase in the desire to eat such foods, there’s a problem.  Even if they don’t realize it, their increased desire for such foods will likely end up causing them to eat more after exercise sessions, eliminating the exercise induced deficit.  Results will be poor and they are likely to quit.

In that situation, either a diet that allows such foods in controlled amounts (e.g. a flexible dieting approach or something like Martin Berkhan’s Leangains) to be consumed or simply the realization that uncontrolled eating will cause problems has to happen.  Clearly left to their own devices, their bodies are causing problems.   They’ll have to find a workaround or count/control their food intake (at least until they stop getting such a pronounced effect).

And tune in next Tuesday for my surprise….

PURPOSE OF REVIEW: Update recent advancements regarding the effect of high-animal protein intakes on calcium utilization and bone health.

RECENT FINDINGS: Increased potential renal acid load resulting from a high protein (intake above the current Recommended Dietary Allowance of 0.8 g protein/kg body weight) intake has been closely associated with increased urinary calcium excretion. However, recent findings do not support the assumption that bone is lost to provide the extra calcium found in urine. Neither whole body calcium balance nor bone status indicators, negatively affected by the increased acid load. Contrary to the supposed detrimental effect of protein, the majority of epidemiological studies have shown that long-term high-protein intake increases bone mineral density and reduces bone fracture incidence. The beneficial effects of protein such as increasing intestinal calcium absorption and circulating IGF-I whereas lowering serum parathyroid hormone sufficiently offset any negative effects of the acid load of protein on bone health.

SUMMARY: On the basis of recent findings, consuming protein (including that from meat) higher than current Recommended Dietary Allowance for protein is beneficial to calcium utilization and bone health, especially in the elderly. A high-protein diet with adequate calcium and fruits and vegetables is important for bone health and osteoporosis prevention.

Background

For decades now, it’s often been thought, felt or claimed that a high dietary protein intake had a detrimental effect on calcium metabolism and bone health; certainly many groups promoting low-protein dietary approaches tend to echo/parrot this idea.

This idea came around in the mid-20th century but was based on some, shall we say, questionable research.  In it, totally purified proteins were given (that is, no other nutrients were present) and a loss of calcium in the body (in the urine) was documented.  It was simply assumed that this had a negative impact on bone health.

Despite later research showing that it was much more complicated than this (i.e. that proteins containing other nutrients had different effects and that other parts of the diet played a major role in the overall effect), this idea is simply repeated as if it were still unquestionably true.  I dealt with this issue to some degree in The Protein Book, in a chapter called Protein Controversies, which is reproduced here on the main site.

As well, there has long been a secondary data set (seemingly ignored by anti-protein folks) showing that higher protein diets actually IMPROVE bone healing following things such as breaks or fractures.  Clearly the idea that ‘protein is bad for bone’ is a bit more complicated than just a soundbite.  The review paper I want to look at today examines the topic in some detail.

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The Paper

The paper begins by pointing out that bone is over 50% protein to begin with and that there has long been concern that the modern Western diet is detrimental to bone health due to the production of acids within the body.  This is something I imagine readers have at least seen mentioned in recent years (I get the occasional question about it) with some going so far as to claim that the body’s pH is THE KEY to all health (some even claim that a drop in cellular pH is the cause of cancer).

While it’s not quite that cut and dry, clearly the modern Western diet tends to promote the production of metabolic acids and at least some degree of metabolic acidosis.  This is due to a number of factors including a high protein intake (proteins are acid promoting), insufficient fruit and vegetable intake (both of which are net base producing for the most part), along with other factors such as sodium and potassium balance (excessive sodium intake relative to potassium can increase the acid load of the body).  You can find long lists of foods online in terms of their net acid or base producing potential.

And certainly, as discussed briefly in Protein Controversies, acidosis can cause problems in the body.  It’s relevant to today’s paper in that the body appears to buffer this acid load by releasing calcium, presumably from bone.  In that current research is suggesting that the RDA for protein is actually too low for some populations (notably older individuals) and with the current interest in high-protein diets for weight/fat loss and maintenance, it’s important to know whether or not these dietary approaches are having negative impacts on bone health.

The paper looks in some detail at the issue of acid/base balance and calcium metabolism. As noted above, the generation of metabolic acids causes a number of effects in the body, all of which could potentially impact negatively on calcium metabolism and bone health.  As well, studies clearly show both that:

1. The generation of metabolic acids causes increased calcium loss in the urine
2. Counteracting acidosis with base-forming minerals (e.g. potassium bicarbonate) decreases calcium excretion

While the above is clear, the direct impact of dietary protein on bone health is a bit less clear with the results of more direct epidemiological data showing mixed results in terms of the actual impact on bone health.  As well, citing a review by Fenton, the paper points out that:

…neither calcium balance nor the bone resorption marker, N-telopeptides, was affected by diet-induced changes in net renal acid excretion despite a significant linear relationship between an increase in renal net acid excretion and urinary calcium.

That is, while it’s clear that increased dietary acid load causes increased urinary calcium excretion, it’s less clear if this has any real direct impact on the body’s net calcium balance or overall bone health.

Moving on to more direct effects, the paper looks at the very old data (using primarily purified proteins) showing that for every increase in dietary protein by 1 gram, there was a 1 mg increase in urinary calcium loss (raising the question of why not simply scale calcium intake to protein intake to offset this); this led to the assumption that bone health was being compromised.

However, in direct contrast to this, the majority of epidemiological studies find that a higher protein intake is associated with increased bone mineral density with only a few finding a negative impact.  As well, while weight loss per se tends to cause a decline in bone health, some research has found that high-protein weight loss diets reduce the loss of bone mineral content; that is, high-protein intakes on a diet are beneficial.

The primary acid formation from protein comes from the sulfur containing amino acids (cysteine and methionine) and these are found in higher amounts in animal vs. vegetable proteins; it’s often been assumed that a higher vegetable protein intake would therefore have less of an impact on bone health.

However, this also turns out to be incorrect; the paper points out that studies of high-meat protein intakes either show no overall effect on net calcium balance and a higher animal protein intake is actually associated with increased bone mineral density; as well studies show a negative association between vegetable protein and bone mineral density.

It’s worth noting that strength/power athletes, who have traditionally consumed a high-protein diet are typically found to have higher bone densities compared to sedentary individuals.  As the paper points out:

Changes in bone mass, muscle mass and strength track together; thus maintenance or an increase in muscle mass and function maintains or enhances bone strength and mineral density.

And while the increase in urinary calcium excretion with increasing protein cannot be simply ignored, current data suggest that this isn’t actually due to a loss of bone mass.  Rather, increased protein intake leads to increased calcium absorption from the gut; the loss in the urine is simply due to more calcium being absorbed.   The increased loss is simply due to more being absorbed from the diet; interestingly, this effect is more pronounced when calcium intake is low to begin with.

In terms of mechanism, higher protein intakes raise levels of the hormone IGF-1, which stimulates bone formation; this probably explains the benefits of a high-protein intake on bone healing.  As well, high protein intakes have been shown to decrease levels of parathyroid hormone (PTH), a hormone that is involved in the loss of bone mass.  Low protein intakes are associated with increased PTH and lowered bone mineral density.

Finally, as I mentioned in the introduction, you can’t simply look at protein intake outside of the rest of the diet and there are clear interactions with other nutrients.  I mentioned above that protein intake interacts with calcium intake, increased absorption.  As well, a high protein intake has been shown to increase bone health in older individuals when calcium and Vitamin D are supplemented.  Finally, ensuring a sufficient intake of fruits and vegetables (which neutralize the acid load of protein) should help to ensure the impact of dietary protein on bone health is positive rather than negative.

Summing up, the researchers conclude thus:

Although a high meat or protein intake increases renal acid load and urinary calcium excretion, recent findings do not support the claim that bone is the source of the extra calcium lost in the urine.  In addition, evidence is lacking that shows high-protein intakes, including that from animal sources, affect whole body calcium balance or contribute to osteoporosis development and fracture risk.

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Summing Up

I don’t have a whole lot to add to the above conclusion.  Clearly the negative impact of dietary protein on bone health would appear to be overstated to some degree. Under certain circumstances (low calcium/Vitamin D intake, insufficient intake of fruits and vegetables), it’s certainly possible that a high-protein intake could have negative impacts.  But again this comes down to an issue of context.   And in the context of sufficient net acid neutralizing foods (fruits, vegetables, sufficient potassium intake) along with sufficient calcium/Vitamin D intake, the impact of protein on bone health would appear to be positive overall.