Evidence-Based Fitness

With change comes disruption

2012-01-08T11:15:00.000-07:00

Today, I decided to integrate this blog a little more with Facebook. Unfortunately, it means that pre-existing comments weren't compatible. I apologize to those of you who have taken the time to leave comments here, and welcome new and re-posted comments! The comments aren't lost; they're just hidden. If there's a way to nicely integrate them, I'm all ears!

Burn the boats: Why you're going to fail. Or not.

2012-01-02T14:42:00.000-07:00

I've been studying and reading health research for decades, and this post is just a bit of my biased gestalt on the state of affairs on obesity, obesity research and the new hope that arises within a TON of people every January.

The preponderance of obesity research indicates that most of you will fail at achieving your goal of weight loss this year; and that of those of you who succeed at achieving the goal within this particular year will ultimately fail because the data generally shows that the weight comes back, resulting in a net effect of zero. What we don't fully understand still, is why this failure happens; and I'm not sure that we're going to truly unearth it anytime soon enough to make a difference in your resolution this year.

The evidence, in short, is incredibly depressing.

However, this is one of those situations in which I think anecdotal evidence has a powerful and important role to play because it provides a very vivid counterpoint to the darkness of sample-based research evidence on predicting your future. What's even more interesting about these anecdotes is finding the common themes within these narratives that highlight the elements of success, many of which cannot be replicated in a study or even reliably sampled because they cannot be truly measured.

Success in weight loss or any self-improvement goal depends mainly on the ability of a person to adhere to a new behaviour. Quitting smoking is a good, simple example (albeit of a very difficult task): You succeed at quitting smoking by engaging in behaviours that do not involve smoking. Do or do not, there is no try. Taking a drag on a cigarette means you've relapsed and are no longer an ex-smoker.

Weight loss is not as simple of a goal. It can involve multiple behaviours, many of which involve changing substantial portions of one's day from both a time and a performance perspective. For instance, beginning to exercise is a behaviour that requires time investment. That means exercise has to DISPLACE another activity that you've grown accustomed to doing. Eating less or eliminating certain foods means the performance of eating changes. And then on top of it all, there's the social dimension of weight loss, which can mean displacing perfectly enjoyable activities that not only provide nutrition/caloric value but also contribute substantially to our sense of well-being and belonging (e.g. a weekly pub night, or after-work drinks and appetizers, or Sunday dinner with parents.)

The most common theme I've discovered (and this is, in and of itself, just opinion and anecdote) from watching patients attempt to enact lifestyle changes and reading stories of people who have had overwhelming success, however, comes down to something perhaps equally as unpleasant as making a lifestyle change that you've failed at in the past: pain, and sometimes, fear. Unfortunately, this is, thus far, a fairly immeasurable quality, so making causal associations between pain/fear and dietary success is fairly difficult, though, with the right research team, not impossible.

When it comes to adherence to new behaviours, (and I'm not sure this has even been studied at all yet, in the way that I'm going to state it), is the introduction of a situation in which the pain of staying in the same place (or moving backwards) becomes so great that success is the only option. I have personally witnessed (though with limited verifiability) patients who, after suffering a serious hand injury that would affect their ability to earn a living, stopped smoking the day of the injury. These were people who had tried to quit in the past unsuccessfully and years later, are still smoke-free, even though the danger of affecting their hand function by smoking is pretty much gone.

In medical school, we're taught to try to find reasons for patients to change their lifestyle. Sometimes, it's an injury or a new diagnosis. Sometimes, it's being around for their loved ones. In most circumstances, it's the pain of the situation, or the pain of the fear that ultimately moves people to action.

Personally, I think that the reason why most people fail at their goals is because it's really not that painful to fail. If you fail, you'll get over it. Your waist size doesn't change, or it might even get a little bigger, but on the whole, your life is pretty good. There is a famous story of Alexander the Great, who upon landing on the shores of Persia, ordered his men to burn the boats, thereby removing all realistic hope of retreat. If your income was contingent on your ability to stay at a certain BMI, regardless of your beliefs about the BMI and whether you are an "outlier" or not, you'd get there and stay there. You would find a way to stay there. You might bitch and complain about it, but given the option of unemployment or BMI, my guess is most people would pick BMI. In a way, it's no different than doing your job. If you don't do your job, you get fired. Come hell or high water, when crunch time comes, you'll find a way to get that job done because you know the personal stakes are high.

Finding that intolerable state is what motivates successful change. Eventually, you may come to enjoy the new life you've created. I can't think of a single ex-smoker who regrets quitting smoking. I can't think of a single person who, after successfully losing weight and keeping it off, regrets making sweeping changes to the way they live. They tell me that the process of quitting/changing really sucked, but that they would never trade their old life for their new one. One patient of one of my mentors, after quitting smoking, kept putting the money he spent on cigarettes in a large jar. A few years later he bought a massively expensive sports car (I can't remember the make/model), which he enjoys far more than any cigarette he ever smoked (or so he tells me.) It doesn't mean you have to live a painful life forever. But enacting change without consequence of failure, I think, is embarking on a journey to which there is always a convenient exit.

So, as unpleasant as it is to contemplate, my challenge to those of you serious enough to take it, is to find that pain. If that means making your life intolerable to failure, then perhaps that's not a bad approach. Find ways to put yourself in situations where getting out is more painful than staying in.

It's 2012. Find your pain. Burn the boats.

For slightly more positive tips on lifestyle changes, here are some my previous posts, or you can click the "lifestyle change" tag in the cloud on the right:

Death by sand: When do the fine details really matter?
Defending yourself against decision overload
The Information Diet
Fitness, nutrition and a Peruvian fruit stall

Twenty three and a half hours

2011-12-10T08:28:00.001-07:00

I love this video. Most of my readers do more than 30 minutes, but let's say you can't get to the gym, or you're injured. Or you're just not in your workout groove. There's making gains, which is what we're always trying to achieve, but sometimes, you have to take victory during times of stress to just not go backwards. So if you do nothing else, know that 30 minutes a day is positively associated with many benefits.

Toe-ing the line: What I think about this whole shoe thing

2011-11-21T14:30:00.001-07:00

Oldest discovered leather shoe: 5500 years old

I've had a few emails asking me to review some of the literature on the new shoe trend. Every company is jumping on the bandwagon to create their version of the Vibram five TOE shoes (sorry, I'm going to be a hand and wrist sub-specialist. Toes are NOT fingers). It's a little reminiscent of the "body-toning" shoe thing, without all of the wildly outrageous claims, and a trend that I think will live long enough to warrant weighing in on. Most studies to date have really focused on how the shoes alter foot and gait biomechanics. I would argue that most of the claims on the Vibram website are still largely unsubstantiated or just what I call "motherhood statements", like: "Eating your greens is good for you," and "Puting on your jacket when it's cold outside is good for you." (basically, statements that don't really have any clout one way or another, but just make you feel better.)

The claims (according to their website) are that they:

1) Strengthen your foot and lower leg muscles
2) Improve range of motion in your ankles, feet and toes
3) Stimulate neural function for improved balance and agility
4) Improve posture by removing heel lift, which aligns the spine
5) Allow the foot and body to move naturally

Oddly, the Vibram website also recommends that you consult your physician or a medical professional to see if natural running in their shoes is right for you. I'm pretty sure most physicians have about as much knowledge on running and gait biomechanics as I know about dark matter (that is, to say, I'm sure someone knows a lot about it, but I don't know who and I sure as hell wouldn't know if I saw it.)

In terms of possible running benefits, we know that barefoot running does tend to produce a gait that strikes more in the mid foot than the heel. Interestingly, this is the same gait change that Masai Barefoot Technology shoes (which then evolved into the rocker toning shoes) sought to achieve with a distinctly different approach to shoe design.

In a culture of increasing complexity and options in almost all dimensions of life, there is a counter-culture of minimalism, and also "naturalism" that has also sprung up. The Paleo diet is an excellent example of going back to "evolutionary roots", and using retrospective vision to justify evolutionary arguments.

There are two main points I want to make about the new shoe issue:

1) "Everything works. Nothing works forever."

I don't know if Alwyn Cosgrove came up with this on his own, but he's the one I remember saying it, so I'm going to credit him for it. It is only in the past year that the five-toed barefoot shoe trend has really caught on. Epidemiologically speaking, we're going to experience "lag-time bias" when it comes to evaluating the effectiveness and "safety" of these shoes. The number of early adopters was small compared to the number of projected users to come before the trend hits a peak. Therefore, the number of injured individuals is going to be tiny until the denominator hits a critical mass for a pattern of injury to become apparent. It's also going to take time for the "barefoot injury" to appear since it's going to emerge only after prolonged chronic use. "Nintendo thumb" didn't become apparent until well after the first generation Nintendo console had been produced. It took millions of kids hundreds of hours to develop a cohort big enough for medical professionals to make the association, and then the _causal_ association.

Barefoot shoes change your gait. There's no dispute on that. If you have a chronic injury that is somehow linked to your gait or your posture in your non-barefoot shoes, then changing your gait or posture is going to make your injury feel different. It's great that the general trend is that these chronic issues tend to feel better in barefoot shoes, but I like to think of it as being similar to putting a knee in a brace. Sure, your knee feels better in the brace, but that doesn't mean your knee is any better off for it.

Do I think barefoot five-toed shoes are harmful? Not in the immediate term. Do I think that in the next few years, there will be at least a few epidemiological studies on injury patterns associated with barefoot five-toed shoes? You betcha.

2) Evolution doesn't necessarily proceed in a beneficial direction.

One of first things a biology undergrad has to learn is to let go of the idea that evolution is always making things better. It's easy to look backwards in time at a giraffe and say, "Well, of course the longer neck is a survival advantage because it allows giraffes to exploit a food source," when in fact, there could have been a whole genetic start-up of longer necked pigs that never made it to the present day, or into the fossil record because there weren't many trees in their habitat. To say that the human foot has evolved to run bare has similar pitfalls, and to state that the human foot is _meant_ to run barefoot is a La Brea tar pits full of pitfalls.

Evolving to run barefoot assumes that running provided a survival benefit; and while we all have been fed romanticized notions of hunters stalking and chasing prey and escaping vicious wild predators, I would posit that in fact, the evolutionary pressure on ancestral man was not to run, but rather to survive. Running towards or away from something is merely a single factor in successful survival. Successful _hiding_ could arguably be just as important as running; and you don't need special shoes for that.

Lastly, there is no question that human behaviour is influenced by technology. The idea that behaving "au naturel" is the best way probably has more to do with our own romanticized ideas of battling increasing technology and further "evolution" than it does with figuring out what's "better". Even if feet were meant to run bare, there's nothing that says that it's the best way to run any more than there is anything behind the statement, "The best way to see is without glasses," or that, "Cold weather is best experienced without clothes."

When it comes to lifting, I think similar arguments apply, with the additional caveat that minimal-sole shoes with no toes are probably just as good. I'm not entirely convinced that the stiff sole allows for much independent toe movement, or that independent toe movement is actually that pivotal to performance or injury prevention. I'm not trying to paint all toed-shoe-users with the same brush (because some of them are my very good friends) but there's something disconcerting about seeing a guy squat in Vibrams with 10-pound plates under his heels.

So in the end, I don't think barefoot five-toed shoes are better than conventional shoes. I think they're just different. If they're a good motivational tool or a psychological support for you, then it's probably worth your investment in them. Likewise, it's probably not a bad thing if they're relieving chronic symptoms--even if there's probably a different host of aches and pains that we're going to read about in the future. But I think their contribution to your success as an athlete, a weekend-warrior, a marathon runner, or just a joe at the gym trying to lift heavier things without getting too injured is tiny compared to the other factors that are probably in play. Wear' em if you like, but don't feel like you're missing out if you're not.

P.S. This Thursday, November 24th is Evolution Day, the anniversary of the publication of "The Origin of Species" Happy Evolution Day!

What will your legacy be?

2011-11-14T08:35:00.001-07:00

There are a lots of things we take for granted. In medicine, this is highlighted every day. It's not just walking or the ability to do things, but also even basic life functions like eating, talking, and breathing; and some cases, just appearing "normal". There are days when I'm just happy my patient has a regular heart beat--I'm not even shooting for independent breathing or even independent blood pressure.

The reality is that if you're reading this, and any part of this blog, you're fairly healthy, mobile, and possessed of your mental faculties enough to read. You have the ability to enact change in your life. If you're sitting on the fence, you're choosing to sit there.

Fitness,working out, dieting--these are all luxuries. They are all choices you are allowed to make because you have food abundance, the economic means to choose, even the mysterious privilege to have been born in an environment that has afforded you technology, education and health care. Each day that you don't take full advantage of these opportunities is a day that is squandered potential--even if the opportunity you're supposed to take advantage of is rest (which is, in and of itself, a luxury.)

I have come to view the opinion that you should live your life as though each day is your last with mixed opinions. I like the underlying message of seizing the day like it's your last one, but it's really hard to live each day that way. There are certain realities and responsibilities that we have already chosen to commit to, and while it's a great idea to plan your escape strategy if you're not doing what you really want to do, the dirty laundry isn't going away in the event you don't die before tomorrow morning.

For another, I think most of us would live our last day in a fairly self-centered fashion. My last day would presumably be filled with all of the things _I_ would want to experience as the last earthly sensations of my existence. I probably wouldn't go to work. And the day would very much be about me. Maybe I'm selfish that way. I confess to having days where I get caught up in the day-to-day, and that it takes moments of reflection for the extraordinary-that-has-become-ordinary to become extraordinary again. But I was lucky enough to have a life-changing experience 2 weeks ago on my first mission with Operation Smile that was so phenomenally powerful that the way I look at the world and my role in it will never be the same again.

Today is the launch day of Brian Grasso's short film, "Life By Numbers". It's a powerful piece asking you to challenge your life. I usually keep my blog endorsement-free to avoid bias, but I think everyone should see this film at least once. I also want to take things one step further, because I think it's not enough to take the courage to pursue the dream you've always want to chase. I think that while you're contemplating what it is you REALLY want to do with your life, it's worth also considering what difference you can make for others who dont't enjoy your position of privilege, and the creation of YOUR legacy.A great body is something we are all lucky enough to have the chance to shoot for and is, in my opinion, a noble pursuit, but what do you want to be remembered for?

What price would you pay for muscles?

2011-11-09T11:43:00.000-07:00

Not everyone works out for performance. I would count myself amongst the folks who work out basically for looks. There was a time when I lifted to get better at my sport, but the reality is that my career and most of my current hobbies don't require me to perform at a much higher skill level than sewing two hollow tubes about 1mm in diameter together, which clearly doesn't require heavy squats to improve.

This entry's article came to my attention from Ryan Zielonka, who wrote,

"Quick question for you. I work out to look good, period. I'm also blessed with a full and thick head of hair. I recently started taking creatine (again, I've never been particularly consistent) and came across some anecdotal evidence as well as one study that shows the potential for hair loss while using creatine.

What are your thoughts on this? I'd hate to sacrifice my full head of hair for just a slight uptick in swoleness."

This is a perfect example of trade-off decision making, which, for the most part, is the central issue in most medical decision making. There's no question that every intervention, fitness or medical (which I think are one and the same, personally) carries risk and benefit. We choose to pursue an intervention based on whether we think the benefits outweigh the risks. Is it worth exposing your wrist to pain, a scar, the possibility of infection and the possibility of no improvement for the chance at getting rid of your carpal tunnel syndrome? Is the risk of injury, and the cost of time, discomfort and (to some extent) denial of "junk food" worth it to perform better or to look better?

Creatine has been shown to have many benefits, not the least of which are performance-related as well as aesthetic. We still don't understand how creatine makes these benefits possible and there are several theories, none of which are truly dominant as to why it works. But what if one of these theories was true and what if the trade-off for using creatine for its benefits meant some form of hair loss? Would this change your decision to use it or not?

van der Merwe J, Brooks NE, Myburgh KH. Three weeks of creatine monohydrate supplementation affects dihydrotestosterone to testosterone ratio in college-aged rugby players. Clinical Journal of Sport Medicine, 19:399-404, 2009.

Introduction:

As much as I agree with the statement that the long-term safety of creatine supplementation has not yet been established, I don't think that the question is going to be answered in my lifetime, but that doesn't mean that we should stop studying it.

There are a few theories as to how creatine improves performance, but none have really emerged as dominant so far. One of these theories is that creatine somehow affects the production of testosterone. Testosterone can be converted to dihydrotestosterone (DHT) which is a more bioactive androgen (i.e. it takes less to have the same effect). It isn't known whether creatine has an effect on DHT production and whether THIS might be one of the mechanisms by which creatine produces the observed effects that it has.

Although DHT is a more potent androgen, it is also linked to other conditions such as baldness (alopecia), male-pattern baldness as well as prostate hypertrophy. Understanding whether creatine alters DHT levels, therefore, has relevance not only in figuring out how creatine works, but also in determining whether long-term use may have other, possibly unwanted consequences.

Methods:

The design of this study was a randomized controlled cross-over design. So, each of the subjects was randomly assigned to receive either a placebo or creatine first, and then after a 6-week washout period of taking neither placebo nor creatine, were given whatever they didn't have in the first phase.

The method by which the subjects were randomized is not one that most trialists would condone: Subjects were given a number based on the order in which they arrived for initial testing. Odd numbers were assigned to one group, and even numbers to the other. Twenty subjects were recruited in total, but the study was only done on 16, due to 4 drop-outs.

The subjects were all 18-19 years old, male rugby players in their competitive season.

The total supplementation period was 21 days. A 7-day loading phase (25g per day) followed by the maintenance phase (5g per day) was used. Creatine was taken with glucose (25g). The placebo group got the glucose with no creatine. It's not mentioned who was blinded in this experiment, only that it was "double blind". The creatine and placebo were given in capsules.

In terms of training and diet, these athletes were all part of an institute and therefore trained together (for their positions) and ate together.

Body mass, and skin folds were measured for Day 0, 7 and 21 for both phases of the study. Blood samples were drawn on day 0, 7 and 21 for serum testosterone and DHT.

Comparisons were made using ANOVA's for repeated measures with post hoc Tukey tests for significant ANOVAs. They did do baseline statistical comparisons, but I've bitched enough about how this is inappropriate, particularly for a cross-over trial.

Results:

None of the body-mass or skin-fold measurements changed substantially at the 7-day or 21-day points. This included percent body fat as well as fat-free mass.

Testosterone levels did not change substantially for either the placebo or the creatine phase at any time point. However, what did change was DHT levels. These levels were higher in the creatine phase at both day 7 and day 21, with the day 7 level being higher.

The baseline DHT level for the creatine phase was 0.98 (SD 0.37). At day 7, this rose to 1.53 (SD 0.50) and then fell at day 21 to 1.38 (SD 0.45). These increased levels were statistically significant. As a result, the DHT:T ratios were also higher and statistically significant.

What's interesting is that the baseline DHT level for the placebo phase was 1.26 (SD 0.52). More on this in the discussion area.

Discussion:

Most of the discussion of this article centred around the potential health effects of increased serum DHT.

I think my only major grief with this study is that they reported that DHT levels were 56% higher after 7 days, and then 40% higher than baseline after 21 days on creatine. But the baseline level of DHT in the placebo phase (i.e. the mean level of DHT in the SAME subjects on day 0 of the placebo phase) was 1.26 (SD 0.52). When compared statistically, the DHT level at day 7 was only 21% higher than this baseline, and not statistically significant; which then begs the question as to whether the variability of DHT (either as normal variance in the assay itself, or as normal physiological variance in 18-19 year old rugby players) is high enough that the increased level of 1.53 is meaningful.

However, this issue is not only a good example of trade-off decision making, but it's also a great example of how a single study isn't always enough to put a particular issue into an appropriate context. Yes, the study shows an increase in DHT. Yes, increases in DHT are linked to male-pattern baldness, but I think it's important to note that the study cited in this paper whose purpose it was to investigate DHT and baldness show that even at the highest levels of DHT measured in these rugby players, the association with male-pattern baldness is not very strong.

In the cited paper (Bang et al, Comparative studies on levels of androgens in hair and plasma with premature male-pattern baldness, Journal of Dermatological Science, 34:11-16, 2004), the median level of DHT in males (aged 26-43)with premature baldness was 2.8 with a range of 1.99-4.88. The range of DHT in males without premature baldness was from non-detectable to 2.74 with a median of 1.20 (aged 25-27). Mind you, these are DHT levels in the HAIR itself, not serum concentration levels (which were published in ng/ml, not nmol/L--the units used in the creatine study) so comparison is tricky.

It's impossible to know whether taking creatine will make YOU go bald prematurely if your baseline DHT levels are hanging out in the grey zone of "just short of going bald" unless you know what your baseline DHT levels actually are. It's also impossible to know whether these rugby players' DHT levels at age 18-19 are compatible with the levels that would have been observed had the baldness researchers measured their prematurely bald subjects at age 18-19 (i.e. we don't know which of these 16 rugby players is going to become prematurely bald).

However, it would appear that despite elevated levels of DHT in the serum of rugby players aged 18-19 after 7 and 21 days of creatine supplementation, that the elevation is not likely to correlate with those levels that one could deem necessary to produce male-pattern baldness. There's also a fair amount of overlap in DHT levels between males who did have male-pattern baldness and those who didn't in at least two studies examining the issue; so elevated DHT is probably not the ONLY causative factor in the case of whether you'll go bald or not.

Bottom line: If you're going to go bald, it's probably inevitable. It seems unlikely that taking creatine is going to be the thing that tips you over the edge into Cueball-world (if you're even hanging out at the edge that is). I, for one, will continue to take creatine for what that's worth.

Why isn't overeating an eating disorder?

2011-10-10T08:00:00.000-06:00

My very first peer-reviewed manuscript was back in the early 2000's, and wasn't a study. It was a discussion paper comparing anorexia nervosa to a new proposed psychiatric disorder which was to be named, "Muscle Dysmorphia". This proposed disorder was popularized by the book, "The Adonis Complex" in which the authors suggested that an emergent pattern of disordered thinking was becoming more prevalent amongst men. This disordered thinking was defined as the preoccupation that one was not muscular enough, and manifested itself in obsessive-compulsive-like behaviour (e.g. compulsion to go to the gym, or significant distress when one was not able to go to the gym) as well as possible self-harming behaviours, such as not participating in social activities because of one's workout or diet routine, or use of anabolic or other performance-enhancing drugs for the purposes of getting more muscular (I'm not going to debate whether taking anabolic steroids is considered "self-harm" behaviour; it is, however, an example of such in the proposed criteria.)

My position on the proposed "Muscle Dysmorphia" remains unchanged. I do not feel it belongs in the DSM in its current state, largely due to the subjective criteria for its proposed diagnostic criteria, which depends entirely on whether the diagnostician feels the patient is already "muscular enough".

However, recent events got me thinking back to my original manuscript. I had originally written the first incarnation of the paper in my undergrad when I took a life-changing course in my final year entitled, "Critical Issues in Medical Epistemology" in which we examined the social construction of disease from a historical point of view. At the time, the first papers on "muscle dysmorphia" had not yet been written, so I had written about what I also thought was an emerging phenomenon which had casually been referred to as "biggerexia", or "reverse anorexia" in some of the popular and sparse academic literature.

Epistemology is the study of how we gain knowledge. By social construction, I'm referring to how a disease entity evolves to become "known"; not just from its biological origins and cluster of symptoms and signs, but inevitably its assigned "source". Broadly speaking, sources come from "within" and "without". For a few years before HIV was isolated, AIDS was thought to be a disease that came from "within". Now, we largely think of AIDS as being caused by an external agent, though there is still a small group of scientists that believes otherwise.

In January of this year, I decided to commit to a physical transformation. During my transforming time (arguably, I am still transforming), what struck me as remarkable was the kinds of comments people around me gave me. Many were complimentary, which was flattering, but some alluded to the idea that I wasn't behaving in a healthy manner. "You're wasting away," was a common one. And because I work in an environment where I am quite close to my colleagues, people noticed when I was fasting, and commented that it wasn't healthy. This experience has been reported by many of my fitness colleagues and their clients as well (though, this is all anecdotal.)

While we recognize obesity as a health problem today, what strikes me as odd is the fact that there has been virtually no "pathologicalization" of the behaviour of overeating (other than "food addiction" which is a whole other topic--Can you, in fact, be addicted to a substance you need to survive?) We are, in fact, more likely to label undereating as disordered than we are overeating. Overeating is, in fact, culturally sanctioned in North American culture, particularly around social events and holidays. It is even celebrated (admittedly, "Man vs Fasting" just doesn't have a sensational pitch behind it.) Undereating is part of some religions, but is largely sporadic, with some exception of some religions advocating weekly or annual, or seasonal fasting. It is otherwise, not that socially acceptable to eat less, or to simple occasionally not eat at all.

However, if we examine overeating as a potential pathological behaviour, it exhibits criteria for a disorder:

1) A substantial amount of time is spent on eating, such that a pre-specified time of day is scheduled and mandated by many labour laws to accommodate this behaviour due to its overwhelming prevalence.

2) A substantial amount of money is spent acquiring excessive calories, despite understanding the consequences of chronic overeating.

3) Eating behaviour continues despite sufficient caloric intake, and/or feelings of satiety, independent of energy requirements to perform daily activities, or even periodic heavy activity.

4) Unchecked by subsequent caloric deficit, it inevitably leads to harm: Heart disease, vascular disease and liver disease being the most direct, with linkages to other diseases such as some forms of cancer.

5) Ongoing overeating behaviour can cause marked anxiety and significant stress on self-image and self-perception.

6) People continue to engage in the behaviour despite knowing the consequences for its continuation.

In the right context, almost anything can be explained in a disease model, including love. This is not to make light of an anorexia or bulimia diagnosis, or true body dysmorphic disorder or obsessive-compulsive disorder. I'm not advocating that overeating be classified in the DSM as a psychiatric disorder, but with some of the negative attention that one receives while trying to make, or demonstrate a positive change, it does make me think a bit more on why it is that pursuing a leaner, even a more muscular body might make it onto the official list of psychiatric disorders before eating more than you need to does.

Fitness, nutrition and a Peruvian fruit stall

2011-10-04T20:16:00.000-06:00

I'm in Peru right now on a volunteer hand surgery assignment. I arrived here about a week ago and when I went to the grocery store the day after I landed to stock up on some supplies, I noticed things in the store that were familiar and things that weren't so familiar.

In an effort to ensure I wasn't going to get scurvy, I felt like I had to buy some fruit. There were oranges and pineapples and mangos and papayas, but I also wanted something portable that I wouldn't have to peel or cut or scoop. So I opted for apples. I speak very little Spanish, so asking the clerks in the store about each fruit, its taste, how to eat or prepare it wasn't really an option.

Over the last weekend, I took a cooking class, which started with a tour of the local Peruvian market. My teacher, a wonderful chef, took me to a fruit stall where he started picking up various local fruits and explained each one to me, taking out a paring knife to show me how to peel and eat each one. The word, "amazing" doesn't even start to describe the experience. So many options and each one more tasteful than the last.

The end result is that I have 4 out of 6 apples left and no desire to eat them. I can get upwards up 15 varieties of apples in Canada. It turns out apples aren't even grown in Peru. They're imported. That's right, my default 'safe' food is actually a luxury item in Peru. Now, I'm just trying to get my fill of camu camu, lucuma, chirimoya, granadilla, tumbo and cactus fruit while I'm here.

So why write about this?

Fitness and nutrition for most people, is la bit ike a Peruvian fruit stall. There's the stuff you know--the apples, and the stuff you don't (things like camu camu, and lucuma!) Some people attack the new stuff with a fervour, trial-and-error be damned. In this case, I would have ended up eating rinds and cactus spines. Others gravitate towards what is familiar, regardless of the price or the relevance of it, staying away from stuff that might not only challenge their status quo, but might even make it better!

The reality is that there's a lot of strange fruit out there. Most of it is edible, but you have to know how to eat or prepare it. With the right guide, strange fruit can be an awesome, enriching experience. Without the right guide, you can end up with spines in your teeth, or at the very least, a bitter taste in your mouth. Counting on the people that sell the fruit isn't really a reliable solution either. They are more than happy to sell you the fruit, regardless of whether you speak the language or not. Some might help you out, but their goal is to get you to part with your money.

In an age of unrestricted access to multiple information sources from both sellers and non-sellers, I predict that the future will not be about finding information, but rather, finding reliable interpreters and guides that can lead your way through the foreign territory where visiting consumers don't speak the language.

Strange fruit can be ridiculously enriching--if you're with someone who knows how to eat it. Who's guiding you?

Now excuse me while I break open this granadilla.

Aerobic exercise vs weights. Who will win?

2011-10-02T21:13:00.000-06:00

There is no question that diet and exercise both play a role in fat/weight loss. Schools of thought range from the "it matters more what you eat" camp to the "it matters more how much you move with subgroups ranging from the "it matters how many calories you eat" camp to the "it matters if you do weights" camp and then the all-popular, "just move more" vs. "move, but move really really fast in short intervals of time" camps.

Jen Sinkler of Experience Life magazine brought this study to my attention, because I belong to the, "it matters if you do weights and probably doesn't matter much if you move more, whether at a steady pace or really really fast in burst intervals." camp ((mostly out of laziness and abhorrence of "cardio")

Slentz CA et al. The effects of aerobic versus resistance training on visceral and liver fat stores, liver enzymes and insulin resistance by HOMA in overweight adults from STRRIDE AT/RT: A randomized trial. Am J Physiol Metab. doi:10.1152/ajpendo.00291.2011, 2011.

Introduction:

One of the first factoids a person learns about when the topic of "weight loss" is the difference between "losing fat" and "losing weight". Despite the misplaced metric of the scale, however, one quickly comes to realize that the goal of "weight loss" is actually "fat loss", and that the two losses are not, in fact, equivalent.

As the journey into complexity continues, the difference between visceral and subcutaneous fat eventually surfaces; subcutaneous fat being the fat that makes you..well, visibly fat, and visceral fat being the fat that exists around your organs, deep to the abdominal fascia. It is also sometimes vilified as "the dangerous fat".

Visceral fat as well as fat _in_ your liver are linked to several disease states, the existence of which are debated (such as Syndrome X) and not (such as type 2 diabetes). High levels of visceral fat are also correlated with dying (from any cause, which, epidemiologically is somewhat problematic, but we won't get into the specifics of all-cause mortality).

Circulating liver enzymes (most notably, alanine aminotransferase, or ALT) have also been linked to diabetes and non-alcoholic fatty liver disease; though it is unlikely ALT is directly in the casual pathway of either of these two conditions.

We know that aerobic exercise improves insulin sensitivity and that it decreases visceral fat. What isn't clear, according to these researchers is the part that resistance training plays in visceral fat levels as well as circulating ALT levels.

Methods:

This was a randomized controlled trial (yay!) comparing the effects of aerobic training alone vs. resistance training alone vs. aerobic and resistance training on subcutaneous and visceral fat levels as well as circulating liver enzyme levels.

The authors looked for adults between the age of 18 and 70, with BMI's between 26-35, mild to moderate cholesterol problems who lead sedentary lives (defined as physically active less than 2 times per week). Subjects also had to be non-smokers and without a history of diabetes, hypertension or heart disease.

After screening 3145 potential subjects, 234 were found to meet the inclusion and exclusion criteria. These individuals were then asked to maintain their existing lifestyle for 4 months prior to the actual study. This is also known as a run-in period. There are many reasons to do a run-in period, but in this case, the authors wanted to weed out people that would not be committed to the study to reduce the number of drop-outs after the study got started. They lost 38 people during the run-in period, which left them with 196 subjects in the study itself.

Unfortunately, the authors did not report how they randomized these 196 subjects into the three treatment groups, but they randomly assigned each subject to one of the three groups.

Subjects were all weighed (average of three weights taken over 2 weeks on different days), height measured once. What sounds like a VO2max test or at least some sort of maximal stress test was performed at baseline and after the intervention period (since it's unlikely sedentary people can actually meet the criteria for a true VO2 max).

The amount of visceral and subcutaneous fat was determined by a CT scan. An image of a single cross-section of the abdomen was taken at the level of the L4 pedicle.

Total weight lifted during each workout was recorded either by a supervising personal trainer or electronically.

The resistance-training only group worked out 3 days per week, 3 sets of 8-12 reps for 8 exercises.

The aerobic-training only group didn't appear to have "days per week", but rather did approximately 12 miles (19.2km) per week of milage at 85% peak VO2. These were done on treadmill, elliptical trainers, and or/exercise bikes, or a combo of the three. Subjects were instructed to stay within a certain heart rate zone.

The combined group did both workout protocols each week.

The trial time was 8 months.

ALT and AST were measured for each time point by blood draw.

I didn't care much for their statistical approach, but in the end, I'm not sure it makes that much of a difference. Each group had 13 paired t-tests to compare the pre- with the post- values with no correction for multiple comparisons.

I do not agree (for reasons that I have stated over and over again in this blog) that a non-significant p-value indicates "no difference" between groups, which these authors use liberally.

Results:

The average BMI in this study was around 30.

In terms of program success, all groups showed both statistically and practically relevant changes in their workout indicators. The subjects in the aerobic training group increased their measured peak VO2 as a group, and the subjects in the resistance-training group increased the amount of total weight lifted per workout over the trial time.

With respect to the variables of interest though, results were lacklustre. The authors commonly interpreted a p-value of less than 0.10 as a "trend towards significance", which has been condemned by biostatisticians across the world as being misleading and inaccurate. If we actually corrected for 13 multiple comparisons (there were actually 45), the p-value required to interpret a difference as "statistically significant" would be around 0.004.

When you separate out all the smoke and mirrors though, what you end up with not that many relevant changes. On average, the aerobic and combined groups lost 2kg (+/- 3ish kg) over 8 months. On average, the resistance group gained 0.7kg (+/- 2.4kg) of body weight.

There were only two between-group differences detected under than 0.05 level, but above the 0.01 level. No differences were under the 0.01 level. Visceral fat surface area was less in the aerobic-only group when compared to the resistance-only group; and changes in the liver/spleen ratio were higher in the aerobic group compared to the resistance-only group (but this analysis was not performed on all subjects, as only 67% of the scans had both spleen and liver in them). In terms of interpreting the liver/spleen ratio itself, a denser liver, compared to a spleen, might indicate less fat in the liver itself.

Discussion:

So where does this leave us on the original question?

I think there are a few angles that are important to consider in this study:

1) If you are not sedentary with a BMI between 26 and 35 with mild to moderate cholesterol problems, this study doesn't apply to you. It doesn't really help inform you on whether you should or should not be incorporating aerobic or resistance training in your current regime. So if things are working, just keep on truckin'.

2) It's really hard to tell what the importance of losing cross-sectional area of fat actually is. While some of these differences between aerobic and resistance training were statistically significant (if we are generous about the multiple comparison oversight), there's no data to help us figure out if losing 16 square centimetres of visceral fat in a single CT slice at the L4 pedicle level means anything in terms of the stuff we're actually interested in, such as diabetes, insulin resistance and dying.

3) Despite the increase in peak VO2 and a nicely progressive increase in total weight lifted in a session of resistance-training, I'd say an average loss of roughly 5 pounds of bodyweight with a range of 11 pounds of weight gain to 20 pounds of weight loss over EIGHT months is pretty dismal for any program with, or without resistance training.

Albeit this was not a diet study; and it does isolate some of the factors that might inform us on how to prescribe exercise to people trying to lose weight. However, if 144 people only managed to lose, at most, 20 pounds over eight months (with most clustered around the FIVE pound area), I'd say the take-home message here is that our primary focus should NOT be on exercise prescription for the purposes of decreasing body weight, fat loss (visceral or subcutaneous) or liver enzymes. I'd even go so far as to argue that if you're around a BMI of 30 and consuming around 2000 calories a day, you probably can't exercise your way to weight loss without eating less.

The bottom line: The motto, "Eat less, move more," is often used by fitness/diet professionals as a simple message on how to lose weight. I think what this study highlights in the end, is that this message should probably also change, probably to, "EAT LESS, move however much you want to," or even just, "EAT LESS. Waaaay less."

Staying simple

2011-09-12T11:11:00.000-06:00

A few months ago, I wrote a post about my personal development as a counter-piece of anecdotal evidence to those examples suggesting poorly supported complexity and expense to achieve a body transformation.

Anecdotal evidence is considered the lowest quality of evidence upon which to base decisions. It is highly susceptible to sampling bias (most people who don't get the outcome they want don't tend to tell their story), selection bias (I get to pick the best pictures), recall bias (most people aren't that great at keeping research-level records of all the factors contributing to their story), as well as out-and-out dishonesty; but when it comes to individuals making decisions, it also seems to be one of the most powerful and potentially driving pieces of evidence. It is something that I think I would like to study in the future (collaborators welcome!), but as an idle musing, I think anecdotes are so powerful because they are generally quite personal, and very accessible. Anyone can read a story. There aren't really any statistics that require courses or books to decipher. And when it comes to basing a decision on an anecdote, there aren't any right or wrong answers. You can decide to use an anecdote because you think it fits your circumstance or not; either way, you're right because there are so many ways in which an anecdote can fit, or not fit your situation.

I decided to post an update to my anecdote for two reasons:

1) I still believe that if you're going to write about fitness and nutrition, or claim any expertise in it, that you should follow what you write. While you may not achieve a stunning result (I still have a long way to go), if you're not following your own recommendations, how can you expect others to do it?

2) There is something to be said about sustaining a 'transformation'. As challenging as a physical transformation can be, there are a lot of factors that keep the drive to transform going: For one, you see and experience changes month by month, which feeds back on itself to push you to continue to experience change. But once you've made a large change, the feedback that used to fuel your changed behaviours diminishes. It then falls to you to find new fuel sources to sustain the "new you". I would argue that it's comparatively easy to be a one-shot wonder. The higher-quality evidence would also suggest the same. Overweight people in diet studies lose weight--almost universally. But they gain it back. This is going to be challenge of population weight-loss studies in the future.

I'm still working out the kinks of staying within 'striking distance' of what I would consider my best shape. I'm still trying to transform, and I know it's not going to be as quick or dramatic as the first one. But I'm still following my own recommendations to get there. I still have a 60-100 hour work week. I still don't eat 6-8 meals a day. I still don't use any supplements other than creatine, a multivitamin and occasionally whey. I still love the Pizza Alla Siciliana from Salvatore's.

Transformation doesn't have to be complicated or expensive. See what you can achieve with less before you add more.

Jan 2011 / April 2011 / August 2011

Photo credit: Shaun Simpson, Shaun Simpson Photography

Control is where you find it

2011-09-02T19:22:00.003-06:00

When I was my first year of residency, I did my 8-week neurosurgery rotation. I have all the respect in the world for neurosurgeons (I mean, apart from the blatant overuse of the "This isn't brain surgery…" joke), but neurosurgery is not for me. Everyone thinks ICU is the most intense, but it's not--at least, not for me. I remember being so tired and so busy and dealing with so many sick patients that about 3 weeks in, I started having what I've described to my friends as, "elevator escape fantasies" where I fantasized getting onto one of the hospital elevators and getting trapped inside, unable to answer my pager and just being able to curl into a little ball on the floor to get some sleep. That's right. Some people's terror-filled nightmare was my escape fantasy. I would take the elevator all of the time (except for real emergencies) on the off chance that I would get stuck. It never happened. And eventually, the rotation came to an end, and I lived to tell the tale.

When I think back on those really tough weeks, there was a lot that I couldn't control. I can tell you what I couldn't control: I couldn't control when to work out. I couldn't control when to study. I couldn't control when to go home, or when to wake up (4:30am, if you must know). I couldn't control when to eat. On call, I wasn't even in control of my sleep. To a certain degree, nothing has really changed since those neurosurgery days. I have a little more control, but just last week, we were up until 4:30am re-attaching a thumb. But even in that chaos, there were things that I could control: I could control WHAT I ate. I could decide to work out on days that I wasn't on call (on the days I was DOG tired, I could decide to just walk INTO the gym and let the workout fall as it would). And I could control my decision to take the stairs or the elevator (The elevator, always the elevator, because you really can't get stuck in a stairwell--AND people are more likely to notice an elevator not working and therefore, find you, whereas getting stuck in a stairwell most likely means something bad has happened to you…See how thoroughly my fantasies are thought out?)

We all have stress in our lives. That's just life. Prioritizing is just a part of it. When you feel like things are spiralling out of control, take a step back and see what's within your reach. Sometimes, winning means managing to just not go backwards.

Restriction: It's not just for calories

2011-08-07T19:17:00.003-06:00

I'm sitting in the Newark airport and having a sandwich at the Earl of Sandwich (it's the only place I can sit down here, it seems). There was a sign as I came up the ramp for "PI" stating that "He's a child isn't a diagnosis", implying that your child's cold could be a sign of "PI". As I'm sitting here eating this club sandwich, there's another sign outside the restaurant also for "PI" or "Primary Immunodeficiency".

Primary immunodeficiency is a condition that affects (at best estimate) about 1 in 100 000 births. There are at least 5000 people that see that sign every day. Of those 5000 people, a much lower number of them will have children and even lower still, the number of those individuals who have a child less than 1 year old. In 20 days (almost a month), that sign would be applicable to a single individual if they were all infants under the age of 1. How many days would it take to pick up one case of PI? Probably more than 6 months to a year. Important? Yes. Because PI or SCID (Severe combined immunodeficiency) can result in DEATH before the age of one year if untreated.

However, one could argue that the sign does more damage than it does good. It plants a certain amount of stress and pain on an individual with a child (they don't mention the age that PI usually affects) who reads the sign. The sign is going to worry approximately 99 999 out of 100 000 people (who have kids) unnecessarily.

This got me to thinking: How much information do you need to achieve your goals? And at what point does additional information deter you from reaching that goal? In other words, when does more information do harm?

If you lived without internet access, and had to lose weight, how would you accomplish that? I think the answer is a fairly simple one: You would eat less and move more. And if that wasn't working very well, you'd probably eat even less and possibly move even more until you got a result.

So the question is, given that we know this method will work, does it really need to be more complicated than that? Is every other "alternative" method simply a mind-gimmick to frame this solution? Does knowing about Primary Immunodeficiency change anything for 99 999 out of 100 000 people? And therefore, does knowing about (and I'm not even talking about understanding) the Zone diet, the Paleo diet, growth hormone (within physiological levels, even high normal levels), insulin, HIIT, toed shoes, or any other more formalized "method"/gimmich/device change anything for 99 999 out of 100 000 people trying to change their bodies? And how harmful in terms of stress, time, and resources (financial or otherwise) is this if I adopt or or don't adopt it?

I blog about studies (even if it is intermittent). I'm trained to interpret and filter, and I'm trained to weed. I'm just as wishful and hopeful to achieve MY goals. Getting there faster is always something in which I am interested. And I always have to ask myself, "Is this something that will genuinely help me, or does it just make me feel unique?" Never underestimate the potential for harm. Limiting your consumption applies both for calories and information.

Flukes--more than fish.

2011-07-17T12:08:00.003-06:00

In January this year, I was in Cancun at a conference (I know, life is harsh). We were traveling from the hotel to the conference and my friend David gave me half a peso back in change because I had lent him too much for bus fare. I said flippantly that he could keep the "half-cent". He pointed out to me that half a peso was more than half a cent, and was, in fact, 5 cents, or a nickel. I said it was barely more, and he rebutted that it was TEN times more. It was then that I realized this was a very good illustrative example of how a statistically meaningful difference still doesn't translate into buying a pack of gum.

Most of the studies I review for this site fall into two categories:

1) Statistically significant, but practically useless: This is the equivalent of saying that a nickel is TEN TIMES more than half a penny. On the face of it, it's a massive proportional difference. But practically speaking, you can't do much more with a nickel than you can with a penny.

2) Practically useful, but statistically coincidental: This one is a little trickier. The whole purpose behind using statistics is to determine whether or not the result in the study is plausibly a real effect, or simply a fluke. You can successfully use statistics to state that it's not a fluke, but if you couldn't prove it wasn't a fluke, you can't really prove that it was a fluke either. You can only state that it definitely wasn't not a fluke. So basically, the result lies in the twilight world of possible fluke-dom. Results that are "promising" or "approaching significance" are examples of this type of study (if you want to see a statistician fly off the handle, tell them that "approaching significance" is a meaningful statement)

I don't know about you, but I'd rather spend my hard-earned cash and irreplaceable time on something I KNOW I'm going to enjoy (say, like a well-dressed bison burger with yam fries) than something that might or might not be a fluke.

Beta-alanine redux: Same question, still no answer. But they still recommend you take it.

2011-06-25T11:21:00.004-06:00

It's been three years since I've written about beta-alanine. I do monitor the literature from time to time to see what's new in the BA research world. But really, there isn't anything new. There still is no definitive answer that BA does anything meaningful. The latest BA study not only failed to find anything meaningful, but also failed to plan to find anything meaningful, allowing the gods of statistical probability to decide if the fruits of their labour would be met with reward.

Kern BD, Robinson TL. Effects of beta-alanine supplementation on performance and body composition in collegiate wrestlers and football players. Journal of Strength and Conditioning Research, 25(7):1804-1815, 2011.

Introduction
Football players and wrestlers can be characterized as athletes who compete and train in a HIIT-style paradigm. Maintaining lean body mass while improving or keeping performance gains, particularly in times of trying to make weight for competitions is therefore of importance and interest.

Methods
This study was reported as a randomized controlled study, but made no mention of any study characteristics that would allow a reader to evaluate the quality of such a design. The authors did not mention how the randomization sequence was generated, how the subjects were randomized, or who was blinded (the term "double-blind" has long lost all meaning in RCT literature). All we know is that about half of the football players and half of the wrestlers took the placebo and the other "about half" of the athletes took 4g of beta-alanine per day for the 8 week study period (it reads like it was 2g at breakfast and 2g at lunch). They did not allow athletes who had taken beta-alanine in the previous 3 months to be in the study.

Performance outcomes included a 300 yard shuttle run, and flexed arm hand (at 90 degrees). Blood lactate was also measured with finger-prick samples. Body composition was measured with a 7-site skin fold test.

The study athletes trained as per their training schedules. Football players practiced 3 days per week and did resistance training 4 days per week. Wrestlers practiced 4-5 days per week and did resistance training 3 days per week.

Statistics
ANOVAs were used to determine if there were any differences between or within the four groups, and if there was, the t-tests were planned.

Results
The paper reports that both the football players and wresters who took beta-alanine had, "…more desirable results in all tests (mean values) compared to those on placebo, though no statistically significant difference was seen between mean change values (pre to posttreatment) on any tested variables…"

The rest of the results section goes on to outline the actual numbers these "more desirable" results were. I'm not convinced they are meaningful even if they had been statistically significant.

Discussion
What surprises me about this study is that the discussion section of this paper talks about these results as though they were actually beneficial/successful. I think this warrants a brief overview of how the p-value is interpreted:

The way I like to phrase the interpretation of the p-value is that is the probability of observing the differences in the data between the two comparison groups if there is no difference in the overall population.

As a point of convention, we define something as "statistically significant" if the probability of observing the difference under the circumstance that nothing special is happening is less than 0.05. That is to say that if beta-alanine had no effect at all, it would be highly unlikely for us to observe X difference. Therefore if we do observe X difference, it must be because beta-alanine is doing something. Failing to meet the 0.05 criteria means that while you can't say beta-alanine does nothing, you also can't rule out the fact that it was all just a coincidence.

The problem with this study is that not only does it fail to find evidence for beta-alanine as an effective supplement (in ANY of the parameters), it lacks the power to say that it doesn't do anything either; and that is largely to do with the planning of this study, and every other beta-alanine study to precede it.

If you were going to build a house, you would probably hire an architect, and perhaps an engineer to design it. You would probably spend a lot of time looking for the best materials you could afford and once that was done, then and ONLY THEN, would you break ground for your house. You probably wouldn't take a look at what was around, start digging a hole and nail gun some boards that were lying around together.

The authors of this study reported that the wresters and football players gained, on average, one pound of lean body mass in 8 weeks, and that the ability to this is meaningful and important. Let's assume that we could actually reliably measure that without any confounding variables like, oh, say..drinking a 2L bottle of Coke. If that is indeed the case, then you would need 115 subjects to prove that that gain of 1 pound of lean body mass wasn't just a coincidence. In short, this study was, unfortunately, a random hole in the ground with some random nailed-together boards.

Nonetheless, the authors of this study conclude, somehow, that beta-alanine does produce meaningful results--by far the most ambitious and overreached set of conclusions I've read in a long time, given the bleak face of the data. It's one thing to argue that a small statistically significant difference is important, but to argue that a small not-statistically significant difference is relevant? That takes balls.

The bottom line: Do I hate beta-alanine? No, I wouldn't say that I hate it. But I do hate the fact that even at only 30-40 dollars a month, thousands of hopeful people are buying into a hype that, apart from unconfirm-able anecdotes, has yet to pan out in any way, shape or form when studied.

Believing that something works is entirely different than something that actually works. In the words of a certain orange-coloured banking company: SAVE YOUR MONEY.

Anecdotal Evidence-Based Fitness

2011-05-09T18:23:00.016-06:00

At some point in every fitness-writer/blogger's lifespan, there comes a point where the rubber has to meet the road. We write about fitness and nutrition and body-image, but I'm sure there are many bloggers who can (and I apologize for the use of two cliches in two sentences) talk the talk, but can't, don't or won't walk the walk.

And at some point in every fitness-writer/blogger's lifespan, there has to be come form of accountability for what he or she writes. A proponent of supplement X should probably be using supplement X and not just writing in favour of it to get paid if they really think it works. A writer who believes in workout A enough to rave about it should probably be able to show that it works at least for themselves. It's of little value to say, "X totally works and everyone should be using X, but I don't."

My blog is about making informed decisions based on available scientific data. It's also about making decisions NOT to use certain things based on the lack of credible or valid scientific data. In some ways, this blog paints me into a bit of a corner if I'm going to follow my own advice.

I've been grumbling along for a while trying for years to gain muscle and then realizing that I was just getting fat. A year ago, I weighed roughly 200 pounds. So I set a goal and a goal date in mid-January and to make it stick, I booked a photoshoot for myself to hold myself accountable. I didn't use HIIT. I didn't drink chocolate milk. I barely even drank protein. I took a multivitamin. I took creatine. I lifted weights, and near the end, I did some steady-state cardio to burn a few hundred calories so I could eat a little more to keep myself sane. I ate less throughout the 12 weeks and I didn't eat 6-8 meals a day. In fact, I ate 1-2 meals a day because it was more satisfying to have an ACTUAL meal, instead of trying to spread 1100 calories into packets of 150-200 calories (seriously, do you have any idea how completely NOT satisfying 200 calories is?)

I still had a 60-100 hour work week. I travelled craptons for fellowship interviews and one Unsummit (seven out of twelve weekends on a plane to somewhere and back). I'm pretty sure I ate my weight in food in Vegas, one week before my photo shoot (which was planned) and there was one week where I decided I just had to eat an entire frosted pound cake because it was just there and I wanted to.

This is just an anecdote. This is my N of 1. For every story that you've heard of person X getting into better shape by following yet another gimmick that has no published proof of effectiveness, here's my one story to show that it is possible to improve the shape you're in without following much of anything gimmicky, or not scientifically validated at all. So yes, it is the weakest form of evidence, but just as valid as every other piece of anecdotal evidence out there.

I'm not the most built guy, but I'm still proud of where I got; and I'm definitely tracking towards moving forward even more.

Before: Jan 31, 2011 After: April 24, 2011

Thanks to John Barban and Brad Pilon for support, both workout/diet and sanity-related. Yes, I am a fan of Aussiebum, so I don't mind giving them some promo :)
Photo credit: Shaun Simpson, Shaun Simpson Photography

Not evidence-based, but still a neat foodhack

2011-04-24T12:57:00.004-06:00

Ever find yourself crushing a bag of snack food? Part of the reason why you can is because it's there. Not only is it there, it's immediately accessible. So here's an idea that you can try while still keeping your sanity.

For some people, certain foods are hair-trigger foods. These are foods you can't resist, no matter how hard you try. They're the foods you'll go out of your way to eat, and over which you have essentially no control (for me, these are profiteroles of any variety, chocolate-covered or not). This foodhack is not for those foods. Those foods are foods you should probably not have in your home except under specific conditions and quantities.

However, for those foods that you do enjoy but tend to overindulge on, try putting it in another room, or at least, far enough away that you're going to have to completely disrupt what it is you're doing to get at it. For instance, there's a bowl of peanut M&M's on my kitchen counter right now. For me to grab a few, I'd have to stop writing this entry (or watching the movie, or reading, or whatever it is that I'm doing currently), get up off the couch and grab a few. My only rule is that I can't start eating them until I've sat back down on the couch; oh, and I can't eat more than I can carry in one hand (this doesn't work well for things like cake).

If I'm willing to overcome all of that inertia just to have a few M&M's then I should be able to have a few. But after the third time up, I honestly had too much inertia built up to go again. The inconvenience of getting up off a comfortable couch, stop typing, put my laptop down for a few M&M's just wasn't worth it anymore. It also means that if I'm going to overcome my inertia, that I'm making a conscious decision to actively pursue eating those M&M's. I actually have an opportune moment to think about whether that action is compatible with my goals, or within the flexibility I have already built into my plan. There's nothing wrong with rejecting your diet at times, as long as you're making an informed decision about doing it, understanding the consequences of your actions. Taking ownership of going backwards is just as important as moving forwards.

It's hard to take ownership over overeating or eating that isn't congruent with your goals when the food is sitting right in front of you, ready for you to consume. It's an absent-minded, reflex-like action to put another M&M in your mouth when there's a bowl within arm's reach. You, in fact, probably don't even enjoy the food that you eat absent-mindedly. It's just a transient sensation of basic taste (sweet, salty, sour, bitter). While I think it's still an action you should own, it's just not always apparent. Geographically situating your food in a place that forces you to derail your current activity can be just enough of an interruption to at least control the rate at which these foods can be eaten, if not cause you to pause for thought.

The Information Diet

2011-01-11T18:20:00.003-07:00

The New Year season is full of resolutions to diet for weight loss. It's also one of the most fruitful seasons for merchants who produce weight-loss products to add to their bottom line. They're easy to find and getting more and more clever with each passing year. They're on Google Ads, banner ads, Facebook, Twitter, youTube, and infiltrate virtually every other on-line media you use on a daily basis.

This easily leads to information overload, as well as fear-based marketing: How do you choose from all of the products available? How do you sift through the inundating assault of those massively lengthy webpages that have PARAGRAPHS of text and testimonials? And worse yet, how do you know that one of those products isn't better than the one you're going to buy?

One saving grace with online marketing is the fact that you get to view product marketing somewhat on your own terms. You get to choose when to click over to their webpage. You choose what to read on that page. However, more often than not, you're going to be asked, enticed, or coerced into giving information that will make you a part of that merchant's "list".

It's one thing to buy a product from a merchant. You've probably done it already. I've definitely done it. Generally, even if you're not interested in buying the main product, there's a way to get a "free" report on some "secrets" which involves giving your email address. Voila, you're on the "list". In fact, online advertising is more about getting you on the "list" than it is about selling you the product.

And this is where the true sabotage begins.

The sabotage begins because one you're on a merchant list, you become subject to additional information. Some of it might be helpful, but for the most part, it's either enticing you to buy more product, someone ELSE's product, or contains some sort of minutiae that is not going to ultimately affect whether you meet or don't meet your health goals this year. The product you bought probably already contains several extraneous elements (e.g. a list of all the food you can or cannot eat).

What destabilizes your progress is the fear that you might not be getting to your goal as quickly or as easily as you POTENTIALLY could. If you're missing out on a SECRET, then surely something THAT important must somehow be incorporated into your existing program for you to succeed faster. So you change your tactics or add more to the set of rules you already have to follow. Eventually, you're the victim of rule overload (where there are so many rules to follow or so many components to track that you end up dropping the ones that actually important for the ones that are inconsequential, or you just give up altogether because trying to juggle that many rules is basically impossible), or worse yet, rule contradiction (where the rules begin to just conflict with one another, like "Work out on an empty stomach in the morning" vs. "Never workout on an empty stomach.")

What makes direct email marketing even worse, is that you don't control when that information comes at you. It just shows up in your inbox beside the emails that ARE important to you (thus creating the subconscious link that their email is somehow also important). It's like some friendly buddy running into as you walk to or from work handing you a can of soda. Randomly. And you drink it every time. And then you wonder why you're still fat.

So this new year, instead of resolving to go on yet another gimmicked diet (when you already know that eating fewer calories than you spend is a tried and true method that works), go on an information diet. Set up a free email account (hotmail, yahoo mail, gmail) and unsubscribe your main email address from all marketing email lists.

If you MUST read the AMAZING SECRET REPORT, you now have an email account that exists for the sole purpose of collecting these reports. You should never let online advertising into your main personal email account inbox where other important messages come in, and where you don't always control when you read what's there. At the very least, you will be able to decide when to read advertising AND you're more likely to see marketing side-by-side, as opposed to isolated glimpses.

There is no magic pill yet. If there was, you can bet you would need a prescription for it; AND you would be reading about it everywhere. It wouldn't be a secret. Keep yourself from being buried alive in the minutiae that isn't going to make or break your resolution this year, and focus on the stuff that will.

Defending yourself against decision overload

2011-01-01T19:18:00.002-07:00

It's 2011, and a new year for the ongoing onslaught of infomercials, internet promises and magazine gimmicks competing for your attention.

A friend of mine once told me, "The most expensive clothes you'll ever buy are the ones you never wear." The same goes for diet programs, online e-books, and new (or just re-branded) products. Most people don't buy new clothes thinking they'll never wear them. Likewise, most people don't buy new fitness products thinking they'll never use them.

In the spirit of the new year, here are my tips for deciding whether to sink your hard earned money and your even-more-valuable time into something new.

1) Take stock of where you are:
I think before being mesmerized by images and promises, it's important to think and reflect on your strengths, from both a mental and physical point of view. What have you already got? What parts of your life are already "handled"? For instance, do you already have a pretty consistent schedule in your life? Have you already gotten rid of those foods in your house that shouldn't really be there? Were you born with one particularly well-developed body part that essentially doesn't need to be worked? Decide on what metric is important to you. For most people, this is actually NOT weight, but actual circumference measurements. But, if weight IS important to you (for whatever reasons), then make that decision.

2) Take stock of where you want to go:
This one is trickier because most people don't know how to measure where they want to go. I don't normally promote products on my blog, but I have found the approach from the Adonis Index and Venus Index to be very pragmatic and takes the guesswork out of coming up with a goal. You basically need to hit the waist circumference for your height and then go from there. Forget the rest. I can't think of anyone who, after losing 10 pounds without making much change to their body shape, says to themselves, "I lost 10 pounds. I'm done." Maybe your goal isn't making a body-shape, but is performance related, in which case, you're the best judge of what relevant to you.

As a side note, you should try to avoid making goals that can fail based on factors you can't control. "Placing in the top ten at X competition," while a worthy goal to have, is one that can leave you feeling unfulfilled after X, because you can't control your competitors (or the weather, or any number of other things that have absolutely nothing to do with you).

3) Simplify what you have:
Before you take on a new gimmick/behaviour, simplify what you already have. So before you take on a new diet approach, take a look at the one you already use before you start adding new rules. Take a look at the food choices already in your home and simplify your choices. You cannot eat what isn't there. Once you have a simplified menu, you can start to thoughtfully add choices to it to avoid being overwhelmed by options and rules. This step-wise approach allows you to also evaluate whether the individual changes in your life are effective, as opposed to trying to sort out a bundle of changes when things aren't going quite as planned.

4) Fill in the gaps:
Now you've reached the point where you can start to add things, IF there's anything even missing in the first place. When you're filling in perceived gaps, the rule is to add things in one at a time, then evaluate before adding something else new. It can be, and should be exciting to try something new. This approach also allows you to dole out that excitement a bit over time as you figure out what does and doesn't work for you or your life.

5) Measure your progress:
You should be taking regular measurements to assess your progress. This can be as simple as measuring how compliant you with your own plan on a daily basis (you either followed your plan that day, or you didn't) and measuring the things you identified in steps 1 and 2 on a regularly scheduled basis. This is only way to decide whether something is working or not. Your emotions and feelings are fluid. The tape measure doesn't share that fluidity.

6) Abandon what isn't working:
If you find your progress isn't going in the right direction, then you need to make a decision whether to keep the new thing or to ditch it. Looking at your compliance may reveal that despite regular measurements, you're not actually meeting your behavioural goals, in which case, you can either re-commit to those goals, or perhaps discover that what you're doing isn't realistic for you and re-adjust those goals. If you're sticking to your new thing about 90% of the time and your progress isn't going in the right direction, it's time to jump ship. And you should jump fast.

The bottom line however, is that you should be wary of the wave of new products making their way to your brain in the coming new year. You probably already have all the tools you need to get where you want to go. The next new thing is just a way to distract you from the task at hand. If something truly revolutionary comes along, you'll hear about it everywhere, including here. So don't worry, you haven't missed anything important yet.

Same message, funnier vehicle

2010-11-11T12:41:00.002-07:00

Thanks to Sid S. who sent me this link in response to "Gymnastics makes you short".

97-year old dies unaware of being violin prodigy (Courtesy of the Onion)

See? I'm not the only one who's crazy.

It was bound to happen

2010-09-26T16:53:00.007-06:00

This blog entry is courtesy of Fran Mayo who read an article in "Runner's World" about some of the benefits of drinking pomegranate juice. It was fairly inevitable that I would get around to talking about pomegranate juice. It is, after all, all the rage right now and POM is currently in the media regarding some dubious health claims.

There are lots of reasons to drink pomegranate juice. Personally, when it first came out as a commercial product, I thought it was a pure novelty. I mean, have you ever EATEN a pomegranate? It takes FOREVER. The whole idea of juicing enough fruit to make a whole bottle of pure pomegranate juice was just unfathomable. So from my perspective, one of the reasons to drink pomegranate juice is because you can. All that pomegranate-y taste without the painstaking work.

But apparently, there are other reasons to drink pomegranate juice apart from the pure sensory ones. And apparently, one of them is to possibly decrease muscle soreness. Or so this study claims. Fran did all the work to track it down (would it be so much work for a magazine to actually cite a study instead of saying, "A study from Joe Schmoe University says…")

Trombold JR, Barnes JN, Critchley L, et al. Ellagitannin consumption improves strength recovering 2-3d after eccentric exercise. Medicine and Science in Sport and Exercise. 42(3) 493-498, 2010.

Introduction

There is a theory that chemicals called polyphenols are good for you. The ways in which these benefits are quantified are variable across studies and the practical significance of these findings may or may not be actually that large, but that's not where I'm going with this review.

The authors of this study thought that delayed-onset muscle soreness would be a good model to study the effects of polyphenols on some aspect of functional improvement (as opposed to physiological improvements which may or may not result in functional improvements). There is good evidence to show that eccentric exercise does cause local inflammation and other physiological changes which could be considered similar, if only transitory, to more serious types of chronic inflammation as are observed in diseases such as rheumatoid arthritis.

The authors reviewed some of the literature on eccentric exercise recovery and other interventions. In their literature review, they could not find any supplements that were able to demonstrate improved muscle function recovery by reducing inflammation or oxidative stress.

The purpose of this study therefore, was to figure out whether pomegranate juice improves muscle function over a four-day recovery period after eccentric exercise.

Methods

This study was a double-blind (a long-archaic term now) randomized placebo controlled crossover experiment. This means that all of the subjects received both interventions (placebo and real pomegranate juice); that two parties (usually the subject and the investigator) were blinded to which subjects got what drink; and that the subjects were randomly assigned with respect to which intervention they got first.

Potential subjects were considered for the study if they were non-smokers, and "recreationally active". However, potential subjects were excluded from the study if they had done any resistance training in the past 3 months, if they were in a formal endurance training program, or had a history of previous upper extremity injury. Potential subjects were also excluded if they had had a "recent" weight change of >5kg, hypertension, or if they were on anti-inflammatory medications or other similar drugs.

Subjects were assigned to receive either a placebo or pomegranate drink in two testing periods, each one 9 days long with a 14 day washout period. During the testing period, subjects drank two 480ml bottles of drink each day, 12 hours apart. On day 5 of the testing period, the subjects then performed an eccentric bicep curl exercise (2 sets of 20 reps, with one rep every 15 seconds, and an eccentric phase of 3 seconds and a rest period of 4 minutes between sets.) The curls were done on a Cybex machine. The subjects used a randomly selected arm for the first test period and then the other arm for the second test period.

Strength was measured at 2 hours, and then 1, 2 and 3 days after eccentric curls and was measured isometrically with a rigged up modified preacher curl and load cell. Testing was performed only on the exercised arm.

Soreness was measured using a visual analog scale. Blood tests were also performed for creatine kinase, myoglobin, interleukin-6 and C-reative protein.

Statistics: The authors used repeated measures ANOVAs and the least significant differences method for pair-wise comparisons to compare the effects of the drinks as well as the outcome values over time. Six ANOVAs were performed, one for each outcome variable.

[The method in which the subjects were randomly assigned to their drink order was not reported. The method in which the arm was randomly chosen for each test period was not reported.]

Results

Sixteen males were recruited for the study. Average age was 24 ish years.

When it came to soreness, or any of the blood tests, the authors failed to detect a statistically significant difference between the placebo and pomegranate juice. When we look at the values between the two drinks, there don't appear to be any differences that I would consider large enough to warrant a discussion about power.

The main result of this paper is the detection of a single difference between pomegranate juice and the placebo in recovery strength. In both trials, a decrease in isometric strength was observed (an almost 30% decrease in strength in both conditions). At 2 hours, and 24 hours, there was no difference detected between the two drinks in strength. At the 48 hour mark, the authors detected a statistically significant difference in strength, with pomegranate juice being associated with higher strength than the placebo. This difference was also statistically significant at 72 hours (day 3). By day 4, this difference had disappeared.

At the 48 hour period, the difference in percent of baseline strength was 7.1%. Strength in the pomegranate condition was, on average 85.4% of baseline compared to 78.3% in the placebo; both with standard deviations of 10.1%. The difference at 72 hours was 4.9%, with strength being 88.9% for pomegranate and 84% for placebo (SD 7.9 ish for both conditions).

[However, the ACTUAL value of the baseline strength was never published, so we are unable to determine the actual value this nearly 30% decrease represents and therefore can't really interpret how significant this decrease is with respect to something practical like, for instance, how much less weight might this translate to?]

The authors did report confidence intervals around some of their "strength deficit" values.

At 48 hours, the mean recovery in strength for the pomegranate condition was 13.9% with a 95%CI of 7.84 to 19.9%.
At 48 hours, the mean recovery in strength for the placebo condition was 5.5% with a 95%CI of 7.84 to 2.38 to 8.68%.

[This should set off a small flag in the back of your head if you're familiar with confidence intervals, as these intervals overlap, which calls the significant p-value into question as possibly spurious. It's not a perfect rule of thumb, but not a bad one as far as rules of thumbs go.]

There was also a significant "ordering effect" detected and reported, where strength was also dependent on the trial (whether it was the first testing period or second testing period). That is to say that strength values were influenced by whether they were collected in the first or second trial, in favor of the second trial. This effect was noted at the 2 hour, 72 hour and 96 hour marks. Nine of the subjects started with placebo drinks, while 6 subjects started with the pomegranate drinks. [Oddly, there were supposed to be 16 subjects in this study as reported above. I don't know what happened to that last guy.]

Discussion:

I think this study is one of the few studies in which the major leak springs up in the introduction of the manuscript and then is followed by subsequent smaller, but contributory leaks. The authors of this study theorized that since DOMS takes several days to recover from, that strength can be used as a reliable indicator of the time course of functional recovery.

I think this theory is wrong. And here's why:

DOMS is primarily manifested by pain, and while DOMS can be so severe so as to keep you from wanting to move or lift, I don't believe the presence/absence/severity/duration of DOMS can be considered an accurate reflection of any reliable physiological parameters, never mind a functional one such as strength. In fact, the loss of strength that is associated with DOMS may be more pain limited than it is physiologically limited such that if you could simply work through the additional pain, you might not have any strength decrements at all 24-48 hours after an initial eccentric exercise bout (which is the typical lag time between exercise and DOMS).

So given the imperfect model of how this is all going to happen, pomegranate juice comes out as having improved strength recovery, and the study is otherwise conducted in a fairly rigorous manner (with the standard reporting problems). However, we are still left with the confounding factors of pain limited recovery vs. physiologically limited recovery. This is re-enforced by the finding that there did not seem to be any differences in the inflammatory markers they selected to study between the placebo and pomegranate juice, which then begs the question, "Did 'reduction of oxidative stress or inflammation' actually occur as a result of the pomegranate juice?"

This is also one of those studies in which the use of 'untrained healthy males' probably does matter. If you're an athlete or even an occasional "weekend warrior" (as the authors suggest as a population to which this study might be applicable), your ability to recover from exercise is not a constant and changes as your body enacts adaptations to the training you do. So, if we subscribe to the idea that recovery from activity gets better with training, this study (in the best case scenario) gives us an idea of what the MAXIMUM benefit would be that we could ever derive from pomegranate juice. Frankly, it seems rather underwhelming if I have to pay about 30 bucks for a bottle that has 16 servings in it (so basically an 8 day supply).

From a training perspective, I think this study has limited utility. There are very few activities that require repetitive eccentric loading to the point of incurring DOMS on a consistent basis (i.e. progressively increasing loads) that individuals participate in on such a frequency basis so as to have to worry about recovery within 4 days. Yes, skiers undergo cyclical eccentric loading, but unless they're getting progressively heavier or moving to progressively steeper/higher frequency loading courses on a workout-to-workout basis in a constantly increasing scale (whether linear or curvilinear), the need to marginally accelerate recovery seems misplaced.

Furthermore to the use of the study for training reasons (which I really don't think the authors actually set out to show), is the whole issue of whether post-exercise inflammation is something we actually want to prevent. If we subscribe to the theory that training causes tissue damage directly and indirectly, and performance/aesthetic improvements occur because these tissues heal/adapt such that they have higher work capacity/size, then inflammation is the first and necessary step of healing. Are we, in fact, doing harm to our fitness goals by preventing what is a physiologically necessary step (i.e. would our results as a result of blocking inflammation be as large as simply allowing the normal time course of healing to occur?) As an example, the trade-off question would be, "Would my biceps get even bigger if I could work them out twice a week at the same intensity because I partially blocked the inflammatory phase of tissue healing than if I just let things happen and trained either less frequently or at a lower TOTAL intensity (since the second bout would presumably be less than the first)?" Or is this a case of slower progression because the "build back stronger" effect is attenuated by blocking the inflammatory response? (i.e. I can lift the same amount of weight 3 days after, which enables me to train biceps twice a week, but the amount of net tissue accretion is actually close to 0 because the inflammatory response provides some sort of "build more than before" signal?)

So while there might not be any direct adverse/side effects from lowering things like "oxidative stress", we are quite in the dark with regards to possible either longer-term indirect "harms" (i.e. not getting where you want to go as efficiently as possible) which might manifest as a result of chronic exposure to "inflammatory reducers".

These are questions to which I do not believe we have the answers to. And so, tinkering around with training protocols as a result of single-exposure pre-post studies is, from the get-go, not a well-informed action.

All of this discussion is assuming that the "significant difference" is actually REAL. The authors never published the results of their ANOVAs (the test statistic, the degrees of freedom, the p-value), only the "protected" t-tests (as defined by the least significant difference method). With 6 ANOVAs and no adjustment, it's entirely possible these "significant" p-values are, in fact, products of pure chance as opposed to reflections on real effects. The fact that there are overlapping confidence intervals in their data suggests that this possibility is not just theoretical.

But even if it IS real, it's really hard to gauge the usefulness of this study. We are given no absolute values with regards to strength. A decrease of 30% in maximum strength could mean something as small as 10 pounds, or as great as 30 (I don't know how strong "recreational, non-resistance trained" 24 year old males generally are). Therefore the fact that pomegranate juice seemed to be linked to a faster recovery in strength has no real meaning given that we don't know what the actual magnitude of recovery was. Do I care that I can lift 4 extra pounds a day earlier? Would it matter if that was 20 extra pounds? And lastly, would I be willing to buy enough pomegranate juice (at approximately 2 dollars per drink) to drink it twice a day EVERY DAY to get that effect?

If you're going to claim to improve hypertrophy, measure hypertrophy. (P.S. Your experiment has to be replicable)

2010-08-14T10:18:00.005-06:00

There's been lots of attention to one of the latest studies out of McMaster University on low-load high volume resistance exercise and protein synthesis. I, for one, am not beneath jumping on bandwagons of any kind. However, let's strike to the core of the matter, as opposed to dancing around all the peripheral (and also somewhat inconsequential) criticisms of the study.

Burd NA, West DWD, Staples AW et al. Low-load high volume resistance exercise stimulates muscle protein synthesis more than high-load low volume resistance exercise in young men. Public Library of Science 5(8): e12033, 2010.

Introduction:

The authors highlight research in their introduction that suggest that lifting heavy may not be necessary to increase muscle protein synthesis. Their theory is that the number of repetitions is the determining factor to maximal motor unit recruitment (as per the size principle of motor unit recruitment) and therefore, load is actually a secondary consideration if muscle protein synthesis is the goal.

Unfortunately, we don't understand muscle growth very well still. There are a whole host of signals that we are barely beginning to understand. Pathways such as the Akt-mTOR pathway, as well as Pax7, which is a marker for satellite cell activation have been identified, but how they play a role in making muscles bigger is poorly understood.

So, these researcher set out to answer the question of whether lifting to failure with a protocol involving 90% 1RM loads would change things like, "anabolic signalling" compared to a protocol involving lifting to failure at 30% 1RM.

Methods (and some results):

The authors studied young men. There doesn't seem to be any indication that there were any pre-planned inclusion or exclusion criteria. They _happened_ to get 15 guys who _happened_ to train legs/lower body with weights or with weights and cycling more than 3 times a week for at least 6 months. It looks like they were looking for guys who were familiar with lower body exercise to minimize the contribution of neuromuscular strength gains.

All subjects underwent 1RM testing for leg extension. This 1RM was repeated to determine if it was a true 1RM. Once the 1RM had been established, the subjects were randomly assigned to 2 of three experiments:

1) 90% 1RM to failure
2) 30% 1RM in which the "work" (as measured by reps x weight) was matched to the 90% 1RM to failure (e.g. if you pushed 90 pounds for 5 reps as your 90% 1RM, "work" would be 90 x 5 = 450. You would then have to do 450/30 = 15 reps at 30 pounds to match the work)
3) 30% 1RM to failure

The subjects were randomly assigned in a "counterbalanced" fashion(i.e. not actually random) to match for leg strength and body weight. There were 10 subjects in each training experiment.

When subjects arrived in the lab, the load was set according to the previous 1RM test. The 30%1RM with "work matching", was performed with the number of reps required to match the work of the 90%1RM experiment. Subjects performed 4 sets with 3 minutes of rest between sets. The tempo was 1-0-1.

[So, in case you're just as confused as I am, this is not a training study. It's a study to look at the effect of a single session of a training condition on "anabolic pathways". The authors had a pool of 15 guys, but for reasons not stated, couldn't run all 15 guys through all three conditions. So, each guy got to do two of the three conditions. For all intents and purposes, there would be an overlap of 5 guys between condition 1 and 2, 2 and 3, and 3 and 1. However, in subsequent text, it seems that the subjects would have gotten either the 1/2 combination or the 1/3 combination, with no 2/3 combos because performing condition 2 was based on the "work" performed in condition 1 (you can't match the work for 90%1RM to failure if you never do the 90%1RM protocol).

So, to summarize this gong-show of a methods section so far:

1) 15 guys.

2) 10 guys perform the 90%1RM to failure protocol and then the 30%1RM with "work matching" protocol. 10 guys perform the 90%1RM to failure protocol and the 30%1RM to failure protocol. By the reporting, no one does the 30%1RM to failure AND the 30%1RM with "work matching" because they HAVE to have done the 90% to failure condition in order to match the work.

3) Each guy did two and only two protocols.

There is no math/logic that I'm aware of where all of these conditions can be true.

This is, in short: What. The. F&#K.]

Diet was controlled using a protocol that I'm not going to go into here because I'm already losing interest in this study.

On testing days, subjects had baseline blood samples drawn. After that, they received an infusion of radio-labelled phenylalanine. The subjects then had one muscle biopsy taken from the vastus lateralis muscle of one leg to determine their resting muscle protein synthesis. Four hours post-exericse, and 24 hours post-exercise, a biopsy was taken from each vastus lateralis.

This muscle was analyzed for protein synthesis as well as the markers for gene expression of 6 different genes linked to muscle protein synthesis.

Results:

Muscle protein synthesis: Mixed protein synthesis was elevated for all conditions at 4 hours post-exercise. The increase was about 3.5x more than resting in the 90%to failure group, 3.2 fold in the 30% to failure group and 2.1x more in the 30% to failure group. This increase was not sustained at 24 hours post-exercise, but remained higher than resting at 24 hours (less than 2x for all conditions).

Myofibrillar protein synthesis was elevated in all three conditions 4 hours post-exericse, but only remained statistically elevated in the 30%1RM to failure group at 24 hours.

Sarcoplasmic protein synthesis was elevated in only the 90% and 30%1RM to failure groups (statistically) at 4 hours post-exercise. Only the 30%1RM to failure group continued to experience statistically elevated levels at 24 hours post-exercise.

"Anabolic" pathways: I'm sorry, I just can't read this anymore.

Discussion:

In their discussion, the authors have the audacity to claim that using a 30%1RM to failure bout of exercise is more effective at increasing muscle hypertrophy than a 90%1RM to failure bout. Their reasoning is that the 30%1RM to failure group had similar myofibrillar protein synthesis as the 90%1RM to failure group at four hours and continued to exhibit higher level of myofibrillar protein synthesis at 24 hours (where the 90%1RM to failure group's level of synthesis dropped back to close to baseline at 24 hours).

This is, in fact, the crux of the entire paper.

I have three points to make:

1) There are massive issues related to inadequate reporting in this paper. The experiment, as reported, is completely not-replicable, and in some places, make no sense at all. While this might not invalidate the results of this study, it does point to sloppy work, which may or may not reflect on the rigor of the actual study quality/protocol. Garbage in, garbage out.

2) Ignoring the reporting atrocities, there are no measures of muscle hypertrophy in this paper. Hypertrophy implies muscle size is getting bigger. Muscle size was never measured. All we can say is that protein synthesis is elevated more in the low-load/high-rep scheme. Just because you can make more money, does not necessarily make you a better dresser. You're definitely richer, but you might not be very good lookin'.

If we accept that muscle size is determined by mixed, myofibrillar and sarcoplasmic protein content (and I'm not convinced that we actually know this to be true), hypertrophy can only occur if there is a NET increase in these constituents. This study, as with most protein synthesis studies, does not take protein breakdown into consideration. If a certain type of apple tree can produce 100 apples a month while another type of apple tree can produce 200 apples a month, this difference is pointless if the second apple tree drops 150 apples to the ground while the first apple tree drops only 25.

3) This is NOT a training study. This is a study about muscle protein synthesis after a single bout of training one way or another. We cannot make any conclusions about how protein synthesis might be different by using the high-rep/low-weight lifting approach as a training strategy. For all we know, protein synthesis falls off after two of these workouts. Or it might not. We just don't know--at least from this study.

The bottom line: If I ignore the horrible reporting (and that's REALLY hard to do), this study STILL isn't good enough for anyone to justify changing their training program to a high-rep, low-load scheme. If what you're doing is working, keep going. You're not missing anything--at least based on this study. In short, from a "How should I train for maximum muscle hypertrophy?" perspective, this study contributes almost nothing.

Actually, yes, you can.

2010-07-28T10:01:00.007-06:00

The amount of time one rests between sets is an often missed, or often underestimated training variable. It's also one of the least studied variables when it comes to looking at hypertrophy as the outcome (as opposed to strength, or other performance variables, or even biochemical markers). So it is a treat to see a study where hypertrophy is the variable of interest, and where measurement of hypertrophy is truly a direct measurement. While not every investigator can measure hypertrophy in this way, it does go to show that "It can't be done," or "It will never get done," are just words, because these researchers, in the words of the famous Dos Remedios, "did work."

de Souza TP, Fleck SJ, Simao R, et al. Comparison between constant and decreasing rest intervals: Influence on maximal strength and hypertrophy. Journal of Strength and Conditioning Research 24(7) 1843-1850, 2010.

Introduction

We know that the less you rest between sets, the less work you're able to do in subsequent sets. Chances are, you're not able to lift as much weight for the same number of repetitions, or you're not able to do as many repetitions for the same amount of weight. There seem to be pros and cons to long-rest and short-rest approaches to weight training though. With long periods of rest between sets, the theory is that you're able to better train to increase your maximal strength. However, there is some evidence to show that short periods of rest (30-40 seconds) may have metabolic and/or hormonal responses to weight training that don't exist in long-rest approaches, which might make short-rest workouts more amenable to hypertrophy, not to mention that workouts could be made to be shorter.

A mixed approach to the problem has been proposed, whereby rest intervals are decreased over time within a training cycle. An example of this would be: 2 minutes of rest between sets in week 1, 100 seconds of rest in week 2, etc. While it's certain that work performed (which can be crudely measured by multiplying the number of reps by the weight moved) per set is going to go down, the hypothesis these authors wanted to test was whether the hormonal changes associated with short-rest training would counter the "deficiency" of not being able to maintain the same workload from set to set.

But that's not even the best part of this study.

Methods

The subjects in this study were young, recreationally trained men. All subjects had been lifting weights for at least one year before this study and trained at least 3 times a week.

The subjects underwent 1RM testing for squat and bench (different lifts on different days) and testing familiarization over 2 weeks before the study. Seventy-two hours after the first testing session, all subjects had the cross sectional area of their right thigh and right arm measured by MRI. Peak isometric torques were also measured for knee extension and flexion, but I'm not going to talk about these results in this review.

The subjects were then randomly assigned to do an 8-week lifting program in which the rest period was either constant (2 minutes between sets for 8 weeks) or decreasing (2 minutes between sets in week 1-2, and then decreasing every week to end up at 30 seconds between sets in week 8)

The program was 6 workouts a week, alternating between a workout A and B, Monday to Saturday. Both groups had the same exercises. In weeks 1 and 2, both groups resting for 2 minutes between sets. From week 3 onwards, the decreasing rest group got less and less rest between sets each week.

[This study, though claiming to be randomized did not report any of the standard elements that should be included in a randomized controlled trial (who was blinded, how subjects were randomly allocated, etc). However, this is actually less important as we will see in the results section.]

Results

I think it's important to pay attention to the characteristics of subjects in a study as it has direct implications as to whether this research might apply to any particular consumer. There were 20 subjects in this study (10 in each group). The subjects in this study group were, on average, in their 20's, somewhere around 5'10" tall and 160lbs. What does this tell us? Well, for one, in terms of a study about hypertrophy, we know that it's likely that of all the guys that could have been in this study, these guys were in the demographic of men most likely to build muscle. So, from a sample selection point of view, this is a trial designed to succeed (which isn't some underhanded thing, since ALL trials should be designed to succeed).

Looking at training volume (defined as weight lifted x reps lifted), the constant rest group almost always did more volume than the decreasing rest group, particularly in week 5 and onwards. Week 5 is also the point in which the decreasing rest group was approaching 1 minute of rest between sets, so it's no surprise that their volumes started to drop off more noticeably.

Looking at maximal strength, both groups improved their bench and squat substantially over 8 weeks, but both groups improved about the same amount, so there were no differences in maximal strength detected between the two rest schemes.

Looking at hypertrophy as measured by MRI scanned cross-sectional areas of muscle in the arm and thigh, both groups improved their cross-sectional areas over 8 weeks--about 9 cm squared in the arm and about 25 cm squared in the thigh (as averages). However, the spread of values (or variance) was very high, so it's hard to tell how important these numbers are. Ideally, the authors would have published an average CHANGE in cross-sectional area which would have been more useful for interpretation. If we make the VERY crude assumption that the cross sectional area of the muscles in the arm is a circle, that's an improvement of about 2 cm in diameter on average.

However, both rest groups improved their cross-sectional areas about the same amount, so again, no differences beyond those we would expect to see by chance alone were detected between the two rest schemes.

Discussion

The immediate criticism of this study that likely comes to most people's minds is, "There's only 20 subjects in this study!"

However, this is one of those studies in which I think the question is still answered despite all of its shortcomings and reporting deficiencies. And here's why:

1) If either rest strategy was better than the other, the population in this study was probably the most likely one in which we would have seen clear superiority. These subjects would likely have been past the initial 'neural adaptation' phase of training, most prone to hypertrophy given their age and proximity to 'juvenile growth phase' and were also likely not close to their growth potential. If we were going to see a clear advantage, any other study sample would have had less of a chance of demonstrating it.

2) While this study was underpowered, the differences in cross-sectional area between the two groups was minuscule (2cm squared in the arm and 4cm squared in the thigh). If we considered this to be a pilot study for a larger trial, there's just no way you could justify the expense and energy to show that the difference observed was due to the different rest scheme and not just chance alone. The difference just isn't big enough to go after that fish.

3) By far, the coolest part of this study was the MRI cross-sectional area. Let's face it, no one working out for hypertrophy gives one rat's ass about how many muscle fibres are there per square centimeter, or how much bigger each weeny fibre is; we want to know if we're going to look bigger. MRI quantified cross-sectional areas separates all the unknowns in 'bigger'. If your arm circumference got bigger because you got fat, or because that baseball bicep is actually a tumour, it can tell. So we can say for sure that while both groups did gain muscle size (not just arm circumference), neither resting strategy was better than the other.

4) Any bias that wasn't reported or identified in this study would have biased the results towards making one groups distinctly better than the other. If the randomization didn't work, we would expect to see one group doing better than the other. If anyone wasn't blinded, and there was a bias towards making the decreasing rest group look better, we would expect the decreasing rest group to do better. However, in this case, neither group demonstrated a clear superiority over the other. So even if the bias was present, it wasn't enough to make us draw a false conclusion.

The Bottom Line: When it comes to hypertrophy, it's pretty unlikely that resting 2 minutes or resting less than two minutes has much of an effect on how fast or big your muscles get. Resting for less time may make your workouts shorter though. Mostly, though I wanted to review this study because it just goes to show that it's NOT impossible to measure hypertrophy directly.

An open letter to OUT magazine

2010-07-20T08:16:00.004-06:00

Dear OUT Magazine,

In reference to Joshua Stein's "Corporeal Downsizing" article (May 2010), the misinformation in such a short paragraph was overwhelming. However, briefly: 1) It is physically impossible for muscle to turn into fat. People may accumulate fat if their daily caloric needs go down while their caloric intake stays the same, but muscle cells do not transform into fat cells even with disuse. They simply get smaller. 2) While circuit training and whole-body workouts are in vogue currently, what determines muscle growth has more to do with consistent increases in workload than it does with which muscles a person uses on which day. You can, in fact, build muscle on a circuit program. And 3) The calories a person burns with "cardio" is quite negligible; you can achieve the same weight-loss effect by reducing your calorie intake. It is misinformation such as that in your article that perpetuates long-disproven fitness myths and propagates ongoing ignorance about effective methods for weight (or muscle) loss. A magazine of your calibre should have higher standards for its sources.

Sincerely,

Bryan Chung MD, PhD

Belief shouldn't be part of why something works (unless it's curing cancer)

2010-07-14T08:26:00.004-06:00

There are a lot of things you should believe in: the resilience of the human spirit, your own resolve to achieve what you want to get out of life, and perhaps that we will be able to sort ourselves out ultimately without destroying ourselves in the process as a species.

But supplements, diets and workout programs shouldn't be things that require your belief.

You don't believe in your car. You know it works because when you turn the ignition, shift out of park and push the gas pedal, it moves. It doesn't require your belief to make it move. You don't believe in ducks. They walk like ducks. They quack like ducks. They look like ducks. They're ducks. Whether you believe ducks exist is mostly irrelevant (except in some realms of philosophy).

Likewise, supplements, diets and workout programs either work or they don't. And if they do, they should work in predictable ways--for everyone (barring some weird genetic variant issue like how codeine doesn't always work for everyone.) And if they don't, you should abandon them with reckless…abandon.

The equation for success probably looks something like this:

Results = Consistency + Effort + Program + Nutrition +/- Supplements

It shouldn't look like this:

Results = Belief + Effort + Consistency

If you haven't got good quality, unbiased proof that any of the components to getting results work, then you're depending on belief to carry you through. Don't get me wrong, belief is a strong force. It's what keeps people taking certain supplements despite not making progress. It's what keeps people on certain diets or workout programs even though they stopped making progress weeks or months ago (if they did at all). Mostly, this stems from not measuring progress. If you catch yourself saying, "I believe that X works," X had better be something esoteric like energy healing. "I believe fasted cardio works," isn't esoteric enough that it should rely on your faith for it to work.

Faith is for God (if you believe in God). Belief is for ghosts. Neither should be components of your fitness/body image strategy.

What are you putting faith in?

Chocolate milk: Yummy, but not special.

2010-06-30T14:42:00.004-06:00

The 'original' chocolate milk study came out in 2006. And it seems like the whole chocolate milk thing just won't die. Alas, document delivery has yet to deliver the article to my inbox yet (have I mentioned how much I love the Internet?), so I leapt forward in time to look at another study in the small puddle of chocolate milk studies.

This study doesn't quite get at the question, "How important, exactly, is post-workout nutrition?" but rather, "How does chocolate milk compare to other forms of post-workout nutrition?"

Gilson SF, Saunder MJ, Moran CW et al. Effects of chocolate milk consumption on markers of muscle recovery following soccer training: a randomized cross-over study. Journal of the International Society of Sports Nutrition, 7:19, 2010.

Introduction

I think we would all like to believe the pre, intra and post-workout nutrition are very important. We've seen one example of how pre-workout protein probably doesn't really make any difference large enough to warrant the extra cost of consuming it. While there have been studies supporting the idea that post-workout nutrition is important and results in better recovery (a fairly vaguely defined term) and better results (an even more vaguely defined term), the debate around WHAT to consume after a workout takes most of us down a path of debate that I believe counts as pure, unadulterated intellectual masturbatory minutae.

But, don't let my opinion count for much of anything.

Let us assume for the purposes of this review, that post-workout nutrition DOES matter. And furthermore, let us assume that post-workout nutrition matters for the non-elite typical gym go-fer.

What do we know about chocolate milk? We know it contains both protein and carbohydrate. We know that in head-to-head comparisons, it tends to do just as well, or better than carbohydrate drinks alone. However, we're not sure whether the fact that in previous comparisons, the drinks weren't calorie controlled might explain why it did so well or whether it actually does affect recovery insofar as we can measure it.

Methods

This study was a randomized cross-over trial of chocolate milk vs. a calorie-equivalent carbohydrate beverage in NCAA Division I soccer players.

Players were tested at baseline on a Monday, and then tested again on Wednesday and then Friday. During this time, they were in the off-season, but had their training volume increased by 25% above their normal volume for this time of year. They took their blinded drink after each training session. Their baseline training schedule was between 45 and 90 minutes of training, seven days a week. The increased training schedule was between 90 and 120 minutes of training, 4 consecutive days in the week.

Players were asked to rate their muscle soreness from 0-100, and mental and physical fatigue on a formal questionnaire. Blood samples were drawn and measured for creatine kinase (a marker for inflammation), and myoglobin (which appears in the blood as muscle is broken down). The players also underwent maximal voluntary contraction testing and performance tests (t-drill and vertical jump).

The players went through a two-week wash-out period between the two, two-week trials.

Statistics

I'm not going to go into a lot of the statistics here, but there is a paragraph that is quite troublesome, "Preliminary statistical analyses were performed on 17 subjects who completed all testing. However, some subjects exhibited large variances in baseline measurements between the two treatment periods, possibly due to activities outside of the study during the two unsupervised days prior to [pre-testing]. This resulted in significant group differences in numerous [pre-testing] measurements...The exclusion criteria had the intended effect of eliminating all significant differences in [pre-testing] values between treatments, making the interpretation of the data simpler. However, it should be noted that exclusion of these subjects did not alter the outcomes of any hypothesis testing…"

[What worries me about this study is that they started with 22 soccer players, but lost 5 subjects due to incomplete testing or training with and without injuries, and "excluded" 4 more players from the statistical analysis because of "large variations in dependent measurements between baseline periods…" I'm sorry, but you don't get to pick and choose who you analyze or don't analyze. And if the exclusion doesn't affect the final interpretation, why exclude at all then? That's called selection bias.]

Results

The average age of the players in this study was 19 years (SD 0.3 years)

Overall, there weren't any notable differences between the carb-only drink and chocolate milk. Creatine kinase levels rose (predictably) with both drinks, although it did not tend to rise as much when the players had chocolate milk instead. The players tended to perform just as well whether they had a carb-only drink or chocolate milk.

However, the investigators in this study did not succeed in creating a 25% increase in training duration in these athletes. While training duration increased equally between the two drink trials, an average increase of 10 minutes per four days is not a 25% training increase. It's more like an 11% training increase. Less than half of intended effect. So what we don't know is whether either of these drinks produces different results if the training duration is increased beyond 11%.

Discussion

The authors of this paper use these results to encourage more study--a conclusion with which I agree. They do state that a major limitation of the study is that there was no placebo or control group--with which I also agree.

So what can we take away from all of this?

I think there are a few points that most readers of this blog can take away:

1) Unless you're a 19 year old Division I soccer player, this study shouldn't be the reason why you choose to drink anything after your workouts.

2) Any study that excludes subjects after having already analyzed the data should be under high suspicion of biased information. In this case, it probably didn't matter, but we'll never _really_ know.

3) I suspect that it doesn't really matter what you drink after your workouts, if anything at all. If there are any applicable links between this study and you, the numbers suggest that you can pretty much do what you want and you'll still play and test about the same.

So in the end, there isn't anything magical about chocolate milk. If you're drinking it anyways, good for you. If you're not, there's no reason for you to rush out and get any. Just do what you're doing. Simplfy what you can, and rest assured that you're not missing out.

Fear of loss: How the fitness claims get you

2010-06-23T14:33:00.002-06:00

All through my undergraduate "career", I worked in labs. Just as there are gym rats, I was a lab rat. Great experience for me. Okay pay for a student. But when I finished my undergrad, I already knew I was going to start my Masters in the fall. And at the time, I also felt that I had never really earned an honest dollar. I had never set foot outside the Ivory Tower and so I wanted to experience what a "joe job" might be like. My first choice was to be a waiter--pretty social, they seem to have a lot of fun for the most part, and the pay was probably better than my lab stipends. But in Toronto, getting a job as a waiter is tough competition. In the end, I lucked out, but there was a period of a month or so where I hadn't found that job.

So what's a 23 year old, freshly graduated biology major to do? Hit the want ads, of course. What happened next is a story unto itself, but the crux of the story is that I ended up doing a short stint as a door-to-door salesman with a franchise of one of the largest direct sales companies in the world.

What I learned from that job would serve me well for the rest of my life (well, so far anyways, though less so these days). And what I learned is how to make a sale. I learned how to sell a product to a total stranger who wasn't even in the market for what I was selling within 3 minutes of them opening the door. And modesty aside, I was good at it.

The company I worked for created a very well-supported training program for their "independent contractors". Every morning we would practice our pitches to each other before spreading out over a particular territory for the day. We would critique each other's pitches, and get ideas from other salespeople on different ways to pitch. But when we critiqued each other, it wasn't on delivery, or words. It was on emotion, and it was based around four factors that had to be in the pitch. They're all important when making a sale, but in this post, I thought I would just focus on one: Fear of loss.

Getting someone to decide to give you money in 2 minutes or less involves appealing to their emotion of fear, and specifically their fear of loss. Or potential loss. The opportunity to gain is temporary and will never return. I almost never went back to a house, even if they asked me to--unless it was to make more sales, in which case they had usually paid me for at least one unit. And I made sure I had a limited supply of product with me at all times (which was mostly engineered by the company, and your previous sales)

When you have a concrete product in your hands, the potential loss is tangible. Pay now, or lose out. But I would argue that in fitness/nutrition marketing, the potential loss is not quite as tangible, but possibly stronger than if it were tangible. Sometimes, it's a limited time offer, in which case, it's also somewhat tangible in the sense of potential money-savings.

What almost all fitness marketing sells you is time. Given enough time, you could probably get to where you wanted to go. But if you could get there faster, you probably would. That's what they're selling you. A faster way. What do you stand to lose? Time. You stand to lose getting there faster than you would without the product.

Once you know this is the emotion you're supposed to have in this type of marketing, you can start to recognize when it arises and evaluate it for what it is. It's a normal emotion in response to a normal fear. And that is all it is. Sometimes, you're going to get duped, depending on how much fear of loss you're exposed to. That's why before and after photos are so powerful and why a single before and after photo will almost always trump any study or logic. Logic doesn't require emotion. When you decide to buy, it's almost never rooted in logic.

Feel the PUMP! Um..that's it.

2010-06-14T17:02:00.010-06:00

First off, I LOVE how this article starts, "The use of nutritional supplements continues to increase with athletes and recreationally active trainees…" That's right, you gym rats (me included); we're not athletes. Quit pretending. It's okay.

Snarkiness aside, I've been wanting to discuss nitric oxide or NO supplements (as well as pre-workout drinks) for a long time; but oddly enough, the literature was incredibly sparse on the topic in terms of studies involving humans and outcomes training individuals would be interested in. NO-type ingredients seem to be in everything, to the point where you don't have to _decide_ to take an NO-related ingredient, you probably just are, particularly if you're taking anything that is designed as a pre-workout supplement. In fact, it's amazing that they can stuff more than 30 ingredients into a single pre-workout drink such that it will still fit into a couple of scoops.

So this review has been a long time in coming. I apologize for not weighing in sooner.

Bloomer RJ, Farney, Trepanowski JF et al. Comparison of pre-workout nitric oxide stimulating dietary supplements on skeletal muscle oxygen saturation, blood nitrate/nitrite, lipid peroxidation and upper body exercise performance in resistance trained men. Journal of the International Society of Sports Nutrition 7:16, 2010

Introduction

Pre-workout drinks aren't new. They're almost old enough to be passé. NO "boosters" used to be (and still are) sold separately, but now it's all "batteries included". In fact, pre-workout drinks are chocked with all sorts of ingredients, which, when studied alone, may have some effects but most of which have been poorly studied or not studied at all, other than very basic studies which contribute to theoretical conjecture about effectiveness. AND generally, the doses of these ingredients is far below their studied doses in which they may or may not have had a beneficial effect.

So, why is nitric oxide purported to be important? The claims are that increases in NO in the blood results in increased blood flow, muscle "pump" and better performance (more reps, or more weight, or both). Basially, they're supposed to make your muscles EXPLODE! But no one has actually studied NO boosters (in particular, L-arginine) and any of these claims. Until now.

Methods

This study was a randomized cross-over design trial. This means that all of the subjects got all of the study supplements but in a random order with a period between supplements with no supplements to allow for the previous supplement to "wash out" (which is why it's called a wash-out period).

There were 5 supplements tested in this study: a placebo, a glycine-propionyl-L-carnitine supplement, and 3 commercially available pre-workout drinks with NO-boosting ingredients.

Each subject went through testing 6 times with one week between each testing session. Testing was done after a minimum 8-hour fasting period (usually overnight). The subjects were asked to rate their "pump" from 0 to 10 (with 0 as no pump and 10 as the most intense pump ever experienced). Circumference measurement was taken of the torso at the nipple line with a tension regulated tape measure. The subjects then drank their randomly-assigned pre-workout drink. The performance tests didn't start for 30 minutes after the drink was consumed (60 minutes for the carnitine supplement). Subjects were allowed to drink as much water as they wanted to, but no other food or drink.

Performance testing consisted of a warm up of 10% of pre-determine 1RM for bench press throws followed by 3 bench press throws using 30% of the 1RM as a test of muscular power. The best attempt was used in the analysis. A sensor was then placed on the anterior deltoid to measure tissue oxygen saturation with near infrared spectroscopy.

The subjects then did 10 sets of machine bench press with 50% 1RM. Each set was performed to muscular failture with 2 minutes of rest between sets. Reps and weight used were recorded. The subjects were then asked to rate their pump again and the torso circumference was re-measured.

Blood samples were taken prior to testing and within one minute of finishing the tenth set of bench press. I'm not going to get into the biochemistry of this study because frankly, I don't think we really care what the biochemistry looks like so much as we are concerned about whether any of this stuff works in the gym.

The researchers tried to get the subjects to control their diet by asking them to fill out a 24-hour diet record and then after having done the first one, asked the subjects to replicate their first 24-hour diet record prior to testing. This is an interesting approach that I have not yet read about and could be looked into more from an academic point of view.

[From a design and reporting perspective, this paper lacks a lot of information. We are not told how the subjects were selected, or what criteria they used to exclude any subjects that might have been in the study but weren't. We are not told how the subjects were randomly assigned to the order in which they received their supplements; or exactly who was blinded to what. The authors mention that all the supplements were fruit punch flavour, but we all know that different companies' fruit punch flavour DOES taste differently. Whether you could tell if you were getting active ingredients or not just by the taste alone is debatable, though if someone had already been using a particular pre-workout drink regularly before, they would probably be able to tell their regular drink from something that wasn't their regular drink. I know that I can tell the difference between different protein shake formulations. Whether I could name them like some sort of oenophile (i.e. a wine taster, "This is an ON whey isolate premium line with a hint of branch-chain amino acids and a creatine finish from the Illinois Valley region…*smack smack*…2008, which was a good year") I have my doubts.]

Statistics

The authors used ANOVAs to test for differences between and within each supplement. Most of it is moot, as you will soon see. [Yes, I just said the statistics are moot. Two-headed calves aren't far off.]

Results

This study managed to recruit 19 guys. All the subjects lifted weights at least 3 days a week for the previous 12 months with the majority of subjects lifting more often than 3 days a week and more than 12 months. The average age was 24 years (SD 4 years). Interestingly (this is for you, Brad) these authors did report some training history. Average number of years of weight lifting was 7 years (SD 4 years) and hours of weight lifting per week was 4 hours (SD 2 hours). The average 1RM bench press was 150kg (SD 39kg). That's 330 pounds.

The meat of the data is Table 3.

This is one of those rare situations in which doing the statistics is relatively useless. Since a non-significant p-value cannot positive rule out whether the results observed were caused by chance alone, doing the test doesn't change the interpretation. As in previous reviews in this blog, it's the actual numbers that are important. The difference between all of the groups for power, reps in the first set of bench press, total reps, total volume load and even perceived exertion are all REALLY close to one another. Unfortunately, all the variances in this table are standard errors and so the variance looks much narrower than it actually is (multiply the standard error by the square root of the sample size for the standard deviation, which in this case, is 4.35 ish). However, even after converting the variances to standard deviation, the only measurements that are affected to any large extent are the power measurements (not particularly important in the grand scheme of things unless you're a power-type athlete), and the reps in the first set of bench press, and the total volume load (which gets magnified quite a bit, and is perhaps where one of the downfalls of this study lies).

BUT having the standard errors readily available means we can make comments on the precision of this study quite easily (i.e. what is the range of plausible values if we were to do this experiment over and over again) and because the error values are so low (except for total volume load), it's unlikely that we would obtain a much different result over repeated experiments with subjects randomly drawn from the same population.

Looking at the oxygenation results, all the numbers are again, very close to one another. We still don't appreciate any noticeable differences, despite the fact that there was one significant p-value that favoured SUPP1.

When we look at the circumference and "pump" measurements, we see that guys generally say they feel like they're getting a better pump, but it's no bigger than when they were taking nothing. Circumference-wise (which should theoretically go up) shows that while it does go up after working chest, it doesn't go up any more than when they were taking nothing, or taking the placebo. Again, these variances are all standard ERRORS (you can do the same multiplication if you're that curious).

[Despite all the reporting shortcomings, it doesn't really chance the interpretation of the paper, since any failure of randomization would result in a bias away from finding "no difference" (e.g. if there was some advantage to getting supplement C as the second supplement and they ALL got second, we would expect supplement C to do better). So even in a methodologically worst-case scenario, this study still pans out.]

Discussion

As I've recently learned, the supplement industry is largely a claims-based industry. And as I've also come to realize rather recently from some reading, food product companies don't care if you actually consume their product, as long as you actually buy them. If you put these two factoids together, a supplement company only has to have enough of a claim to make you buy the supplement, regardless of whether you consume it or not; and regardless of whether it works or not. To this end, many companies seem to have veered away from producing research that is of practical benefit to support their claims and have resorted to using physiological-type studies to support their claims (i.e. L-arginine is a precursor to nitric oxide synthesis, therefore if it can be shown that putting more L-arginine in the body (either orally, or intravenously) increases the levels of L-arginine in the blood, it can be DEDUCED that nitric oxide and all of the purported effects of such also increase). But from a consumer point of view, increasing arginine in the blood means nothing if it doesn't make one's training more efficient (from either a work or results perspective).

The studies that have examined the relationship between L-arginine and increased blood flow (by means of vasodilation) have used amounts far in excess of the doses in your pre-workout drink. We're talking 20-30 grams INTRAVENOUSLY, not 3-5 grams ORALLY. And the studies that have looked at oral L-arginine even at 10-20 grams haven't shown increased vasodilation.

The bottom line: There may be a psychological benefit to taking a pre-workout drink. How much more work you can do in a gym as a result of said psychological benefit is probably negligible in the grand scheme of causing muscle growth or fat loss. Dumbo needed a feather to make him believe he could fly, but the reality (such as it is in a Disney flick) is that he could fly without it. You can probably fly just as well without a pre-workout drink.

P.S. Dear supplement companies, why would you put a theoretical vasodilator contributor (L-arginine) in the same drink as a known vasoconstrictor (caffeine)? Just curious, mostly, as I must be missing something.

If research isn't the "real world", then what can it show us?

2010-06-07T18:14:00.005-06:00

When I was in physics class in my undergraduate degree, I remember doing an experiment to demonstrate the laws of momentum. I don't remember the specifics of the experiment, but I do remember using an air-table (similar to an air hockey table, but smaller) and pucks (similar to air hockey pucks, but smaller) to demonstrate how conservation of momentum occurs in an almost frictionless environment.

Now, I don't know about you, but I don't live in a frictionless world. Those of you who live on air-hockey-table-like-environments, I can't speak for you. And back then, I probably thought very similarly to the way some people think about research now: "If nothing on Earth is truly frictionless, short of air-hockey tables and mag-lev devices, why do we have to do this experiment?" The answer back then, was, "Because we're telling you do it, so quit bitching already and push the friggin' puck." But I've tried that answer on people who ask, "We never use supplement X/training technique Y in tightly controlled situations, so how do the results of these studies help us?" and a) it doesn't go over very well, and b) they're really confused about some mysterious puck.

The problem with the mentality that all research is imperfect or impractical is that it throws the baby out with the bathwater. It's analogous to saying that no workout program is perfect, so why bother working out at all?

So, if the real world isn't a research study, how does research inform us about the so-called real world?

Most well-designed intervention research is, well…designed to look at the effect of a single change (or collection of changes) on some attribute. A particular diet's effect on weight loss; a drug on death rates from heart attacks; a training program on strength. It's also designed to isolate the change as much as possible so that a causal relationship can be established between the change and the effect. Failure to isolate (either methodologically or statistically) makes the casual relationship blurred and therefore muddies the waters a lot.

A failure to establish a causal relationship means one of two things: 1) the change under investigation doesn't cause any effect, or 2) the conditions are too muddled to see the effect under the noise of failing to isolate the change sufficiently. In the first case, the change of interest doesn't do anything, so it's worth abandoning as long as we're sure that's why we failed to find an effect.

But in the second case, there are things we need to ask ourselves before we can justify abandoning a line of investigation. After all, we don't want to accidentally throw away something that could actually be helpful. The first question is whether the effect we've observed is important enough to continue. Even muddled, if the signal is large enough to show through the noise, it may be worth pursuing. If the effect just isn't that important (as we've already seen in several revews), it may as well not be there, and therefore, it's worth dropping and spending our energies elsewhere.

But noise notwithstanding, it is important not to discard things that are potentially helpful. This means that when we design trials on newer interventions, we want to give it the best chance of showing us that it is capable of creating an effect.

So when it comes to training and diet studies, selecting the right group of people to study becomes vitally important. It is for this reason that a good designer looking to determine if a change works at all will choose a study population that has the most potential to change. That population is the population furthest away from the theorized "optimal effect". Subjects who have the most distance to travel are more likely to travel A distance. If everyone was 7/10 at the start, that's only 3 point to move. The chances of seeing an effect are statistically diminished.

"But all beginners improve no matter what they do," is the most common argument against the utility of this type of research. However, this is where the comparison group comes into play. An appropriately designed trial accounts for "beginner's luck" by creating two comparable groups. If the intervention is useful, then there should be a change that is better than the control group that doesn't get the intervention. If the change isn't better, or is too small for us to care, then the experiment is essentially over.

Once an intervention has been shown to work in individuals far away from optimal, then we can start looking at creating better generalizability to individuals who might actually use the intervention (i.e. non-beginners). And the same process applies.

Although somewhat less applicable to some exercise-based studies, testing individual components of a nutrition or training program/strategy under highly controlled conditions gives us an idea of whether the new supplement/exercise/diet/thing has a snowball's chance in hell of working in the real world. If it can't work under optimal conditions, then it's not going to work in sub-optimal ones.

How much would you pay for 2 more reps at the end of your workout?

2010-05-31T20:51:00.010-06:00

The concept of progressive overload is a cornerstone to any weight-training program. Lifting more weight, or lifting the same weight for more reps is the goal that is theorized to produce muscle growth, or better performance (however you decide to measure that).

Citrulline malate has been an ingredient in a multitude of sport supplements. It is theorized to work through 3 proposed mechanisms: 1) malate is proposed to accelerate ammonium clearance and citrulline is proposed to facilitate lactate metabolism (these effects however, were noted in microbial models, i.e. germs in a dish); 2) citrulline malate has been noted to protect against acidosis which is proposed to counter fatigue; 3) Citrulline malate is proposed to increase nitric oxide production, which has been shown to have many potentially physiologically beneficial effects (though none of these effects may affect the stuff you're concerned about like muscle growth, fat loss, or any performance benefit).

So, basically, if you were to consider taking citrulline malate, it would be for the fatigue-resistant properties mostly, and a potential side-benefit of increased NO production (a topic for a review in the future)

The researchers in this study therefore, wanted to see if the proposed claims of citrulline malate supplementation had any effect on muscle fatigue and the perception of muscle soreness, using a bench-press as the main test of interest.

Perez-Guisado J, Jakeman PM. Citrulline malate enhances athletic anaerobie performance and relieves muscle soreness. Journal of Strength and Conditioning Research, 24(5):1215-1222, 2010.

Methods

This study took place in Spain and recruited subjects from 6 gyms. It was a randomized cross-over trial, which means that all subjects went through the testing twice with a washout period in between the two testing sessions. Each subject would have received either citrulline malate or a placebo the first time around, and then the one they didn't get the second time around.

To participate in the study, subjects had to be weight training for at least 3 hours per week, with a program that included the flat bench press. They had to avoid other sporting activities during the study and had to sign statements that they had never used anabolic steroids in the past, and had not used creatine, HMB, or thermogenics in the past 8 weeks prior to the study.

All the subjects had their 1RM tested for the flat barbell bench press. To measure fatigue, the subjects were asked to perform 4 sets of bench press at 80% of the 1RM at the beginning of a chest workout, and then 4 sets of bench press at 80% of the 1RM at the end of the same workout. The number of reps performed in each set was recorded.

The chest workout consisted of the initial 4 sets of testing at 80%1RM, followed by 4 sets of incline bench press at 80% of the 1RM of the flat bench press, and 4 sets of incline flyes at 60% of the 1RM of the flat bench press. Tempo was 1-2 seconds on the concentric and 1-2 seconds on the eccentric. Rest between sets was standardized in the program. Subjects were asked to avoid caffeine before the workouts, and all workouts were done at the same time each day for each subject (but not all subjects did their workouts at the same time as each other). Every set was taken to muscular failure.

Each subject drank a pre-workout beverage one hour before the workout. Each drink was 200mL in volume with similar appearance, smell, consistency and taste. The citrulline drink had 8 grams of citrulline malate in it. The person who made the drinks was different from the person who did the testing.

In addition to fatigue testing, the subjects were asked to rate their degree of muscle soreness 24 and 48 hours after testing from 1 to 5, 1 being no soreness and 5 being maximum soreness with physical disability for immediate training (i.e. I'm too sore to work chest today). But I'm not going to get into these results in this review, as they are peripheral to the main issue.

Statistics

To test if the difference observed between the two trials was attributable to chance or not, the researchers used ANOVAs. The muscle soreness score was compared using the Wilcoxon signed rank test. The researchers also tested "responders" vs "non-responders" using a Fisher Exact test (but they didn't report how they defined who was a responder or a non-responder).

Results and Discussion

While the design of this trial wasn't bad, the reporting of results was incredibly confusing, as you will soon see. I think there's limited utility in presenting individual data unless you can do it in a really clear and concise manner. A series of squished up histograms is really hard to read, even up close and doesn't help to clarify the data. It's like saying you've found the needle in the haystack, but only provide a photo of the haystack.

Forty-one men were recruited to participate in the study. Average weight was 81.12 kg (SD 17.43 kg) (that's about 180lbs) and average age was 29.8 (SD 7.54). The subjects trained for an average of 6 hours a week plus or minus 2 hours, and did 4 (give or take 2) workouts per week.

The meat of this study is in Table 1. You'll see how seeing the raw data makes the issue totally confusing. Here's the data for set 1 and 4 post-workout (notice also the change in scale in the y-axis):

Almost completely useless, eh?

Here's table 1:

What we see here is also a bit of a mess of numbers with odd labels. I would encourage you to avoid staring at all the really low p-values. What you should be paying attention to is the last column which is the 95% confidence interval for the difference in reps performed between placebo and citrulline malate, as well the actual numbers in the reps columns with placebo and citrulline malate.

Sets 1 to 4 are the pre-workout sets. Sets 1' to 4' are the post-workout sets after 8 sets of chest stuff with each set taken to muscular failure.

On average, it looks like there aren't really any meaningful differences in the number of reps these guys could squeeze out until set 2' or even set 4'. While the investigators were able to demonstrate statistical significance between the two trials for almost all of the sets, practically speaking, I don't consider 1 extra rep to be really meaningful--even if it's one extra rep over 3 sets. In total, you might accrue 4-5 extra reps over 4 sets. The confidence interval gives us a range of plausible values that you might get if you did the same experiment again and again. So, by this data, at the best, citrulline malate might eke out 1-2 extra reps per set.

What is striking is that the biggest differences in fatigueability don't really appear until after set 2', which is actually 14 sets into the workout. So, if you were to take citrulline malate, you would be taking it mostly for the last few sets of a typical workout--provided you had already worked that particular muscle group (that you were trying to get the extra reps on) already to muscular failure on previous sets.

Of course, the unanswered question is whether eke'ing out a few more reps at the END of a workout has any benefit from a performance or aesthetic perspective. My take on it is that citrulline malate costs between 20 and 35 dollars for a 200 gram container. Their recommended serving size is 2 grams, but according to the dose in this study, you would need to take 8 grams (though we don't know if there is a dose-dependent effect). Roughy, that's about a dollar per dose (if you're going to dose it at 8g). In the grand scheme of things, that's not a lot of money for a lot of people.

So what it comes down to is your willingness-to-pay and whether the marginal number of reps you _might_ get at the end of a workout (in which you had already essentially exhausted the muscle ALREADY) contributes all that much to your progress. Theoretically, descending sets might accomplish the same thing for free, given that you could probably produce the same amount of "work" (instead of doing the extra 2 reps at 100 pounds, you could do 4 reps at 50 pounds, to use an arbitrary number of pounds). This, of course, doesn't take into consideration that most reputable trainers would not recommend training to true muscular failure, but instead generally get their clients/athletes to train to technical failure (which is not studied in this paper.)

Bottom line: If you think you're that optimized (and I'd venture to say the vast majority of weight-trained folks aren't) that an additional 2 reps at the end of a very intense workout is going to make or break your improvement (either weight/rep or looks-wise), you could try citrulline malate. Otherwise, you're probably doing just fine without it.

Get off the never ending path to nowhere

2010-05-25T18:57:00.003-06:00

Everytime I'm at the gym, I notice the banks of "cardio" machines. In fact, for many consumers, the number and availability of the card machines is the single most important factor in decision making when buying a guy membership (which is why gyms can get away with less-than-optimal weight areas but they can't get away from sub-par cardio equipment.) In the winter time (in Canada) I can understand how using a cardio-machine can be useful. Personally, I abhor most forms of cardio for the sake of doing cardiovascular work. I've been a competitive swimmer, and a competitive rower and we never did cardio just to do cardio. We worked out because we wanted to get faster. That being said, if it's nice outside and you can run (or bike, or climb stairs, or row), there are a number of very good reasons why you should leave the gym and the endless run/bike/stairclimb to nowhere, but I'm going to focus on the biomechanics and energetics of running/walking.

Treadmill running is very different than overground running. Treadmill _walking_ is very different than overground walking. This has been shown time and time again in numerous biomechanics studies. But when it comes to fat loss and treadmill running or even treadmill intervals (if you're of the school that cardio, in any of its many forms, including HIIT is important for fat loss), these differences are quite important. To understand some of these differences though, we need to have a language for gait.

It doesn't matter where you start in the gait cycle, but there are essentially four phases to any given step that you take: Heel strike, stance phase, push off, and swing through. Stance phase is sometimes divided into double stance and single stance phase, but for the purposes of our discussion, the distinction is likely not very important. Heel strike occurs from the moment your foot touches the ground to the time you start to put weight on your foot. Stance phase starts as soon as you start to put weight on your foot to just before your foot leaves the ground. Push-off, or toe-off happens in the time that you push off the ground with your foot behind you; and swing through is the period of time your foot is in the air.

On top of the four gait phases, there are two more terms to understand: Stride length, which is the length (in distance) between one heel strike and the next heel strike of the same foot (or any identical points of the gait cycle really); and cadence, which is the number of steps you take in a minute (counting for both feet).

When you walk overground, your heel strikes the ground and you move your weight over your foot. Your body passes over your foot and then as you strike with your other foot in front of you, the foot behind you pushes off. The biggest difference between treadmill running/walking and overground running/walking is the relative position of your body to your foot while it's on the ground. On a treadmill, your heel strikes the belt, and your foot moves under your body behind you. As your foot is assisted off the ground behind you, you strike the treadmill belt with your other foot.

Sounds almost identical, doesn't it? However, in overground walking, you are moving the weight of your body over your foot. In treadmill walking, the belt does all the moving for you. You're not propelling your weight; the belt is propelling your foot. Your foot, in fact, leaves the belt because a) it feels comfortable for you to do so, and b) because it's not ALLOWED to stay on the belt past a certain angle of your hip due to simple laws of physics and the length of your leg. Your stride length is therefore dictated by how fast the treadmill is running and how fast you can react to your leg flying by beneath you. Your cadence is also dictated by the speed of the belt (you can run faster by increasing your stride length or cadence, or both; but generally, stride length is a relative constant and most people adapt to faster speeds by increasing their cadence).

The relative up-down motion you perform while running is generally pretty small in comparison to the forward-backward motion. Since the forward motion is basically taken away from treadmill running, the energetics of treadmill running are vastly altered. You therefore, require less energy to run on a treadmill than you do when you're running overground. Even at much higher speeds and inclines, the only mass you're moving on a treadmill is the mass of your leg as you carry it through space on the swing-through. If you're on a non-powered treadmill, you're also moving the weight of the belt (although the force required to move it once it's going is somewhat reduced because you're not moving it from rest with each step).

From a training perspective, treadmill running might be good for generally conditioning in the same way a lat pulldown is somewhat useful for working your way up to chin-ups/pull-ups. Obviously, the treadmill is better than nothing if nothing is truly your alternative. Eating less to lose fat is a great alternative, but it won't really make you run faster if that's your goal. But now that its almost summer, there's no reason from a weather, biomechanics or energetics standpoint to stay indoors.

EDIT (Feb 2, 2012): There was a small debate in comments before the Facebook change, however, there are a number of studies to support the metabolic difference as well as the biomechanical differences between overground and treadmill running:

1) Differences in gait while walking were observed in mid- to late-stance phase (mid-stance is the phase of walking where your foot is directly under you, and late-stance being just before you push off with your toes) between treadmill and overground conditions, particularly at higher speeds

White, SC et al. Comparison of vertical ground reaction forces during overground and treadmill walking. Med Sci Sports Exerc 30(10): 1537-42, 1998

2) Differences in gait while running were also observed in mid-stance phase were reported between overground and treadmill running, with differences in oxygen debt (overground incurring 36% more oxygen debt than treadmill running).

Frishberg BA. An analysis of overground and treadmill sprinting. Med Sci Sports Exerc 15(6)478-85, 1983.

This is contrasted by another more recent study that concluded that there was no metabolic difference between the two conditions though the data were only collected at the last 150m of a 950m run.

Basset DR et al. Aerobic requirements of overground versus treadmill running. Med Sci Sports Exerc, 17(4):477-81, 1985.

3) Differences in muscular activity were noted between overground and treadmill running with greater activation of the soleus muscle during push-off in the overground condition.

Baur H et al. Muscular activity in treadmill and overground running. Isokinetics and Exercise Science 17: 165-171, 2007.

Six people. One study. No practical outcomes. You drink protein before working out.

2010-05-17T13:42:00.005-06:00

There is a neat research tool that I use a lot. It's called the Web of Science. A lot of you use PubMed to find articles. You punch in a topic and it spits out a list of studies about that topic (roughly). Web of Science is a similar database, but it's like a reverse lookup for studies. I punch in a study and Web of Science tells me about all the studies that have citied that study (i.e. have listed it in the references). This is an extremely useful tool when looking for follow-up studies.

We've already talked about very recent evidence about pre-workout protein and energy expenditure, so this week, I wanted to find the most recent evidence of using pre-workout protein for muscle growth, since that's probably the REAL reason you're drinking protein before a workout. While there are some studies that have looked at post-workout protein as well as both pre and post-workout protein, surprisingly, there haven't been many studies on just pre-workout protein use and muscle growth.

Except one.

The Tipton et al study of 2001 is one of the earliest and only studies on the use of pre-workout protein and muscle synthesis. It's also the most widely used study in terms of justifying pre-workout protein. I'll be getting into the guts of this study in this post, but what's really interesting is that in the Web of Science, there haven't been any studies that citied Tipton et al 2001 that have looked at pre-workout protein use alone since then. And if a researcher was going to look at pre-workout protein use (either alone or in combination with anything else), they would be very remiss in not including this study in their references.

So, where's the beef? Apparently, this is it.

Tipton KD, Rasmussen BB, Miller SL et al. Timing of amino-acid-carbohydrate ingestion alters anabolic response of muscle to resistance exercise. American Journal of Physiology, Endocrinology and Metabolism 281:E197-E206, 2001.

Introduction

We know that lifting weights causes muscles to grow more than they are broken down. We also know that putting amino acids intravenously into someone after lifting weights increases muscle growth more than putting amino acids into someone at rest. But the question in this study is whether ingesting amino acids before exercise increases muscle growth more than ingesting amino acids after exercise.

Methods

Six subjects were recruited for this study (3 men, 3 women). Average age, 30 years old (SD 3.1 years). They were "recreationally active" and otherwise healthy. One week before the experiment, they were all familiarized with the strength testing protocol as well as leg press and leg extensions.

The night before testing, subjects fasted from 2200h until about 0600h. The next day, which was the day of testing, the subjects had catheters inserted into the femoral artery and vein as well as an IVs in both arms. Blood samples were taken and then an infusion of radiolabelled phenylalanine was started through one of the arm IVs, and an infusion of indocyanine green was infused through the femoral artery.

After 2 hours of infusion, more blood samples were taken to determine the concentration of amino acids in the blood. Muscle biopsies were also taken at this time from vastus laterals to determine the concentration of amino acids in the muscle while the phenylalanine was being infused.

After the muscle biopsy, the subjects drank either a placebo drink, or a protein-carb drink. The protein-carb drink had about 5 grams of essential amino acids (including a bit of radiolabelled phenylalanine) and 35g of sucrose (table sugar). The placebo drink was just water with aspartame.

The subjects then did 10 sets of 8 reps of leg press at 80% of 1RM, and then 8 sets of 8 reps leg extensions at 80% of 1RM. The subjects had more blood taken after the 4th and 8th set of leg press and after the 2nd and 8th (or final, whichever came first) of leg extension). Another muscle biopsy was taken between the 7th and 8th set of leg extensions.

After all of this, the subjects drank either a placebo or a protein-carb beverage (whichever one they didn't drink before). More blood was taken 10, 20, 30 45, 60, 90 and 120 minutes after exercise; and two more muscle biopsies were taken at 55 and 115 minutes after exercise.

Each subject did the whole over again, switching the order of the drinks at some later date.

[On a personal note, I cannot imagine going through all of this. Muscle biopsies hurt!]

Blood was analyzed for free amino acid concentration. Muscles were measured for free amino acid concentration. Calculations for amino acid uptake were made based on differences between arterial and venous blood samples, the rough theory being that nutrients are brought to the muscle through the artery and then the blood continues on its way with less amino acids in it. I won't go into the calculations here.

Statistics

Phenylalanine concentrations were compared using one-way ANOVAs for time. Differences between pre and post values were compared using t-tests (unadjusted for multiple comparisons). I stopped counting the number of tests after 20.

Results

Phenylalanine concentrations were higher in the pre group at rest than the post group. The phenylalanine concentrations remained higher than the post group at all time points. However, after adjusting for the differences at rest, these differences essentially became inconsequential.

In the muscle biopsies, the pre group had an uptake of 180mg (SD 50mg) of phenylalanine, while the post-group had an uptake of 39mg (SD18mg) of phenylalanine over the 3 hours of the study. This was found to be statistically significant, but this difference only seemed to be preserved if you tested for the entire 3 hours. When tested for only the last 2 hours, the pre group had an uptake of 195mg (SD 37mg) while the post group had an uptake of 130mg (SD 45mg).

[The reason why uptake is more over 2 hours than it is 3 hours probably has more to do with protein breakdown which was factored into the calculations.]

Discussion

So, what exactly does all of this mean?

Well, this study does show an increase of phenylalanine uptake with 5g of protein and 35g of sugar in muscle. There only one problem. Phenylalanine isn't metabolized in muscle cells. This study assumes that all other amino acids (including the ones that your muscles DO metabolize) are taken up as at least as well as phenylalanine (which, on the whole is probably not unreasonable). But it's a bit more of a leap of faith to take to assume that just because the amino acid is taken up by the muscle, that it is actually USED. And despite the intuitive idea that more amino acid uptake might imply increased protein synthesis, we have already seen in at least one other study, how producing "significantly" higher levels of something doesn't necessarily result in a change in the factor that we're ACTUALLY interested in: namely muscle growth.

We also don't know what happens beyond the 3-hour testing time frame. Does the supposed increased uptake AND metabolism actually result in bigger muscles? How much bigger? Over what time? And how generalizable are these results to the rest of us, given that only six people were actually studied?

So many unanswered questions, yet this is the level of research evidence upon which the recommendation to drink (or eat, but mostly drink probably) protein before your workouts to increase muscle mass is based. Yes, the recommendation in the fitness magazine. Seems pretty flimsy, eh?

This isn't to say that this is a bad study, because it's not. It answers the question it set out to answer. What's bad is that the recommendation YOU'VE received as a result is based on a single experiment (that I could find at any rate) on six people, using a test that doesn't directly measure protein synthesis and cannot make statements about whether the alleged increase in protein uptake actually results in larger "protein accretion", as the authors call it (or, in plainspeak, "bigger muscles".) I haven't found any other study to support this strategy. If you know of a study that has looked at actual muscle growth (and not a surrogate indicator), and pre-workout protein, let me know!

Death by sand--when do fine details matter?

2010-05-11T14:17:00.005-06:00

There are many iterations to the famous story about some guy who fills a large jar with big rocks and asks other people if they think the jar is full. They inevitably say, "Yes" and then he puts pebbles into the jar that fall in the spaces between the rocks and asks the same question for the same answer. He then pours sand into the jar that fills all the space between the pebbles and the rocks. Same question, same answer. And then he pours a liquid (water or beer) into the jar, the moral of the story in my favorite version being, "No matter how full your life is, there's always room for a beer."

The very fact that you are reading this means that you are a person who is looking to improve yourself. Maybe you're not quite started yet, or maybe you've been well on your way for many years; or maybe you're trying to help other people.

There is a lot of information out there on how to make yourself better. And it's not just about making yourself better, but making yourself better in the shortest amount of time possible. I am personally, on the whole, not a big "it's all about the journey" kind of person. The journey is hopefully pretty cool, but if I don't end up at my destination efficiently, I don't care what's on the side of the path (unless the goal is precisely to look at the the stuff on the side of the path).

It's easy to fall prey to "death by information" too. It's all at your fingertips: convenient, fast, and completely unfiltered. It's actually harder to get filtered information than it is to get it unfiltered.

However, what gets lost in the quagmire of easy information is the big rocks. In the case of your fitness and your nutrition, the jar is your time and your effort. It's not your money, or even your attention (which is we like to believe the marketers are after). You only have so much time, and you can only spend so much effort. And if you're filling your jar with sand, then there is no space for the big rocks.

Unfortunately, it's the big rocks that actually allow you to build anything of note. Sand is transient. It washes away with very little effort. Spending your time with sand means you're spending your time with details that are not going to have large impacts on the outcome. When to eat, what to eat, how much protein, how much fat, trans-fats, whole grains, sugar, sucralose, whether corn in any form including syrup is evil, which exercise style, steady-state cardio vs. HIIT, beta-alanine, creatine, nitric oxide…it's all sand. If your big rocks aren't in place, it doesn't matter how much sand you put in the jar, you're going to need a LOT of it to make any difference in your results.

If you're not taking care to spend most of your time and effort on the big rock-type things, you will ultimately fail to build anything of importance. So what are the "big rocks" of fitness and nutrition? These are just a few:

1) Are you consistent with your fitness and nutrition program?

2) If you are trying to lose fat, are you eating fewer calories than you are spending? How do you know?

3) If you are trying to gain muscle, are you progressively lifting more weight? How do you know?

4) Are you objectively measuring your progress? How are you doing this?

If you're not taking care of the things that will make the MOST impact on your health and fitness (and looks--let's face it, most of us could care less as long as we look good within reason), everything else is just fluff. Sand only makes the a difference when the jar is already full of large rocks. And you shouldn't need a whole jar full of it. Keep things simple. Clear the clutter. Defy the madness and don't get buried alive by the sand. Put your energy and effort into the things that will make the biggest difference. Worry about the small stuff only after you've taken care of the big things.

An iPod Shuffle! For almost free! (Oh, and protein timing)

2010-05-04T03:49:00.006-06:00

Eating protein before and after workouts has been touted to be one of the most important things you can do to decrease DOMS, increase protein synthesis, prevent protein breakdown, and in this article, increase your resting metabolic rate. The other claims…maybe I'll tackle those another day (This post is hellishly long enough)

There are many reasons to increase muscle mass. For one, it makes you look more attractive (for the most part). Increased muscle mass is usually associated with being stronger. However, increasing muscle mass to burn more calories while at rest (because muscle is more metabolically active than fat) is kinda like saying that ordering a diet Coke with two Big Macs and a large fries is calorie reduction--TECHNICALLY, you reduced the number of calories you COULD have consumed. But then again, you also didn't order McNuggets on top of THAT, so maybe you could have had that regular Coke after all, if that's the rationalization you're choosing to indulge in.

In other words, growing your muscles so that you can eat more (or exercise less, or lose weight faster) is not really where you want to spend your effort (if effort is a limited resource, and for most people, it is) because the benefit is quite negligible.

But I digress.

When to eat your protein lies amongst the magical treasure trove of the mythical muscle growth dragon. And if you take this study at face value in terms of the words they write, the treasure is within grasp. On the other hand, you could just wake up from your dream and see the reality.

Hackney KJ, Bruenger AJ, Lemmer JT. Timing protein intake increases energy expenditure 24h after resistance training. Medicine and Science in Sport and Exercise 42(5): 998-1003, 2010

Introduction

Individuals who engage in Heavy Resistant Training (HRT) increase muscle mass and strength. We know that resting energy expenditure (REE) increases for 12-72 hours after a heavy lifting workout (even if it may not be by all that much). However, one of the reasons we think EPOC (excess postexercise oxygen consumption) exists is because of the increased metabolic demand of creating new muscle (i.e. protein synthesis). Protein synthesis has been shown to be increased (again, even if it may not be by all that much in absolute terms as opposed to relative ones) up to 24 hours after a heavy lifting workout. So this group of intrepid researchers wanted to find out whether REE and RER (which is the respiratory exchange ratio and an indicator of non-protein energy consumption) went up more if you ate protein vs. carbs before a heavy lifting workout.

Methods

The researchers performed a double-blind, crossover trial between a protein-laden pre-workout drink against a carb-laden pre-workout drink.

A "double-blind" means that two sets of people didn't know which drink the subjects were getting. Usually it means that the subjects did not know which drink they were getting, and also that the researchers themselves did not know which drink the subjects were getting. However, this isn't always the case. A crossover trial design means that all the subjects got one of the drinks in an initial experiment, then got the other drink in a later experiment, with about 30 days between the two experiments.

[The paper does not tell us who was actually blinded in this study, whether the subjects could tell the difference between the two drinks by taste or consistency, and whether the researchers could tell which drink the subjects were getting, and who made the drinks?]

There were no explicit requirements for any of the subjects to qualify for the study. They did use resistance-trained subjects (defined as strength training or weight lifting for at least 3 days a week for at least 6 months), but whether this was something they decided beforehand or not isn't really known.

They measured body composition (with a BOD POD), one rep max's (bench press, squat, bent-over row, bicep curl, lateral raise, and shoulder press; as well as leg extension, leg curl and triceps extension on machines) and taught the subjects how to use a food log and how the testing would go (if you've ever tried any of these, you'll know that there is somewhat of a learning curve).

REE and RER were measured for four consecutive days, all at 0700h. The first day was a baseline measurement. The second day, the subjects drank one of the drinks 20 minutes before a workout [They don't tell us how they decided who to give which drink.]. The protein drink was 18g of protein, 2g carbs, 1.5g fat. The carb drink was 1g protein, 19g carbs, and 1g fat. Both drinks are available commercially. The workout was standardized for all of the subjects and each subject used a weight of about 70-75% of their 1RM.

Statistics

The researchers did the following significance tests:

1. A paired t-test to compare workout volume (sets x reps x load) between carb and protein trials
2. A paired t-test to compare REE between carb and protein trials on day 1
3. A paired t-test to compare REE between carb and protein trials on day 2
4. A paired t-test to compare RER between carb and protein trials on day 1
5. A paired t-test to compare RER between carb and protein trials on day 2
6. A repeated measures ANOVA (trial by time) to compare REE between carb and protein trials as well as baseline to day 2, 3 and 4.
7. A repeated measures ANOVA (trial by time) to compare RER between carb and protein trials as well as baseline to day 2, 3 and 4.
8. A repeated measures ANOVA (trial by time) to compare total energy intake (basically how much they ate per day in kJ) between carb and protein trials as well as baseline to day 2, 3, and 4.
9. A repeated measure ANOVA (trial by time) to compare macronutrient intake between the carb and protein groups as well as baseline to day 2, 3, and 4.

Significant results in the ANOVAs were further explored with Bonferroni tests, which is pretty good.

[1 - (0.95)^9 = 1 - 0.63 = 0.37, which is the probability that at least one of their "significant" p-values would lead them to the wrong conclusion. Look here if you need more explanation.]

Results

Nine people were involved as subjects in this study. Six of them were (should that be "are"?) men and three of them, women. One man dropped out of the study because he couldn't hack the lifting schedule, which leaves us with 5 men, and 3 women. The men were, on average 23 years old (plus or minus 3.8 years), and the women were 24 years old (give or take 1.5 years). The men had %BF of 12.6% (plus or minus 7.5) and the women, 26.5% (plus or minus 6.7%)

[That's about right for the age of your typical grad student. While they did have enough power to detect statistical differences (and more on statistical vs. practical later), the fact that there were only 8 people in this study means the results (if you want similar ones) are only applicable to people who are similar to these 8 people.]

In terms of the things that might confuse issues (i.e. confounders), diets tended to stay similar from one trial to the next. Workout intensity was also similar from trial to trial. Figure 3 in the paper is basically what all the hullabaloo is about:

The dark squares represent REE after protein consumption and a heavy workout. The hollow square represent REE after carb consumption and a heavy workout. The * represents a value higher than the baseline value for which p was less than 0.05 in this experiment. The # represents a value that is higher than the other trial for which p was less than 0.05.

As you can see, 24 hours after their first workout, both groups appeared to spend more energy at rest than they were spending before their workout, regardless of whether they had a high carb or a high protein drink 20 minutes beforehand. This higher rate of energy expenditure lasted at least 48 hours. However, at 24 hours, the resting energy expenditure in the protein trial was higher than the carb trial, and this seemed to be a difference that was greater than what we would expect to see by chance alone (p<0.05). style="font-weight: bold;">

Discussion

So, huzzah! Drinking 18g of protein 20 minutes before a workout increases resting energy expenditure more than drinking 19g of carb 20 minutes before a workout! Drink that protein! A six-pack and/or slimmer waist awaits you!

Or…save your money?

As we've visited before, a statistical difference does not beget a practical or important difference. There are three interesting features in figure 3 (which is what this paper hangs on) that aren't really discussed in the paper itself.

1) REE went from an average of 93-ish to 100-ish in the protein trial in 24 hours. However, REE went from an average of 91-ish to 98-ish in the carb trial in 48 hours, above the REE in the protein trial at 48 hours. Let's take an 85kg guy (the mean mass of the male subjects). And since I don't want to do elementary school-ish math dividing triangles up for areas under the curve, let us assume that the measured REE is the REE for the entire 24 hours:

Protein trial: (93kJ/kg/day x 85kg) + (100kJ/kg/day x 85kg) + (95kJ/kg/day x 85kg) = 7905 + 8500 + 8075 = 24 480 kJ in 3 days

Carb trial: (91kJ/kg/day x 85kg) + (95kJ/kg/day x 85kg ) + (98kJ/kg/day x 85kg) = 7735 + 8075 + 8330 = 24 140 kJ in 3 days

That's a grand whopping total difference of 340kJ over 3 days. In calories (kcal), that's…81 calories.

But Bryan, you might say, "Couldn't you just workout on day 2, and keep the REE at 100kJ/kg/day?" This brings us to point 2:

2) Let's argue that you can actually do exactly that. The argument forces us beyond what the study can actually tell us, because we don't know what would happen if instead of doing nothing on day 2, they would have ingested another 18g of protein and worked out. And the black square for that kind of figure could really be anywhere. But, even if that were the case, let's look at the actual numbers:

The protein trial had an average REE of 100 kJ/kg/day at 24 hours. The carb trial had an average REE of 95 kJ/kg/day at 24 hours. Again, for an 85kg guy, that would be 8500kJ/day vs. 8075 kJ/day, for a difference of 425 kJ/day. In calories, that's 102 calories per day.

HOWEVER

3) The baseline REE for the two trials was different. Not necessarily "statistically" so, but still different. And on a scale where a "statistically significant difference" is 5 points, a baseline difference of 2 points is an interesting one to think about.

If we take the ACTUAL difference in REE, we see a very different picture:

The protein trial went from 93-ish to 100-ish. That's an increase of 7kJ/kg/day.

The carb trial went from 91-ish to 95-ish. That's an increase of 4kJ/kg/day.

For the 85 kg (187lbs) guy, protein caused his REE to go up by 142 calories for a day, while carbs caused his REE to go up by 81 calories for a day. That's a 61 calorie difference between the two drinks once you've adjusted for the difference that they started with.

And what about the drinks themselves? If we take only the primary macronutrient, the protein drink was 18g x 4kcal = 72 calories; and the carb drink was 19g x 4kcal = 76 calories.

Bottom line: No matter how you slice it, I'm not sure 81 extra calories per day (point 1), 102 extra calories per day (point 2), 61 extra calories per day (point 3), or even 142 extra calories burned per day (which is the "extra" you MIGHT burn compared to drinking nothing at all--a very unlikely scenario since we know a workout alone also increases REE) PROVIDED you weigh 187lbs means much of anything (you can do your own math for your own weight, but the benefit decreases with decreasing weight.) If we were to argue that your REE didn't change AT ALL after a workout, you would only net a 70 calorie benefit in the first 24 hours (since drinking the protein puts 72 calories into your system.) You could simply not eat 70 calories somewhere in your day, not eat anything before your workout, and achieve the SAME effect, while saving the cost of buying those 70 calories AND the cost of buying the extra protein.

How much money do you save? Well, online, the protein powder they used in the study costs $9.99 plus shipping for 13 servings. Shipping is $5.99, so a single serving costs $1.23 USD. That's how much 72 calories costs. Now, if you're of the school that "every little bit counts" when it comes to calories and weight loss, that's 49 days for 3500 calories (1 extra pound of fat) provided you're already eating under maintenance. Monetarily, that's $60.27 for that pound. Just for not buying the protein. You can buy an iPod shuffle for that kind of money.

So when it comes to weighing the costs and benefits of timing protein for the purposes of increasing resting energy expenditure and this study, the best timing seems to be no timing at all. And you can afford to buy yourself some tunes and STILL lose fat. How is that not a win-win?

More is not better--when statistics turn bad (it's just not as entertaining as when animals do)

2010-04-27T19:39:00.006-06:00

As with everything, more is not usually better. In statistics, more actually makes you more prone to being accidentally wrong (or, in statistics-lingo, spurious). Today, I'd like to talk about a basic concept that is taught to students in their introductory statistics courses (and hence, you would think, most researchers): The effect of multiple significance testing.

Taking off from last week's post: In an experiment (or bet) where a coin is flipped 60 times, the chances that less than 22 heads or more than 37 heads will come up are less than 5%, or 0.05 (0.025 for less than 22 heads + 0.025 for more than 37 heads), PROVIDED the coin is a fair coin.

However, as you probably very astutely noted, even if the coin is fair, it IS possible to flip less than 22 heads or more than 37 heads. It certainly isn't impossible. It's even possible to flip 60 heads or 0 heads with a fair coin (it's just highly improbable). When we incorrectly conclude that the coin is NOT fair when, in fact, it is (because we happened to flip a high improbable result), we are committing a Type I error. In statistic-speak, we reject the null hypothesis incorrectly.

Remember, that if a statistical test yields a p-value of less than 0.05, we make the inference that there is something going on between the two groups, because for us to observe the difference that is present between them would be highly unlikely if there wasn't anything going on. But it is possible that we are wrong in making that inference. And the likelihood that we are making that mistake increases as we do more tests:

If the null hypothesis (i.e. there is no difference between the groups) is true and we consider 0.05 to be the critical level at which we would infer that there is something going on between groups, there is a 0.95 probability of yielding a non-significant p-value when we do a single test (i.e. that the statistic would fail to show a significant value by chance alone).

If we do two tests, the probability of BOTH of them being non-significant is 0.90. We get this number just from multiplying the probabilities of both tests being non-significant (as per the laws of probability):

0.95 x 0.95 = (0.95)^2 = 0.90 (remember the ^ means, "to the power of")

If we do 20 tests of significance, the probability that ALL of them will be non-significant is:

(0.95)^20 = 0.36

Since the sum of all probabilities has to be 1, the probability that at least one p-value that is less than 0.05 when in fact, nothing special is going on (the null hypothesis is true) is:

1-(0.95^20) = 0.64

So, in a study (like most of the beta-alanine trials) in which 20 or more p-values are generated, there is more than a 50/50 chance that at least one of the p-values less than 0.05 is not reflective of the reality.

There ARE ways to correct a p-value for multiple comparisons; and there are ways to minimize detecting a "spurious" p-value. Unfortunately, many researchers don't know or understand this fact and will often hone in on the one, or handful of significant p-values in the sea of non-significant ones to say, "Ah ha! See? See? There IS something going on!"

A good example of this is the beta-alanine study in which 36 subjects were given either beta-alanine or a placebo and then tested for multiple variables. I stopped counting the number of tests after 20. There were several significant p-values, amongst which was lean body mass. The authors concluded that beta-alanine increased lean body mass (despite it not doing so more then the placebo group).

This is also why reading ONLY the abstract of a study is generally a bad idea, because an abstract will usually only contain the positive findings due to limited space (usually 200-500 words, depending on the journal). Reading the back of the book isn't the same as reading the book itself. The same goes for reading only the abstract of a paper.

P.S. If you're coming to my blog for the first time from the Phi Life podcast, welcome! Alas, I have nothing to sell you. And if you haven't heard the Phi Life podcast, you're missing a great show. Not that me being on it makes it that way...

This episode is brought to you by the letter p

2010-04-20T16:36:00.005-06:00

What does the p-value actually mean?

Today, I was going to talk about the effects of multiple significance testing, but then I realized that to do that, you would need to understand what the p-value means, and that I haven't actually written about that in this blog yet. So, one step back before we take 2 steps forward, shall we?

Most researchers bow down to the almighty p-value. The p-value, for them and most casual science readers, is the number that tells them whether one result is different from another result (usually either between two comparison groups, or as a pre-post measurement). Most researchers use 0.05 as the critical level by which they define "significant" against "non-significant". A p-value less than 0.05 is considered "significant" and above 0.05, "not significant". This is different from "important" and "not important", which I have discussed (perhaps prematurely) before.

To understand why multiple testing is inappropriate, you have to understand what the p-value is. Again, most researchers, and most casual science readers tend to use the incorrect definition that the p-value represents, "the probability that the null hypothesis is true." However, this is a massive simplification of what the p-value actually represents.

To illustrate the p-value, I fall back onto the classic coin-toss.

From elementary school (and barring high improbable events like landing on the side), we know that the probability of flipping a heads on a fair coin is 0.5, and the probability of flipping a tails on a fair coin is 0.5. No big mental energy spent there.

If we were to put money (because the root of statistics is gambling--really, it's true!) on how many heads would be flipped in 60 coin tosses, you'd be pretty safe to bet 30 heads, or somewhere around that number. Still no big mental energy spent there.

If 31 heads, or 29 heads were actually flipped in the gamble, and you had bet 30 heads, you would probably shrug your shoulders and disappointingly hand over your money.

And at 33 heads, or 27 heads you might still do the same thing.

But at some point, the number of heads (either higher or lower than 30) would make you wonder if the coin was rigged (assuming a fair flipper), and if anything beyond your range of "fairness belief" was actually flipped, you might not walk away from the table, a poorer soul, without some sort of fight.

Take out a piece of paper. Write down what that number would be for you. Above what number of heads and below what number of heads would you start a fight to get your money back?

Got it? Good.

If someone actually went and flipped a fair coin 60 times, and then did this thousands of times, you would end up with a graph that looks suspiciously like this:

The x-axis represents the number of times heads are flipped out of 60. The y-axis represents the number of times that particular number of heads came up as a proportion of the total number of experiments.

The green lines represent the number of heads below (on the left hand side) or above (on the right hand side) which there is a 0.025 probability of attaining a result more extreme (i.e. there is a probability of 0.025 of flipping 22 heads or less, and there is a probability of 0.025 of flipping 37 heads or more).

Statistically, if we were to use 0.05 as our p-value cut-off (or alpha level), we would say that the coin wasn't fair if someone managed to flip less than 22 heads or greater than 37 heads, because the probability of that happening is so low if the coin is fair.

However, you can only make the statement, "There is a probability of 0.05 of flipping either less than 22 heads or more than 37 heads," if the coin is fair to begin with! If the coin was ACTUALLY weighted, the curve would look totally different!

The coin has to be fair.

The interpretation of the p-value therefore, is the probability of observing the result obtained in the study under the condition that the null hypothesis is true (i.e. the coin is fair; i.e. there is nothing special going on; i.e. in the real world, there is no difference between the groups). If that probability is very low (less than 0.05, or 5%), then we make the inference that the results must be because there IS something special going on (e.g. the supplement does in fact, do something above and beyond a placebo effect.)

Now, what number did you write down?

If your numbers were more extreme than 22 and 37, then the 0.05 cut-off, in this scenario, isn't good enough for you. If your numbers were less extreme than 22 and 37, then you might be prepared to accept a p-value that is greater than 0.05 as a cut-off.

"But Bryan," you exclaim, "it IS POSSIBLE to flip less than 22 heads or greater than 37 heads with a completely fair coin!"

Yes, young grasshopper, it is, but that is a topic for another day.

Beta-alanine revisited: Failing to plan, or planning to fail?

2010-04-11T18:06:00.011-06:00

In the past 2.5 years, a few more studies on beta-alanine have emerged. As I've written before, my goal isn't to become the anti-beta-alanine blogger, but I do feel that watching this supplement develop from its relative inception to its current state does provide an interesting prototype for how similar products develop a strong following despite the limitations on the research available to support (or not support) its use.

Surprisingly, beta-alanine has not panned out to be as effective as previously touted. One study on the effect of beta-alanine supplementation on endurance performance and body composition in men doing HIIT failed to detect a difference BETWEEN placebo and beta-alanine in terms of VO2-peak, time to exhaustion, or body composition, despite finding statistically significant differences WITHIN groups (i.e. the beta-alanine group did better compared to itself at baseline, but on average, no better than the placebo group).

However, the prevailing limitation to these studies, ultimately comes down to sample size, and as a result of what I'm going to talk about in this post, whether the study that would be required to demonstrate an effect for beta-alanine on the variable of your choice, AND that would show that the difference observed between a beta-alanine group and a placebo group was VERY likely not an effect observed by chance alone would ever be possible or even worth doing.

The p-value is a number. That's it. It is mathematically calculated. The calculation may be a little complicated, but it is still a calculated number. So, yes, a p-value can be manipulated, insofar as one can optimize the factors that affect the p-value. You can, of course, OVER-optimize for a significant p-value, but that's usually pretty expensive, and the supplement companies would have us believe that it's too expensive to run an optimized study, so there's very little danger that someone is going to out of their way to fund an OVER-optimized one.

The equation that is used to compare two averages or means to each other looks like this:

N is the total sample size (the total of both groups together). The weird "o" with the squiggly tail is a small case sigma, and represents the variance of the sample (in this case, a standard deviation). D represents the mean difference observed between the two comparison groups. Zcrit is the Z-score for the critical p-value at which one would conclude that the effect observed is not by chance alone; Zpwr is the Z-score for the probability that one would fail to detect a difference between the two samples incorrectly, and is related to power (for those of you who care, but it's not actually very relevant to the point I want to make).

Zcrit and Zpwr are two variables that most researcher rarely touch. There are reasons to mess with them, but on the whole, Zcrit will be 1.96 (the Z-score for a p-value of 0.05) and Zpwr will be 0.842 (the Z-score that corresponds to 80% power).

The number 4 is just the number 4.

So, ultimately, the only two things that ACTUALLY vary when it comes to calculating a sample size is sigma and D.

Some of you might ask at this point, "Well, aren't you most interested in the power of a study that employs a small sample size?"

I'm of the opinion that my brain is actually quite lazy (read: I am lazy.) And while the higher functioning parts of my brain COULD deal with interpreting a power number, I feel that the effect of spitting out a power calculation is actually quite thinking-intensive and doesn't quite capture the appropriate sentiment of exactly how harmful a small, underpowered study actually is.

Enough of this geek-speak, let's plug in some numbers, shall we?

In one of the more recent beta-alanine trials (a randomized controlled trial of 46 college aged men; that's 23 per group), time to exhaustion in the beta-alanine group at baseline was 1168.2 seconds (SD 163.6) and in the placebo group at baseline, 1128.7 seconds (SD 166.9). After 28 days of beta-alanine or nothing (and HIIT), time to exhaustion in the beta-alanine group was 1386.7 seconds (SD 234.9) and in the placebo group 1299.6 seconds (SD 164.9).

At a glance, the beta-alanine group fared better. They started out marginally better than the placebo group as a whole (about 40 seconds better), and ended, on average, about 87 seconds better than the placebo group. However, while the average time to exhaustion was better, it seems that the consistently in the result got worse, as reflected by the increase in the variance (or spread) of time to exhaustion values in the beta-alanine group. Eight-six seconds can mean the difference between gold and silver. But, in recreationally active men, 87 seconds probably doesn't mean a whole lot. It probably means even less if you're the guy on the lower end of that variance, because it means you might have done WORSE than when you started.

But, for argument's sake, let's say 87 seconds is REALLY important. And let's give beta-alanine users the benefit of the doubt, since we can only use one variance number for this equation. We'll fudge it so that as a group, they were just as consistent as the placebo group with a standard deviation of 164.9.

So, according to the sample size equation (the "^2" means squared, 'cause I have no idea how to superscript something in this blog editor):

N= 4(1.96+0.842)^2(164.9)(164.9) / (87.1)(87.1)

N= 112 (rounded to the nearest even number)

That means to demonstrate an 87 second difference between the two groups, with a standard deviation of 164.9 seconds, you would need 56 men per group; or slightly more than twice as many men as were actually used in that study.

But how many of you care about time to exhaustion? You just want to look good! In the same study, the average percent body fat in the beta-alanine group was 13.7% (SD 6.3) and in the placebo group, 16.1% (SD 7.5). After 28 days of supplementation of beta-alanine or placebo, the beta-alanine group had an average of 13.7% body fat (SD 5.6) and the placebo group had an average of 16.0% body fat (SD 7.9). That's a mean difference between groups of 2.3%. Again, we will use the more advantageous standard deviation (5.6). Never mind the fact that body fat percentage didn't actually change at all from pre to post-testing in the beta-alanine group itself; let's say a difference of 2.3% body fat (which you would theoretically benefit from being on beta-alanine) is practically, somehow important.

N= 4(1.96+0.842)^2(5.6)(5.6) / (2.3)(2.3)

N= 186 (rounded to the nearest even number)

That means to demonstrate a 2.3% difference in body fat with a standard deviation of 5.6%, you would need 93 men in each group to calculate a p-value that would indicate that the 2.3% wasn't a number obtained by chance alone. That's roughly four time the number of subjects used in this study.

So what does all of this mean?

Well, there are two issues at play here. The first issue requires that you understand something about your body and what you want out of a supplement. If increasing your time to exhaustion by 87 seconds, plus or minus 164 seconds above and beyond what you could normally do with no beta-alanine (and yes, that means you COULD get slower--well, actually it means the data is probably not normally distributed, but for the sake of argument, let's put that aside for now), is REALLY important to you, then it MIGHT be worth taking beta-alanine.

However...

If the difference we're seeing in these studies between placebo and beta-alanine groups IS REALLY important, these trials are being set up to fail. Why? Because they're inadequately powered. To answer the question, "Does beta-alanine increase time to exhaustion by 87 seconds plus or minus 164 seconds more than a placebo?", the study would require a MINIMUM of 112 subjects.

The existing studies are destined to fail, unless the difference between groups is huge (i.e. way larger than 87 seconds), or the variance is very low(i.e. lower than 164 seconds). It is therefore impossible, with the current designs, to determine whether the effects observed in the beta-alanine groups are due to beta-alanine or freak chance. It is mathematically impossible for the equation, under the current parameters, to give us any information to guide our decisions about whether beta-alanine works or not!

And if the differences we're seeing between placebo and beta-alanine groups AREN'T important (i.e. if I'm taking a supplement to improve my body-fat, it had better reduce my body fat by more than 0.1 percent (Seriously, is that even real, or just within the error of measurement?), then there's no study of any size, significant p-value or not, that would indicate to me that the supplement is worth taking.

Bottom line: If the differences we're seeing in these beta-alanine studies ARE practically important, then until there are studies with 186 people in them, the question of whether beta-alanine works under minimally-biased conditions will remain unanswered. And perhaps that's where the companies want the answer to be--unanswered; so that you will continue to rely on anecdotal evidence to make your decisions. My opinion is that none of the differences between placebo (which IS different than taking nothing at all) and beta-alanine are important enough to warrant larger studies. It just doesn't seem to have the effects that everyone is purporting it to have (and yes, this is despite there being very good physiological evidence that it does increase intramuscular carnosine, but the increase doesn't seem to translate to anything useful).

The EBF point of view: Remember, that fitness decision making has three main components. Personal preference can and does at times, overrule all other things. But let's not pretend the decisions made on personal experience are based on some "scientific" evidence. It's been 2 years since my last beta-alanine post, and we are no further ahead now than we were back then.

References:

1. Smith AE, Waler AA, Graef JL et al. Effects of beta-alanine supplementation and high-intensity interval training on endurance performance and body composition in men; a double-blind trial. Journal of the International Society of Sports Nutrition 6(5), 2009.

The most successful people aren't necessarily the ones you want to listen to

2010-04-08T09:24:00.003-06:00

I recently joined Twitter. Mostly, because I wanted to see what the fuss was about and it seemed like a neat way to tap into yet another network. The interesting thing about Twitter early on, is that (for those of us who have attention spans of gnats) that Twitter feed page doesn't change very often unless you start following people's Twitter feeds (I'm sorry, but "tweeps"? Seriously, no.) So I started searching for names of people I thought would be interesting to follow and whether they had feeds to follow or not. And on my journey through Google, I stumbled on this excerpt from someone I would consider to be one of the most impressive physique models in the world. I've broken them down, point by point instead of the entire crammed-in paragraph. but they are sequential (and I don't think they're taken out of context):

1) "A few "rules" I live by is that I try to go to bed on an empty stomach so my body is breaking down fat throughout the night."

2) "I drink tons of water and stay away from sugar; I eat low-carb and high-protein diet; I don't eat anything four hours before I go to bed; "

3) "I do cardio in the morning and lift in the evening before going to bed; I eat two large meals a day (sometimes only one), and above all I check my pride at the gym door everyday."

4) "I don't go after lifting a certain amount of weight. I go after the pump which is achieved quicker with lighter weight and proper form as opposed to your ego getting involved and causing you to lift a load too heavy for you that causes you to get out of form and possibly injured. "

5) "Also, on eating, I eat to fuel my body ... not to satisfy an appetite. The hell with what it taste like -- it's about feeding your body what it needs, not your taste buds. Now, some will read what I say and call BS to my routine, which is fine."

6) "This is what works for me, maybe it works for you, maybe not ... we all are different, but what one cannot say is that it hasn't worked for me as I have more covers than anyone else in the world in the last two years and recently named the number one male fitness model in America by Iron Man Magazine and just this month, named one of the "25 fittest Americans" by Men's Fitness ... hard to argue with success."

Point number 6 is the absolutely, most difficult argument to counter. Clearly, what he does works for him. And he has the covers and nominations to show for it. The N of 1 trial is clearly a success. And it really is hard to argue with success.

However, almost everything this model reports that he does runs counter to the present-day advice of who we might consider as leading experts in this very field. Going to bed on an empty stomach, cardio in the morning, infrequent feeding, going for "the pump"? I haven't heard anyone utter these phrases since the late 1990s.

This brings into question the entire premise of decision-making in fitness. Has this model succeeded _in spite_ of what he does, or is this, in fact, the optimal interaction between his genetics and environment? And from a consumer/trainer perspective, can any of us make decisions on our training/nutrition based on these "rules"? Albeit, he's not proselytizing his rules; he's just telling us what works for him. Nonetheless, the testimonial evidence is difficult to dismiss.

This case is where the rubber meets the road. Given enough monkeys with typewriters and enough time, Shakespeare will be reproduced. I suspect that this model would be the way he is, no matter what approach he took to his training and nutrition (short of being completely sedentary). How many clients/consumers are succeeding _in spite_ of what they are doing? And how much of that success can be attributed to the trainer or program?

I think the hallmark of an excellent trainer is one who can identify under what circumstances something is going to work, or not work; and one who is able to quickly adapt to things that aren't working, despite there being a veneer of success.

The testimonial is never going away--particularly in the current trends of marketing strategy. Fitness professionals who tout numerous success stories are successful at producing results in a select portion of their client population. I, for one, think we would be able to differentiate those who are successful because they are truly savvy vs those who succeed because they are lucky to stumble on clients who will succeed no matter what they do to them if there were more on how initially unsuccessful clients became successful ones.

Are your fitness decisions fully informed?

2010-03-17T12:04:00.007-06:00

Everything we do shapes our opinion of effectiveness. The opinions of others also shapes our ideas of effectiveness. And while your own recall of what works and what doesn't work likely falls on the side of the majority of the time (if you prescribed intervals vs steady-state cardio for a bunch of clients, and most of them lost more fat on intervals, chances are your recall bias is unlikely to think that steady-state cardio is the way to go), it is nonetheless, biased, because you are also less and less prone to prescribing other things when you think you've found the thing that actually works. And sometimes you remember the dramatic cases preferentially, when it's the other thing that works most of the time.

From a "public health/fitness" point of view, it's also a waste of time and resources for 1000 fitness professionals to individually try the new thing against their old thing when the new thing is shown not to have an advantage over the old thing in a well-conducted, unbiased, generalizable study. Even if it takes just 10 clients to figure out the new thing isn't really worth doing, that's 10 000 clients who just wasted however much time it took (likely at least a month) for their fitness professional to figure out it wasn't worth doing. And that's assuming that there are ONLY 1000 fitness professionals who adopt this approach.

There is a trend in medicine. It's called Evidence-Based Medicine. It's such a popular trend, that it's not even optional in medicine. Every major certifying exam in medicine has a component of "EBM" in it, worth as many marks as the question on how to cut open a belly, which drug to give to someone in rapid atrial fibrillation, or how to tell if someone has "flesh eating disease". As with all things that are mandated, EBM is always regarded with mixed (or not so mixed) feelings--usually a mixture of loathing, hatred and confusion. We, of the firmly-in-the-EBM camp, have struggled to make the EBM approach to medicine more palatable and accessible, and sometimes, compromising our ideal goal of everyone having as much understanding as we do of the issue--much like how the recommendation of 20 CUMULATIVE minutes of exercise per day having an incremental health benefit really does just compromise the whole goal of making people, in general, less fat. People, in general, view exercise like bland rice cakes. They're about as exciting and tasteful as cardboard. There are some people in this world who LOVE bland rice cakes and cardboard; and in a world where bland rice cakes are being mandated, bland rice cake lovers are trying to figure out a way to make them at least tolerable; because we know you'll never love bland rice cakes (or in some people's case, plain tilapia and broccoli) as much as we do.

So why is this relevant to you? And more importantly, how does "evidence" (which may or may not be formalized research) help inform your decisions? To this end, some of the people who are smarter than me, have come with a "new" framework in which EBM (and hopefully, EBF) can be practiced in a sane, practical and useful manner.

EBM has traditionally been viewed as an "us vs. them" approach to medicine. The practitioner feels compelled to change their practice based on some sort of evidence and often feels at odds with their personal experience and clinical acumen. Sometimes, this is justified--why fix something, that in your mind, isn't broken?It's interesting to see how physicians interact with research evidence because this "us vs them" mentality is still very prevalent. Yet, if you were to talk to someone who is genuinely comfortable with the EBM philosophy, none of them see it that way. The researchers aren't trying to take over the world--not yet anyways. But for whatever reason, it took a fairly talented writer and one of the big Kahuna's of EBM, Gordon Guyatt, to succinctly frame what we have all been thinking for years yet have been unable to express adequately to our colleagues.

The current model looks a little bit like this:

This model pits clinical expertise against research evidence. Clinical decision making occurs in the tiny intersection where clinical expertise, research evidence and patient factors intersect. This means that large parts of clinical expertise are distinct from a large proportion of research evidence, and vice-versa.

But as Dr. Guyatt so elegantly frames it, there is room for a newer paradigm:

The "new" model basically redefines what it means to be an expert. It is an integrated model--one in which clinical expertise is comprised of knowledge of the patient's body, physiology and disease (Clinical state and circumstances); the patient's preferences and research evidence. The clinical decision, therefore, is a true decision and not a substituted decision, overridden by the research.

By this token, a decision that is based on expertise that does not include research evidence can be viewed as an incompletely informed decision. It is a decision that is largely based on biased recollection of personal (and perhaps somewhat limited) experience and on knowledge that may or may not be current! It is what we might call "dogmatic" practice.

In terms of being a trainer or a coach, this paradigm doesn't really change much. As a fitness professional, program design decisions are largely influenced by personal experience (both as the trainer and the trainee--which is a perspective that most physicians will never have); formal and informal ongoing instruction, which is largely self-selected (i.e. you tend to choose to be taught by individuals who share your training philosophies as opposed to those who have different ones); and your educational foundation (e.g. whatever textbook you used in your certification exam, or the undergraduate degree you might have in a kinesiology-related field that supplied you with basic physiology-type knowledge). Program design is further modified by client preferences and realities (e.g. you cannot design a 5-day a week program for someone who cannot train five days per week; you cannot design a program that requires 2-hour sessions if your client can only realistically train for 45 minutes per workout; and you can't really recommend that your client increase their milk intake if they're lactose intolerant).

However, I would argue that if you're not taking in some sort of systematically conducted research into your programming decisions for your clients, that you're making decisions that are fundamentally incompletely informed. I think given enough clients, and enough time, any trainer can probably build a "successful" client base, on the same basis that every medical school class in North America has great grades--your fitness practice simply self-selects for "excellence" because those clients who experience positive results will stay with you, while those who don't will leave you and thus, won't ever really show up on your "training failures" radar. These "successful" trainers succeed in spite of their decisions, not because of them.

So what does research get you anyways? Minimally biased research gives you the perspective that you don't have (and in some cases, don't want). It attempts to evaluate decisions in an objective, unbiased way, such that the failures are counted in with the successes, so you're not blinded by the self-selection bias that exists in your own "practice". The downside to this paradigm is that it demands a baseline of research literacy that is not something that currently taught in certification programs, or even sufficiently at the undergraduate level (medical or otherwise). So if you're serious about making fully informed decisions about your clients and using the full extent of the resources that are available to you; perhaps you might consider spending _some_ portion of your time learning about becoming research literate.

References:

1. Haynes RB, Devereaux PJ, Guyatt GH, Clinical expertise in the era of evidence-based medicine and patient choice. ACP J Club. 2002 Mar-Apr;136(2):A11-4. Figures stolen shamelessly from this editorial

New directions

2010-01-17T10:14:00.002-07:00

I'm still surprised that people still come to this site and to all my readers: It's incredibly flattering. I still get the occasional e-mail from a reader and every time, whether positive or not-so-positive, it's still amazing.

You may wonder why I haven't been writing. Apart from the rigors of residency, I haven't been writing because I've been trying to decide on the direction of the blog. I've gained a bit of a reputation as the nay-sayer blogger: Nothing works; it's all a hoax and they're all out to get you and your dollar and your time. And while I don't have an issue with being that person (I believe that growth and forward movement comes from debate, and a discussion in which everyone agrees is a just a party), there comes a point when one has to re-evaluate the contribution one is making to the overall community. The role I want to take is not one in which proponents of new training methods/supplements/rehab techniques are driven away, but rather one in which my commentary sheds light on decision making.

In many ways, the challenges that I've faced with this blog are no different than the challenges I face with the same issues in surgery. And surgeons are far more bullish than any trainer or coach that I've met. But there is a paradigm shift occurring, and I'll keep pushing to be a part of that. The whole idea of "evidence based practice" is still quite new. The concept wasn't really around until the early 1980's. And for a field of study, that's pretty young. So while those of us who are proponents of it are big fans of it, we are still struggling in terms of how to really integrate it in a practical, palpable way that makes sense to those people who would practice it, if only it didn't seem so pedantic and irrelevant.

That being said, there have been some steps forward in the past few years, and even within the "evidence-based" field, the way we look at how this approach can be applied is changing dramatically. So, in the coming entries, I'll be talking more about what the whole concept means and how it applies to fitness professionals, their clients in general, and to you, the fitness consumer.

Don't worry, there will still be research reviews, but hopefully this new direction will bring a better life to this flailing blog.

Where is your information coming from?

2009-10-04T07:51:00.005-06:00

Even though it's been a year since I've written in this blog, I still get offers of sponsorship or "partnership" with other sites, services and products. Most of the time, it's to create some sort of linking relationship: If I put their site on my links, they'll put my site on their links and presumably, the traffic to both of our sites equilibrates to a higher level than ever before.

But more recently, I got an email from a company asking me if I would be willing to write reviews on other websites and to post my reviews of those websites in my blog:

"Hello,

I'm Joy from XXXXXXX.com.

I would like to know if by any chance you would be interested in getting paid to publish reviews of products and websites on your blog http://evidencebasedfitness.blogspot.com/.

If you are interested please let us know the amount of money you want in order to publish a review by clicking the following link: XXXXXXXXX

As soon as you do that we'll start sending you paid review proposals from our customers.

Thanks,

The XXXXXXXX Team"

The customer of this company, is presumably a website that is looking to increase its traffic. And the way in which the company can help that website is by paying blogs to write about their customer.

It seems like a fairly straight-forward method of advertisement, only there's a minor catch: There's no obligation on a blogger's part to declare any conflict of interest when they write a review in their blog. And this is where things get murky.

I decided to take a look at their offer--What do I have to lose? And here's the kicker:

If I'm willing to NOT declare my conflict of interest, I can make much more money from this company. If I write an endorsement of a website on MY blog and conceal the fact that I was paid to write the endorsement from my readers, I can make more money.

Now, I haven't written a research review here in a year. I don't know when I will write another one still. My blog's purpose is not to review other people's websites, and I don't intend on changing that. So, I'm not overly inclined to change my relatively inactive blog to make a few bucks. But, you have to admit, this system is a pretty... interesting one.

Where do you think your information is coming from?

You don't always get what you want, even if you get what you need

2008-10-10T18:59:00.007-06:00

One of the newer supplements on the market are the aromatase inhibitors. They purport to increase free testosterone levels by inhibiting the enzyme that is responsible for converting androstenedione to estrone as well as converting testosterone to estradiol. By preventing the breakdown of testosterone precursors and the breakdown of testosterone itself, the concentration of testosterone should theoretically increase.

Sounds great, doesn't it?

If any of you have read the advertising, Gaspari Nutrition's Novedex touts the Baylor University study in its ad literature. This paper was published in 2007.

Willoughby DS, Wilborn, C et al. Eight weeks of aromatase inhibition using the nutritional supplement Novedex XT: Effects in young, eugonadal men. International Journal of Sport Nutrition and Exercise Metabolism, 17: 92-108, 2007.

Introduction:

Lots of guys are interested in getting more muscular. Some of them turn to anabolic steroids. Others have tried testosterone precursors like androstenedione, but both of these substances are technically banned or outright illegal in many countries. However, if you can block, or partially block the action of the enzyme that converts androstenedione to estrone, and testosterone to estradiol (a task accomplished by the same enzyme), you should be able to increase free testosterone and therefore achieve an anabolic effect (e.g. increase lean mass, decrease fat mass) because estradiol is the main hormone that feeds back to your brain to tell it to produce less stimulating hormone to your testes (which is where testosterone ultimately comes from). This enzyme is in the class of aromatases. And thus, the ingredient in Novadex that was tested in this study is in the class of aromatase inhibitors.

[Edit: I forgot to mention that this study was funded by Gaspari Nutrition, and appropriately disclaimed in the paper.]

Methods:

The authors chose to study eugonadal men in this study. Eugonadal means that they were producing normal amounts of testosterone. Guys who had used any nutritional supplements in the 2 months prior to the study were excluded from participation (this included creatine). All of the subjects had at least 3 years of resistance training experience. So, we're looking at non-beginner lifters who didn't use creatine or androstenedione or steroids for 2 months before the study.

[I think it's easy for novice readers to dismiss this study on the basis of these inclusion criteria, but I wouldn't share that opinion. This study does use the right kind of guy: beginner lifters probably shouldn't be using aromatase inhibitors right off the bad. Most non-beginners are probably using creatine, but as a researcher, you want to give your new "drug" as good of succeeding as much as possible. Having guys on creatine or other supplements means that you have to account for gains by creatine or other substances and therefore whatever gains you see, might not be attributable to Novedex. I suppose there's an outside chance that there's a synergistic effect, but I'm always leery of claims of synergy of two substances that, on their own, don't do much, but together somehow magically make huge differences (not that I'm saying creatine does nothing, because the evidence for creatine is quite good)]

Measurements were taken at 0, 4, 8 and 11 weeks. The researchers measured percent body fat, fat mass, fat-free mass, total body water as well as total and free testosterone, testosterone precursors and metabolites. Blood tests for safety were also performed, but I'm not going to focus much on those.

The subjects were simply told to continue their workout and diet schedules. Logs of physical activity and diet were kept during selected intervals of the experiment.

Subjects were split into two groups, matched by age and body mass, then assigned to get either Novedex or a placebo.

[The reporting gets a bit sketchy here, since it's not clear how they decided who would get which pill.]

The Novedex group took 4 Novedex capsules at bedtime. The placebo group took 4 placebo capsultes (maltodextrin) at bedtime. After 8 weeks of taking either pill every night, the subjects didn't take either of the pills for 3 weeks. Subjects were not told which group they were in, and apparently, neither were the researchers.

[Again, the reporting gets sketchy because although the paper says, "double blind", we're not sure who they're referring to as the second blind. We're also not told that steps were taken to make sure people didn't somehow figure out their group assignment).]

Statistics:

The researchers used 2x4 ANOVAs with repeated measures for every variable. This included their safety variables--about 45-50 of them ranging from complete blood count to triglycerides and urine ketones.

[That's a lot of variables to test!]

They then did separate 1-way ANOVAs to test for differences between groups and between each of the time intervals.

[This is redundant and unnecessary, and actually increases your chance of finding a significant p-value when a true difference does not exist in the "real world".]

The researchers estimated their required sample size on an unknown variable, presumably free testosterone, and figured they needed 8 subjects per group to detect a difference between the two groups of between 0.8 and 1.25.

[I have no idea if this was calculated on possible vales of free testosterone or not, or what the units of 0.8 or 1.25 are, or if this was a ratio difference or what. It also seems highly unlikely that you would need the same number of people to detect a difference of 0.8 as you would need to detect a difference of 1.25, but maybe you only needed 4 or 6 people to detect the larger difference? Their sample size estimation method wasn't referenced.]

Results:

The guys:

On average, the subjects were aged 26.1 (SD 4.4), were around 182 cm tall (71 inches, or 5'11"ish, weighed about 91kg (SD 14), or about 200 lbs, had a fat free mass of 75 kg (SD 9.5) 165 lbs, and had a body fat percentage of about 17 (SD 5.9)

Diet and Physical Activity:

The two groups did not really differ in any meaningful way from one another in terms of macronutrient ratios or total calories consumed. "Subjective" analysis of workout logs showed that none of the subjects changed up their workout routines.

Hormones:

Total testosterone and free testosterone were observed to increase at the 4 and 8 week points for the Novedex group. On average, total serum testosterone was noted to rise about 4 times (from about 5pg/ml to about 25pg/ml, with a very wide variance for total), and from less than 25ng/ml to just under 150ng/ml with a very large variance for free testosterone. However, even with this huge variance in effect between subjects in the Novedex group, there is no question it was larger than the non-existent change in testosterone of the placebo group. By the 11 week mark, both groups had returned to the week 0 level of total and free testosterone.

Body composition:

The authors reported that there were no statistically significant changes in body comp measurements except the the Novedex group loss more fat mass than the placebo group (about 3.5% on average). But looking at the graph and the data, I'd be hard pressed to make the same conclusion and I would attribute the two statistically significant p-values to be accidental due to the massive number of significance tests that were performed. Even if it really is "statistically significant", I would say that the observed difference isn't actually remarkable. At all.

In fact, if you look at the reported numbers, the placebo group started at an average body-fat percentage of 18.4 (SD 6.3) and at week 8 with a body-fat percentage of 18.7 (SD 6.5) for an average change of +0.3%, while the Novedex group started at an average body-fat percentage of 16.1 (SD 5.6) and at week 8, had an average body-fat percentage of 15.3 (SD 5.3), for an average change of -0.8%. That makes an average difference between the two groups of a mind-numbing 1.1% over 8 weeks.

Safety markers:

There were no marked differences in general blood work noticed.

Discussion:

We know that testosterone in _supraphysiological_ doses increases muscle mass and strength. However, even with a 4-fold increase of total testosterone and a 5-6-fold increase of free testosterone, 8 weeks of Novedex doesn't seem to put a dent in body composition. Apart from the moderately poor reporting of this randomized controlled trial, it's not bad. And the weaknesses in the study aren't really fatal flaws because all the biases in this study either affect generalizability (as opposed to validity) or are all in the same direction as the findings. For instance, the fact that no beginner lifters were included in the study doesn't affect the validity of the trial, only the generalizability (i.e. we can't use this study as justification for beginner lifters to use Novedex, but there's nothing glaringly wrong with the study itself). The fact that we don't know who was blinded or whether some of the subjects figured out their "pill assignment" doesn't really affect the validity of the study because if control group subjects found out they were on the placebo pill, they would have been biased to show that it did nothing (which it did anyways).

The only real weakness in this study of consequence is the coincidental finding of a "significant" reduction in fat mass (as determined by a significant p-value). But with so many tests of significance, we would expect there to be a very high chance (i.e. greater than 50%) that at least one of their tests would be significant by chance alone. And when you look at the actual numbers, you see that it probably is a coincidence that the p-value is less than 0.05, as opposed to being something meaningful, since none of the body comp numbers really changes at all.

One additional problem that you might (correctly) pick out is that this study involved only 16 guys. But again, this goes to narrowing the field of people this study applies to, not the overall validity of the study. If you don't fit into a demographic profile that is similar to these guys, it's really hard to use this study as justification to use Novedex.

One thing that I found very interesting is the range of values that subjects had in response to Novedex. The range of total testosterone and free testosterone in response to Novedex was pretty huge, which leads me to believe that there are probably guys who respond more than others on aromatase inhibitors. If there was a way to predict who was a responder, or if a larger study had been done so that a sub-analysis of high-responders vs. low-responders could be performed, I think we would have had a winner of a study on our hands. Maybe we would have seen substantial changes in body comp that would justify the use of Novedex. However, the average change in fat-free muscle mass and fat mass wasn't very large and unfortunately, neither were the variances, which means that in spite of very impressive increases in testosterone levels, these increases don't seem to translate to a noticeable benefit. You can get what you want (more testosterone), but still not get what you need (more muscle, less fat), even if you're a theoretical high-responder.

The bottom line: Unfortunately, this study leaves us with more questions than answers. If the fact that this study is cited in the ads for Novedex is why you're thinking of, or have decided to use Novedex, you might want to reconsider your decision. Of course, anyone can try just about anything based on hype or anecdotal personal testimonials, but that's not why you're reading this, is it?

Why I'm not writing about beta-alanine lately

2008-02-26T17:44:00.004-07:00

I've had a more than a few requests to write more reviews on beta-alanine, since it seems to be all the rage. It is so much the rage lately, that I get more hits on my reviews of the three beta-alanine studies than anything else, by a very large margin. The reviews have been linked by so many people that this blog is on the third page of a Google search for the term "beta alanine" (and this search includes hits from ALL of the supplement sites that SELL beta-alanine), and the FIRST hit when you search Google for "beta alanine studies". The. First. Hit. Holy. Crap.

However, I haven't been writing on beta-alanine for a few reasons:

1) This isn't the beta-alanine blog. There are other studies to review, and apart from reviewing for content, I like to review studies that also highlight particular common methodological mistakes, or, ones that highlight particular methodological strengths to build on the fact that good research in fitness IS possible (if we should just line up all the strengths seen in multiple studies into a single study).

2) I don't want to seem like I'm attacking the work of a single research group. Most of the beta-alanine studies come out of a small number of research centres. The authors of these studies often overlap with one another, or come up repetitively. What I did with the three reviews was pick out the ones that I thought would have the most relevance with respect to generalizability to the largest number of people, or would be considered foundational studies. To continue to review each and every beta-alanine study (which I have been challenged to do) makes it seem like I'm malicious towards people who are probably very nice and respectable.

3) There isn't anything in the other studies that would actually change the current level of evidence for beta-alanine supplementation from "There is inadequate evidence to support using beta-alanine," to "Beta-alanine is worth using." It seems repetitive and, frankly, a bit boring to review yet another beta-alanine study that does not add substantially to the existing body of knowledge regarding its efficacy or effectiveness. If a landmark study of higher AND sufficient quality is published, you can be sure I will definitely review it here. This has not yet happened.

Am I aware that there are new studies? Yes. However, these studies have not yet been indexed. Many of them have not yet been fully published in peer-reviewed journals. With the exception of the Trapp thesis, I generally only reviewed peer-reviewed articles. I think we all know what my feeling is on reviewing abstracts.

Am I aware that beta-alanine has been proven to increase muscle carnosine levels? Yes. However, the fact remains that DESPITE this "significant" increase in muscle carnosine levels, beta-alanine remains associated with non-meaningul (as statistically significant as they might be) changes in performance--except possibly at the highest elite level (which has not yet been adequately studied).

I understand that my blog makes it appear like I have a vendetta against beta-alanine, and there really isn't anything I can write here that would change the opinion of people who have that opinion of me. However, the standards I apply here to my reviews are the same standards that I would apply in a review of a submitted manuscript to the journals for which I am invited to be a peer-reviewer. They are consistent with international standards (such as a CONSORT statement on reporting standards for randomized clinical trials--which is openly linked in my link list.) I don't make the standards up, nor do I make the evidence up. The studies I review are available publicly in many university libraries, and are indexed as part of the Index Medicus (which anyone can access through PubMed.) I have no financial interest in seeing beta-alanine succeed or fail. I have no relationships with any supplement companies other than the fact that I buy supplements for myself. My only interest, with respect to this blog is to simply present the evidence in a critical and as unbiased a way as possible, so that others can make informed decisions about health decisions as they pertain to fitness.

I appreciate all of the feedback and notes that I have received throughout this blog's existence. Most of it has been very positive. And I appreciate all of the support that I have received so far. This blog is linked to many sites and I am flattered that people think it's worth reading to the point that they would recommend it to their friends and blog readers. I hope that someday, it will be more than "the beta-alanine blog", but I'll take whatever successes I can glean.

Thanks again for reading.

Rest vs. Active Recovery

2008-02-17T12:56:00.003-07:00

Lots of stuff happens when you're not doing anything. It's amazing. Your muscles rebuild (hopefully stronger than before). Your bones deteriorate less (if you've been doing weight bearing exercise). Britney does something silly (again). All while you're doing nothing! Rest is an integral part of any training program. Certainly, we know that inadequate recovery is responsible for a myriad of bad things, like decreased performance, and an increased risk of injury. But what about this thing called "active recovery"?

Active recovery can be loosely defined as a low-intensity activity (such as submaximal cycling or low-intensity weight training) used to enhance the recovery process between training sessions or competitions. The theory is that by increasing blood flow (your heart rate increases, therefore your blood is making more 'rounds' as it were), lactate and other 'waste products' are cleared faster, thereby minimizing their detrimental effects in tissues. This should translate practically to a faster recovery than if your blood were moving at its normal velocity. This would mean that you could train more frequently at sustained or higher intensity levels without exposing yourself to the risks of inadequate recovery. Sounds like a great idea, eh?

A recent study however, puts this translation of theory to practice into question. Its scope is somewhat limited, but worth looking at.

Andersson, H., et al. Neuromuscular fatigue and recovery in elite female soccer: Effects of active recovery. Medicine and Science in Sport and Exercise. 40(2):372-80, 2008.

Before we even get into the guts of this study, you can probably tell that we are looking at two major limitations: 1) the results of this study are only generalizable to the sport of female soccer; and 2) elite soccer, at that. So, while this study does challenge the concept that active recovery is useful, it only challenges that concept in the context of elite female soccer players, which likely excludes most of you (It definitely excludes me, on all three levels).

Introduction

Soccer is a high-intensity sport, but we don't understand a lot about recovery, particularly after games, and particularly about female soccer players. Most of the studies to date have been either inconclusive or non-demonstrable in demonstrating many changes in the biochemistry of soccer players, despite an observed performance decrease after games. Active recovery has been studied in male soccer players, but not in female ones. Until now.

These researchers wanted to know a two things: 1) what happens neuromuscularly, and biochemically to elite female soccer players after a game, and 2) does the same things happen to them if they're on passive or active recovery?

Methods

To answer this question, they recruited 22 elite female soccer players from the highest division in Sweden and Norway. Only 17 of these players were studied, because two of them were goal-keepers (and while a very difficult and demanding position, not the same activity profile) and three of the remaining 20 were not available for testing. These 22 players played two 90-minute friendly games, 72 hours apart. The same players participated in both games and played the same positions each time. After the first game, each player was randomly assigned to either passive or active recovery, with balancing for age, height, weight, VO2 max, and field playing position.

[With that many balancing factors, one has to wonder how random it actually was]

Active recovery consisted of 2 recovery sessions, at 22 and 46 hours after the first game (20 minutes of cycling at 60% of their peak heart rate, 30 minutes of low-intensity resistance training and 10 minutes of 60% cycling again).

Prior to the first match, players were tested for 20 meter sprint time, countermovement jump, maximal isokinetic knee flexion and extension and perceived muscle soreness. Blood samples were taken 3 hours prior to the first game, immediately after the first game, and then at 21, 45, and 69 hours after the first game and again immediately after the second game.

The blood was analyzed for creatine kinase (otherwise, known as CK, a general inflammatory marker), urea, and uric acid (both waste products).

All players wore heart rate monitors during their games, and each player was filmed for the entire game. These films were later reviewed to tabulate the intensity of the game. Distance covered, running intensity as well as time spent at each running intensity was calculated to ensure that the players weren't slacking off when compared to one another.

All players were given a meal plan to attempt to standardize diet.

Statistics

The data was analysed with multiple repeated-measures two-way ANOVAs, with the Dunnett as the post hoc test.

[That's a lot of tests!]

Results

Work intensity: The average heart rate was significantly higher within the two groups in game 2 vs. game 1. But it was higher in both groups, so the groups remained comparable.

Physiology after the first game: All performance tests were worse after the first game. And all three biochemical markers were elevated too.

Recovery time: Almost everything was back to baseline by 69 hours after the first game, regardless of which group the subjects were in. Sprint time was the first to recover (5h). Knee extension strength recovered by 27 hours, and knee flexion strength at 51 hours. Countermovement jump (similar to vertical jump) never recovered in either group in time for the second game. CK calmed down by 69 hours, while urea and uric acid returned to baseline by 21 hours. Muscle soreness was reportedly gone by 69 hours.

Between groups: The researchers failed to find a difference between the two groups at any time point. If we consider sprint time to be the major variable of interest, at 69 hours post-game 1, which was before game 2 at 72 hours, the 20m sprint time for the active recovery group was 3.25 seconds (SE 0.03) and 3.23 seconds (SE 0.04) in the passive recovery group.

What I liked about this study is that the researchers went out of their way to determine that the groups remained comparable throughout the study, hopefully recognizing that their randomization scheme might not be enough. What I also liked about this study was that they showed that there was a detrimental effect to performance and biochemistry after the first game. We are unable to say that these soccer players were SO elite that a single game was insufficient to cause performance decreases from which they would have to recover.

Limitations (or, why some of the limitations you might think are here aren't):

The biggest limitations to this study are the ones I've already mentioned. You can't really use this study to justify why _you_ (or I) should sit on a couch--unless you happen to be an elite, female soccer player.

There were definitely some reporting issues. I definitely wonder about the quality of their randomization. If you have to balance for 5 things between 17 players, it's not going to be that random. How many choices are you going to have if you have to find another 22 year old, 5'8, 125 pound forward with a specific VO2 max? I suppose it's possible that elite female soccer players might be all very similar to one another...

We don't know anything about the blinding. And we definitely don't know about adherence. The paper doesn't mention whether the people doing the testing knew which group each player was in, though, with most of these measurements, you'd be hard pressed to bias one way or another short of deceptively entering a false number. However, we don't know what "passive" recovery meant for the passive recovery group. Did they sneak off to do some passive recovery on their own? In some ways this isn't a limitation, as it simply reformats the question to ask whether adding 2 sessions of structred active recovery aids in recovery from a game, as opposed to unstructured active recovery (which the non-active group may have done, on purpose or not).

However, adherence aside, the groups did remain comparable throughout the study for most of the variables we would consider as confounders. And ultimately, the goal of randomization is to create comparable groups.

One of the criticisms that I usually make is that there were multiple tests of significance. However, that's only really a problem if you find you have a significant result and focus on it as though you had set out to look specifically for it. In this case, there were none between the two groups. So despite the fact that the chance of seeing a statistically significant difference by random chance was higher, they failed to detect one.

Lastly, one might think that 17 players is too small a sample size and that that quality makes this a bad study. Remember that statistical significance does not dictate whether an effect size is important or not. You use a statistic to bolster the argument that the difference between two groups (which you have deemed important beforehand) is not one that you got purely by random chance alone. However, the differences observed between the two groups were always miniscule. One could argue that statistical testing is unecessary for such numbers because even if they were statistically "different", it wouldn't be enough of a practical difference to justify one behaviour over the other.

The argument one CAN make with a sample of 17, however, is that these 17 players are somehow not an accurate representative sample of all female elite soccer players. I can't speak to that, not knowing what female elite soccer players are like in general. Certainly, you could make a case that this study may even only apply to Scandanvian elite female soccer players (which, I found out to my embarrassment this past summer, does not include Icelandic elite female soccer players), if you could justify why other elite female soccer players from other countries are distinctly and substantially different than Scandanavian ones.

The bottom line:

Stricly speaking, you don't really get to use this study to change anything you do, unless you're a Scandanvian elite female soccer player. If you are, it might be okay for you to sit on the couch between games. For the rest of us, loosely, you can probably do whatever you like best, whether it's sitting on the couch, or getting some active recovery in, feeling relatively assured that it's probably not going to hurt you. But certainly, this study draws attention to question whether active recovery, though theoretically sound, is actually any more beneficial than passive recovery.

This entry's title is most definitely not, "Ice, Ice Baby"

2007-11-12T15:47:00.000-07:00

But maybe I should call it, "Just because there are mistakes, doesn't mean it's all bad."

Ice--the ubiquitous item in every trainer, coach, therapist, doctor's arsenal. Whether you use a frozen bag of peas, a "magic bag", or actual ice attached via several feet of cling wrap, or actual cold-water immersion, there are many reasons to use ice, or more fancily, "cryotherapy". One of these reasons is delayed-onset muscle soreness, or DOMS. DOMS is the pain that you experience 1-2 days after a workout, usually after a significant change in your routine or program. It goes away on its own, but can, in some cases, hinder training, since athletes who are sore after strength training may not be able to train to the same level in their sport. Some sport teams encourage or even mandate contrast baths post-training, for a variety of reasons. I don't know of any lay-people that fill their tubs with ice water, but I'm sure someone will tell me that they, or someone they know does. So, the question is, "Does cold-water immersion reduce DOMS?" Is it worth getting into a tub up to your waist in ice-cold water?

Sellwood KL, Brukner PB, Williams D et al. Ice-water immersion and delayed-onset muscle soreness: a randomised controlled trial. British Journal of Sport Medicine, 41: 392-397, 2007.

Introduction:

The mechanisms by which DOMS actually occurs are still relatively poorly understood. We do know that there are structural changes seen on microscopy and biochemical changes in serum levels of things like creatine kinase and prostaglandins. We also know that DOMS tends to manifest more after eccentric exercise. Ice-water immersion is used, particularly by high-level athletes to minimize DOMS, and it is theorized that it decreases inflammation and also causes blood vessel constriction, so as to prevent some of the swelling (which is also part of the inflammatory process). There have been other studies looking at ice-water immersion on DOMS, but they haven't been very good, and the authors state that most of the studies are underpowered (i.e. not enough people), not blinded, have used resistance trained people (thus decreasing the likelihood of DOMS) as reasons why previous trials have tried and failed. So, these authors decided to put it to the test properly. In Oz, they seem to use a one-minute-on, one-minute off cycle, for three immersions.

Methods:

This was a well-reported study. There are a few issues that I have concerns with, but on the whole, there were almost no elements in this paper that I found were missing.

This study recruited volunteers from the University of Melbourne using posters around the schools of physiotherapy and medicine. Subjects had to be older than 18 years of age. They could not have performed any eccentric quadriceps exercise for 3 months prior. They could not have any neurological disease in the lower limbs, could not have any current injury to the lower limbs, could not be diabetic or have a disease for which cold-water immersion would not be allowed (e.g. Raynaud's phenomenon). They also had to understand English.

All subjects went through a protocol to determine their 1RM for a seated leg extension on their non-dominant leg. They then went through 5 sets of 10 reps of _eccentric_ leg extensions using 120% of their 1RM. The subjects got one minute of rest between sets.

Subjects were randomly allocated to receive either a) an ice-water bath, or b) a warm-water bath. The ice-water bath was "...melting ice water at 5 (plus or minus 1) degree Celsius." (That's 41 F, for the backward countries who refuse to join the rest of the civilised world :P )The warm water bath was 24 degrees Celsius. Subjects had to stand submerged up to the level of the anterior superior illiac spines (basically just below your belly button). Three sets of one-minute-in, one-minute-out were done. [Disappointingly, the authors were a little sparse on their reporting of randomization, stating that the sequence was generated using a random numbers table (which is fine), but didn't say whether patients were allocated by any kind of blocking or whether it was just simple. The fact that they ended up with exactly 20 people in each group is somewhat fortuitous for them.] They did mention that the evaluators of the outcomes were blinded though, which is a plus, and also mentioned that subjects were not told which intervention was considered therapeutic (which is an excellent way, if you can ethically justify it--and you can, to blind patients in whom you cannot conceal the actual treatment from).

The subjects came back at 24, 48 and 72 hours after their eccentric workout, and filled out visual analogue scales rating their quad pain for:
-pain on sit-to-standing
-passive quadriceps stretch
-one-legged hop for distance (and distance was also recorded for this test as a measure of quad function)
-maximal isometric contraction

They were also tested for tenderness on pressure, which was assessed using a pressure algometer, which is basically a device that can measure how much pressure is being delivered through it.They exerted a force of 6 pounds per square cm (what an odd mix of metric and imperial...) on two standardized points of the quads and asked the subjects to rate their pain during pressure.

Subjects' thigh circumference was also measured and recorded at two standardized reference points. Blood work was drawn to measure creatine kinase (CK) levels.

The authors calculated a sample size of 30 subjects to detect a 25% difference between the two groups (i.e. the cold-water group were expected to have at least 25% less pain than the warm-water group). They based their calculation on the fact that a previous study found that there was an average increase of 69mm on the 100mm VAS for pain at 48 hours after eccentric exercise.

[This will prove to be the Achilles heel later on. The decided to recruit 40 patients in case people dropped out--which is also good planning. However, they used an alpha level of 0.05 and a beta-level of 0.8 to calculate this sample size--which is puzzling because their alpha level when it came to analysing their data was 0.01. What saves them in the end here, is that with an alpha level of 0.01, they needed 21 subjects per group, and they ended up recruiting 40. Unfortunately, it doesn't save them enough. Read on.]

Statistics

The authors used an intention-to-treat analysis (which means that regardless of whether someone stayed in the study or not, or whether they went off on their own or not to immerse themselves in freezing water, they were part of the analysis and in the group they were randomly allocated to), which is pretty much the accepted standard in randomized controlled trials. The carried the last value forward for any missing values (also the going standard, which many studies don't do).

[Again, disappointingly, they decided on an alpha level of 0.01 to protect against a type I error (finding a significant difference when one does not truly exist) because of the number of significance tests they were going to perform. I stopped counting at 50. On a conservative Bonferonni adjustment, an alpha level of 0.01 would be the appropriate adjustment for 5 significance tests. So, even with the more conservative alpha level, 50 tests is just downright inappropriate. This is a case of poor prioritization as to defining a single primary outcome. However, despite the gross error of judgement, it surprisingly doesn't really affect the conclusions of the study all that much.]

Results

First off, the authors reported a few demographic statistics with respect to age, body-mass index and so on, but then went on to state that, "No significant difference was noted between the participants in the two treatment groups at baseline..."

[It is a well-established caution that significance testing on baseline values in the context of a randomized controlled trial is inappropriate. This is for 2 reasons: 1) You cannot use classic significance tests to positively find "no difference". You can only find that there is insufficient evidence that a difference exists. Absence of evidence is not the same as evidence of absence. 2) The null hypothesis of a significance test is not, "No difference exists between the two groups," as most beginners will tend to tell you (for the reason stated in number 1 of this list), but rather that the probability of observing data as or more extreme than the observed data is lower than that of random chance. However, in the case of randomization, the group a person ends up in IS up to random chance! So the probability that your observed data is by random chance is...1! So the interpretation of a significant p-value in baseline comparisons is problematic at best, and completely non-sensical at worst.]

I'm not going to go through every significance test that they authors did here. The bottom line is that apart from a few significant p-values in tests that weren't that important, the authors failed to find a significant difference in any of the outcomes that actually mattered. This is why the more conservative alpha level, though an inappropriate way to deal with multiple comparisons when you're planning more than FIFTY tests, is not that big of a deal in this case. They did find that the ice-water group had "significantly" more pain at the 24h more than the warm-water group, but with over 50 tests, there's bound to be a few spurious p-values. I certainly would not agree with the statement that ice-water immersion, "...may make athletes more sore the following day." on this basis. That's data fishing.

However...

The highest median pain score in this study was 38mm (interquartile range 13.8-55.0mm), which is FAR below the score we expected to see compared to the previous study that had a mean pain score of 69mm. So, unfortunately, even though they recruited 40 subjects, if they wanted to detect a difference of 25%, they would have needed at least 45 people in each group (with an alpha of 0.05) or 67 in each group (with an alpha of 0.01). The problem with using a percentage as your criteria for practical relevance is that the estimation equation for sample size doesn't care--it only cares about the absolute difference between the two groups (and the variance within each group). So, while 75% of 69mm is 51.75, for an absolute difference of 17.25, 75% of 38 is 28.5, for an absolute difference of 9.5. It is invariably tougher to detect a smaller difference that it is to detect a larger one. So, for all its efforts and criticism of previous underpowered studies, this one is, alas, underpowered. But, as with the closing sentence of many paragraphs in this review, this "mistake" is also somewhat moot.

Discussion

As with any critical review of a study, it's easy to poke holes in things. This is by far the excuse I have heard the most from people who would prefer not to use studies as evidence for why things work or don't work. "You can find a study to prove anything," is the second. But the trained reviewer understands that it's not enough to poke holes in papers--you have to understand how the hole ultimately affects the study's conclusions. In this study's case, it wasn't really that important that the authors did a bajillion significance tests (I think bajillion is somewhere higher than 50, but less than a gazillion) because they didn't actually affect the study's conclusion that they failed to find a difference in pain reduction between ice-water and tepid-water immersion.

The authors acknowledge the limitation of their study in that they failed to elicit as high a pain as other studies (and more importantly the study they based their sample size calculation on), or alternatively, maybe they just had tough-as-nails subjects who didn't rate their pain very high. They said that the strength deficits were pretty small with respect to the DOMS, and also the CK levels didn't rise as much as other studies, but honestly...5 sets of 10 reps of eccentric leg extensions at 120% of your 1RM (if it's a true 1RM, and there is a debate as to whether an untrained individual can generate a true 1RM) seems like more than I would do or would recommend as a strength workout, so how much more would be comparable to a "trained" or "athletic" workout? And do those other studies demand workloads that are far in excess of what is actually done in the "real world" in an effort to create SUPER SOUL-ANNIHILATING DOMS!!!! (tm) ?

And always, the authors hedged on the fact that maybe ice-baths have a psychological benefit to athletes (quite like taping!), and that even if there might not be any benefit (from both a physiological and a pain perspective), who's to take that value away from an athlete who might become mentally crippled if he/she were unable to take an ice-bath or tape their ankles?

Looking at the numbers, I come away from this study with 2 thoughts (apart from the ones above): 1) Maybe DOMS isn't that crippling for most people, and if it is, maybe we should be asking whether that kind of training load is necessary rather than trying to come up with ways of preventing or treating DOMS; and 2) Regardless of the power of the study, if it's an accurate picture of what DOMS pain looks like, I don't need a statistical test to tell me getting in a tub of ice-water up to my belly button is an experience I could probably go without, because the difference between warm and ice-water is tiny.

The bottom line:

Getting into a tub of testicle-shrinking ice-cold water is probably unnecessary for most of us in terms of preventing of treating DOMS. It's probably more fun if there's vodka and a sauna involved though (but they didn't study that).

A return?

2007-10-15T16:41:00.000-06:00

For those of you who have followed my blog, thanks for all your support. I realize that I have been remiss in keeping it up, but residency...well, it's a whole new kettle of fish, and I'm not even sure they're all fish in there. I will likely not be updating my blog every week, though, I will try, depending on my call schedule. Basically, a review takes about 2 hours to type up, proof-read and edit (and even then, it could probably use a bit more work), but when I'm sleep-deprived, the last thing I want to do is a blog entry--as fun as it is. The tutorial entries don't take quite as long. Two entries a week would definitely be wishful thinking at this point. If I knew how to send out auto-update notices, I would, but seeing as I don't, I guess you'll just have to keep checking back. RSS feeds can be useful that way.

Going the extra mile doesn't always make things better (but then again, it might)

2007-10-15T16:37:00.000-06:00

I picked this study for two reasons: 1) It's actually not a half-bad study, and 2) It addresses a significant fitness issue that has been plaguing athletes, trainers and coaches for decades--to stretch or not to stretch. However, despite the study's many strengths, it falls just short of making it truly useful in helping active people make the decision whether or not to perform static stretching.

Kokkonen J, Nelcon AG, Eldredge C, Winchester JB. Chronic static stretching improves exercise performance. Medicine and Science in Sport and Exercise. 39(10): 1825-1831, 2007.

Introduction:

I really liked this introduction. The authors did a great job of presenting the literature, including why the previous literature doesn't really give us any definitive answers on whether non-pre-event static stretching has detrimental effects on performance. They define their boundaries early on and don't dispute the clear literature base on pre-event stretching. This is not the issue here. However, they make a great case as to why we are still in the dark with regular static stretching and where it should be placed (if at all) in a training program. Clearly, it is not before significant events (which, for many active people, includes their "workout"--whether that be lifting weights, going for a run or otherwise), but is there a place for stretching on say, rest days, or post-workout? And if so, what kinds of benefits might we see from it?

The authors go on to review the literature on performance benefits derived from static stretching, most of which are strength related. Yes, that's right. Stretching might make you stronger. Well, some of you anyways, as we will see.

The purpose of this study therefore, was to determine whether a static stretching program could have an impact on strength, muscle endurance and power. (For those of you who are scratching your heads at "static stretching", this refers to the "stretch and hold" variety of stretching--as opposed to "bounce" or "move" varieties, also referred to loosely as "dynamic stretching")

Methods:

The authors recruited 40 students (why 40, I have no idea, as there is no sample size justification in this paper) who were attending Brigham Young University in Hawaii (Damn it, I should have gone to university in Hawaii). The authors describe these students to be either inactive or recreationally active. They further narrowed this vague term down to exclude anyone who did specific endurance or strength training on multiple days during the week; as well as anyone who did more than 60 minutes of physical activity more than 3 times per week. This basically excluded anyone who lifted weights more than once a week, anyone who went for a run more than once a week (strength and endurance training, respectively), anyone who played basketball for more than 60 minutes, more than 3 times per week, and anyone who went for a walk for more than 60 minutes, 3 times per week. They also excluded people who did any sporting activities more than 6 times per month. Basically if they thought you were doing any kind of structured or planned physical activity, you got booted from the study. And from the sounds of the description, they were fairly strict about it.

[The authors' selection of subjects is both one of the biggest strengths and biggest weaknesses of this study. In order to isolate the effect of stretching on strength, muscular endurance and power, they chose to study people who were basically sedentary. This has two advantages: 1) If you study a group of people who do basically no physical activity other than stretching, then improvements in physical activity testing can be attributable to the stretching; and 2) you are most likely to see the biggest changes in those people who are furthest away from their "athletic potential". You are least likely to see an improvement in reading ability if you study lawyers than if you study third graders (debate what you will about lawyers, but they read good). The same principle applies here.

The drawback to this approach, is naturally, the extent to which we can generalize these results to anyone but basically sedentary people. If you study third graders' reading, you can't go and claim that your revolutionary program is going to improve the reading ability of the lawyers--or even fifth graders. BUT, given that we know so little about static stretching and performance in this context, this study IS the most appropriate starting point, as it gives us the best chance of detecting a benefit. If these researchers had gone with "trained college men" and NOT found a difference, we would still be in the dark because that population is in the middle of the road. Given that the study finds that static stretching improves performance in the least-trained individual, we can then start working our way up to see if this effect persists with more-trained people.]

Subjects were "randomly assigned" to either the stretching group or the control group. The control group were asked to refrain from any stretching activities, but otherwise, the groups were told to maintain what little physical activity they were doing. The researchers also made sure that there were the same number of men and women in each group. Every had to keep a log of their activities.

[I really wish they had gone into just a little more detail about randomly assigning people to groups.]

In addition to all of this, the authors report that all local recreational facilities were monitored by research staff and, "...the presence of any subjects was noted and collaborated with their exercise logs."

[Holy big brother, Batman. This is by far, the furthest extent to verifying non-activity I have ever encountered. A little creepy perhaps, but from a scientific perspective, one of the more rigourous ways of ensuring subject compliance (or non-compliance, as the case may be) ]

Outcomes:

The authors tested the following things:

1) Sit and reach (flexibility)
2) 20m sprint time (power)
3) Vertical jump height (power)
4) Standing long jump length (power)
5) Knee extension and flexion 1RM (strength)
6) Knee extension and flexion endurance (endurance)
7) VO2 peak (endurance)

Testing was done over 3 days. The details of this aren't that important. If you're really interested, read the article.

[We are not told who is blind to what in this article. So, for all we know, everyone know what everyone is doing (i.e. subjects, evaluators, group-assigners, the gym spies...I still can't get over that.) ]

The stretching program:

The stretching program was a 10-week program with 15 different stretches. Each stretch was held for 15 seconds and each stretch was repeated 3 times. All stretches were performed non-assisted, and 12 of the 15 stretches were performed again, but with assistance. Stretching sessions lasted about 40 minutes each.

[I won't go into each of the individual stretches. They are described though. Forty minutes is a long time to stretch though, even for a static stretching program. I would say that this is perhaps one of the bigger weaknesses of the study. How feasible would this be if this were you?]

Statistics:

This is by far the least liked part of the study for me. The authors decided to treat the data as four separate experiments, in order to avoid adjusting their alpha-level to oblivion with 7 multiple tests. So, instead of having to meet an alpha-level of 0.007 (which is 0.05 divided by 7), they had to meet an alpha-level of 0.05 for the "flexibility experiment" (only one test there), 0.017 for the "power experiment" (3 tests), etc. There is an argument that can be made for this kind of strategy--certainly the "experiments" are grouped logically and not haphazard, but given that it's all on the same population, it's still ONE experiment. However, this point is relatively moot when we get to the results.

Otherwise, statistical testing was appropriate with a two-way ANOVA with the protected Tukey as a post-hoc test.

[I'm always a bit conflicted with respect to using the two-way ANOVA in these studies. Basically, you're trying to see if a significant difference exists either between the two groups (the first way), or within each group (the second way), or both. However, in the context of a randomized controlled trial, we are really not interested in whether one group did better compared to itself (i.e. the stretching group improved their, say, strength, when compared to their pre-testing), because whether the stretching group did better compared to itself is irrelevant, if the control group ALSO did similarly well (significantly, or not). So why bother seeing if the groups do better compared to themselves?]

Results:

Thirty-eight subjects finished the study. One subject from each group dropped out because they wanted to exercise. Of the remaining subjects, no one exercised for more than 18 days of the 10 weeks. No one in the stretching group missed more than 2 stretching sessions.

[Overall, I did not like the reporting style, nor the statistical reporting of this paper. Everything was reported and interpreted in percentages, despite the authors providing the actual numbers in a table. This leads me to wonder whether the statistical tests were done with the percentages as well, as opposed to the actual number results--which has implications for the likelihood of uncovering a significant difference, since differences may become magnified once converted to percentages. This includes confidence intervals, which were used, and I think any authors who use them should get some kudos. I just wish they had done them on the actual numbers]

Flexibility: The stretching group was more flexible than the control group after 10 weeks. I'm sure you're all floored. Fortunately, the control group's flexibility did not change (on average, it got worse), which is a good thing because even if they DID stretch on the sly (away from the piercing eyes of the gym spies), they didn't get more flexible, so we can still make statements about the effects of increasing flexibility on other things.

I could go through all of the outcomes, but in the end, the stretching group always did better than the control group from a percentage point of view.

However, when I look at the all-important results table with the actual numbers, what I see is very very small improvements, with not a whole lot of convincing numbers to show that the "significant differences" detected through percentages carry through with the raw performance numbers. For example, the stretching group ended up with an average knee extension 1RM of 82.0 kg, but a standard deviation of 25.8, while the control group had an average 1RM of 71.0 kg, but a standard deviation of 20.8! While the difference is 11 kg, on average, the variance is SO large that I would be surprised if that turned out to be statistically significant. Less dramatic would be something like the 20m sprint time: Stretching group average 3.8 (SD 0.51), control group average 3.68 (SD 0.31), both post- values. Even if that was statistically significant, I'm not sure that a difference of 0.18 seconds is anything to write home about--remembering that we are not talking about Olympic athletes upon which tenths of a second are important.

So, in the end, what we have is a bit of a mixed bag of a study. It has some REALLY strong points (I mean, KUDOS for spying on all your subjects at the gym!), and a few weak points, but overall, fails to produce data that shows us that static stretching is a worthwhile pursuit, unless your life is judged on percentages alone. Given that one would have to stretch for FORTY minutes, 3 times a week, I can think of several things I would rather do for 40 minutes, 3 times per week, which might produce the same (i.e. possibly very little) _absolute_ benefit in strength, power and muscular endurance.

Still, I suppose if I was unable to do any activity other than stretching, I could be convinced that it might prevent me from deteriorating too much. And that's not necessarily a benefit to sneeze at, given that there are many athletes who are sidelined into inactivity due to injury or other circumstances, not to mention several patient groups in inactivity for health reasons. So, in a way, it all depends which side of the fence you're approaching the problem.

The bottom line:

If you can't do anything else, static stretching for 40 minutes, 3 times a week could keep you from deterioration from a muscular strength, power and muscular endurance perspective.

Update on me

2007-06-28T14:03:00.001-06:00

For those of you who don't know (which is pretty much 99% of you), I've just moved and am starting a residency program here. Hence the major disruption to the blog. Thanks for continuing to check back. I am in the process of cleaning my apartment and buying furniture right now. As soon as I'm settled in, I'll be more regular, I promise.

The mystery of the taped ankle...

2007-06-13T20:34:00.000-06:00

I'm back from a one-month vacation in Sweden, and thanks to a horrible delay at the Frankfurt airport was able to get a review done for this week. Thanks for being patient with me and as soon as I install the rest of my regular software on this new hard drive, I'll be fully up and running...if only I could remember which box I packed it all in...

This week, I give you a review on a study about ankle taping.

It's not often that I see a study whose main intention is to investigate a placebo effect. Athletic taping has long been disputed in terms of whether it actually has a physiological benefit with respect to injury prevention. The body of evidence in the literature tells us that taping does, in fact, reduce the incidence of injury, but is unclear as to the mechanism by which that happens.

This study aims to look at one of those possible mechanisms, while at the same time, investigating whether there are any actual physiological parameters that can be measured to show that ankle taping alters the way in which specific tasks are performed. The premise of this study is that ankle taping, in fact, doesn't have any physiological benefits, but that the way it might prevent injury is, in fact, the psychological effect that believing that something will help you, will, in fact, help you.

In browsing the study, I think there are only two obvious weaknesses to it, but I guess we're going to find out.

Sawkins K, Refshauge K, Kilbreath S, and Raymond J. The placebo effect of ankle taping in ankle instability. Medicine and Science in Sport and Exercise, 39(5): 781-787, 2007.

Introduction:

I think one of the strengths of this paper is the acknowledgment of the preceeding literature. We know that ankle taping does reducing ankle injuries, but we don't understand why. One of the theories is that the athlete's expectation that the taping will help them, is sufficient to change their performance such that it does.

This study differs from most randomized control trials in that the authors used deception to blind their subjects. This is not an often-seen tactic, but can be very useful in isolating the effect of interest. In this case, we are interested in seeing whether "real" taping is different from "placebo" taping in terms of objective testing and in terms of subjective reporting of experience. To isolate this difference, the subjects needed to have the same expectation of the two taping methods. This way, everything stays the same, including the psychological factors, and any differences we observe between the taping methods should be attributable to the taping methods themselves.

Methods:

It's not entirely clear where the subjects in this study came from. Presumably, they were recruited at the University of Sydney. People were eligible for the study if they had ankle instability from previous ankle sprains. Ankle instability was defined by a cut-off score on the Cumberland ankle instability tool (CAIT). People were excluded from the study if they had had an ankle sprain within 3 weeks of testing, if they had a past history of fracture or surgery to the lower limb, or if they had pain or palpable swelling of the ankle, or if they had any neurological, visual or vestibular deficits.

[I'm not personally familiar with the CAIT, and I'm a bit nervous with the reference not being a specific validation of the CAIT. However, even if the CAIT is not valid and there were some people with stable ankles who were included in this study, it might not change the actual conclusion that we can make from this study.]

Subjects were not informed as to the true intent of the study--only that the researchers were interested in comparing two types of taping--a mechanical one and a "proprioceptive" one. They were not aware that the relabelled "proprioceptive" taping method was, in fact, a placebo.

This study was a cross-over randomized control trial. That is, each subject acted as his/her own control and the order in which treatments were used was random.

[Taping is a great example of a crossover trial that works because there's no real carry-over from one treatment to the next. The effects of one type of taping disappear once the tape is removed and there's no need to have an extensive "wash-out" period between treatments. Within-subject trials have two major benefits: 1) You don't need as many subjects (in fact, you need only half the number you would normally need!) and 2) there is less variability between treatment groups because whatever intrinsic variables that exist are the same between the groups because the person is the same. This means that you have the ability to either detect a smaller (and hopefully practical) difference between two treatments (you have better resolution), or you can detect a larger difference with a smaller number of people.]

Subjects were tested in three conditions: mechanical taping, "proprioceptive" taping and no tape. They did 2 physical tests and a questionnaire.

The first physical test was the hopping test, in which the subject had to hop onto 8 squares, one at a time and then back. Four of the squares were level, 1 square had a 15 degree incline, 1 square had a 15 degree decline, and 2 squares with a 15 degree lateral inclination. The outcome measured with the hop test was the time it took to complete the 16 hops (8 forward, turn around, 8 back). There was a time penalty of 1 second if a subject landed outside a square, or if they did the square in the incorrect sequence (the squares were not arranged in a line).

The second test was the modified star excursion balance test. The setup for the this test is a star, made up of 4 strips of tape--two strips to form a cross, and 2 strips to make up the X through the cross to form an 8-ray star. Subjects started the test by standing on both feet in the middle of the star. They were then instructed to stand on their test leg, and to move the other leg along one of the rays as far as possible without losing balance, or touching down with the non-test foot. Start and finish positions had to be maintained for at least 1 second. The outcome measured in this case was the distance travelled by the non-test foot. Three measurements were take (one for the anterior ray, one for the lateral ray and one for the posterior ray.)

The questionnaire asked the subjects how they felt during the tests under the different taping conditions. It asked how stable they felt, how confident they felt and how much reassurance the taping provided. Stability referred to how steady and controlled the subject felt. Confidence referred to how well the subject felt they could perform the test and reassurance referred to how confidence they were that they could do the test without spraining their ankle.

Taping

The mechanical taping was a standard ankle tape job: An anchor, three stirrups, a low anchor, a figure of six and a heel lock. Subjects were told that this method of taping increased mechanical support to stabilize the ankle, and that it would help them perform better in the tests.

The proprioceptive taping was a single strip of tape (10 cm long) applied on the lateral aspect of the leg just above the lateral malleolus. It was aligned with the peroneus longus. Subjects were told that this method of taping would increase cutaneous input and improve proprioception to prevent ankle sprains, and that it would help them perform better in the tests.

Subjects were additionally blindfolded during taping and the actual taping was covered up by a cloth skirt to prevent the subject from seeing the tape job.

[Why they did this is not _entirely_ clear, as you can presumably feel when one or more strips of tap are applied and whether you can see your ankle or not probably doesn't affect whether you can feel like there's one or more pieces of tape on your leg. But okay, I can accept that they did it.]

Statistics:

The taping methods were compared using a one-way ANOVA for the hopping test, and a two-way ANOVA for the modified star test. The questionnaire was qualitatively analyzed to identify whether subjects felt improvements in any of the three categories (stability, confidence, reassurance) and then a chi-square test was used to see if the rate at which people reported improvements was different between the two taping methods.

Results:

The researchers failed to detect a significant difference between groups with respect to their primary outcome--the Hopping test. When using the real tape job, subjects completed the test in 10.5 (SD 3.6) seconds. When using the placebo tape job, subjects completed the test in 10.5 (SD 3.6) seconds. And when using no tape at all, subjects completed the test in 10.5 (SD 3.7) seconds.

The authors also did not detect a significant difference on the modified star excursion test. There were some differences detected within subjects, between excursion directions, but examination of the actual numbers shows that despite detecting a statistical difference, the actual difference was millimeters of difference, and thus, it is not meaningful to say that one tape job produced a relevant different effect that the other.

What is interesting is that despite the lack of objective differences between groups, almost all of the subjects reported feeling more stable during the hopping test (29 out of 30 subjects), more confident (24 out of 30 subjects) and more reassured (23 out of 30 subjects) with the real tape job, compared to only 8, 7 and 7 subjects reporting better stability, confidence and reassurance respectively with the placebo tape job.

This pattern was mirrored in the modified star excursion test, but to a lesser extent.

Discussion:

The authors spend a bit of their discussion talking about how the star test was limited because they didn't adjust for leg-length, but I'm not nearly as concerned about this, because the modified star test isn't fully validated and wasn't their main outcome of interest. The modified star test also tests stability during a static activity, and thus is less useful in drawing conclusions about things like injury prevention during activity or dynamic activity (which is most often when ankle injuries occur in sport.)

What we have here is a study that shows that the placebo effect of ankle taping in terms of improving _feeling_ of performance is incredibly high, but that it is most definitely a placebo effect because it doesn't actually alter the performance of the subject when they have no tape on at all (subjects performed the same, regardless of whether they had tape of any kind on or not.) This is in the context of a previously injured population as well, in which we would expect to see differences if they existed. So, the question is, whether the power of belief is SO strong, that it actually prevents injuries despite not changing any of the physical factors of performance, and by what mechanism this might occur, because intuitively, this makes no sense. It would be almost like saying if you believe a helmet will protect you from injury in a parachuting accident, it will.

I think what I would have liked to have seen in this paper was an analysis of actual within-subject differences. Although the means are the same between the two tape jobs, it's possible that they appear that way because some subjects performed with such drastic difference that they evened each other out. The mean of thirty 20's, is 20. The mean of fifteen 30's and fifteen 10's is also 20. Obviously the standard deviation is totally different (this is an example for drama purposes), but it is possible to have a similar spread (which is what the standard deviation is a measure of) with large differences in performance.

However, it still doesn't change the fact perception of confidence, stability and reassurance were so drastically different. So basically, if anyone is thinking of inventing a new method of preventing ankle injury and comparing it to taping, they're going to have to overcome a MASSIVE placebo effect to derive a bigger benefit in terms of perceptions of security, but perhaps not in actually improving stability.

One last component missing from this paper is a comparison to people who didn't have ankle instability at all. What this paper lacks is a bit of context (which may be in the preceding literature). How did the ankle-unstable subjects compare with their healthy counterparts with respect to the Hopping test?

The bottom line:

This is a fairly strong paper showing that ankle taping improves the feeling of stability, but actually doesn't improve athletes performance in tests designed to test ankle stability in both dynamic and static activities.

More excuses

2007-05-24T02:54:00.000-06:00

I'm in Sweden right now--Stockholm actually. My laptop's hard drive failed and is now sitting in the Apple dealer's store waiting for a new hard drive. Fortunately, I managed to back everything up on my iPod (yay!). Unfortunately, this also means that I will not be updating this blog until I have my computer back. I swear I am not making this up. Thank you for being patient.

I promise, this blog is not dead.

2007-05-09T14:03:00.000-06:00

Sorry, sorry, sorry.

More EBF next week some time, unless I somehow find the time in between pre-convocation festivities, entertaining my parents and relatives, packing the remainder of my apartment, convocating, post-convocation festivities and dealing with my landlord.

You never know.

If all goes according to plan, I'll be posting from Sweden next week.

Thanks for checking in!

Apologies, no blog this week

2007-04-30T10:13:00.000-06:00

I was going to review a study on ankle taping this week, but packing to move across the country, trying to plan a trip across the ocean and trying to study across all subjects got in the way.

So, no blog entries this week, because I'm writing my medical board exam on Friday. Thanks for all your support over the past two months! Send me ideas for topics you want to see covered!

HIIT vs Steady State--Again.

2007-04-23T14:17:00.000-06:00

Thanks to Mike Knowles who suggested this week's study (which, incidentally, was incorrectly cited in that publication you sent me, but that's not your fault :) ).

Commitment can be such a harsh word for some--especially scientists. I did my undergraduate degree at Queen's University, where I was a part of the faculty of Arts and Science. I'm sure this isn't what they meant when they named the faculty, but it's a propos to my point today, because even in "Science", there is Art. As researchers we strive so hard to be objective, and reductionist, that we lose sight of the qualitative judgments that are required to do our work. Too often, we are blinded by "objective" p-values, effect sizes and sample size "calculations". I think it's an advanced concept (and certainly one that I did not grasp fully until I was almost finished my PhD) that research design and statistical analysis is as much a subjective "art" as it is a "science". Anyone can apply rigid principles and create _a_ study (for instance, "Is my brother smarter than a hamster?") This is not to say that research cannot be objective, but that it takes a certain "finesse" to create a study that is not only objective and as unbiased as possible, but also practical and relevant to current practice (or, the "real world").

Commitment in science is about sticking to your guns and justifying why you do what you do. It means not leaving the decision making up to a p-value. It means deciding what effects are practically important BEFORE you run the significance tests to see if they're "statistically" important. It means realizing that statistics are used to SUPPORT your hypothesis, not to prove it. And it means figuring out what you're going to need to optimize your tests so that you will ACTUALLY answer the question as opposed to leaving the type I and type II error rates hanging in the air to chance.

So, that being said, the topic this week goes back to HIIT vs Steady state training (I know, it's a recurring theme. I promise to review another topic next week).

Gibala MJ et al. Short-term sprint interval versus traditional endurance training: similar initial adaptations in human skeletal muscle and exercise performance. Journal of Physiology 575:901-911, 2006.

I'm not going to reprint the abstract here because you already know that reading abstracts on their own is not the most useful exercise.

Rationale:

There has been some evidence to show that short-term sprint interval training (SIT) improves factors that are associated with improvements in endurance activity performance, but no one has put them head-to-head in a standardized way to see if SIT might be a, "...time-efficient strategy to induce muscle and performance adaptations similar to high volume endurance training."

The question being asked by the researchers is, "Does SIT do as good as a job as ET (endurance training) in improving exercise capacity and molecular and cellular adaptations in skeletal muscle?"

[So, right off the bat, this is NOT a fat-loss study, or a weight-reduction study. Let's get that clear right away. But what it is, is a study that may address one of the largely popular concerns that HIIT compromises "health benefits" in that one does not accrue these "health benefits" that have been shown in ET studies.

The problem with this study is that, by its question, it's a non-superiority trial. That is, the researchers are trying to show that there is no difference, rather than trying to prove that SIT is better than ET. And the problem with "traditional basic" research design, is that its main limitation is its inability to positively show "no difference", since you cannot accept the null hypothesis; you can only reject or fail to reject it. If you reject it, then you are saying that the difference between two groups in the observed data is as, or more extreme than difference you would have obtained purely by chance. If you fail to reject the null hypothesis, then you are saying that you lack sufficient evidence to show that the difference you observed was as or more extreme than by chance alone. But lack of evidence is not positive proof of no difference. As the saying goes, "Absence of proof is not the same as proof of absence."

So in the best case scenario, where the researchers will fail to reject the null hypothesis (i.e. that there is no difference between the two groups with respect to exercise capacity and muscle adaptations), we will still be unable to conclude that there IS no difference, due to the overriding limitation of the study design itself. Non-superiority, or equivalence trials are a totally different animal from traditional designs, and should generally not be performed without some expert guidance.]

In their introduction, the authors state, "We hypothesized that both SIT and ET would increase muscle oxidative capacity and 750 kJ time trial performance, given the major contribution from aerobic metabolism during this task. In contrast, we hypothesized that SIT but not ET would increase muscle buffering capacity and 50 kJ time trial performance given the large contribution from non-oxidative metabolism during this task."

[I like the second, concrete and useful hypothesis, but the language of the first one demonstrates the lack of commitment to answering the question. We are not interested in knowing the both SIT and ET increase oxidative capacity and time trial performance. We already know that they do. If we didn't know that they did, then this study could not be justified. We are interested in knowing what they do COMPARED to each other. If you never COMPARE the two protocols directly, you CANNOT make generalizable statements about them.

There used to be more prevalent "classically bad" designs where researchers would put two groups through separate protocols, compare them against themselves and say things like, "Well, group A improved significantly when compared to themselves, and group B didn't improve significantly when compared to themselves. We didn't bother comparing them to each other, but we're going to conclude that group A is better than group B." Absurd, eh? Similar concept here, just a slightly different twist.]

Methods:

Sixteen men were recruited to this study. They were physically active students who, "...took part in some form of recreational exericse two to three times per week (jogging, cycling, etc). None of the subjects were engaged in regular training for a particular sporting event." The 16 men were randomly assigned to one of two groups: the SIT or the ET group.

[Insert my usual comment about lack of sample size justification, and lack of reporting on random allocation methods here.]

Pre-testing: Subjects all went through VO2 max and Wingate testing. Also, they all practiced a 50 kJ and 750 kJ time trial to familiarize themselves with the testing protocol for the study itself. This all happened on separate days, and at least 3 days before baseline testing.

Baseline and post-testing: Subjects all did the 50 KJ and 750 kJ time trials, with no verbal, time or physiological feedback (i.e. no one was encouraging them to go faster, or harder; no one told them how long they had been pedaling for; no one told them what their physiological outcomes were). The only feedback they got was estimated distance on a computer monitor (50 kJ was approximately 2 km, 750 kJ was approximately 30 km). Subject also had a resting needle muscle biopsy taken from the vastus lateralis muscle. The order in which the testing was done was 1) muscle biopsy, 2) 1h after, the 50 kJ time trial, 3) 48h after, the 750 kJ time trial.

Training: Forty-eight hours after the 750 kJ test, subjects began the training protocol. Both groups trained 3 days a week (Monday, Wednesday, Friday) for 2 weeks. The SIT group's protocol was 30 seconds of maximal cycling with 4 minutes of recovery. Escalation was 4 repetitions for sessions 1 and 2, 5 reps for sessions 3 and 4, and 6 reps for sessions 5 and 6. The ET group's protocol was 90-120 minutes of continuous cycling at 60% VO2max. Escalation was 90 minutes in sessions 1 and 2, 105 minutes in sessions 3 and 4, and 120 for sessions 5 and 6. All training sessions were supervised by study personnel.

Additional collected data: Subjects did diet logs.

Muscle analysis: I'm not trying to say that this stuff isn't important, but unless you're interested in the really fine details of this analysis, I'm not going to summarize things like which primer sequences were used for Western blot anlaysis. They measured muscle oxidative capacity by quantifying the amount of cytochrome C oxidase (mitochondrial subunit) expressed in the muscle biopsy (both from a protein standpoint and an mRNA expression standpoint). Muscle buffering capacity was measured with a previously published protocol, and muscle glycogen was measured with fluorometry.

[The big take home message here--and this really is the biggest strength of this study, is that there was a deliberate planning to ensure that the SIT group did substantially less volume and spent substantially less time than the ET group training.]

Results:

Time trials: Both groups significantly improved their time trials times. The SIT group improved by 10.1% and the ET group improve by 7.5% in the 750 kJ time trial, but the actual time improvements were not reported, nor was there any variance reported around the improvement numbers. No significant difference was found between the two groups with respect to this improvement. They did report the mean times (with standard error) for the 50 kJ test. The SIT group went from 117s (SE 6s) to 113s (SE 6s). There were some problems with the reporting of the ET group. The researchers reported that the ET group improved by 3.5% in the 50kJ test, but reported pre-values of 115s (SE 9s) and post-values of 122 (SE 10s). I think there's a typo in this article somewhere.

Muscle oxidative capacity: Maximal activity of COX improved within both groups. The researchers failed to detect a significant difference between the two groups, but stated, "No difference between groups".

Muscle buffering capacity: Muscle buffering capacity increased by 7.6% (no raw numbers or variance reported) in the SIT group, vs. 4.2% in the ET group. No significant difference was detected between groups.

Muscle glycogen content: Same result as above--both groups improved when compared to themselves, no difference detected between the two groups.

[In this case, it just happened by chance that the fact that they did multiple uncorrected significance tests didn't result in a spurious significant finding.]

Interpretation:

The difficulty with interpreting this study is that it doesn't actually definitively answer the research question it set out to answer. "Absence of proof is not proof of absence." The real question is whether the 4 seconds that make the SIT group different from the ET group in the 750 kJ time trial is important, REGARDLESS of the statistics. Whether or not the p-value was greater than 0.05 is actually pretty irrelevant either way. If the 4 seconds is important, then they should have done the study with enough power to detect that difference. If it's not important, then even with a p-value less than 0.05, the difference is STILL not important. Obviously, I don't think being able to cycle 4 seconds faster over approximately 30 km is that big of a deal--particularly in a population of recreational athletes, so in some ways, the conclusion is the same. But the difference between my interpretation and their interpretation is that I'm not relying on the statistic to support or not support my argument. Four seconds isn't important. That's it. The statistics can say what they want, those 4 seconds aren't going to get any more important. In THIS population anyways.

The problem though, is that my interpretation also has no further back-up to demonstrate that it's a valid one. And this is because the statistics and, more importantly, the design were mishandled to answer the question they said they set out to answer.

Bottom line:

This study is weak evidence to show that with respect to time-trial times and physiological muscle predictors of endurance performance, SIT has similar benefits to ET, but with substantially less time commitment. The good news, I suppose, is that if you're already doing HIIT, at least it's not evidence to show that you shouldn't be. But, I think that's more a result of luck than actual deliberate design.

P.S. I'm a little disappointed that no one seemed to get the title of last week's tutorial and its parallel to the song, "War", and the chorus, "War, what is it good for? Absolutely nothin'!" All that effort for a catchy title... (I even had the "Huh!" in it.)

Abstracts! Huh! What are they good for?

2007-04-16T09:23:00.000-06:00

I think it's a pretty safe statement to say that most fitness end-users, and even trainers, do not have the time or the interest (or, in some cases, the access) to read full papers. Most people tend to have easy access to PubMed abstracts, and are quite happy to read the "chunk-style" format of an abstract (thanks, Lou) because they're generally short, and fairly easy to understand (because brevity forces simplicity most of the time).

However, using abstracts as a basis for decision-making can be very problematic because there are often disparities or omissions in the abstract when compared to the full study itself.

In the research world, abstracts are used as "enticement", similar to a marketing tool. The abstract gives the reader a taste of what lies within. Most journals have a word limit of 100-200 words for an abstract of a paper that is up to 3000 words long (not including graphs and tables). Reputable researchers will never use _only_ the abstract to help them design a study or to support their research. And similar to the "enticement" of biting into a chocolate, you never know if it's going to be the one with the gross marachino cherry in the middle.

So, I guess my first piece of advice if you're one of those people who cites studies based on abstracts, is to be very careful, because it's very likely you're missing something very important. And my second piece of advice is that if you stumble on an abstract that makes you very excited, then maybe it's not such a bad idea to track it down and read the whole thing.

That being said, this article is for those of you who don't have, or don't want access to full articles and who go the already-extra step of finding the study that supports or doesn't support your particular ideas about a topic.

Human studies that involve an "intervention" (whether that's a training program, a supplement, a drug, a therapy or surgery) generally fall under a fairly small number of broad categories:

1) The case series study: This is your classic, "We gave 10 people a supplement for 4 weeks and found that it made them stronger" study. It's just a report of several single cases, amassed together.

2) The parallel case series study: This is the study that says something like, "We divided a group of people into 2 groups: one treatment group and one placebo group and give them a weight training program or a walking program and found that people on the weight training program were stronger than the people on the walking program." There's a control group of some kind, but it's not randomly assigned. So, we're still looking at the report of several or many single cases with some sort of biased comparison group.

3) The case-control study: These don't happen very often in fitness, but they crop up once in a while. "We looked at two groups of people: One group of people who were fat and another group of people who weren't fat, and looked at whether they came from rich families or poor families. We found that there were more fat people who came from poor families and there were more thin people who came from rich families," is a rough example of a case-control study. This type of study is different because we look backwards in time. We pick people who have already had an outcome of interest (the cases, in this case, fat people) and we also pick people who don't have the outcome of interest (the controls, in this case, not fat people.) We look backwards in time at something we know happened before they got that way (in this example, parental income when they were a child) and look at whether that differs between the cases and the controls. This design can be very powerful, but is tricky to use if you don't know what you're doing.

4) The randomized controlled trial: This is the gold standard study, "We randomly put people into two groups and gave one group surgery, while the other group got physiotherapy. We found that the group that got surgery did better than group that got physiotherapy."

In the research world we have a scale of evidence quality that goes from Level 1a to Level 5, with Level 1a being the highest level of evidence. The well-designed randomized controlled trial falls in the Level 1 category. Everything else falls in the Level 2 or below category. I won't bore you with the rest of the rating scale because it also depends on the quality of the study as to which Level you end up placing it.

If you can't do a randomized controlled trial (and this situation is actually quite rare), then we would prefer to see prospective data with a control group (the parallel case-series design). After that, it's a toss up between the case-control and the case-series design, with the case-control coming out slightly ahead of the case-series.

So, as a reader of abstracts, this is usually information you can identify readily in an abstract. And that's probably the most useful piece of information you can extract, because right away, you can mentally rank how good this evidence is going to be. A case-series design is automatically going to be less powerful than a randomized controlled trial, regardless of how well it's done (yes, there are exceptions, but those are finer details that come with experience and more education). Realizing you have weaker evidence right off the bat can be a very useful way of deciding how much stock you're going to put into it.

The second piece of information that you can sometimes glean from an abstract is what population was studied--and whether you, or the clients you're reading this for fit in that population. If they don't, the study automatically has less relevance for you as the reader. It doesn't mean it's useless, but it is definitely less useful. A good example of this is the classic women vs. men scenario where the vast majority of fitness studies have been performed with males only. Technically, this study does not extend to females because there were none studied! But you have to be able to ask (and possibly answer) the question of whether gender is actually important. Yes, there will probably be some kind of difference between genders, but there may also be benefit even if you were of the opposite gender of the study, unless there's something critically different between women and men that would make the study not applicable to the opposite gender. Unfortunately, this judgement call is something you learn to make over time and requires an above-"normal" working knowledge of what differences might be important and why.

The sad part about this blog entry is that this is pretty much where it ends. The reality is that you can't get a whole lot out of an abstract (as a general statement). I've read great abstracts in submitted manuscripts to a journal where I've stopped reviewing the manuscript and rejected the paper (i.e. the study does not get published) after the methods section. I barely even glance at the results section, because if the methods are critically flawed, then the results are invalid. Abstracts tend to be results-oriented because that's how they entice the reader to dig out the article. So we have this paradigm where the really important part of the study is not the part that is emphasized in an abstract, which makes it even less possible to decide whether the results you're so excited about are actually even worth reading.

Critical appraisal is as much a skill as program design, or physical skill acquisition. It requires a broad base of knowledge and consistent practice to do well. But as they say, "Practice doesn't make perfect. Perfect practice makes perfect." If it's something you really want to do, then you should learn to do it from someone who already does it well, because I can tell you that even the vast majority of Bachelor level "scientists" are inadequately prepared to do it.

My advice when it comes to abstracts is to interpret them with a healthy dose of caution. They were never meant to be used as "chunk-style" information upon which to base an action and really shouldn't be used that way.

Beta-alanine: The Harris Study (this is what grad students are actually used for)

2007-04-11T15:51:00.000-06:00

I was going to write a review of the Harris study on beta-alanine, but after reading it in detail, I realized it wasn't a randomized controlled trial at all, but rather a physiological study, with biochemical outcomes, but no "functional" ones. And despite the fact that one of their experiments was a "quasi" randomized controlled trial, I haven't got a lot to say about it because this was not a study to look at the effectiveness of BA, but rather to profile its effects. On the up side, there was a rather nice recipe for chicken broth--which is where they got their beta-alanine for one of the experimental groups:

"Fresh chicken breast (skinned and boned) was finely chopped and boiled for 15 min with water (1 litre for every 1.5kg of chicken). Residual chicken meat was removed for course filtration. The filtrate was flavoured by the addition of carrot, onion, celery, salt, pepper, basil, parsley and tomato pure, and re-boiled for a further 15 min and then cooled before final filtration through fine muslin at 4 C. The yield from 1.5kg chicken + 1 litre of water was 870ml of stock. A portion of the stock was assayed for total beta-alanyl-dipeptides (carnosine and anserine) and beta-alanine. Typical analyses were: total beta-alanyl-dipeptides, 74.4 mmol per litre; free beta-alanaine, 5.7 mml per litre. From this a dose estimated to yield 40 mg per kg body weight of beta-alanine was calculated and was provided hot to each subject."

All this and more, in: Harris RC, Tallon MJ, Dunnet M, Boobis L, Coakley J, Kim HJ, Fallowfield JL, Hill CA, Sale C, Wise JA. The absorption of orally supplied beta-alanine and its effects on muscle carnosine synthesis in human vastis lateralis. Amino Acids, 30: 279-289, 2006.

In brief, they did three experiments.

Experiment 1:

The original purpose of the first experiment was to look at the pharmacokinetics of taking 40mg beta-alanine per kg of body weight in the form of a beta-alanine drink (called Carnosyn) vs. the same dose in chicken broth vs. a drink with no beta-alanine. However, the first few subjects experienced really bad side-effects with the drink (not the broth)--symptoms of flushing, skin irritation and a prickly sensation, which began within 20 minutes of ingestion and lasted for up to an hour. Flushing was reported to occur on the ears, forehead, scalp, upper trunk, arms and back of hands, lower back and buttocks. These symptoms were unpleasant enough that 2 of the 6 subjects refused to take the 40mg/kg dose. So, the investigators decided to study beta-alanine at 20 and 10mg/kg instead. Subjects still had effects on 20mg/kg, but the symptoms were less intense. Only 2 of the 4 subjects who took the 10mg/kg dose had flushing symptoms. None of the subjects had flushing symptoms with the chicken broth, even though the dose of beta-alanine was 40mg/kg in the broth.

In the end, the researchers found that consuming beta-alanine increased the concentration of beta-alanine in the blood. The difference between the drink and the broth seemed to be that beta-alanine levels in the blood were about half for the broth compared to the drink, and took longer to peak with the broth than with the drink, but the total amount of beta-alanine detected was about the same.

There also appeared to be a non-linear relationship between the increase in peak concentration of beta-alanine in the blood, when compared with the dose given in the drink. The peak concentration of beta-alanine (BA) in the blood was 6-8 times higher when subjects drank 20mg/kg of BA than when they drink 10mg/kg of BA. But the peak concentration of BA in the blood was only 2.2 times higher when the subjects drank 40mg/kg of BA compared to when they drink 20mg/kg of BA. So there seems to be a trend of dimishing returns (i.e. every time you double the dose, the peak concentration of BA in the blood doesn't double, but progressively higher by smaller amounts).

Experiment 2:

The second study was done to see what would happen if the subjects took 10mg/kg of BA every three hours (for instance, did the body develop some sort of "tolerance" to the BA and clear it faster with repeated dosing?)

The peak concentration of BA did not change with each dose. And 3 hours was sufficient time for the subjects to return to baseline concentrations of BA before their next dose. Repeated dosing also did not produce significant side effects, other than occasional mild flushing.

Experiment 3:

The third study was done to see if 4 weeks of taking BA had any adverse effects on blood chemistry.

This study had 16 male subjects in it (the other two had only 6). The subjects were divided into 2 groups. Half the subjects took 800mg of BA, four times a day. Nothing bad happened to them. The other half got a placebo. Nothing bad happened to them either.

Experiment 3.5:

This study was lumped in with the description of experiment 3, but was a separate experiment. The purpose of this study was to look at the effects of BA on muscle. Twenty-one males were recruited. They were physically active and regularly ate meat. These subjects were divided into four groups:

Group 1 (n=5): 800mg of BA, four times a day.
Group 2 (n=5): More frequent dosing. Week one was every hour at doses of 800, 400, 400, 400, 800, 400, 400, and 400mg at 9, 10, 11, 12am and then at 3, 4, 5, 6pm. Week 2, saw an increase to 800mg for the 11 and 5 o'clock doses. Week 3, the 10 and 4 o'clock doses went up to 800mg, and in week 4, all the doses were 800mg.
Group 3 (n=5): L-carnosine in the same dosing regimen as Group 2, but 2000mg and 1000mg carnosine instead of 800mg and 400mg BA
Group 4 (n=6): Maltodextrin in the same dosing as Group 2.

A single muscle biopsy was taken from the vastus lateralis at the beginning and after 4 weeks of supplementation. Extracts were tested for BA, histidine, carnosine and taurine.

Flushing occured in week 2 for four of the five subjects in Group 2; and for 3 of the 5 subjects in Group 3 in week 4; and 1 subject in group 4 (yes, even placebos have side effects!)

BA was below the limit of detection in most muscle extracts both before and after supplementation. The mean carnosine content did increase in all groups, but only statistically significantly in Groups 1-3. No difference was detected between Groups 1-3 with respect to carnosine content.

No change was observed in body mass in any of the four groups.

Conclusions:

The authors concluded in this series of experiments that the maximum practical dose of BA should not exceed 10mg/kg per dose to avoid the unpleasant side effects. They also noted that none of the subjects had side effects when they took the BA through chicken broth and that the peak blood concentrations mimicked those of subjects who took 20mg/kg of the BA drink, despite there being 40mg/kg of BA in the broth. At 20mg/kg, many subjects still had undesired side-effects, so the recommendation from this study is to keep dosing at the 10mg/kg level, which is about 800mg for a guy.

They also concluded that there was a significant enough increase in muscular carnosine with BA supplementation to go to the next step--which would be to see if the increase in muscular carnosine would have effects on intracellular acid-base regulation, "...as a limiting factor to performance with different exercise modalities."

The Bottom Line:

The thing to take home from this study, is that if you're going to take BA, then make sure your dose doesn't exceed 10mg/kg to avoid flushing side-effects. BA is one of the precursors to carnosine, which is actually the molecule of interest in reducing fatigue. You might ask why we're not supplementing with carnosine instead of BA, and I'm afraid I don't have a good answer to that question--it may have to do with the pharmacokinetics of carnosine--definitely over the head of this humble methodologist. I know that Biotest makes a time-release version of BA, but how they are ensuring adequate dosing, I'm not entirely sure--because time-release formulations in general can be quite unpredictable. But again, not my field of expertise, so I can't reallly comment on it either way. Either way, it's not entirely clear why one would want a steady of level of BA in the blood throughout the day, if activity is restricted to only part of the day. I assuming that carnosine is possibly broken down if it's in "excess" so you're interested in keeping the "excess" constant--but why throughout the day, I'm not sure.

There's nothing in this study to support the use of BA in terms of improving the outcomes we're interested in (less fatigue, more intense workouts, bigger muscles, or less body fat). It's all fine to say that there's more carnosine in the muscle, but does that increase in carnosine translate to anything observable that might indicate that it's a worthwhile supplement to take? This is where the utility of the physiological study ends, and where clinical research picks up; and the authors of this study acknowledge that and state that there are sufficient physiological results to warrant looking at performance outcomes.

So, I'm going to end this series on beta-alanine here for now. My conclusion from the clinical trials is that there is insufficient evidence, and of the available evidence, there is insufficient quality of evidence to support the use of beta-alanine to produce performance benefits. This doesn't mean that beta-alanine doesn't work, but that we are lacking proof of benefit.

It's funny. We all violently denounce the spam on new "vitamins" or gels, or the use of raw, unpasturized milk as an anabolic agent (I swear, I found this thread on the JPFitness forum), but for some reason a hook gets created by someone somewhere that causes all-out blind acceptance hype for a pill that we should consider just as skeptically as the newest penile enlargement supplement.

I will go back to one my previous points in that my own philosophy is that every decision we make about fitness is a health decision, whether that's how we train, how we eat, what supplements we take, how we take care of injuries or how we recover from injuries. And that just because physicians don't take part in the vast majority of this aspect of health, it doesn't mean that we should hold these decisions to any less of a standard than the ones that physicians are involved in. If you're going to make the decision to take beta-alanine, then at least make an informed decision about the step that you're about to take. You should be aware that uncomfortable flushing of your ass is a possible side effect if you don't take the correct dose. You should also be aware that there is about as much evidence to support the use of beta-alanine in weight lifting as there is evidence to support the use of gel-caps filled with baby powder. Now, this evidence could change in the future--as more studies are done (if any), we will hopefully get a clearer and clearer picture of what role (if any) beta-alanine has in weight training (and other activities); but today, it's no different than baby powder.

Another beta-alanine study. Don't buy the hype.

2007-04-10T18:41:00.000-06:00

Some day, I'm going to preface a review with a sentence like, "Today's study was really well done. I was impressed by the comprehensiveness of the reporting, the concise data analysis and the practical relevance of the trial."

Today is not going to be that day.

I really try hard not to be antagonistic in these write-ups. And I really hate the fact that I sound like a broken record in every review (too many significance tests, no primary research question, inappropriate statistics, inadequate reporting of trial details--can you see the glaringly obvious trend here?), but I don't make this stuff up. I don't think I could if I tried. Quite honestly, these kinds of studies just make me angry.

In keeping with the beta-alanine theme, here's my angry review of:

Hoffman J, Raramess N, Kang J, Mangine G, Faigenbaum A, Stout J. Effect of creatine and beta-alanine supplementation on performance and endocrine responses in strength/power athletes. International Journal of Sport Nutrition and Exercise Metabolism. 16: 430-446, 2006.

Part of the reason why I keep bringing the same points up is because we've seen Hoffman and Stout before in previous reviews. If anyone is looking for a methodologist, I'm available--and at pretty cheap rates too! Who am I kidding...I'm not making any friends with these reviews....

The purpose as stated by the authors was, "...to compare the effects of creatine plus beta-alanine to creatine alone on strength, power and body compositional changes during a 10-week resistance training program in collegiate football players. In addition, a secondary purposes of this study was to examine the effect of creatine and creatine plus beta-alanine supplementation on the hormonal responses to resistance training."

Unfortunately, this is not what they actually did. Or maybe they did, but it's not what they reported. Read on.

Methods:

Thirty-three male "strength power athletes" were recruited for this study. I guess football players are also strength power athletes--whatever that means. Subjects were not permitted to use any other nutritional supplement (again, not sure what goes in this category), and did not use steroids or other "anabolic agents". All subjects had at least 2 years experience with resistance training.

Subjects were randomly assigned to one of three groups. One group got creatine with beta-alanine (10.5g/day of creatine monohydrate and 3.2g/day of beta alanine); another group got creatine (10.5g/day of creatine monohydrate); and the last group got a placebo (10.5g of dextrose). All subjects had one drink in the morning (the powder packet mixed in 8-10 oz of water), and then within 1 hour of their workout, or in the late afternoon or evening if it was a non-gym day.

[Broken record note: There is no description of the method by which the randomization sequence was generated, who assigned people to their groups, who had access to the sequence, how allocation concealment was performed, nor how blinding was performed (they mentioned the "double-blind" word, but who was the other blinded party apart from the subjects? Why thirty-three subjects? Is this another one of those, "Oh, ten subjects per group should be enough," things?]

All subjects received the same workout (4 day upper/lower body split roughly). All workouts were supervised by study personnel. This study was done for 10 weeks.

Variables:

Strength: Subjects were tested for 1RM for squat and bench press.

Power: Subjects underwent Wingate anaerobic power testing. Wingate testing is a standard protocol of interval cycling (warm-up with some 5 sec sprints for 5 minutes, followed by 3 minutes stead state, followed by 30 second all out sprint, then 3 minutes steady state, 30 seconds sprint, 3 minutes steady state and 30 second sprint). In addition to the Wingate test, subjects also did an unvalidated "jump power" test, which involved performing 20 consecutive jumps off a portable force plate with the instruction to maximize the height of each jump with minimal time in contact with the force plate. Subjects had to keep their hands on their waist at all times. The data was processed by some unknown means, reported as, "Computer analysis was used to calculated peak power, mean power and a fatigue index."

[What the *bleep* is this fatigue index??]

Body composition: Body composition was measured using DEXA.

Biochemical outcomes: Blood was drawn as fasting samples (except for 9 subjects who had their levels drawn 2h post-pradially--after a meal, that is, because of class scheduling). They tested for serum testosterone, growth hormone, IGF-I, sex hormone binding globulin, and cortisol levels.

[Why they bothered to test for cortisol levels if the 9 subjects weren't fasting and first-thing in the morning is beyond me. This pretty much invalidates any cortisol analysis in this study--one third of subjects would have had an inappropriate, invalid cortisol level.]

Diet: Subjects used a 3 day recall method to track diet.

Statistics:

The authors used repeated-measures ANOVAs to make comparisons within groups. The used regular ANOVAs to make comparisons between groups. They also calculated an effect size, "...to determine the magnitude of treatment effects, and [the effect sizes] are reported with all statistically significant results as a measure of practical significance."

[Pet Peeve number 1: In a randomized controlled trials, we are not generally interested in whether the groups did better compared to themselves. It's usually interesting, but not very important, because the question we're trying to answer here is, "Does beta-alanine with creatine do better than creatine alone or a placebo?" not, "Does beta-alanine with creatine, creatine or a dextrose improve strength/body composition/etc?" The reason why it's interesting and not important is because even if dextrose doesn't improve anything and beta-alanine with creatine does improve everything, if their effects are not substantially different from one another, the fact that dextrose did nothing and BA with creatine did something is irrelevant.

Pet Peeve number 2: You should, as a researcher, never use a statistic (like a calculated effect size) to determine whether something is practically relevant or not. The statistic doesn't know what's important or not. It's just a number. If we were looking at an always-fatal disease and found that a therapy could save 20% of patients' lives, that would be practically relevant, despite an abysmal effect size. I refer to you back to a previous entry, "Different kinds of important."

Broken record note: Lots of variables means lots of tests. And a higher chance of making a type I error. Pick a primary variable already.]

Results:

[Broken record note: There was no mention as to how many subjects dropped out of the study or why. When I count the little dots on the horrible graph above, I count 30 dots. Whether this means that 3 people dropped out, or were lost to follow-up, or whether it means that 3 people's dots overlap 3 other dots, I have no idea.]

Apart from the weaknesses I've pointed out above, the results section in this paper was...hellish to read. Let me try to sort this out by variable.

Diet: No statistically significant difference was detected between any of three groups for caloric intake. What's evident is that there was MASSIVE variation within each group in terms of caloric intake. The mean caloric intake of the placebo group was 2991 calories (SD 809 kcal). The BA+Creatine group ate an average of 3222 calories (SD 856 kcal), and the creatine group ate 2999 calories (SD 546kcal).

[In a normal distribution (which is implied when you report a mean and standard deviation--although, not everyone knows this), 66% of all the observed values will lie within one standard deviation of the mean; 95% of all the observed values will lie within 2 standard deviations. So, for the BA+creatine group, 95% of the subjects in that group ate anywhere between 1510 calories to 4934 calories a day! Albeit, it doesn't look like the groups really differed from one another very much, so we are relatively assured that this doesn't really affect the final conclusion of this study, but that's still a very wide variance!]

Body composition: No significant differences were detected within groups from PRE to POST with respect to total body mass. Redundant testing of the change in total body mass also did not reveal and significant differences within groups.

This is where the reporting goes all wonky.

The authors report that significant differences were found for change in percent body fat, but only cite two numbers: -1.21 (SD 1.12) vs. 0.25 (SD 1.53). Err....there were THREE groups in this study. What's even more baffling is that they don't tell us which two of the three groups these number belong to! The same goes for the reported significant difference between two groups for change in lean body mass: 1.74 (SD 1.72) vs -0.44 (SD 1.62). What the hell is that?

There are three graphs as well, that look like this:

The above graph is supposed to represent individual data for change in lean body mass. This has got to be one of the most useless graphs I have seen in a paper. The only thing it tells me is that the BA+Creatine group (CA) isn't normally distributed--they're all clustered up in the 2.5-3 kg range--which is good if you're trying to show BA+Creatine helps to build lean body mass, but bad if you're using summary statistics (i.e. mean and standard deviation) that are meant for normal distributions when your distribution clearly isn't normal. And also bad if you're using parametric statistical tests on non-parametric data. Just because a test is robust against violations of its assumptions, doesn't mean you should just go ahead and use it. The reason why we even bothered to figure out how robust it was, was because it was clear that a crapload of investigators were using inappropriate statistics and we didn't want the research to go to COMPLETE waste.

[What gets my goat though, is the fact that they found a significant difference between groups in change in percent body fat, but didn't find one in change in fat mass, but one of the "major" findings it that beta-alanine+creatine caused a greater decrease in percent body fat. So, basically, they picked the "significant p-value" to report as a major finding, while ignoring the disparate result that they failed to find a difference in change in ACTUAL fat mass. So does beta-alanine+creatine help you burn fat or not? Apparently it does if you use one number, but not if you use a different one--even though they measure the SAME THING. I suppose it's possible that BA+creatine increases lean body mass to the point where you'll see a difference in relative fat mass (which is what percent body fat is); but I don' t see any results for "percent lean body mass". ]

Strength: All three groups showed strength improvements in comparison to their initial 1RM's for both squat and bench press. Both the creatine and the BA+creatine groups did statistically better than the placebo group. The authors did not comment on how they did compared to each other. I can only assume that they failed to find a statistically significant difference between the two groups (at least that's how it looks in their graphs).

Power: No significant differences were detected within or between groups for any of the power tests.

Blood chemistry: No significant differences were detected between groups for any of the biochemical markers. They did find a significant difference within the creatine group for resting testosterone levels, but that's after more than 20 statistical tests. And again, no difference between groups, so it's pretty moot anyways.

Workout intensity/volume: The authors also did an unplanned analysis of workout intensity and volume. Intensity was measured by how close subjects lifted (for squat and bench press) to their 1RM. Volume was measured as the total weight lifted for bench press or squat. They found that both the creatine only and the BA+creatine group tended to have more intense workouts with higher volumes for squats, but only higher volumes for bench press.

[Unplanned analyses can be tricky. They're good for generating questions for future studies, but should never be taken at face value when the research question isn't being addressed.]

Discussion by the authors:

Before I delve into the authors' conclusions, I want to preface this section by saying I lost count of the number of significance tests performed on the data. All of the authors conclusions are based on significant values observed in the midst of a multitude of tests. There was virtually no effort on the part of the authors to explain all of the non-significant results. Instead, much of the focus was placed on the significant findings, despite the fact that they're all on a background of a plethora of tests and unadjusted for multiple testing. Additionally, even though the original stated purpose of the study was to compare creatine to creatine+beta-alanine, there was very little comment towards making conclusions to this comparison.

The major points by the authors were:

1) "The use of creatine and creatine with beta-alanine appeared to provide for a higher quality workout, and the addition of beta-alanine to creatine appeared to enhance training volume more so than supplementing with creatine alone."

If I ignore the background of multiple tests, then I could agree with the fact that both creatine and creatine with beta-alanine appeared to make for a better workout. However, there's nothing in this paper to support the idea that the addition of beta-alanine enhanced workout "quality" more than just creatine alone.

2) "In addition, beta-alanine supplementation appeared to have the greatest effect on lean tissue accruement and improvements in body fat composition."

I think I've already been through this one above.

3) "It does appear that the addition of beta-alanine to creatine provides an additive benefit in reducing fatigue rates during training sessions compared to creatine alone."

I have absolutely no idea where this conclusion comes from. It's true that just because you don't find a significant difference between groups that one doesn't actually exist in the larger population, but there's no evidence in this study to back-up this conclusion at all.

4) "No significant changes were seen during the 10wk training program in any of the power performance measures..."

The authors attribute this finding to the fact that the subjects did not train specifically for the Wingate test (i.e. the lifted weights, instead of doing interval cycling training), which begs the question of why they chose to use the test in the first place. Specificity is not exactly a new concept in training...

5) "A significant elevation in total testosterone concentrations was seen in this 10wk study for creatine only. In addition, a trend (P=0.056) was seen for a greater free testosterone index in creatine as well, suggesting a greater availability of testosterone to interact with androgen receptors. It is difficult to explain why resting testosterone concentrations were elevated for creatine but not for creatine with beta-alanine..."

If I thought I could swear on this blog without sounding unprofessional, I would (for those of you who will be at the JP Summit this weekend, you will likely get the full sensory experience that is "Bryan loses it.") a) It's not difficult to explain at all, if you consider how many tests were performed. Could this be a type I error? (The answer is most probably, "YES.") b) A p-value that is close to the critical level (in this case 0.05) does NOT, I repeat NOT indicated a "trend". You either meet the critical value or you don't. There is no meaning to the phrase, "The data approached p=0.05." At any rate, if we actually corrected for multiple tests, a p=0.056 wouldn't even come close to the adjusted critical alpha level. So this discussion point is moot.

The discussion rambles on, but I don't think I can stand picking apart the rest of it because it just makes me angry.

Both this study and the Stout study (from last week) come from the same research group and are both funded by EAS. I'm not saying that that invalidates the study--because there's so much more that does that, but I'm glad to see that it's in their disclaimer.

The Bottom Line:

If I ignore a lot of bad stuff, here's what I take away from this study:

1) There is weak evidence from this study to show that creatine and creatine with beta-alanine supplementation can have benefits to body composition, strength and workout quality.

2) There is NO evidence from this study to show that the addition of beta-alanine to creatine supplementation has any additional benefit to anything that was measured in this study.

3) I despair at the future of fitness research on a weekly basis.

So, if you're thinking of buying beta-alanine, stop. Serious. Just stop. I don't know how to get this point across any more effectively. Stick with your creatine and you'll be fine.

I really need a flashy anti-ad to compete with the beta-alanine hype.

Follow-up on the PWCft

2007-04-08T12:39:00.000-06:00

In my last post, I said I would defer to an EMG expert with regards to the PWCft test. So, I did.

I fired off an email to one of my former office-mates while I was in grad school, who was doing her PhD in Kinesiology, and is a content-expert in EMG studies. She didn't have a lot of time to give a really detailed answer, but here's what she said:

"- the EMG-force relationship is very tricky and non-linearly related. People are very sceptical to relate the two because of limitations like effort of the subject, the unquantified nonlinearity of the relation, attenuation of the surface EMG signal by adipose tissue and EMG signal crosstalk. Some researchers are currently trying to quantify the relationship, but most seem sceptical.

- NM fatigue - I know that James Wakeling did both running and cycling EMG experiments that looked at how well surface EMG can predict "fatigue". He was very cautious in the description, so that he stated they were quantifying a decrease in the signal amplitude, or a shift in the frequency of the EMG signal with muscular fatigue. Relating subsequent trials with a t-test would make me a bit nervous, as you would need to control many variables like, electrode placement (especially if over several days), sweat has been shown to attenuate
signals and can cause electrode movement, etc., etc."

Isn't collaboration wonderful?

Beta-alanine vs. um...stuff. No one really wins.

2007-04-02T23:35:00.000-06:00

Ok, I'm behind the times. By about 3 months. But you know, it's 'cause I have to go searching for this stuff all by myself! Maybe we should consider this a bit of catch-up, since the blog was started only a month ago. If you see a good study, or mention of one, send me the freaking reference! Some "cutting edge" blogger I turned out to be, eh...

I picked this paper out after listening to the FitCast (yes, thank you again, Kevin) and hearing about beta-alanine. Of course, doing a quick search on JPFitness revealed that people were talking about it in December, and that not only had it discussed on T-Nation already, with an article by Dr. Stout, I had inadvertently picked Dr. Stout's paper for this week's review. It's always risky to criticize a study that has already received fairly rave reviews, but...here goes.

Stout JR, Cramer JT, Mielke M, O'Kroy J, Toro DJ, Zoeller RF. Effects of twenty-eight days of beta-alanine and creatine monohydrate supplementation on the physical working capacity at neuromuscular fatigue threshold. Journal of Strength and Conditioning Research, 20(4):923-931, 2006.

Rationale:

Beta-alanine has been shown to increase carnosine levels in the muscle. Increased levels of carnosine have been suggested to be associated with buffering action and may assist in decreasing "neuromuscular fatigue" by buffering hydrogen ions that are produced during muscular work. Creatine has also been shown to decrease neuromuscular fatigue, though this aspect of creatine benefit has been less studied than its other effects. So, the researchers decided to look at using both beta-alanine and creatine to look at whether there would be a combined effect. To this end, they used an incremental cycle ergometer test called the physical working capacity fatigue threshold (PWCft).

[Now, a note about the PWCft. Admittedly, I did not have the time to go and dig into the journal, Ergonomics, to find the original studies where the PWCft test was developed--mostly because it would have involved hoofing it to the library to grab the hard-cover bound copies of Ergonomics, because Ergonomics only goes back to 1996 in our electronic collection here.

BUT, according to Stout et al, the PWCft is a test that "...utilizes the relationship between EMG amplitude and fatigue during submaximal cycle ergometry to identify the power output that corresponds to the onset of neuromuscular fatigue. The PWCft represents the highest power output that results in a non-significant (p>0.05) increase in muscle activation of the vastus lateralis over time."

So, I have three immediate comments about this study before I've even read the methods section. Again, I will emphasize the fact that I have not gone back to read about the development of the PWCft, so the comment here is based solely on the authors' description of what it is:

1) It seems that PWCft is basically a probabalistic test, and operates under a fundamental fallacy that a p-value that is greater than 0.05 is equivocal to implying that "no difference" exists in muscle activation after a certain power output has been achieved, and thus, assigns that power output to mean that the neural component to force generation has tapered off, and calls that "neuromuscular fatigue". However, even in the face of a correct interpretation of a p-value greater than 0.05, which would be, "there is insufficient evidence to show that a difference exists," (which would not necessarily mean that one doesn't exist--we just can't tell), we're still looking at using a non-significant p-value in a series of repeated significance tests to delineate not-fatigued from fatigued. Now we know the error rate on a single significance test is 5% in terms of finding a significant difference when one does not truly exist, but what are the chances that we're going to make the opposite error, the Type II error, which is not finding a difference when one DOES truly exist? And that has more to do with power, or the beta level, than it does the alpha level. Perhaps I will discuss the beta level later this week. Either way, using a non-significant p-value to determine anything is dubious at best.

2) We're looking at surface EMG here. Now, I understand that the PWCft is validated, and reliable and sensitive to change (all important components to validity), but I find myself skeptical about it from the get-go, knowing that surface EMG is incredibly imprecise and can be affected massively by very small factors such as electrode placement, skin moisture, atmospheric moisture, subcutaneous body fat, and luck. For the most part, there seems to be a lot of work still being done to investigate processing methods to extrapolate more information than "muscle is on, muscle is off" from surface EMG data. I'm not an EMG expert though, so if this was a real peer-review, I would either defer to one, or consult one.

3) This is NOT, I repeat, NOT a study on weightlifting. It's a study on cycling. So before you get all excited about it, I'll ask you: If there was a study showing that six sets of 30 seccond all-out intervals of cycling made your legs stronger, would you start doing 6 sets of 30 second all-out intervals of squats? (The answer is, maybe, but not based on a running study!) IF we assume that the PWCft is a valid measure of fatigue, we are still looking at fatigue over time during submaximal cycling (i.e. a test where you sit on a bike and pedal with increasing resistance until you can't maintain a pre-set RPM), not periodic lifting (i.e. a situation in which you go through a short period of activity with a constant load, rest, and do another short period of activity with a constant load, which may or may not be different than the last one). There is a certain amount of "fatigue is fatigue" to this, but fatigue is also contextual--and in particular "neuromuscular" fatigue--whatever _that_ means (which could be influenced by things like neurotransmitter reuptake, vesicle release, kinetics in the synaptic cleft--all of which would be HUGELY affected by the fact that you take a minute of rest between sets).

So based on these issues, before I even delve into the guts of the study itself, I would be leery of starting beta-alanine supplementation based solely on this study for improvement in lifting performance. Especially if it's expensive and I'm poor. However, if it's cheap and I can afford it, I _might_ try it, but that decision would not be based on anything but anecdotal hype--which, so long as you know that's what your decision is based on, is fine. Hey, I'm just as desperate as the next guy.

And yes, the opening square bracket of this comment is waaaaay the hell up there, isn't it?]

Methods:

As a general comment, the reporting of this trial was actually quite sub-par. There was a lot of detail missing.

Subjects:
There was no mention of inclusion or exclusion criteria. The authors mentioned that none of the subjects had ingested creatine or any other dietary supplement for at least 12 weeks before the start of the study. What we don't know are things like training history, where the subjects were recruited from, how many subjects were considered but excluded, why subjects were excluded if they were excluded, etc. We don't know who this study was supposed to target, and so making statements of generalizability (i.e. the population to which we are supposed to most closely extend these results to) is difficult.

Randomization:
The method by which the randomization sequence was generated was not discussed, nor was randomziation concealment, who had access to the code, what the randomziation scheme itself was, and whether there were any stratifying factors.

Blinding:
The authors stated that the subjects were blinded because they got identical tasting and appearing supplements, and that they were randomized in a "double-blind" manner. Who the other blinded party was is not known (trainer? evaluator? investigator? supplier?)

Treatment groups:
There were four arms to this trial: 1) the placebo group (34g dextrose), 2) the creatine group (34g dextrose and 5.25g creatine), 3) the beta alanine group (34g dextrose, 1.6g beta alanine), 4) the combined group (34g dextrose, 5.25g creatine and 1.6g beta alanine). The groups took their assigned supplement dissolved in 16oz of water, 4 times per day for the first 6 days and then twice per day for the remaining 22 days.

[This doesn't happen very often, so it's probably not that important, but the weight of the supplement in each of these groups is different. There have been trials that have failed because of an oversight such as weight, and subjects unblinding themselves--or at least figuring out they're not on the active treatment arm. Mostly, this comment is a teaching point.]

Measurements:
The EMG electrode was placed on the vastis lateralis, in a standardized fashion (shave the skin, scrape it with sandpaper, make a standard measurement--in this case, midway between the greater trochanter and the lateral femoral condyle, and stick the electrode on. The PWCft was determined as described above. Subjects were asked to pedal at 60 W, and 70 rpm. The power output was increased every 2 minutes by 30 W until the subject couldn't maintain 70 rpms. The authors also did a spot sample of 12 subjects to test the reliability of the PWCft. They claim to have calculated the intraclass correlation coefficient, but called it "r", which is usually the symbol for a Pearson correlation coefficient, not an ICC (whose symbol is generally ICC). There's a reference to a study by Weir, which describes how to calculate r, but I haven't gotten a copy of it yet. Just for the record, an ICC is VERY different from an r. So, maybe it's an ICC, or maybe it's a Pearson correlation coefficient. When I get the Weir study, I'll find out. The major issue here is that an ICC is generally a good tool to determine test-retest reliability, while a simple correlation coefficient is completely inappropriate.

Statistics:
The authors performed two ANCOVAs with the pretest PWCft as the covariate. [An ANCOVA is an analysis of co-variance. You can use it like an ANOVA, but it's useful when you want to control for an extra variable--in this case, pre-test PWCft.] It's not entirely clear why they did two, because I only see one ANCOVA described in this section. The authors also described using a least squares regression to examine the linearity of the relationship between the pretest PWCft and the post-test PWCft within each of the treatment groups. In the case of a significant p-value from an ANCOVA, they used Bonferroni-corrected post-hoc tests to suss out where the differences were. [I really wish they had just told us WHICH post-hoc test they used, since I can think of 3 off the top of my head.] They also used a partial eta squared to calculated effect size.

[This is one of those statistical sections that makes very little sense to me, because I'm not aware of how you use regression analysis to determine linearity, because linearity is a REQUIREMENT of least-squares regression usually. I have a suspicion that what this means is that they fiddled with the regression equation with different transformations of the predictor variables, until they got the highest R^2 value, but I'm not sure. If that's what they did, then that's also totally inappropriate too, because the highest R^2 value doesn't imply that the relationship is linear either. The reference for two of their statistical methods was the manual for SPSS, which is a statistical analysis package. I'm not saying that this analysis was necessarily inappropriate, and I'm completely willing to concede that it's possible that it's just way over my head, but this is one the most confusing descriptions of statistical methods I've read in a paper, and gut-feeling-wise, is reminiscent of some pretty random stats.]

Results (finally):

Fifty-one subjects were recruited for this study. Thirteen in the placebo group, 12 in the creatine group, 12 in the beta alanine group, and 14 in the combined group. Presumably no one dropped out of the study or was lost to follow-up, but there are no "n's" or sample sizes published in the statistical reporting, and no report on whether there were any drop-outs or losses to follow-up, so it's hard to tell.

Results were reported as means with standard errors.

[Unfortunately, a standard error is not a very useful measure of variance, because it's more a measure of precision (the standard error is derived by dividing the standard deviation by the square root of the sample size--in other words, the standard error is roughly the standard deviation adjusted per person). Equally unfortunately, is the lack of a published sample size in each group, because it's impossible to calculated the standard deviation from the standard error without the sample size, so I really have no good way to tell you much about this data or these results. And I refuse to make the assumption that there were no drop-outs to calculate the standard deviation using the original sample sizes. Why they chose to report the data this way is completely mind-boggling to me, and only re-enforces my notion that there were some pretty random decisions made with respect to the statistical analysis.]

I'm sorely tempted to stop the review here, because telling you the rest of the results can only be done in a pretty tainted kind of way. There's a lot of random reported things in the results section that, again, are either WAY over my head, or just downright inappropriate. There is no good reason why the analysis was as complicated as it was reported to be.

So, taintedly, here are what I think are the important results--and I'll just spare you from the rest of this mess. Keep in mind that reporting these results in this way, goes against every statistical fibre in my body and that in NO WAY SHAPE OR FORM, should you attempt to take these results as strong, or even moderate evidence for anything.

The primary outcome of this study was the PWCft.

The placebo group went from a mean of 215.8 to 211.2 W. Total mean change: -4.6 W

The creatine group went from a mean of 172.5 to 183.8 W. Total mean change: 11.3 W

The beta-alanine group went from a mean of 170 to 198.8 W. Total mean change: 28.8 W

The combined group went from a mean of 190.7 to 214.3 W. Total mean change: 24.4 W

Notice that I did not report the standard errors here. I will just say that given that the standard errors were in the ballpark of between 11 and 23, that the standard deviations would have been HUGE if the sample sizes were anywhere close to the sizes that they were at the start of the trial.

Nonetheless, significant differences were detected between the beta-alanine group and placebo group; and between the combined group and the placebo group. No significant difference was detected (which does NOT mean that there was no difference) between the creatine group and the placebo group; or between the creatine group and the beta-alanine group; or between the creatine and combined group.

Lastly, I think it's worth mentioning that interpreting what a PWCft actually MEANS is very difficult, particularly in the context of comparisons between groups. What is a practically important difference (see my entry of Different Kinds of Important) in PWCft? Is 28.8 W a difference that reflects a PRACTICAL improvement in performance? That's a questions that I'm really at a loss to answer and would also defer to someone more qualified.

The bottom line:

So the bottom line, if we take the data at its face value (which I am VEHEMENTLY opposed to doing, but I know people will, so I may as well interpret it with this caveat of EXTREME CAUTION)--and keep in mind that we're NOT looking at weightlifting trial here, so it all applies to "neuromuscular fatigue" in the context of submaximal cycling.

1) There is some evidence to demonstrate that beta-alanine, with or without creatine, is better than a placebo in decreasing "neuromuscular fatigue".
2) There is no evidence to demonstrate that beta-alanine is better than creatine in decreasing "neuromuscular fatigue".
3) There is no evidence to demonstrate that there is any combined effect to taking beta-alanine and creatine together in decreasing "neuromuscular fatigue".

So, the best case scenario is that I'm a doofus, and that the data can be taken at face value as I've told you above. The real-case scenario is that this study (given the way it was reported) was a dog's breakfast of statistics, and that there were MASSIVE GAPING holes in reporting, such that comprehensive and concise interpretation of the results is impossible; AND there's the additional problem of whether the PWCft is a valid outcome or not and whether the observed changes in PWCft were meaningful or not. Either way, I would say that if you're already taking creatine, then keep doing it because creatine is well studied and its effects are well documented with some pretty good and robust studies out there. And if you're thinking of taking beta-alanine instead of creatine, consider taking creatine instead, because if this study is the reason why you're thinking of beta-alanine, you'd be making an unsupported faith decision. And if you're thinking of taking both, think again, and consider just taking creatine because the best-case scenario indicates that there is no evidence to support taking both.

And if you're considering the real-case scenario, you'd need a better study.

All in all, a very disappointing paper.