My name is Nick and I am currently doing my PhD in physiology with an emphasis in muscle physiology. Welcome to my exercise science blog. Unlike a lot of fitness blogs out there, this one is unique because it is backed by true science. You will find only articles that have been peer reviewed and published in top tier science journals on this blog. For the fast easy read, just read the bold type. If you have any questions do not hesitate to ask me. I am at your disposition for any advice in exercise or just basic physiology. This is not a progress blog to benefit myself but rather to share some of my knowledge and expertise with you that I have gained over my years dedicating my career to exercise science. If I do not know the answer, I will do my best to search through the journals to find it for you. Although I am in biomedical research, I am not a licensed medical professional so please consult a physician before entering any exercise or nutrition program.
July 22, 2013
Overtraining - Conclusion
Over the past month I’ve outlined what exercise scientists consider as “overtraining”. If you’ve been following these posts you have probably come to the conclusion that overtraining does not exist. I would have to agree with that due to the lack of clear evidence of support on the topic. Although I could not put it so elegantly as CT Fletcher, I must admit that the human body does possess a high capacity to adapt to any stimulus that it is given. An adaptation to training can occur even after one bout of resistance exercise (known as the repeated bout effect). Most of you spend the majority of your day sitting at sedentary jobs or in classrooms. To have a truly taxing workout for 1-2 hours per day seems implausible to hinder recovery and performance. The problem is that there are too many variables (nutrition, sleep, mood, etc) to consider to even have a well-controlled study on overtraining. Of course, you must have proper rest and adequate nutrients to continue performing at a certain level. Lacking those two variables alone could be the culprit in the decrements you see with training and not the actual training itself. The best available source for coaches to try to diagnose overtraining is in this checklist provided by the ACSM review. I hope that you were able to take away the recent standpoint on overtraining in the scientific community and understand the lack of concise and consistent data in support of it.
The following was presented by Eric Rawson at the 2013 ACSM Conference. It is my pleasure to share it with you.
1.) Creatine monohydrate
Doses: 0.3 g/kg/day for 5 days or 0.03 g/kg/day for 30 days is sufficient to increase the concentration of creatine by 20-25%.
Washout period: 6 weeks is usually recommended
Performance factor: Increase performance of high intensity exercise of durations less than 30 seconds
Safety profile: Excellent
Doses: 3-6g for 4-8 weeks can elicit 40-50% increases. Acts as a buffer
Washout period: 10-15 weeks
Performance factor: Good for H.I.I.T. or sprinting. High intensity exercise (1-6min duration). Overall 2.58% increase in performance
Safety profile: Safe but may cause a niacin flush (paresthesia)
3.) Sodium Bicarbonate (NaHCO3)
Doses: 300mg/kg taken 1-3 hours pre-exercise can act as an extracellular buffer
Washout period: None. Some suggest as a chronic dietary supplement.
Performance factor: 1-2% increase in body mass. Increase in high intensity exercise (1-5min). Shown previously to take 0.8s off of a 1 min race.
Dose: 0.4 g/kg/hour of exercise (Milk is the best bang for your buck) 1.6-1.7 g/kg/day.
I think it also important to not neglect your carbohydrates. In exercises lasting 30 seconds to 1 minute, a lot of people think that most of the energy is coming from creatine. In actuality, 10% is coming from creatine whereas 47-60% is coming from carbohydrate stores. 1.2 g/kg/hour of carbohydrates post-exercise is sufficient for muscle glycogen resynthesis.
Several physiological factors have been proposed that could relate to overtraining syndrome. It seems the most plausible one is a reduced maximal heart rate but studies suggest this is not a valid tool to measure OTS due to inconsistent results.
Sustained periods of intense training leads to decreases in innate and adaptive immunity. Depressed immunity typically is said to occur for athletes at the end of the season or during the most intensive periods of their training. The only evidence that exists for a decrease in immune function in athletes experiencing OTS is anecdotal.
In regards to resistance training, when excessive volumes of max loads are used, maximal muscular strength is one of the last performance measures to be negatively affected. Rather, high speed (ie. sprinting) and power are the first types of performance to be affected.
There is no evidence that OTS can be treated. Rest and very light training seem to be the only agents capable of effecting recovery. It is generally recommended that athletes should have one passive rest day each week. Trying to prescribe an exact amount of hours of sleep per night is difficult. Therefore, a good starting point is to advise athletes to sleep for the amount of time required to feel wakeful during the day.
When scientists use psychological questionnaires about athletes’ moods there was a consistent reporting of an increase in negative mood states (tension, depression, anger) and a decrease in vigor during periods of vigorous training. This is shown in a dose-response relationship, meaning that the longer the periods of intense training the more the athlete will report these negative mood states. As little as 2 days of intense training can increase these negative moods and currently there are no differences in the mood responses reported between male and female athletes.
Of course it is difficult to decipher whether these negative moods are a result of the training or hardships from social situations. Therefore, some researchers have developed a sport specific scale to use rather than the typical psychological questionnaires called a Training Distress Scale (TDS). You can find a spreadsheet of this scale here. The TDS was shown to be more accurate in identifying overtraining than the typical psychological scale.
A new tool that researchers are using to diagnosis overtraining syndrome is a psychomotor speed test, which measures the cognitive factors of the athlete (memory & concentration). This test could simply be a reaction time test. Reaction times have been reported to decrease in athletes when they increase the intensity of their training for several weeks. These studies lead us to believe that central fatigue (a tired brain) is possibly the most early predictor of overtraining.
The most consistent overall finding in endurance and strength-trained athletes who have OTS is a decrease in the maximal lactate concentration while submaximal values are unaffected or only slightly reduced. Glutamine levels are often toted as another possible marker to indicate excessive training stress. However, several problems exist with biochemical testing of overtraining:
Lactate differences can be subtle and depend on the type of exercise test used.
No lactate changes are reported in strength athletes.
Glutamine may decrease with excessive training but low levels are not a consistent finding in OTS.
At first, scientists tried to measure the testosterone/cortisol ratio as a marker of overtraining. This is not possible because this ratio only indicates the actual physiological strain of training. Furthermore, during rest days in endurance-trained athletes, 24 hour cortisol secretion is normal and even comparable to levels of sedentary individuals. Problems exist with hormonal testing as well:
Many factors other than exercise affect blood hormone concentrations such as stress or food intake.
In females, it depends also on the menstrual cycle.
Different hormones are released depending on the modes of training (endurance vs. resistance).
It is noted that there is no definitive way to identify overtraining syndrome (OTS). The only way a coach can do so is by eliminating all other factors that could be causing these symptoms. Once all of the other factors are eliminated, one can then diagnose OTS. The only clear sign is a decrease in performance during competition or training.Currently, there are no simple diagnostic tests to diagnose overtraining and the theories regarding what triggers it are speculative at best.
Taking into account the overlap and still unclear guidelines of overreaching/overtraining, I will now list for you some of the statistics on the prevalence of OTS.
One survey listed a rate of approximately 10% in collegiate swimmers and other endurance athletes.
For elite runners, 60% of females and 64% of males indicated experiencing OTS with numbers being 33% in non-elite adult runners
A recent longitudinal study reported a rate of 29% in age-group swimmers
91% of US collegiate swimmers that reported OTS a first time went on to experience it a second time or more.
To assess OTS, several studies have listed it as being the sum of multiple life stressors, such as training, sleep deprivation, environmental stress, work pressure, and interpersonal problems. Scientists are still looking for a biomaker (in the blood) to measure and determine the existence of OTS.
We know that there must be a balance between appropriate training stress and adequate recovery. Otherwise, this leads to what exercise scientists define as overreaching. Overreaching is an accumulation of training and/or non-training stress resulting in short-term decreases in that capability to perform with or without related physiological and psychological signs and symptoms of maladaptation. Restoration of performance capacity could take several days to several weeks. The difference between this and overtraining is that overtraining is long-term,in which restoration of performance capacity can take several weeks or months. We are looking at solely a time difference between the two.
An example of an athlete who is overreaching would be one that goes to a training camp. The intensity level of the camp is normally very vigorous, which would lead to a temporary decline in performance accompanied later by overall improvement of performance. This can also be noted as functional overreaching. When it gets to the extent of not helping the athlete improve their performance capacity, it then can be described as non-functional overreaching because it leads to stagnation or decreases in performance which will require several weeks or even months to recover.
Overtraining syndrome is considered a syndrome because it takes in to account not just exercise as the main factor but also inadequate nutrition, illness, psychosocial stressors, and sleep disorders.
Below is an example of the difference stages of training and how they relate to overreaching and/or overtraining.
Are you a girl who regularly skips breakfast? Read on because this well-controlled study is for you.
Introduction: Breakfast skipping is strongly associated with a greater chance of weight gain. Furthermore, this trend is also linked to poorer food choices. Higher protein meals are becoming more popular as a way to improve satiety and appetite control. The purpose of this study was to examine if it is better to skip breakfast or eat one higher in protein in regards to appetite control throughout the remainder of the day.
Methods: Twenty overweight or obese girls between the age of 15-20 who normally skip breakfast were recruited for this study. They were tracked for 7 consecutive days and randomized to one of 3 groups: breakfast skipping (BS), a normal cereal meal for breakfast (NP), or a high-protein breakfast (HP) consisting of beef and eggs for breakfast. Breakfast and lunch were controlled but the rest of the day they were free to eat as much as they wanted.
NP & HP led to a 60% reduction in daily hunger.
HP lead to a greater increase in total fullness.
NP & HP led to a 30% reduction in daily desire to eat.
HP breakfast but not the others suppressed an important hunger stimulating hormone (ghrelin) by 20%.
HP breakfast but not the others increased an important satiety-stimulating hormone (PYY) by 250%.
BS & NP led to greater evening snacking than HP.
Discussion/Conclusion: A small breakfast of merely 350kcal led to reductions in perceived hunger, the desire to eat, and prospective food consumption. In addition, it also increased fullness. What is even more interesting is that the high-protein breakfast group had additional benefits of a reduction in the hunger-stimulating hormone ghrelin, increases in PYY (a hormone that makes you feel fuller), and decreases in evening snacking, particularly of high-fat foods. The authors note that a limitation of this study was that the breakfast skipping group and the high-protein group had similar total amounts of calories consumed during the day. Although this study looked at 1-week of food consumption, it is not certain if eating a high-protein meal for longer periods of time (a year or more) would prevent weight gain.
My input: The most obvious inferences that the authors draw come from the simple fact that the breakfast skipping group is fasted. Of course, their perceived hunger/fulness, desire to eat, and prospective food consumption will be higher in the morning because they just woke up. I think the most powerful part of the study came from the blood draws and the actual measurable physiological significance that a high-protein breakfast did decrease a hormone responsible for making you want to eat and increase a hormone that tells your brain that you are full.That is what truly stands out as powerful rather than all the other results based solely on questionnaires. For that reason, I’d suggest trying out the high-protein diet over your standard cereal-based breakfast and seeing how it works with your own feelings of satiety throughout the day.
Apologies for the period of dormancy. I’m back and I’m bringing you new articles every Wednesday. With that said, here we go.
Introduction: Men and women store fat on different areas of the body. Women store fat in larger amounts of subcutaneous adipose tissue (the fat under the skin) and men store more visceral fat (the fat around the organs). In general, women have more body fat than men. How much adipose tissue contributes to whole body metabolism is not well known; therefore, this was the aim of the study.
Methods: This was a large cohort coming from hundreds of men and women. The researchers looked at adipose tissue gene expression as well as expression of genes involved in mitochondrial function.
For the two sexes, fat mass and fat free mass positively correlated with resting metabolic rate (when one went up, the other went up).
Women have a higher metabolic rate per kilogram adipose tissue than men.
Women have a higher expression of genes related to mitochondrial function than men.
Women have a higher number of brown adipocytes in subcutaneous adipose tissue than men.
Discussion: Just to give you an idea of the relative contributions of tissue to basal metabolic rate (BMR), the brain and internal organs account for 70-80% but only make up 5% of the body weight. Skeletal muscle, which everyone in your gym says influences BMR the most, is 20 times lower than the internal organs. Skeletal muscle accounts for about 15% of a person’s BMR. Adipose tissue falls in at around 6% of BMR so we can say it is not that active of a tissue.
From the lab to the gym: So what’s the main takeaway of this study? The practical message is from bullet point 4 of the results and particularly a molecule found in those brown adipocytes known as UCP1. UCP1 is a protein that allows the mitochondria to create heat in the brown adipocytes. Women have a higher amount of UCP1 in their subcutaneous adipose tissue (the fat you want to lose under your skin). Therefore, this study suggests that women have a higher capacity to burn calories by converting energy to heat. Of course the internal organs and muscle are going to contribute the most to your BMR, but the higher metabolic rate of adipose tissue in women gives them an advantage to burn more calories in a resting state than men.
A fresh article was published in the New England Journal of Medicine yesterday that looks at the most common myths, presumptions, and facts about obesity. What really makes this paper intriguing is that the authors used internet searches to find these. Since some of you might not have assess to the full text, or not have the time to read the entire article, I’ll highlight some of them for you below.
The myths (the authors define myths as “beliefs held true despite substantial evidence refuting them”)
Small sustained changes in energy intake or expenditure will produce more substantial long-term weight changes.
Setting realistic goals for weight loss is important; otherwise, people will become frustrated and likely lose less weight.
Slower gradual weight loss is better than large rapid weight loss in regards to long-term outcomes.
PE classes in school play an important role in reducing or preventing childhood obesity.
A bout of sexual activity burns 100-300 kcal for each participant. (The authors state the actual numbers are more like 14-21 kcal considering the average sexual experience lasts 6 minutes, ouch).
The presumptions (the authors define presumptions as “unproved yet commonly espoused propositions”)
Eating breakfast each day as opposed to skipping it is protective against obesity.
Eating more fruits and vegetables will result in weight loss or less weight gain, regardless of any other behavioral or environmental modifications.
Weight cycling (yo-yo dieting), is associated with increased mortality.
Snacking contributes to weight gain and obesity.
An individual’s environment (parks, recreational playgrounds, etc.) influence the incidence and prevalence of obesity.
THE FACTS (“sufficient evidence to be considered empirically proved”)