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Giving Feedback on Skill Performance

This post is intended to give an overview of several aspects of coaching science, in particular surrounding provision of feedback to athletes, something which numerous coaches (both strength and technical/sport coaches) often don’t do effectively.

There are two main types of feedback – intrinsic and extrinsic. Intrinsic feedback can be viewed as ‘self’ feedback and something that the athlete knows occurred, for example if an athlete bails from a snatch they are intrinsically aware that this occurred. Extrinsic feedback comes from external sources such as, and most commonly, a coach, but can also come from video analysis and the use of mirrors.

In terms of extrinsic feedback, most authorities in coaching science (i.e. Gabriele Wulf and Nick Winkelman) agree that using external feedback/cues is more effective than using internal – for example in a vertical jump ‘touch the ceiling’ instead of ‘extend your knee and hips quickly’. There are two types of extrinsic feedback, you can inform them of what you saw (descriptive) or elaborate on what they need to do to fix the error you witness (prescriptive). Descriptive is regarded as better for athletes with a lower training age/less experience, whereas prescriptive is better for more technically mature athletes.

The author of the article referenced below (Wrisberg) talks about when to give feedback, providing a key quote – “when in doubt, be quiet”.  He (Wrisberg) is of the opinion that coaches should resist the temptation to provide assistance and coaching cues too often and instead permit the athletes to practice skills on their own (a form of guided discovery). He then goes on to say that the least helpful form of feedback is simply providing extrinsic feedback that is the same as their own intrinsic feedback – provide feedback only when an athlete can’t identify the error or pick up on the intrinsic feedback. An example of this is if an athlete drops the bar mid-way through a deadlift there is little point in informing them that their grip failed/was weak. The most beneficial form of feedback for an athlete will direct them towards sources of intrinsic feedback. I recently encountered an example of this in my own coaching practice whereby an athlete who I was teaching to clean wasn’t keeping the bar close and ‘brushing’ the thigh. To rectify this I put lines of chalk from the middle to the upper portion of his thigh and told his to try to brush the chalk off with the bar with every repetition.

Keeping the bar close in the clean

Once athletes are proficient at identifying relevant intrinsic feedback on their own, they will eventually need less extrinsic feedback and cueing from the coach. The caveat to this is that if athletes have not fully ‘bought in’ to strength and conditioning they may not be interested in learning the skill we are teaching (such as the clean) thus they are unlikely to ask for feedback and they will not focus on their own intrinsic feedback. This highlights a motivational aspect to this element of coaching science.

Recent research in coaching science has suggested that giving more frequent feedback is not more effective when it comes to promoting skill development when compared to giving less frequent feedback. Wrisberg suggests that coaches give the minimally effective amount of feedback to avoid overloading the athlete. If more feedback is deemed necessary then it may be appropriate to utilize summary/average feedback after a session during a breakdown. Athletes’ performance will still improve in the absence of frequent extrinsic feedback as the athlete is required to solve their own movement errors and they are able to focus more acutely on their own intrinsic feedback. If feedback is provided too often athletes may become dependent on it, as they will immediately attempt to incorporate the feedback in the next repetition and, if they’re provided with different feedback each time, they will be incapable of achieving any stability in their performance. As a result of this they will not gain an understanding of what they’re doing and the outcome that they’re achieving. Thus an overall rule is to give feedback to athletes more regularly during early learning phases and progressively less frequently as their skill levels improve.

Quality of feedback is more important than quantity; to achieve higher quality feedback coaches must consider the content, precision, timing, and conciseness of the cues in order to deliver the most effective message to the athlete/s. Wrisberg also says that delaying feedback has some benefits as it encourages athletes to become self-sufficient. The best way to delay feedback is to first ask athletes questions such as ‘why do you think ____ happened?’, which will force them to evaluate their own intrinsic feedback, only after they answer will extrinsic feedback be provided by the coach. Challenging athletes to detect their own errors and come up with solutions will facilitate skill development and improve their ability to detect and correct mistakes.

Increasing feedback precision is another important aspect of skill acquisition and coaching. Wrisberg suggests the use of bandwidth feedback, something that I have utilized regularly in my coaching practice. Bandwidth feedback requires establishment of a performance bandwidth – this being the amount/extent of error you will tolerate before cueing/providing extrinsic feedback to the athlete (a tolerance zone). If an athletes’ skill performance remains within the tolerance zone, there’s no requirement to give feedback, if it deviates outside of this zone then corrections must be made via feedback. With lesser skilled athletes the bandwidth will be wider, which allows coaches to provide more general feedback in order to improve gross performance of the skill. With athletes of a higher level (and where precision is more important) the bandwidth should be narrowed, meaning feedback will be given for even minor performance errors. From a skill acquisition perspective I believe this is a very useful tool. If working memory can only store seven +/- two pieces of information then it’s important to avoid overloading the athletes’ memory with excessive cues (particularly if they’re poorly thought out). In my coaching I try to focus on three main points for every skill/lift in the session (plus any general safety considerations), for example when coaching band resisted acceleration drills in speed/agility sessions I inform the athletes to focus on a good torso lean, powerful arm drive (hip pocket to eye socket), and to apply maximum force into the ground with every step. I then only emphasise these points (or cues relating to these points).

Being aware of the science of giving feedback not only allows us to coach our athletes more effectively and efficiently, it also helps in preventing reinvestment.  Reinvestment is the attempt to consciously control your own movement during skill execution by constantly trying to apply explicit and rule-based knowledge to the skill. For example immediately prior to the second pull in the clean an athlete might think ‘how do I catch the bar?’ if they’ve been over-coached/had excessive feedback in their rack position or catch technique. This can also be known as choking, freezing, or the ‘yips’.


Reference

http://www.humankinetics.com/excerpts/excerpts/considerations-for-giving-feedback-on-skill-performance

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Movement Screening

Movement Screening

Introduction 

Understanding the physiological and biomechanical demands of a sport and the current ability of an athlete to meet these demands is of paramount importance when both preparing for competition and providing late stage rehabilitation following injury.1 In order to evaluate these demands a needs analysis of the sport and athlete is undertaken, this will consist of varying elements depending on the sport in question. It will often include, for example, a time motion analysis, a profile of energy systems, strength diagnostics, sport biomechanics, and research into injury epidemiology and aetiology.2 3

An essential component of the athlete-specific needs analysis is a movement screen, commonly consisting of a battery of assessments with the aim of determining potential injury sites, movement restrictions, and kinetic chain dysfunctions from a global perspective. The presence of dysfunction and restrictions will force the body to create compensatory movement strategies (CMS) in order to retain its ability to carry out movement tasks, These CMS are often kinesiopathologic,4 5 due to suboptimal load transference throughout the system and causation of undue mechanical stress to bodily structures. As such, it is important for a strength coach/sport rehabilitator to perform movement screens since it is far more effective and efficient to be proactive in addressing dysfunctions and restrictions rather than being reactive to injury when it occurs.

Movement screens are generally based around functional movements rather than isolated motion on a plinth, this allows the strength coach/sports rehabilitator to determine any CMS the athlete uses when performing sport-specific tasks. This is highly important during initial screening, but maybe more so in late stage rehabilitation as it must be ensured that the athlete is sufficiently robust and mechanically sound to avoid re-injury. This is particularly evident as previous injury has been demonstrated as the most reliable predictor of re-injury.6  

Numerous function-based screens have been developed and demonstrated to be effective, some of these include; the Y Balance,7 Performance Matrix,5 and Functional Movement Screen (FMS).1 All of these screening systems have their individual merits, however currently the FMS is the most well-known and used. The aim of this paper is firstly to discuss, critique and provide possible modifications for the FMS. Secondly an evaluation of an athlete’s deep overhead squat (OHS) will be provided, whereby restrictions will be highlighted along with potential interventions to improve their performance of the movement.

FMS 

The FMS1 consists of a battery of seven fundamental movements which challenge mobility, stability, and motor control (see Cook1 and Cook8 for full details of the movements involved). These movements theoretically form the foundation of all other sport-specific patterns.9 The premise of the FMS is that athletes may be predisposed to injury and suboptimal performance if asymmetries, weaknesses, limitations or imbalances are present in any of these movements.1 10 This subsequently alerts strength coaches/sports rehabilitators to these issues and permits them to carry out diagnostic testing on the athlete concerned.

To determine movement competency each movement is scored on a zero to three ordinal scale. A score of zero signifies that pain was experienced in the movement. A score of one indicates an inability to fully complete the movement. A score of two signifies movement completion but with a degree of compensation. A score of three is given if optimal performance is demonstrated. Five of the tests are given a separate score for the left and right side of the body to account for asymmetries, although only the lower of the two is taken for analysis. The sum of these scores forms a composite score of between zero and 21.

The FMS has been demonstrated to have an acceptable ability to predict injury in male military personnel,11 male athletes,10 and female athletes12 when the composite score is <14 (determined via use of a receiver-operator characteristic curve.13 In fact findings from Kiesel et al10 stated that football players were as much as 12 times more likely to be injured with a score below this cut-off point. There are, however, issues with 14 being a cut off score. One argument is that it is possible to score more than 14 even with asymmetries in all of the two-sided tests. Asymmetries are suggested to be a risk factor for injury by a number of authors.1 14-15 Yet little evidence exists to support this suggestion. In a study by O’Connor et al11 no statistical evidence supported asymmetry as a risk factor for injury in military personnel. Additionally it is possible, as in the case of stroke victims, amputees, and cerebral palsy patients, to function and live pain-free with compensations and asymmetries. On the contrary, an athlete in a lower-limb dominant sport may receive a composite score of 14 but still have scored mostly threes in the lower-limb movements. This raises the question of whether this athlete is truly at risk of injury.

Research has additionally critiqued the FMS composite score as a whole, stating that it lacks internal consistency and does not function as a unidimensional construct,16 thus changes to the scoring system have been.17-18 In one study18 it was suggested an objective motion capture system could be used. The researchers compared manual grading (standard subjective FMS criteria) to an objective grading criterion using video and kinematic thresholds related to each FMS grading criteria. The rationale for this research was that the FMS scoring system assumes the tester can adequately distinguish the mechanics relevant to each of the grading criteria in order to grade them accurately. The results of this study showed discrepancies between the manual grading and objective grading methods, highlighting that manual grading may not be a valid method. Butler et al17 also proposes changes, suggesting a 100-point grading scale. The researchers theorise that this will promote greater precision (higher inter-rater reliability) and provide more distinction between scores along with offering more detail as to when movement issues occur.

Despite the aforementioned scoring system faults the FMS has been shown to have high levels of inter- and intra-rater reliability19–21 And although content validity, construct validity, face validity, and sensitivity are deemed to be suboptimal, its specificity and injury prediction abilities are regarded as strengths.18 20 

Within the suboptimal elements, lack of content validity may be an issue. This presents itself in the fact that the FMS only tests low load/low threshold movement strategies, whereas in sport the majority of tasks are high load/high threshold (different neural pathways). Frost et al22 looked at the influence of load and speed on five different foundational movement patterns and found that the subjects adapted their movement strategy as a response to heightened task demand. A screen should be a comprehensive, global approach to determine sport specific ability. A lack of high load movements in the FMS prevents it from fully achieving this aim. To improve this aspect of the FMS it would be advisable to borrow from the Performance Matrix method5 which utilises screen for both low load/motor control and high load/strength and speed deficits to identify problems.

Overhead Squat

The OHS is a commonly used screening tool due to its ability to test global mobility, trunk stability, control of posture, and overall total body mechanics. As a triple flexion/extension movement pattern, the ability to perform a bilateral squat has application to numerous physical activities. In the OHS, as per FMS criteria, an ideal technical model would include the points outlined in Figure 1 along with the ability to descend and ascend in a stable and controlled manner and maintain stability whilst in the bottom position.

Figure 1. Technical model for the deep overhead squat.

Figure 1. Technical model for the deep overhead squat.

Figure 2 was taken from the video provided and demonstrates an athlete’s ability to perform an OHS as per the FMS protocol. When comparing the screenshots in Figure 2 to the technical model in Figure 1 it is apparent that the athlete has a number of limitations in their performance of this movement. In the sagittal plane there is an excessive anterior trunk lean, an inability to break parallel (hip crease below knee level) in the bottom position, and a noticeable lack of dorsi-flexion. In the frontal plane the athlete demonstrates uncontrolled motion manifesting as a weight shift onto the right side, this is also apparent due to the angulation of the dowel held overhead. Due to these dysfunctions, the athlete would have scored a one on the (albeit flawed) FMS scoring criteria.

FMS OHS 1

Figure 2. Athlete performing the deep overhead squat.

If an athlete scores a one on the FMS OHS they are permitted to attempt the movement with a two inch heel lift. Figure 3 shows the effect of this on the athletes’ performance. Noticeable improvements in depth, trunk angle and movement control are visible, which suggests that a lack of closed kinetic chain ankle dorsi-flexion is a limiting factor for this athlete. This athlete would now score a two on the FMS scoring criteria.

FMS OHS 2

Figure 3. Athlete performing the deep overhead squat with a heel lift.

The ability to dorsi-flex the ankle has been demonstrated as essential when performing the OHS.23 To complete a full OHS with the foot in full contact with a flat surface evidence has demonstrated that 39 ± 6° of dorsi-flexion24 is required. Without ankle dorsi-flexion this athlete will likely be predisposed to injuries such as Achilles tendinopathies, anterior talofibular ligament (ATFL) sprains, hamstring strains, and flexion-type lumbar spine injury. These injuries may occur as the body will compensate for the lack of ankle dorsi-flexion by prolonging or increasing the velocity of pronation (to allow dorsi-flexion to occur at the mid-foot) which has adverse effects further up the kinematic chain. Decreased ankle dorsi-flexion may also cause inhibition of the peroneus longus muscle (amongst others); this muscle is required to decelerate ankle inversion (part of the mechanism for ATFL injury). If the body is unable to compensate through the foot complex, motion may come from increased hip flexion, increasing spinal loading during high load tasks. In addition to this, if a joint can not feel motion (due to restriction) mechanoreceptor function will be compromised, preventing afferent signals travelling to the central nervous system.

This athlete has previously had treatment on the contractile, non-contractile and neural tissues surrounding the ankle in order to improve dorsi-flexion range of motion (ROM), however these had proven to be ineffective. Therefore in order to address this restriction it would be prudent to now address the arthrokinematics of the talocrural joint.25 Reductions in dorsi-flexion ROM is linked to an inability of the talus to posteriorly glide on the tibia,26 potentially due to an anterior positional fault of the talus due to previous lateral ankle ligament injury.27

Mulligan28 29 suggests the use of mobilisations with movement (MWM) for individuals with this articular positional fault. These techniques have been demonstrated to cause a significant increase in ankle dorsiflexion ROM in 60 healthy subjects in functional tasks.30 An MWM for ankle dorsiflexion will involve a continuous passive mobilisation whilst performing full ROM active dorsi-flexion movements; these can be carried out either weight bearing or non-weight bearing.

A weight-bearing (half-kneeling) MWM was used as an intervention for this athlete. Prior to the mobilisations the athletes’ ankle dorsi-flexion range was measured objectively using the weight-bearing lunge test (WBLT)31 (Figure 4), this was important in order to determine if the MWMs were having an effect. If the WBLT score did not improve it would have been evident that the restriction may not have been articular in nature. Three sets of 15 repetitions (approximately 60 seconds) were performed on each ankle at a sustained and controlled pace. Upon re-doing the WBLT significant improvements were noticed in ankle dorsi-flexion ROM. This new ROM was then tested globally in the OHS, where improvement in squat depth and trunk angle were observed (similar to when using the heel lift), indicating that the MWMs were effective as an intervention. In light of this, the athlete was instructed on how to perform a self-mobilisation reported to have the same effect26 (Figure 5).

 

Ankle Mobs

Conclusion

This paper has highlighted the importance of movement screening in athletic populations. A movement screen is comprised of battery of movements with the aim of detecting movement faults, which then enables strength coaches/sport rehabilitators to retrain these faults to prevent injury/re-injury. It is important to understand that there is no ‘one size fits all’ screen, as every sport involves different movement patterns and has different injury sites, thus it is appropriate forstrength coaches/sport rehabilitators to create their own. Every test, movement, exercise, or performance therefore can be used as an assessment. A number of screens have been suggested (such as the FMS) however these ‘pre-packaged’ screens commonly have flaws which can impact their application to clinical practice. These include limitations in scoring techniques, movement context (high vs low load) and sensitivity. An analysis of an athlete’s OHS was provided; optimal performance of this movement indicates good global mobility trunk stability, control of posture, and overall total body mechanics, which demonstrates good athletic performance potential. This athlete showed compensations when performing the movement, which upon investigation were due to a lack of ankle dorsi-flexion. Leaving this unaddressed could predispose the athlete to injury (ankle dorsi-flexion is a common probable suspect for injury). After a treatment of MWMs the athlete improved dorsi-flexion ROM and overall OHS performance. It may therefore be appropriate to recommend that this athlete (and others who lack dorsi-flexion) incorporate self-mobilisation of the ankle into their training regimes in order to enhance athletic performance and reduce the risk of injury.

References

  1. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function – part 1. N Am J Sports Phys Ther 2006;1:62–72.
  2. Kraemer, W J. Exercise prescription: Needs analysis. Strength Cond J 1984;6:47–8.
  3. Newton R, Dugan E. Application of Strength Diagnosis. Strength Cond J 2002;24:50-9.
  4. Sahrmann SA. Diagnosis by the physical therapist–a prerequisite for treatment. A special communication. Phys Ther 1988;68:1703–6.
  5. Mottram S, Comerford M. A new perspective on risk assessment. Phys Ther Sport 2008;9:40–51.
  6. Schwellnus M. A clinical approach to the diagnosis and management of acute muscle injuries in sport: review article. Int Sport J 2004;5:188-199.
  7. Plisky PJ, Gorman PP, Butler RJ, Kiesel KB, Underwood FB, Elkins B. The reliability of an instrumented device for measuring components of the star excursion balance test. N Am J Sports Phys Ther 2009;4:92–9.
  8. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function – part 2. N Am J Sports Phys Ther 2006;1:132–9.
  9. Minick K, Kiesel KB, Burton L, Taylor A, Plisky P, Butler RJ. Interrater reliability of the functional movement screen. J Strength Cond Res 2010;24:479–86.
  10. Kiesel K, Plisky PJ, Voight ML. Can Serious Injury in Professional Football be Predicted by a Preseason Functional Movement Screen? N Am J Sports Phys Ther 2007;2:147–58.
  11. O’Connor FG, Deuster PA, Davis J, Pappas CG, Knapik JJ. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc 2011;43:2224–30.
  12. Chorba RS, Chorba DJ, Bouillon LE, Overmyer CA, Landis JA. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther 2010;5:47–54.
  13. Fan J, Upadhye S, Worster A. Understanding receiver operating characteristic (ROC) curves. CJEM 2006;8:19–20.
  14. Parkin S, Nowicky A V, Rutherford OM, McGregor AH. Do oarsmen have asymmetries in the strength of their back and leg muscles? J Sports Sci 2001;19:521–6.
  15. Gorman PP, Butler RJ, Plisky PJ, Kiesel KB. Upper Quarter Y Balance Test: reliability and performance comparison between genders in active adults. J Strength Cond Res 2012;26:3043–8.
  16. Kazman JB, Galecki JM, Lisman P, Deuster PA, O’Connor FG. Factor structure of the functional movement screen in marine officer candidates. J Strength Cond Res 2014;28:672–8.
  17. Butler R, Plisky P, Kiesel K. Interrater reliability of videotaped performance on the functional movement screen using the 100-point scoring scale. Athl Train Sport Heal Care 2012;4:103-4.
  18. Whiteside D, Deneweth JM, Pohorence MA, Sandoval B, Russell JR, McLean SG, et al. Grading the Functional Movement ScreenTM. J Strength Cond Res 2014;1:10-12.
  19. Elias JE. The Inter-rater Reliability of the Functional Movement Screen within an athletic population using Untrained Raters. J Strength Cond Res 2013;11:5-8.
  20. Beardsley C, Contreras B. The Functional Movement Screen: A Review. Strength Cond J 2014;36:72-80.
  21. Smith CA, Chimera NJ, Wright NJ, Warren M. Interrater and intrarater reliability of the functional movement screen. J Strength Cond Res 2013;27:982–7.
  22. Frost DM, Beach TA, Callaghan JP, McGill SM. The influence of load and speed on individuals’ movement behavior. J Strength Cond Res 2013;12:11-20.
  23. Kasuyama T, Sakamoto M, Nakazawa R. Ankle Joint Dorsiflexion Measurement Using the Deep Squatting Posture. J Phys Ther Sci 2009;21:195–9.
  24. Hemmerich A, Brown H, Smith S, Marthandam SSK, Wyss UP. Hip, knee, and ankle kinematics of high range of motion activities of daily living. J Orthop Res 2006;24:770–81.
  25. Loudon JK, Bell SL. The foot and ankle: an overview of arthrokinematics and selected joint techniques. J Athl Train 1996;31:173–8.
  26. Cosby N, Grindstaff T. Restricted Ankle Dorsiflexion Self-mobilization. Strength Cond J 2012;34:58-60.
  27. Cosby NL, Koroch M, Grindstaff TL, Parente W, Hertel J. Immediate effects of anterior to posterior talocrural joint mobilizations following acute lateral ankle sprain. J Man Manip Ther 2011;19:76–83.
  28. Hing W, Bigelow R, Bremner T. Mulligan’s Mobilization with Movement: A Systematic Review. J Man Manip Ther 2009;17:39–66.
  29. Mulligan B. Manual Therapy: NAGS, SNAGS, MWMS, etc. 6th edn. Minnesota: OPTP, 2004.
  30. Guo L, Yang C, Tsao H, Wang C, Liang C. Initial effects of the ankle dorsiflexion mobilization with movement on ankle range of motion and limb coordination in young healthy subjects. 物理治療 2006;39:93-94.
  31. Konor MM, Morton S, Eckerson JM, Grindstaff TL. Reliability of three measures of ankle dorsiflexion range of motion. Int J Sports Phys Ther 2012;7:279–87.

 

Optimal Methods for Gaining Muscle

arnieMuscle hypertrophy – increasing muscle size/promoting muscle growth. Probably the most popular reason for most people joining gyms and/or beginning lifting (alongside fat loss). Gaining lean muscle mass makes you look better and feel better, it’ll also help with fat loss (muscle tissue is highly metabolic/’energy hungry’) and can lead to improvements in strength and power – and therefore sports performance.

Many people join gyms, begin a programme and see results fairly quickly, and these results continue for a few months until the ‘beginner gains’ plateau is hit. At this point things slow right down, frustration sets in, and the person will inevitably quit or at best end up stuck in a rut, miserable, and paying an expensive gym membership for nothing. This usually occurs because trainers and trainees have no understanding of how to trigger muscle hypertrophy (following the initial ‘honeymoon’ period of being a beginner), and therefore don’t really know how to write an effective, science-based programme that progressively produces results and avoids plateaus.

There’s been a plethora of research on muscle growth over the past decade in an attempt to fully understand how hypertrophy occurs and, although it’s difficult to determine for certain, several researchers have some fairly good ideas. One of these researchers is Brad Schoenfeld (http://www.lookgreatnaked.com/), who published an excellent study in 2010 titled “The mechanisms of muscle hypertrophy and their application to resistance training”. This blog post is heavily based on that article and others by Brad Schoenfeld and Bret Contreras.


Definitions

As previously stated hypertrophy simply means muscle growth and is the opposite of muscle atrophy (muscle loss).

Hypertrophy has two secondary categories;
Transient Hypertrophy – the short lived, post-workout ‘pump’
Chronic Hypertrophy – long term lasting gains, actual changes in muscle architecture (i.e. what we’re training for)

Chronic hypertrophy occurs in two ways according to research –

hypertrophy_2-300x251

Contractile/Myofibrillar/Functional Hypertrophy – This involves the addition of sarcomeres (basic muscle units) in parallel. Contractile elements (actin and myosin) also enlarge and multiply and the extracellular matrix (everything else inside the cell) expands. This is deemed ‘functional’ as the tissue that is hypertrophied and supplemented is ‘contractile’ and thus capable of contracting and generating force. This is ‘powerlifter hypertrophy’ to put it simply.

Non-contractile/Sarcoplasmic/Non-functional Hypertrophy – This is the increase in size of the non-contractile elements inside the muscle cell (collagen, glycogen) and sarcoplasmic fluid. This is ‘non-functional’ as it doesn’t directly involve changes to the contractile elements and therefore doesn’t produce changes in force expression. This is ‘bodybuilder hypertrophy’ – big but not necessarily strong. This form of hypertrophy can have knock-on effects which promote contractile hypertrophy – hydration and thus cell swelling may lead to subsequent cell growth due to pressure on the cell wall.

web-new-balloon-dk-blue-jpg

A simple analogy to help understand the difference between sarcoplasmic and myofibrillar hypertrophy is to consider a water balloon. Sacroplasmic hypertrophy is simply filling the balloon up with water, whereas myofibrillar hypertrophy is increasing the size of the balloon itself.


Mechanisms

In order to get bigger we need to maximise protein synthesis (create an anabolic environment) and minimise protein breakdown/catabolism. Multiple mechanisms/factors are proposed for this.

Three Main Factors

  • Mechanical Tension
  • Muscle Damage
  • Metabolic Stress

Mechanical Tension
This is a combination of force generation and stretch. It’s the amount of tension that muscle fibres produce when a load stimulus is introduced.
Mechanical tension disturbs the integrity of skeletal muscle, it facilitates molecular and cellular responses that trigger hypertrophy.
There are two types of muscular tension:
– Passive tension – which occurs during eccentric contractions (‘stretching’ a muscle under load)
– Active tension – relating to the contractile elements of the muscle. Occurs during hard, forced contractions of a muscle (i.e. lifting heavy stuff).

Muscle Damage
This is localised damage to the muscle tissue caused by novel/unfamiliar exercise, slow eccentrics (lowering part of the exercise), or forced stretching of a muscle whilst it’s in an activated/contracted state.
It creates ‘myotrauma’ (muscle trauma) which triggers an acute inflammatory ‘healing’ response that stimulates growth factors that mediate and promote hypertrophy.

Metabolic Stress
Putting a muscle under repetitive, sustained stress causes metabolite accumulation which triggers an anabolic response (raises testosterone, IGF-1, growth hormone, and mechano growth factor).
Metabolic stress can be induced best via anaerobic glycolysis (hard, intense exercise with limited amounts of oxygen, lasting 10s – 2min). This causes a build up of metabolites – lactate, hydrogen ion, inorganic phosphate, creatine (amongst others) and promotes an acidic, ischemic, and hypoxic environment in the muscle (which can also trigger hypertrophic adaptations).

All three of these elements are inter-related, and training in a way that optimises and combines all three will produce the greatest results.

Pump

Why do muscles get ‘pumped’? When training in a moderate to high repetition range the veins that carry blood away from the working muscles get compressed/squeezed, whilst the arteries (which bring blood into the muscles) continue functioning as normal. This results in a large increase of blood plasma inside the muscles, which will subsequently ‘leak’ out and into the interstitial spaces (spaces between bodily tissues). When these spaces eventually fill up the excess plasma will be pushed back into the muscle thus causing a ‘pump’ effect.


Application to Training

Intensity
Train with a minimum intensity of 65%1RM (15 rep maximum), in moderate repetition ranges (6-12 reps). This prescription will cause a metabolic build up which boosts testosterone and growth hormone. It will also induce a pump (ischemia and hypoxia) which triggers hypertrophy and an increase in protein synthesis.

Additionally the more repetitions that are completed the longer the time the muscle is under tension which means more microtrauma/damage to the muscle (through eccentric contractions).

Volume
For maximum hypertrophy a higher volume, multiple set approach must be taken. Greater volume will stimulate greater growth hormone release and hypertrophy will result.

To facilitate this a body part split routine may be more beneficial that a full body routine as it will allow more regular training whilst still permitted muscles to fully recover. Again, more total reps also equates to more eccentric contractions which results in more muscle damage.

Exercise Selection
Multi-planar and multi-angled exercises must be included to allow for variance in muscular structure (i.e. fibre orientation) and to fully stimulate the entire muscle. Regular rotation of exercises will also make sure of this.

Whilst selecting exercises it’s essential to incorporate a mix of multi-joint and single joint exercises. Single joint (“isolation”) exercises will help to prevent imbalances and can develop weaker areas that may be neglected during compound/multi-joint movements.

Not all exercises are created equal, some lend themselves better to different rep ranges, different tempos, and different focuses (hypertrophy, strength, power). Certain exercises will produce a ‘pump’ effect more easily than others, some will create tension in a muscle better than others, and some exercises are more suited to slow eccentric contractions or tempos that will damage fibres.

Big, multi-joint, compound exercises are best for developing high tension in a muscle and activate the greatest amount of muscle mass – squats, deadlifts, bench presses, rows, pull ups (etc.). Incorporate variations and assistance exercises to ensure all fibres are hit.

Constant tension exercises are best for creating the pump effect – lateral raises, concentration curls, leg extensions (etc.).

Exercises that produce high tension whilst the muscle is in a lengthened state are best for creating muscle damage – dumbbell pec flyes, RDLs, incline curls (etc.). It’s important to be careful with these highly damaging exercises as, although damage is an effective hypertrophic stimulus, excessive damage can prevent you from training and cause more harm than good.

Rest Periods
Moderate (60-90s) rest will allow sufficient metabolic stress, adequate strength recovery, and create a more anabolic environment within the body.

Training to Failure
Training to concentric muscular failure is highly beneficial and should be done regularly (although not necessarily in every exercise/set), it’s important to ensure that the repetitions are still technically good (and safe) – a spotter is usually important here. Reaching failure allows the maximum number of motor units to be recruited and creates high metabolic stress.

fail

Training to concentric failure

Repetition Tempo
A moderate concentric speed (one or two seconds) with continuous muscle tension creates a greater metabolic demand than very fast or very slow repetitions. Slower eccentric repetition speeds are beneficial for hypertrophy as they will inflict more muscle damage and positively affect protein synthesis.

Intensification Methods
Employ intensification methods sparingly to push a set or exercise to the limit. These methods can include eccentrics/negatives, drop sets, rest-pause, cluster sets, supersets, tri-sets, and quad-sets. These methods can trigger additional hypertrophy stimulating signals that can lead to augmented muscle growth over time. Using this as a finisher at the end of a session for the final exercise or final set of the final exercise may be most beneficial and will limit the potential for injury.


In Summary…

Screen Shot 2015-10-13 at 16.28.48

Example Session Structure – Leg Day

Tension A1) Back Squat – 5×6 @ 80%1RM, 90s rest interval, 3 sec eccentric
Tension B1) Split Squat – 4×8 @ 75%1RM, 60s rest interval, 3 sec eccentric
Damage  C1) RDL – 3×8-10 @ 77.5%1RM, 4 sec eccentric
Damage C2)  Nordic Hamstring Curl – 3×6 @ BW, 90s rest interval, 4 sec eccentric
Metabolic Stress (“pump and burn”)
Tri Set
D1) Leg Extension – 3×12 @ 70%1RM, 3 sec eccentric
D2) Leg Curl – 3×12 @ 70%1RM, 3 sec eccentric
D3) Calf Raise – 3×12 @ 70%1RM, 60s rest interval, 3 sec eccentric
High Intensity Technique Finisher
Rest Pause
E1) Leg Press – 2×12+ @ 70%1RM, 60s rest interval


References

Schoenfeld, B. J. (2010). The mechanisms of muscle hypertrophy and their application to resistance training. The Journal of Strength & Conditioning Research, 24(10), 2857-2872.

Fry, A. C. (2004). The role of resistance exercise intensity on muscle fibre adaptations. Sports medicine, 34(10), 663-679.

http://bretcontreras.com/training-for-maximum-muscle-growth-explained/

https://www.t-nation.com/training/why-bodybuilders-are-more-jacked-than-powerlifters

https://www.t-nation.com/training/hypertrophy-specialist

http://www.muscletalk.co.uk/articles/muscularhypertrophy.aspx

https://www.t-nation.com/training/5-strategies-for-choosing-exercises

Overtraining and Marathon Running

Overtraining

When training for a marathon an athlete must apply regular exercise-based stress to their body in order to increase their performance, using a method known as functional over-reaching (FO) (Meeusen et al., 2006). FO is where a high degree of stress is placed upon the athlete, resulting in acute fatigue and temporarily reduced performance, but when balanced out with optimal recovery a supercompensation effect occurs where the body adapts and performance improves (McFarlane, 1985).

Balance of imposed stress and adequate recovery

Balance of imposed stress and adequate recovery

However if an imbalance occurs between this stress and recovery, and the acute fatigue is not managed it can lead non-functional over-reaching (NFO), a chronic form of fatigue that can take several weeks to recover from and elicits no performance improvements (Meeusen et al., 2006). Due to the high mileage endured as part of their training, it is estimated that around 65% of distance runners will suffer from NFO sometime in their career (McKenzie, 1999).

 

When an athlete is in a state of NFO and stress is continually applied, it is possible for them to become over-trained. Over-training is also known as the unexplained underperformance syndrome (UUPS) as it is unclear what the specific cause is, and is difficult to diagnose due to its similarities to NFO. The definition of UUPS is a reduction in an athlete’s performance with no improvement after six weeks of rest (whereas NFO is alleviated in this period) (Budgett, 2000), and is characterised as an abnormal response to training.

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Abnormal response to training (Budgett, 2000)

 

It should be noted that UUPS is multifactorial, and involves other stressors in addition to exercise, such as inadequate nutrition, illness, psychosocial stressors and sleep disorders, which will need to be accounted for and monitored.

 

Symptoms of UUPS (Kreher & Schwartz, 2012)

– An unexplained decline in performance
– A recent intense training cycle
– Upper respiratory tract infections (cough, sneeze, sore throat)
– Muscle soreness or feelings of tightness/heaviness
– Altered moods – depression, lack of motivation, lethargy, confusion
– Poor sleep quality/quantity
– Low energy and vigour
– No desire to train or compete
– Changes in appetite/desire to eat

Note: Symptoms of UUPS are individual and it should be down to the athlete, coach and other relevant team/family members to make a diagnosis.
It must be made certain that the athlete is not suffering from any organic diseases or disorders such as, for example, endocrinological/hormone disorders (such as diabetes), anaemia or eating disorders (bulimia or anorexia nervosa), asthma or undiagnosed infections.

Causes of UUPS

Imbalance of the Autonomic Nervous System (ANS)

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The ANS is a branch of the peripheral nervous system that regulates the function of our internal organs (heart, stomach, intestines), it incorporates the two commonly heard phrases ‘fight or flight’ and ‘rest and digest’. The ‘fight or flight’ aspect is the sympathetic nervous system, it mediates stress responses and an imbalance (dominance) in this system results in it being constantly ‘switched on’ at rest, causing restlessness and hyper-excitability.

The ‘rest and digest’ aspect is the parasympathetic nervous system, and dominance of this system is more common in marathon runners, causing fatigue, mood disturbances and prolonged recovery (Bosquet, Papelier, Leger, & Legros, 2003). This mechanism seems unlikely however, as a study by Pichot (2000) shows an abrupt recovery of symptoms within a week of rest.

Hormonal Disturbance

A disturbance to the hypothalamic-pituitary-adrenal (HPA) axis has been indicted as a potential mechanism of UUPS (Kreher & Schwartz, 2012). The HPA axis is a major part of the neuroendocrine system that controls reactions to stress and regulates bodily processes such as the immune system, mood, and energy storage, and is responsible for the production of adrenocorticotrophic hormone (ACTH), cortisol and testosterone.

Cortisol and testosterone are catabolic and anabolic (respectively), catabolic meaning that it breaks down muscle and anabolic the opposite. Cortisol rises during endurance exercise and negatively affects immune function and the production of testosterone (Karkoulias, 2008). Findings are mixed as to whether changes in these hormones relate to UUPS (Mackinnon, Hooper, Jones, Gordon, & Bachmann, 1997; Uusitalo, Huttunen, Hanin, Uusitalo, & Rusko, 1998) however an imbalanced testosterone:cortisol ratio (low testosterone, high cortisol) does indicate the physiological strain of exercise (Halson & Jeukendrup, 2004).

Immunological Causes

Periods of over-reaching cause a decreased level of immune function for a short period following exercise, this ‘open window’ of immune function is largest in endurance athletes (such as marathon runners) due to the prolonged nature of the sport (Gleeson, 2007). Indicators of this immunodepression include upper respiratory tract infections (URTIs) (Matthews, 2002) such as sore throats, coughs and sneezes. This could be due to a decrease in immunoglobulin-a (Ig-A), an anti-body found in mucus/saliva (i.e. in the nose, mouth, gastrointestinal tract) that can be diminished due to intense exercise (Gleeson, 2007).

Screen Shot 2015-08-29 at 15.28.18

Smith (2000) suggested a ‘cytokine hypothesis’ whereby intense exercise causes damage to muscles/bones/joints causing widespread inflammation which releases cytokines, signalling molecules that promote inflammation, such as interleukin-6 (IL-6). An elevation in cytokines can have a large number of effects on the body, including ‘sickness behaviour’ due to effects on hormones, reduced glucose transport to muscles, and disruptions in the testosterone:cortisol ratio, all of which lead to feelings of fatigue and symptoms of UUPS. Scientific evidence of this is sparse and has shown that cytokine levels are not imbalanced in over-reached athletes (Halson, Lancaster, Jeukendrup, & Gleeson, 2003) although the same study suggests that decreases in glutamine, an amino acid that is beneficial in many ways to the body, may be indicative of UUPS.

 

Fatigue and Marathon Running

Fatigue and marathon running are almost synonymous in most people’s opinion, and indeed acute fatigue is a natural consequence of any exercise activity.

fatigue

Fatigue can be defined as a reduction in the ability to produce or maintain the force required for a given activity (Celine et al., 2011), resulting in greater perceived exertion– an increased sensation of effort (Enoka & Stuart, 1992).

The exact causes of fatigue are unclear, although it has been attributed to the central nervous system (brain and spinal cord) and the muscles. These causes are more technically referred to as central and peripheral fatigue (Davis, 1995).

Peripheral Fatigue

Peripheral fatigue occurs at or past the neuromuscular junction (the area at which a neuron activates a muscle to contract) and is related to biochemical changes within the muscles metabolic environment that lead to reduced responses to activation signals (Amann, 2011).

p fatigue

Potential causes of peripheral fatigue in marathon running include (Kent-Braun, 1999):

  • Energy depletion –In order to produce energy (in the form of adenosine tri-phosphate – ATP) during prolonged sub-maximal exercise, the body utilises glucose in the blood stream. Fatigue occurs when blood glucose declines due to a disruption to gluconeogenesis and glycogenolysis in the liver because of a re-distribution of blood flow.
  • Acidosis/accumulation of metabolites – During anaerobic exercise (such as bursts of speed during a race) the body will use glucose for fuel; a by-product of this is a build up of lactic acid. This results in a build up of hydrogen ions; these inhibit an enzyme called phosphofructokinase (which affects blood glucose regeneration) and can also interfere with the release of calcium which will impair muscle contraction.
  • Excitation-contraction coupling impairment– This refers to a failure of the parts of the muscle fibres needed for muscle contraction and can be linked to the aforementioned decline in calcium release. This impairment has a very slow time course of recovery when compared to the energy depletion mechanism.

Research has suggested that damage to the actual muscle fibres (due to the high volume of eccentric contractions during a marathon (Overgaard et al., 2004) and disruption to the excitation-contraction coupling mechanism is the most likely cause of peripheral fatigue (Ross, 2007).

Peripheral fatigue can also be divided into two subsections due to the stimulation required to elicit fatigue. Low frequency fatigue is demonstrated during electrical stimulation of the muscle at a frequency of 1-20 Hz (roughly equates to exercise such as jogging) whereas high frequency fatigue is shown at 50-100 Hz (activities such as hopping) (Tomazin, Strojnik, & Sarabon, 2002).

Central Fatigue

Central fatigue is related to the central nervous system which consists of the brain and spinal cord, and is often described as an impairment to the central drive to a muscle (central drive refers to the flow of neural activation signals) (Ross, 2007).

c fatigue

It is effectively a reduction in the voluntary activation of muscle and can be noticed when, towards the end of a marathon, an athlete’s running technique becomes sub-optimal (they appear to have ‘heavy legs’), demonstrating that muscle fibres are not switching on fully due to decreased recruitment and firing frequency.

The extreme of central fatigue in a marathon is seen when an athlete ‘hits the wall’.

The most likely cause of central fatigue is due to the effect prolonged sub-maximal exercise has on serotonin in the brain, a hormone responsible for mood, sleep regulation and feelings of lethargy, also known as 5-HT (Cotel, Exley, Cragg, & Perrier, 2013).

Prolonged (primarily) aerobic exercise such as marathon utilises fat as a fuel source, when this fat is mobilised it causes free fatty acids to be released into the blood stream, which then attach to branched chain amino acids.

The regular function of branched chain amino acids is to ‘hold onto’ tryptophan (the pre-cursor to serotonin) to prevent it crossing the blood-brain barrier and producing serotonin. When free fatty acids prevent branch chain amino acids from doing this, serotonin is produced in the brain and central fatigue occurs.

The Central Governor Theory

The idea that there is a mechanism that prevents an athlete from dangerous over-exertion whilst running was originally suggested by Hill,Long and Lupton in 1924 and then renewed by Noakes in 1997 who gave it the term ‘central governor’.

governor

The central governor theory is a function of multiple brain areas (as opposed to an actual area inside the brain); Noakes (2007) explains it as a neural control system that can reduce the activation levels of muscles in order to enforce homeostasis (steady state) in the body. Noakes and others (Hampson, Gibson, Lambert, & Noakes, 2001; Tucker, Marle, Lambert, & Noakes, 2006) believe that if homeostasis is not controlled the body would be capable of causing catastrophic damage to its vital organs and skeletal muscle.

This theory has been criticised in other research (Shephard, 2009; Weir, Beck, Cramer, & Housh, 2006) for several reasons, specifically in that, if the central governor exists, then it should be impossible for athletes to contract hyperthermia and to induce muscle damage and ischemia. Additionally it has been shown that even when voluntary muscle activation is decreased, maximal activation can still occur with the use of electrical stimulation and it does not result in injury, just additional fatigue (Garland & McComas, 1990).

 

The mechanisms of action for the ACE gene and its potential role in endurance performance.

Introduction

Many genetic elements have been discovered that affect human physical performance (Zilberman-Schapira, Chen, & Gerstein, 2012), among these, the polymorphisms of the angiotensin I-converting enzyme (ACE) gene have undergone scrutiny. Rigat et al. (1990) discovered two polymorphic alleles of the ACE gene that correlate with concentration of ACEplasma, an insertion allele and a deletion allele. Insertion/deletion (I/D), double insertion (I/I), and double deletion (D/D) alleles all exist within the population (Jones, Montgomery, & Woods, 2002). Research has attempted to find correlations between ACE polymorphism and sporting performance with the goal of qualifying the use of ACE gene concentration as a performance biomarker; however confounding factors such as economy, ethnicity, sporting discipline and other gene interactions are present. A high level of endurance performance (EP) refers to success in an exercise that relies on, amongst other things, an individual’s maximum aerobic capacity (VO2Max), this being the maximum amount of oxygen which can be inhaled, absorbed into the vascular system, transported, and used by the working muscles (McArdle, Katch, & Katch, 2010). This paper looks at the potential role of the ACE gene on EP.

Mechanism

ACE affects the renin-angiotensin system (RAS) (Figure 1), an endocrine system present in blood plasma and local tissues including the heart, vasculature, and kidneys. Research deduces it to be responsible for regulation of blood pressure, fluid homeostasis maintenance, regulation of tissue growth and response to trauma (Paul, Mehr, & Kreutz, 2006). Beginning in the RAS, angiotensinogen, a liver produced serum globulin, is cleaved by renin, a peptide hormone secreted renally due to sympathetic activity or hypotension. This mechanism creates angiotensin I (ANG I), a peptide precursor to angiotensin II (ANG II) (Puthucheary et al., 2011). ACE, secreted predominantly by pulmonary and renal endothelial cells, although also present in circulation as ACEplasma, converts ANG I to ANG II (Montgomery et al., 1999). ANG II has an agonistic effect on the angiotensin type 1 receptor (AT1R), which is responsible for its substantial cardiovascular effects. AT1R activation increases arterial blood pressure due to arterial vasoconstriction and water retention through the release of aldosterone, a steroid hormone produced by the adrenal cortex. It additionally stimulates sympathetic nervous system (SNS) activity, further increasing vasoconstriction and elevating heart rate (Inagami et al., 1999) and is linked to left ventricle hypertrophy (Liu et al., 1998). ACE has an additional effect on the vasodilator peptide bradykinin, whereby it is inhibited and diminishes hypotensive ability (Tanriverdi et al., 2005).

ACE

Studies have found correlations between the ACE gene and EP, especially in athletes with a greater concentration of the I-allele (Myerson et al., 1999; Gayagay et al., 1998). The I-allele is linked to improved cardiovascular function and therefore oxygen delivery to working muscles (Hennes et al., 1996; Jones, Montgomery, & Woods, 2002), which can be quantified through measurement of VO2Max using Fick’s equation (McArdle, Katch, & Katch, 2010). The I-allele increases stroke volume, a limiting factor in cardiac output and thus VO2Max, via an increase in preload due to vasodilation and the Frank-Starling mechanism (Levine, Lane, Buckey, Friedman, & Blomqvist. (1991). Vasodilation also affects arteriovenous oxygen (a-vO2) difference, which also influences VO2Max. Hagberg, Ferrell, McCole, Willund & Moore (1998) found subjects with the I-allele had a large a-vO2 difference, possibly due to greater release of vascular tone (due to vasodilation) and therefore increases in capillary perfusion. This could also be due to the I-allele’s link to an increased percentage of type I muscle fibres which had a greater capillary density than type II, leading to increased blood supply and oxygen diffusion (Zhang et al., 2003). Additionally nitric oxide release due to bradykinin activity, along with its vasodilation effect (Tanriverdi et al., 2005), may stimulate mitochondrial biogenesis (Nisoli & Carruba, 2006) leading to higher mitochondrial density and hence energy production. Evidence, however, suggests EP success is not just a product of physiological factors, with studies showing variable performance in athletes with the same VO2Max (Joyner, 1991; Lucia et al., 2008).

Economy

Economy is defined as the energy demand for a given velocity of submaximal exercise (Saunders, Pyne, Telford, & Hawley, 2004) and is improved by minimising superfluous factors; studies (Coetzer et al., 1993; Lucia et al., 2008) have shown its elements to be better predictors of EP than VO2Max. A multitude of elements can influence success in athletes with identical VO2Max and have been proposed as key in running economy. These include biomechanical and biochemical factors, which will indirectly relate to oxygen kinetics and may result in more efficient substrate utilisation and decreased metabolic heat production and thus reduced thermal stress. Fractional utilisation is the greatest percentage of VO2Max an athlete can sustain for the duration of a race and is a key determinant of EP (Costill, Branam, Eddy, & Sparks, 1971). Another determinant is velocity at VO2Max (vVO2Max), this is the speed which an athlete can maintain whilst at 100% of their VO2Max and is crucial to success in a competitive environment (Billat & Koralsztein, 1996).

It has also been shown that highly economical runners have short ground contact times (GCT) resulting in less braking/decelerating forces and greater vertical displacement (Kong & De Heer, 2008). GCT can be affected by anthropometrics (Lucia et al., 2006) and stiffness (Chelly & Denis, 2001), an athlete with good energy storage capacity and low compliance in tendons, and optimal foot and ankle structure will have decreased GCTs. Body mass also plays a part, and when adjusted for essential weight of organs and muscle, is made up of considerable deadweight including bone, connective tissue, and fat mass. When deadweight is excessive, there is an increase in propulsive and support forces, decreasing energy efficiency as more muscle mass is activated (Taylor, Heglund, McMahon, & Looney, 1980).

Ethnicity

East African runners hold the most records for EP of any population (Joyner, Ruiz, & Lucia, 2010). Naturally there has been speculation as to the factors underlying the success of these athletes in comparison to other populations, one being the association between ACE genotype and ethnicity. Studies have shown that ACE genotype and its relationship to endurance success varies, with most studies suggesting a positive association between the I-allele and Caucasian endurance athletes (Rigat et al., 1990; Collins et al., 2004), but a negative association with black African endurance athletes (Scott et al., 2005). It seems that in homogenous groups of ethnicity, sporting level and sporting discipline there is a relationship (Wang et al., 2012). Collins’ et al. (2004) study on South African ironmen found a higher frequency of the I-allele in the fastest 100 South African-born finishers, an outcome witnessed in studies by Alvarez et al. (2000) and Myerson et al. (1999). Research on heterogeneous cohorts by Sonna et al., (2001) and Rankinen et al. (2000) have failed to find a positive correlation between the I-allele and EP. Rankinen investigated ACE genotype in elite Caucasian endurance athletes finding no association, potentially due to the diverse mixture of sports included, which have extensive physiological demands. A divergent finding by Amir et al. (2007) was the positive relationship between the D-allele and EP in Caucasian Israeli athletes, prompting more questions about the ACE genotype’s effect in different populations.

Perhaps the Kenyan endurance success is not related to ACE genotype, Saltin et al. (1995) and Lucia et al. (2006) compared performance in African and Caucasian runners, finding, although equal in VO2Max score, fractional utilisation and vVO2Max was superior in the Africans. Additionally Africans were shown to have a lower body mass index, body fat percentage and a higher hamstring to quadriceps ratio (Kong & De Heer, 2008). Pitsiladis, Onywera, Geogiades, O’Connell, & Boit (2004) suggested that physiological adaptations to living at altitude, African ‘running’ culture and diet could be explanations of their impressive economy and endurance success.

Other Factors

It can also be established that there are other components that influence ACE genotype. According to Wang et al. (2012) variations in I-allele occur depending on the sporting discipline investigated. The majority of studies that have found a positive link between the I-allele and performance have been on cyclical sports, predominantly running, cycling, mountaineering and swimming (Puthucheary et al., 2011). Conversely Muniesa et al. (2010) found the I-allele was less common in rowing which, although an endurance sport, has a prominent power emphasis. Research has been carried out on other genes that are correlated to EP since two thirds of variance in athlete status is said to be affected by genetics (Ahmetov et al., 2009). Ahmetov et al. (2009) analysed 1423 athletes of various sports and found three genetic markers specifically associated with EP, NFATC4, TFAM and PPARGC1B. The former two alleles code for transcription factors which initiate cellular processes, whereas the latter allele is a co-activator of a transcription factor, they are all linked to mitochondrial biogenesis, substrate metabolism and cardiac hypertrophy. This finding suggests that elite EP likely depends on an individual’s endurance-related genetic make-up.

Conclusion

The ACE gene is just one factor that ties into successful EP, with its I-allele linked to improved cardiovascular function and muscular efficiency and the D-allele with sprint/power performance, however the mechanisms are inadequately explored. The majority of studies find an association between the I-allele and EP; however it seems to be an inconsistent relationship that presents itself only in homogenous cohorts of similar sporting discipline and competitive level. This is potentially due to interpretation of the results found and the fact that correlation does not imply causation. Other factors have been presented as significant performance predictors, economy being of high importance and reportedly a better predictor of endurance success than VO2Max, and ethnicity being influential through numerous facets to endurance success – as proven by distance running records. To summarise, successful EP is dependent on many factors, with the effects of ACE only significant in certain situations and populations, and even then its effects are minor and further research is needed into other genes that work with ACE in linkage disequilibrium or affect performance individually.
Reference List

Ahmetov, I. I., Williams, A. G., Popov, D. V., Lyubaeva, E. V., Hakimullina, A. M., Fedotovskaya, O. N., & Rogozkin, V. A. (2009). The combined impact of metabolic gene polymorphisms on elite endurance athlete status and related phenotypes. Human Genetics, 126, 751-761.

Alvarez, R., Terrados, N., Ortolano, R., Iglesias-Cubero, G., Reguero, J. R., Batalla, A., & Coto, E. (2000). Genetic variation in the renin-angiotensin system and athletic performance. European Journal of Applied Physiology, 82, 117-120.

Amir, O., Amir, R., Yamin, C., Attias, E., Eynon, N., Sagiv, M., & Meckel, Y. (2007). The ACE deletion allele is associated with Israeli elite endurance athletes. Experimental Physiology, 92, 881-886.

Billat, L. V., & Koralsztein, J. P. (1996). Significance of the velocity at VO2max and time to exhaustion at this velocity. Sports Medicine, 22, 90-108.

Chelly, S. M., & Denis, C. (2001). Leg power and hopping stiffness: relationship with sprint running performance. Medicine and Science in Sports and Exercise, 33, 326-333.

Coetzer, P., Noakes, T. D., Sanders, B., Lambert, M. I., Bosch, A. N., Wiggins, T., & Dennis, S. C. (1993). Superior fatigue resistance of elite black South African distance runners. Journal of Applied Physiology, 75, 1822-1827.

Costill, D. L., Branam, G., Eddy, D., & Sparks, K. (1971). Determinants of marathon running success. Internationale Zeitschrift für angewandte Physiologie einschliesslich Arbeitsphysiologie, 29, 249-254.

Collins, M., Xenophontos, S. L., Cariolou, M. A., Mokone, G. G., Hudson, D. E., Anastasiades, L., & Noakes, T. D. (2004). The ACE gene and endurance performance during the South African Ironman Triathlons. Medicine and Science in Sports and Exercise, 36, 1314-1320.

Gayagay, G., Yu, B., Hambly, B., Boston, T., Hahn, A., Celermajer, D. S., & Trent, R. J. (1998). Elite endurance athletes and the ACE I allele–the role of genes in athletic performance. Human Genetics, 103, 48-50.

Hagerman, F. C., Connors, M. C., Gault, J. A., Hagerman, G. R., & Polinski, W. J. (1978). Energy expenditure during simulated rowing. Journal of Applied Physiology, 45, 87-93.

Hennes, M. M., O’Shaughnessy, I. M., Kelly, T. M., LaBelle, P., Egan, B. M., & Kissebah, A. H. (1996). Insulin-Resistant Lipolysis in Abdominally Obese Hypertensive Individuals Role of the Renin-Angiotensin System. Hypertension, 28, 120-126.

Inagami, T., Kambayashi, Y., Ichiki, T., Tsuzuki, S., Eguchi, S., & Yamakawa, T. (1999). Angiotensin receptors: molecular biology and signalling. Clinical and Experimental Pharmacology and Physiology, 26, 544-549.

Jones, A., Montgomery, H. E., & Woods, D. R. (2002). Human performance: a role for the ACE genotype. Exercise and Sport Sciences Reviews, 30, 184-190.

Joyner, M. J. (1991). Modeling: optimal marathon performance on the basis of physiological factors. Journal of Applied Physiology, 70, 683-687.

Joyner, M. J., Ruiz, J. R., & Lucia, A. (2011). The two-hour marathon: who and when?. Journal of Applied Physiology, 110, 275-277.

Kong, P. W., & De Heer, H. (2008). Anthropometric, gait and strength characteristics of Kenyan distance runners. Journal of Sports Science and Medicine, 7, 499-504.

Levine, B. D., Lane, L. D., Buckey, J. C., Friedman, D. B., & Blomqvist, C. G. (1991). Left ventricular pressure-volume and Frank-Starling relations in endurance athletes. Implications for orthostatic tolerance and exercise performance. Circulation, 84, 1016-1023.

Liu, Y., Leri, A., Li, B., Wang, X., Cheng, W., Kajstura, J., & Anversa, P. (1998). Angiotensin II stimulation in vitro induces hypertrophy of normal and postinfarcted ventricular myocytes. Circulation Research, 82, 1145-1159.

Lucia, A., Esteve-Lanao, J., Olivan, J., Gomez-Gallego, F., San Juan, A. F., Santiago, C., & Foster, C. (2006). Physiological characteristics of the best Eritrean runners-exceptional running economy. Applied Physiology, Nutrition, and Metabolism, 31, 530-540.

Lucia, A., Olivan, J., Bravo, J., Gonzalez-Freire, M., & Foster, C. (2008). The key to top-level endurance running performance: a unique example. British Journal of Sports Medicine, 42, 172-174.

McArdle, W. D., Katch, F. I., & Katch, V. L. (2010). Exercise Physiology: Nutrition, Energy, and Human Performance. Philadelphia, PA: Lippincott Williams & Wilkins.

Min, S. K., Takahashi, K., Ishigami, H., Hiranuma, K., Mizuno, M., Ishii, T., & Nakazato, K. (2009). Is there a gender difference between ACE gene and race distance?. Applied Physiology, Nutrition, and Metabolism, 34, 926-932.

Montgomery, H., Clarkson, P., Barnard, M., Bell, J., Brynes, A., Dollery, C., & Humphries, S. (1999). Angiotensin-converting-enzyme gene insertion/deletion polymorphism and response to physical training. The Lancet, 353, 541-545.

Muniesa, C. A., González-Freire, M., Santiago, C., Lao, J. I., Buxens, A., Rubio, J. C., & Lucia, A. (2010). World-class performance in lightweight rowing: is it genetically influenced? A comparison with cyclists, runners and non-athletes. British Journal of Sports Medicine, 44, 898-901.

Myerson, S., Hemingway, H., Budget, R., Martin, J., Humphries, S., & Montgomery, H. (1999). Human angiotensin I-converting enzyme gene and endurance performance. Journal of Applied Physiology, 87, 1313-1316.

Nisoli, E., & Carruba, M. O. (2006). Nitric oxide and mitochondrial biogenesis. Journal of Cell Science, 119, 2855-2862.

Paul, M., Mehr, A. P., & Kreutz, R. (2006). Physiology of local renin-angiotensin systems. Physiological Reviews, 86, 747-803.

Pitsiladis, Y. P., Onywera, V. O., Geogiades, E., O’Connell, W., & Boit, M. K. (2004). The dominance of Kenyans in distance running. Equine and Comparative Exercise Physiology, 1, 285-291.

Puthucheary, Z., Skipworth, J. R., Rawal, J., Loosemore, M., Van Someren, K., & Montgomery, H. E. (2011). The ACE Gene and Human Performance. Sports Medicine, 41, 433-448.

Rankinen, T., Wolfarth, B., Simoneau, J. A., Maier-Lenz, D., Rauramaa, R., Rivera, M. A., & Bouchard, C. (2000). No association between the angiotensin-converting enzyme ID polymorphism and elite endurance athlete status. Journal of Applied Physiology, 88, 1571-1575.

Reisenleiter, F., Katz, N., & Gardemann, A. (1996). Control of hepatic carbohydrate metabolism and haemodynamics in perfused rat liver by arterial and portal angiotensin II. European Journal of Gastroenterology & Hepatology, 8, 279.

Rigat, B., Hubert, C., Alhenc-Gelas, F., Cambien, F., Corvol, P., & Soubrier, F. (1990). An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. Journal of Clinical Investigation, 86, 1343.

Saltin, B., Larsen, H., Terrados, N., Bangsbo, J., Bak, T., Kim, C. K., & Rolf, C. J. (1995). Aerobic exercise capacity at sea level and at altitude in Kenyan boys, junior and senior runners compared with Scandinavian runners. Scandinavian Journal of Medicine & Science in Sports, 5, 209-221.

Saunders, P. U., Pyne, D. B., Telford, R. D., & Hawley, J. A. (2004). Factors affecting running economy in trained distance runners. Sports Medicine, 34, 465-485.

Scott, R. A., Moran, C., Wilson, R. H., Onywera, V., Boit, M. K., Goodwin, W. H., & Pitsiladis, Y. P. (2005). No association between angiotensin converting enzyme (ACE) gene variation and endurance athlete status in Kenyans. Comparative Biochemistry and Physiology – Part A: Molecular & Integrative Physiology, 141, 169-175.

Sonna, L. A., Sharp, M. A., Knapik, J. J., Cullivan, M., Angel, K. C., Patton, J. F., & Lilly, C. M. (2001). Angiotensin-converting enzyme genotype and physical performance during US Army basic training. Journal of Applied Physiology, 91, 1355-1363.

Tanriverdi, H., Evrengul, H., Tanriverdi, S., Turgut, S., Akdag, B., Kaftan, H. A., & Semiz, E. (2005). Improved endothelium dependent vasodilation in endurance athletes and its relation with ACE I/D polymorphism. Circulation Journal: Official Journal of the Japanese Circulation Society, 69, 1105.

Taylor, C. R., Heglund, N. C., McMahon, T. A., & Looney, T. R. (1980). Energetic cost of generating muscular force during running: a comparison of large and small animals. The Journal of Experimental Biology, 86, 9-18.

Wang, G., Mikami, E., Chiu, L. L., de Perini, A., Deason, M., Fuku, N., & Pitsiladis, Y. P. (2012). Association analysis of ACE and ACTN3 in Elite Caucasian and East Asian Swimmers. Medicine and Science in Sports and Exercise. Advance online publication. DOI: 10.1249/MSS.0b013e31827c501f

Zhang, B., Tanaka, H., Shono, N., Miura, S., Kiyonaga, A., Shindo, M., & Saku, K. (2003). The I allele of the angiotensin‐converting enzyme gene is associated with an increased percentage of slow‐twitch type I fibers in human skeletal muscle. Clinical Genetics, 63, 139-144.

Zilberman-Schapira, G., Chen, J., & Gerstein, M. (2012). On Sports and Genes. Recent Patents on DNA & Gene Sequences, 6, 180-188.

My undergraduate dissertation abstract: Assessing athlete readiness using jump monitoring is ineffective following repeated sprint exercise

Assessing athlete readiness using jump monitoring is ineffective following repeated sprint exercise.

Abstract

The aim of the present study was to investigate the comparative sensitivity of the drop jump (DJ) and the countermovement jump (CMJ) when used as tools to detect neuromuscular fatigue following a repeated sprint protocol. Seven trained male participants (age 20.6 ± 1.5 years; height 176 ± 7 cm; body mass 84.6 ± 14.8 kg) volunteered for this study. Dependent variables of flight time, jump height, peak power, vertical velocity at take off, contact time, RSI and stiffness were measured using a force plate. Following baseline jump testing participants performed 15 x 30m sprints with an enforced 10m deceleration; a 60 second walk-back recovery was allowed between sprints. All dependent variables were re-measured on the force plate immediately after the sprints, then again at 24 hours, 48 hours and 72 hours to quantify the effects of fatigue. A one-way ANOVA with repeated measures determined that there were no significant differences (p > 0.05) or meaningful changes in any of the CMJ or DJ force variables measured over the 72 hour testing period. This investigation has shown that assessments of athlete readiness using the DJ and CMJ do not display adequate sensitivity in detecting fatigue following a repeated sprint protocol.

Key words: countermovement jump, drop jump, neuromuscular fatigue, sprinting, sensitivity.

Protein Supplementation – what’s in it, how much should I take and when?

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Dead animal flesh – best protein source you can hope for

Protein powder and bars are the biggest selling supplements in the supplement industry, you’ve probably seen the (misleadingly) named varieties – Anabolic Extreme, Super Mass, Protein Powder for muscles-on-muscles – in supermarkets, health food shops and just about anywhere else. The problem is, a lot of people misunderstand what the supplement even is and have no idea how much they should actually be taking, and its not all their fault, the way its marketed and the dosages stated by the companies are misleading and generally designed to get the maximum number of people buying the stuff, and using more of it!

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100% Whey….. but what else is in it?

WHAT IS IT?

Protein is a structural component of all the cells in your body, it is made up of chains of amino acids.
As a macro-nutrient, protein is essential in the body for muscle contraction (actin and myosin are both proteins), cellular respiration (producing energy – we get 4 k/cal per g of protein*), to create anti-bodies to fight against disease, for blood pressure maintenance and for growth and repair of tissues.
* Although we can use it for energy, carbohydrates and fats are utilised first as they are more readily available.

In terms of usage, its the amino acids we specifically want, of which eight are essential (meaning they need to be included in our diet as our body cannot make them).
1. Isoleucine
2. Leucine
3. Lysine
4. Methionine
5. Phenylalanine
6. Threonine
7. Tryptrophan
8. Valine

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Leucine – Responsible individually for an increase in muscle protein synthesis, and for spiking insulin levels

HOW MUCH DO I NEED
The majority of people who eat a healthy diet will get the minimum amount of protein they require (for healthy function) – about 0.8g per kg of bodyweight per day according to the Institute of Medicine. This amount will come naturally from anything that walks, swims or flies (and through combinations of lenitls beans etc.).

The amount of protein you need increases the more you exercise, with a rough amount being between 1.0 and 2.0g per kg of bodyweight for both strength and endurance athletes, with endurance athletes being nearer the 2.0g end of the scale due to them being more likely to use protein for energy production. Additionally in strength and power athletes the more trained they are or the more muscle mass they have means they may need more, but still only in the 2.0g per kg per day range.

In terms of taking too much protein, there is no real risk, especially through the use of supplements. The reported risks include:
– Kidney damage (not backed up by science and no other proof)
– Nitrogen intoxication (not backed up by science and no other proof)
– Increase in coronary heart disease (CHD) has been noticed but this is down to the source of protein (high levels of fat)
– Wasting money – taking in too much protein can increase protein synthesis, but also causes the body to use protein (before carbs and fats) as a energy source, resulting in wastage (of protein and hard earned cash!)

Research says the optimal amount per intake (pre/post workout and in meals) is 18-20g.

SUPPLEMENTATION

Three main types;

  • Whey – Water soluble, easy to mix, rapid digestion
  • Casein – Water insoluble,coagulates in the gut and is digested slowly
  • Egg Albumin (Egg whites)

Whey protein tends to be the most popular variety, mainly down to the three points listed above. It also has a rich amino acid profile that covers the whole spectrum (including the three branched chain amino acids, leucine, isoleucine and valine).
Whey is left over when milk coagulates and contains everything that is soluble from milk. It is a 5% solution of lactose in water, with some minerals and lactalbumin. It is removed after cheese is processed.

There are four types of whey protein powder:

  • Ion exchanged whey protein
  • Whey protein concentrate
  • Whey protein isolate
  • Hydrolysed whey protein concentrate

Ion exchanged whey protein goes through a process called, you guessed it, ion exchange. This is where there is an addition of acidic chemicals and separation of protein by an electrical charge. Companies do this as it is only about 20% of the cost of micro filtration (a better, more expensive alternative I’ll cover shortly) and has the same effect of removing bacteria. However, the process also denatures certain proteins, including ones that aid with immunity, digestive capability, calcium absorption and satiety (feeling full) and the protein lactalbumin.

Whey protein concentrate is made in with three main stages. Pasteurisation is where the solution is heated to 72 degrees celsius for 15-30 seconds in order to kill of any bacteria (good or bad). Ultra filtration (similar to micro filtration) is a process where the solution is driven at high pressure and heat (40-50 degrees) though molecular ‘sieves’ in order to remove or concentrate different components. The size of the ‘sieve’ membranes are about four times smaller in ultra filtration than in micro filtration, meaning its better, and gives a finer and smoother powder. Finally evaporation is used to boil off the water.

The key parts in making whey protein isolate are, diafiltration, which uses ultrafiltration membranes to remove or lower the concentration of salts, fats and other solvents from the proteins. Added water ‘dilutes’ the solvents for removal leaving the protein behind. Microfiltration is then used – similar to ultra filtration – to clarify whey proteins and remove bacteria. Finally spray drying is used, which is the process by which the concentrated whey liquid is sprayed as a mist into a tower at temperatures from 80-175 degrees celsius to convert it into whey powder.

Hydrolysed whey protein concentrate is made, along with other methods (ultra filtration, drying), by using enzyme treatment. This treatment begins to pre-digest the proteins into smaller peptide bonds in order to aid digestion. This creates a bitter taste meaning most companies won’t have more than 20% hydrolysed protein.

There is also one other term to look out for – Cold processed whey. This term (although it is fairly loose) means that lower temperatures are used (40 degrees) during micro/ultra filtration and spray drying is often avoided and freeze drying is used instead. This stops some of the protein from being denatured and makes it easier to digest.

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I know how you feel dude!

So what to look for when you’re shopping for a whey protein supplement?

  • Pure whey protein with no fillers (artificial sweeteners, monosodium glutamate, colourings and flavourings)
  • Cold processed
  • Contain whey protein concentrate, isolate or is hydrolysed (to aid digestion)
  • DO NOT go for ion exchange

WHEN SHOULD I TAKE IT?

Taking 18-20g of protein post exercise has been shown to slow down protein degradation and slightly increase protein synthesis.
Taken ❤ hours post exercise protein synthesis is at a 120% increase, <24 hours post exercise it is at a 80% increase and <48 hours post exercise it is at a 40%. Protein supplementation increases these numbers slightly, but the main benefit is the decrease in degradation so the protein can be used for longer resulting in maximal gains.
Additionally, taking the supplement soon after exercise can increase strength and muscle cross sectional area as opposed to taking is >2 hours after.

Taking 18-20g of protein pre-exercise (when combined with a carbohydrate) can increase protein synthesis, increase blood flow and help maintain a positive nitrogen balance (a marker of atrophy – muscle wastage – when negative).

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Aaaaaaand, breathe….

Wow, so that was a fairly long (understatement) post, but hopefully its covered most areas and has cleared up a few things!