Technical Report

The Influence of SKINS A400 Lower

Body Compression Garments on Running

and Neuromuscular Performance

Human Performance Unit

The University of Essex, UK, CO4 3SQ

by

Chris McManus, Human Performance Unit Manager, The University of Essex

Kelly Murray, Human Performance Unit Sport Scientist, The University of Essex

Nicholas Morgan, Sports Integrated Ltd

EXECUTIVE SUMMARY

In the present study we assessed the effects of (1) correctly fitted and (2) oversized, full-

length compression tights on parameters of running and vertical jump performance,

metabolic response and ratings of perceived exertion.

Study outcome

During steady state running at a fixed intensity of 60% vVO2max (12.1 ± 1.3 km/h),

running economy was significantly lower (p < 0.05) in correctly fitted compression tights

when compared with running shorts. We observed no significant changes in any other

performance, mechanistic or subjective measure.

What is running economy and why is it important?

Running economy is defined as the energy required to run at a set speed. It has been

demonstrated to be a strong predictor of endurance performance, and a better predictor

than VO2max. Put simply the lower the running economy, the better the endurance athlete.

What does the finding of this study mean?

When wearing correctly fitted compression compared to running shorts, the runners

demonstrated that they used less energy when running at a sub maximal speed. They were

more economical and efficient.

What does this mean in practice?

It is widely accepted that runners who are more economical during sub maximal speeds

have the ability to push harder or run longer during their training and/or events.

How does compression improve running economy?

It is suggested to occur as a result of one or a combination of:

> Enhanced proprioception

> Reduced muscle oscillation and vibration, therefore optimising neurotransmission

> Enhanced running technique / posture

> Improved circulation coupled with decreased muscle oscillations reduce energy cost

INTRODUCTION

Compression claims are leveraged generically across brands to help provide evidence of

their performance benefit. However, it is important to recognise that this assumes an

appropriate size, fit and compression profile. Furthermore, the type of garment appears to

play a pivotal role in the efficacy of whether particular performance, mechanistic or

subjective variables are influenced, further complicating the issue of extrapolating specific

observations into generic ‘compression-wide’ claims.

Consequently, no garment is “proven” unless they have been shown to provide a

performance benefit under research conditions. SKINS have led the way in proving that

their garments are efficacious under various research conditions. With the launch of the

new A400 range it is important to provide evidence that they maintain a proven benefit.

METHODS

Participants

Eleven healthy, recreationally active (>3 sport specific training sessions per week) males

(mean ± SD; age 28.7 ± 6.6 years, weight 68.2 ± 5.3 kg, VO2max 54.15 ± 4.9 ml/kg/min,

vVO2max: 19.2 ± 1.4 km h-1

(corrected for 1% gradient)) participated in the study, which

was approved by the university’s ethics review board. Subjects were instructed to continue

with normal dietary practices whilst participating in the study, and to keep a 3-day food

and activity diary prior to testing. They were requested to follow the same dietary intake

the day prior and day of testing for all subsequent testing dates. Participants were asked to

refrain from exercise, caffeine and alcohol intake 24 hours prior to testing and refrain from

strenuous or competitive exercise 48 hours prior. Furthermore, subjects did not consume

any food or fluid (other than water) in the 2 hours prior to testing.

The Garment

The compression garments used in the current study were Skins TM

Men’s Compression

A400 Long Tights (Zug, Switzerland), and the correctly fitted garment for each subject

was in accordance with the manufacturer’s instructions (correctly-sized garments; CSG).

For the oversized garment condition (over-sized garments; OSG), subjects wore 2 sizes

above the manufacturer’s instructions (M = XL; L = XXL). Subjects were blinded to the

garment condition by removing the size label. The pressure exerted by the compression

garments on the lower limbs were evaluated by the Picopress® pressure monitor (CV =

2.79%, Partsch and Mosti., 2010). Pressure measures were recorded a 6 anatomical

locations (5cm above superior sphyrion, medical calf, posterior calf, anterior thigh,

posterior thigh and gluteus maximus). The pressure sensor was inserted from the bottom

for the sphyrion and calf measures and inserted from the top for the thigh and gluteus

maximus. The average of 3 measures was recorded for each anatomical location for both

compression garment conditions.

The control garment consisted of loose fitting running shorts, thereby providing a

comparison between compression garments and garments typically worn by recreational

runners. The same short sleeve top was worn on every testing occasion, as were the same

running shoes always worn.

Experimental Approach

The experimental protocol consisted of 4 sessions, held between 2-4 days apart for all

subjects. Each subject attended their sessions at the same time of day, with similar

environmental conditions (temperature: 18 ± 1.0° C) to minimise circadian rhythm. A

randomised, crossover design was incorporated into the study.

The initial session was used to determine individual maximal aerobic capacity (VO2max),

maximal aerobic velocity (vVO2max) and maximal heart rate (HRmax). After a 5 min

warm-up at 7 km h-1

(0% gradient) subjects undertook an incremental exercise test on a

treadmill (Saturn, HP-Cosmos, Nussdorf, German) wearing the control garments

previously described. The progressive exercise test was used from a previously published

method (Goh et al., 2011), to determine maximal performance parameters. Following the

5 min warm-up, treadmill speed was increased by 1 km h-1

every minute until 16 km h-1

was achieved. At this point, gradient was increased by 2% each minute thereafter until

volitional exhaustion. VO2max was determined as the point where (a) a plateau was

observed in VO2 consumption over a 30 s period and decreased thereafter with increasing

workload, (b) HR was within 10 beat min-1

of age predicted maximum HR, (c) a

respiratory exchange ratio (RER) of >1.1 was observed and (d) volitional fatigue was

achieved (Dupont et al., 2003). To determine vVO2max, gradient increases were converted

to a running velocity whereby a gradient rise of 1.5% equated to an increase in speed of 1

km h -1

(Margaria et al., 1963).

Following the incremental test, a familiarisation process was undertaken which included

subjects running for 5 min at a pre-determined sub-maximal intensity (60% vVO2max) and

completing two sets of five counter-movement jumps (CMJ) using a force platform (0.36

m x 0.36 m, PASCO Scientific PS-2142, Roseville, CA) collecting at 1,000 Hz. Subjects

were provided with verbal instructions and a physical demonstration of the correct CMJ

technique. Subjects were required to achieve a jump height coefficient of variance value of

<5% for the second set of CMJ, otherwise additional attempts were requested to ensure

consistency in technique.

During sessions 2-4, subjects provided a urine sample upon arrival to assess specific

gravity (Atago Co., Ltd., Tokyo, Japan) and provided a 24 hour dietary intake record to

ensure subjects had adhered to the food and fluid recommendations. Subjects were

randomly assigned to each testing condition in an attempt to limit any learning effects. For

those sessions when a compression garment was worn, pressure measures were recorded

prior to undertaking a cycle warm-up (Monark 818 E, Sweden) of 5 min at 100W. Exactly

3 minutes following the warm-up, 5 x counter-movement jumps were performed. Subjects

were required to jump as high as possible for 5 consecutive efforts with a 3 s pause

between jumps. Countermovement depth was self-selected by the subject. A self-selected

countermovement depth was chosen to assess reliability of variables using a technique

requiring minimal intervention thereby maximizing the potential application to practical

settings where time limitations may exist. Each trial was then analyzed using custom-

designed software (Forcedecks, UK) capable of automatically detecting values for the

variables of interest. Jump height, flight time, mean and peak concentric force were

variables of interest, whereby the mean of 5 jumps was used for data analysis.

Five minutes after the completion of 5 x CMJ, subjects underwent a 15 min steady state

(SS) running task at 60% vVO2max, at a gradient of 1%. During the SS run the VO2, VCO2,

minute ventilation and RER were measured constantly with a breath-by-breath gas

analyser (Jaeger Oxycon Pro, Erich Jaeger GmbH, Hoechberg, Germany). Values for VO2

were smoothed over 5 s to de-emphasis breath-to-breath variation. Running economy

(ml/kg/km -1

) was calculated using the VO2 data from the final 3 min of the SS run task.

Ratings of perceived exertion (RPE) where recorded at minute 3, 6, 9, 12 and 15 using the

Borg 6-20 scale (Borg, 1970) and a SS session mean was established from the 5 RPE

values provided. After 15 min of SS running, subjects straddled the treadmill belt and a

capillary blood sample was obtained to determine lactate concentration. All blood samples

for lactate concentration measurement were collected in a capillary tube (Eppendorf AG,

Hamburg, Germany) from the right ear lobe and analysed using a Biosen lacate analyser

(EKF Industrie, Elektronik GmbH, Barleben, Germany).

A second set of CMJ performances were then assessed, exactly 5 min following the

completion of the SS run task, followed by the final exercise task, requiring subjects to run

to exhaustion. The time to exhaustion (TTE) test would begin 10 min after the completion

of the SS run task, whereby subjects would run at 100% vVO2max (1% gradient) for as long

as possible. Timing would begin when subjects released the handrail and stopped when

subjects made contact with the handrail at the point of volitional fatigue.

Statistical Analysis

To investigate the effects of wearing a compression garment on running and

neuromuscular performance, all data were calculated with conventional procedures and are

presented as mean values and standard deviations. Subsequently, all data were initially

compared using a paired t-test, after which, a statistical analysis was performed using a

specifically designed spreadsheet available for crossover studies. We used a contemporary

statistical approach because small performance changes can be beneficial for high

performing athletes, whereas conventional statistics can be less sensitive to such small but

worthwhile changes. From the spreadsheet, we used magnitude-based inferences about

effect sizes (η2), and then to make inferences about true (population) values of the effect,

the uncertainty in the effect was expressed as 90% confidence limits. Changes and errors

were expressed as percents via analysis of log-transformed values, to reduce bias arising

from non-uniformity of error and back transformed to obtain changes in means in raw

values. The probability that the true value of the effect was practically negative, trivial, or

positive accounted for the observed difference, and typical error of measurement. The

effect size, Cohen’s d (defined as (difference in means)/standard deviation (Cohen, 1988)),

was calculated for all variables between each clothing condition. Thresholds for small,

moderate, and large effects were 0.20, 0.50, and 0.80, respectively (Cohen, 1988). All

statistical tests were processed using the statistical package SPSS (Version 18) and

Microsoft Excel (Microsoft CorporationTM

, Redmond, WA, USA).

RESULTS

Sub-garment pressures

Pressure differences were significantly lower in the OSG condition when compared to

CSG for 5 of the 6 anatomical locations (see Table 1).

Table 1. Compression profiles (mmHg) of correctly fitted and oversized

garments.

Oversized Correct size p value

Ankle 1.3 ± 0.9 3.1 ± 1.3 <0.001*

M. Calf 9.4 ± 3.1 11.5 ± 3.0 <0.05*

P. Calf 9.2 ± 2.7 10.6 ± 3.1 >0.05

A. Thigh 3.7 ± 1.0 6.7 ± 0.6 <0.001*

P. Thigh 4.6 ± 1.7 7.1 ± 2.0 <0.001*

P. Gluteal 3.1 ± 0.7 5.3 ± 0.6 <0.001*

Physiological and perceptual values

All physiological and perceptual data is presented in Table 2. Most variables identified

from the CMJ performance did not differ between trials, and this is evident for both before

and after the 15 min SS run task (P>0.05). However, when wearing the CSG, peak

(53:44:3%; η2 = 0.2) and mean (39:58:3%; η

2 = 0.2) concentric force following the SS run

demonstrated a small effect size when compared with the control condition.

RPE during and blood lactate following the 15 min SS run were unaffected by the garment

condition, as was TTE when running at 100% vVO2max (P>0.05). Wearing the CSG

resulted in an improved running economy at 60% vVO2max (Fig. 1) when compared with

control and OSG (P=0.02; 96:4:0%; η2 = 0.6).

*

180

185

190

195

200

205

210

215

220

225

230

Control Oversize Correct

Eco

nom

y (

ml/

kg/k

m)

Fig 1. Running economy during steady state at 60% vVO2max

Table 2. Physiological and perceptual values when wearing CSG, OSG and control garments.

Variable

Counter-movement Jump^

Pre steady state:

Mean concentric force (N) 1344.6 ± 119.9 1353.1 ± 118.8 1353.2 ± 104.1 0.7 ± 3.0 25; Possibly 9; Unlikely

Peak concentric force (N) 1707 ± 199.6 1691.1 ± 156.9 1716.9 ± 216.7 0.5 ± 2.8 15; Unlikely 5; Unlikely

Jump height (cm) 31.0 ± 7.9 30.8 ± 7.8 30.4 ± 6.6 -1.3 ± 6.2 3; Very unlikely 19; Unlikely

Flight time (s) 0.499 ± 0.064 0.497 ± 0.065 0.495 ± 0.053 -0.7 ± 3.0 4; Very unlikely 19; Unlikely

Post steady state:

Mean concentric force (N) 1359.5 ± 106.3 1361.3 ± 121.0 1375.8 ± 105.4 1.2 ± 2.4 39; Possibly 3; Very unlikely

Peak concentric force (N) 1706.4 ± 155.7 1716.3 ± 171.7 1739.7 ± 198.6 1.7 ± 3.0 53; Possibly 3; Very unlikely

Jump height (cm) 31.8 ± 6.8 31.7 ± 8.0 31.5 ± 6.2 -0.8 ± 3.7 1; Very unlikely 8; Unlikely

Flight time (s) 0.507 ± 0.054 0.505 ± 0.064 0.505 ± 0.050 -0.4 ± 1.8 2; Very unlikely 8; Unlikely

Steady state running^^

Running economy (ml/kg/km) 214.19 ± 11.58 211.21 ± 10.35 207.38 ± 10.79 3.2 ± 2.1 96; Likely 0; Almost certainly not

RPE 11.44 ± 2.28 11.58 ± 1.77 11.25 ± 2.02 1.2 ± 4.8 18; Unlikely 3; Very unlikely

Blood lactate (mmol/L) 3.0 ± 1.1 2.9 ± 1.0 3.0 ± 1.0 4.1 ± 13.6 30; Possibly 6; Unlikely

Maximal Testing^^

Time to exhaustion (s) 134.6 ± 37.3 132.4 ± 40.2 138.3 ± 36.1 3.3 ± 5.8 23; Unlikely 2; Very unlikely

*denotes statistical significance p <0.05

^ 10 subjects

^^ 11 subjects

0.1 0.6

0.1

Correct Size-None Chances (% and qualitative) of a substantial

improvement or impairment

Improvement Impairment

0.5

Compression Effect size (%) ± 90%

confidence limitNone Oversized Correct Size Best effect size Best P

0.1 0.7

0.2 0.2

0.1 0.7

0.2 0.3

0 0.7

0 0.7

0.1 0.3

0.6 0.02*

0.1 0.6

0.1 0.5

DISCUSSION

Running Economy

Running economy (RE) can be defined as the energy required for a sub-maximal running

speed and is determined by measuring oxygen uptake (VO2) in steady-state conditions.

RE has been demonstrated to be a better predictor of performance than maximal oxygen

uptake (VO2max) in athletes who have a similar VO2max (Hausswirth et al, 2001; Saunders

et al 2004). RE is closely associated with performance since a good RE would reduce the

% of VO2max required to maintain a given mechanical load (Lucia et al., 2002).

The results of this study demonstrated that during steady state running at a fixed intensity

of 60% vVO2max (12.1 ± 1.3 km/h), RE was significantly lower (p < 0.05) in correctly

fitted compression tights when compared with running shorts. The results of this study are

similar to Bringard et al., (2006), who reported an improvement in RE when compression

tights were worn and running velocity was ~12 km·h-1

. Furthermore, a non-statistically

significant, but large effect size (ES = 0.9) was reported in RE when compression

stockings were worn while running at ~15-17 km·h-1

(Varela-Sanz et al., 2011).

It is important to recognise that not all study’s report positive findings with regards to RE

(Sperlich et al., 2010; Lovell et al., 2011). However, comparisons between studies are

difficult due to variations in study design, whilst the impact of a varied individual response

requires further investigation.

When trying to understand the mechanism behind improved RE, alterations in running

technique offer a plausible explanation. In 2014, Born et al. investigated the influence of a

novel, long compression tight with adhesive strips, on repeated sprint performance. In the

final 10 sprints (~20km/h; 30 x 30 m sprint, one sprint per minute), hip flexion angle

reduced, while step length and activation of the m. rectus femoris significantly increased.

Whilst, the garment used is uniquely different to SKINS and the pressure compression

profile exerted higher (~20 mmHg), this is the first to report a measured change in running

mechanics when wearing compression tights, therefore suggesting that altered sprint

mechanics may explain improved performance, unlike previously proposed physiological

mechanisms; such as changes in hemodynamics and oxygen uptake.

Currently, this area of research remains immature (Valera-Sanz et al., 2011; Stickford et

al., 2015; Born et al., 2014) and consequently clear conclusions have yet to be reached. In

investigating further, consistency in garment use and the variables measured is required.

Further, it has been hypothesised that athletes may need an accommodation period for

systematically experiencing the benefits of a compression garment (Valera-Sanz et al.,

2011) and as such the measurement of an acute response may not provide the true extent

of the benefits of compression. This provides an interesting angle for future investigation.

Increased proprioception and muscle coordination have also been suggested as possible

mechanisms to explain a reduced metabolic cost of running when wearing compression

tights. In 1995, Perlau et al reported improved technique in a stationary knee extension

task when elastic bandages are applied to the leg. In addition, Kuster et al, (1999) reported

that a sleeve worn on the knee improved the integration of the balance control system and

muscle coordination in subject’s recovery ACL surgery. Currently, the evidence to support

the claims remains largely unproven in a dynamic, athletic population.

During low-moderate exercise intensity, reduced oscillation / vibration of the musculature

has been reported as a result of wearing compression clothing (Bakken, 2011; Doan et al.,

2003). Cardinale et al., (2003) demonstrated that vibration of the muscle results in

increased activity (as measured by EMG), and consequently, cardiorespiratory and

metabolic demands are increased (Rittweger et al. 2000; Rittweger et al. 2001). Therefore,

it was a justifiable proposition put forward by Bringard et al., (2006) to suggest that a

reduction in muscle vibration by wearing compressive tights will cause a reduction in

oxygen uptake during steady state, sub maximal exercise.

Compression Profile

As to be expected, the oversized compression tights applied a significantly lower level of

pressure at most anatomical landmarks when compared with the correctly fitted garment.

However, the lack of distinct differences between these values (mean compression values

<12 mmHg for both garments) supports the proposal from Brophy-Williams et al., (2014)

that future research studies should aim to standardise garments based upon compression

profiles rather than manufacturers recommendations, which has previously been the norm

(Driller & Halson, 2013; Ménétrier et al., 2011; Rugg & Sternlicht, 2013).

Whilst no predetermined ‘ideal’ compression profile at specific anatomical landmarks, or

gradient has been defined in the literature, it has been reported that a pressure of 18 mmHg

at the ankle, dissipating to 8 mmHg at the calf (mean pressure = 12 mmHg) to be most

effective in increasing venous flow velocity when compared to higher and lower pressures

(Lawrence and Kakkar, 1980). Conversely, Watanuki and Murata (1994) suggest that 17.3

mmHg is the minimum physiologically effective pressure at the calf, decreasing to 15.1

mmHg at the thigh. Although sports compression tights and leggings exert different

pressures, the optimal pressure to induce the greatest increase in venous blood flow,

muscle oxygenation, EMG and many other parameters is yet to be determined.

Although compression values reported in the literature vary greatly, the weight of

evidence is currently suggestive that values between 15-25 mmHg are optimal for

physiological change. In light of the lower values observed in this current study, this may

have had an impact on the results observed.

Blood Lactate

Despite some authors reporting a reduction in lactate concentration following exercise

with compression garments (Berry & McMurray, 1987; Chatard et al., 2004), the current

study found no difference in blood lactate between any clothing conditions.

RPE

Similar to that of Bringard et al., (2006), RPE was not different between the garment

conditions when running at ~12 km/hr in the current study. As with all compression

exercise studies, it is not possible to truly blind the subject to the garment condition,

therefore prior knowledge of the presumed benefits of compression garments may

predispose subjects to believing that their performance would benefit from using the

garment (Goh et al., 2011; Desharnais et al. 1993).

Interestingly, it has been reported that SKINS long tights reduce RPE at both 10 and 20

min during a sub-maximal run at 32°C when compared to normal running shorts.

Furthermore, a reduced RPE following fifteen minutes of continual running (5 min at 50,

70 and 85% heart rate reserve) was reported when compression tights were worn (Rugg

and Sternlicht, 2013). The compression profiles of the tights were 18, 12.6 and 7.2 mmHg

at the ankle, calf and thigh respectively, therefore similar profiles at the calf and thigh to

that of the current study.

Vertical Jump Performance

No significant differences were observed in vertical jump performance either prior too or

post completing a 15 minute steady state run between garment conditions. The variables

analysed include the mean and peak concentric force, jump height and flight time. A

small effect size (ES = 0.2) was observed in mean and peak concentric force following the

steady state run when wearing correctly fitted compression tights. These findings are

similar to that of Ali et al., (2010), who reported no difference in jump height or peak

power between garment conditions following a 40 minute sub maximal run (~80%

VO2max).

Rugg and Sternlicht, (2013) report a significantly greater mean counter-movement jump

height in graduated compression tights following 15 minutes of steady state running. The

difference in finding between this and the present study may be related to the method of

jump height assessment (Vertec vs force platform). Furthermore, countermovement jump

has been shown to improve (or attenuated a decline) following various exercise modalities

when wearing compression clothing (Jakeman et al., 2010; Kraemer et al., 1996; Kraemer

et al., 1998).

Future research should identify if vertical jump height is improved during athletic

performance. Data in this area is lacking and would ultimately identify if any identifiable

benefit is gained, does this translate into ‘on field’ performance i.e. peak and mean jump

height of ‘blockers’ during volleyball game.

Time to Exhaustion

The time to exhaustion data presented in this study is generally aligned to previous

findings, in that compression garments have no statistical or practical significance on

running time to exhaustion at vVO2max (Goh et al., 2011; Sperlich et al., 2010).

Goh et al., (2011) investigated running performance undertaken at the same exercise

intensity, with SKINS long tights, reporting a similar compression profile (13.6 ± 3.4 and

8.6 ± 1.9 mmHg at the calf and thigh respectively) supports the current finding that time to

exhaustion is not improved. A worthwhile point is that whilst at 10°C, TTE was not

improved, a small effect size (ES = 0.48) was reported at 32°C when wearing full length

SKINS compression tights.

Future Research

In light of the improved RE, it would seem prudent to further explore this finding in

relation to exercise performance. Firstly, future research should look to explore if a change

in RE at ~12 km/h translates into a measureable performance enhancement. This

investigation should require subjects to exercise for a prolonged period of time as most

literature is based upon 3-15 min of exercise. Secondly, a deeper understanding into the

mechanistic explanation behind why these findings are observed may shed light on what

physiological/biomechanical variables(s) contributes towards this ergogenic benefit.

Furthermore, whilst speculative at present, it could be hypothesised that potential benefits

gained from wearing compression clothing could be strongly associated with the desired

exercise intensity and compression profile (mmHg). It might be that when running at a

lower intensity (jogging), a lower compression profile (5-15 mmHg) would suffice and

bring about physiological benefits such as a reduced oxygen cost. Whereas when

considering sprinting performance, applying appropriate (i.e. higher) levels of

compression, altered running gait/posture may explain the possible ergogenic benefit.

However this hypothesis remains to be explored and future research should look to address

this.

Finally, it should be mentioned that there is an increasing prevalence of authors

speculating about a possible individual response when wearing compression. Possible

inter-individual differences in sub-maximal running economy due to experience has been

reported (Stickford et al., 2015), while the question regarding whether an optimal time-

course of wearing compression (i.e. number of wears/required duration of experience) to

elicit the greatest physiological benefit has also been mentioned (Valera-Sanz et al., 2011).

However, differentiating between ‘sub-conscious’ measures that cannot be altered by an

athlete’s perception of compression clothing (i.e. energy cost) and ‘conscious’ variables

than can (Time to exhaustion; TTE, and rating of perceived exertion; RPE), should be vital

when attempting to understand any effects of ‘compression experience’. It has previously

been reported in a study using compression shorts, that 93% of participants using

compression garments believed that the garment was beneficial. This, in conjunction with

mass-participation compression clothing-usage data, suggests that there may be a

significant perceptual component to the ergogenic effects associated with compression

apparel (Bernhardt and Anderson, 2005).

CONCLUSION

In conclusion, the results of this study support that of Bringard et al (2006) that in the

same environmental conditions, a lower running economy is produced, despite no

observed change in subjective rating of perceived exertion. When wearing correctly fitted

SKINS A400 long tights compared to running shorts, the runners demonstrated that they

used less energy when running at a sub maximal speed. Wearing compression clothing

during running may decrease muscle oscillations and alter running gait/posture, thereby

promoting lower energy expenditure at a given intensity. Future studies are required to

elucidate on the mechanisms integrating with the observed changes in running economy,

plus identify if these physiological changes translate into a measurable performance

enhancement.

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